diff --git a/.env.template b/.env.template index 328d3301..c2a4d8a2 100644 --- a/.env.template +++ b/.env.template @@ -55,6 +55,10 @@ SPEAKER_SERVICE_URL=http://${DOMAIN}:${SPEAKER_PORT} # JWT secret key - make this random and long AUTH_SECRET_KEY=your-super-secret-jwt-key-here-make-it-random-and-long +# JWT-token issuer ACCEPTED_ISSUERS can be a comma-separated list of accepted issuers +# defaults to 'chronicle,ushadow' if not set +# ACCEPTED_ISSUERS=chronicle,ushadow + # Admin account ADMIN_EMAIL=admin@example.com ADMIN_PASSWORD=secure-admin-password diff --git a/.github/workflows/README.md b/.github/workflows/README.md index 3b645800..5e98cd18 100644 --- a/.github/workflows/README.md +++ b/.github/workflows/README.md @@ -86,6 +86,6 @@ uv sync --dev cp .env.template .env.test # Add your API keys to .env.test -# Run test (modify CACHED_MODE in test_integration.py if needed) -uv run pytest test_integration.py::test_full_pipeline_integration -v -s +# Run Robot Framework integration tests +uv run robot --outputdir test-results --loglevel INFO tests/integration/integration_test.robot ``` \ No newline at end of file diff --git a/.github/workflows/integration-tests.yml b/.github/workflows/integration-tests.yml deleted file mode 100644 index ce2677b4..00000000 --- a/.github/workflows/integration-tests.yml +++ /dev/null @@ -1,83 +0,0 @@ -name: Integration Tests - -on: - push: - branches: [ main, develop ] - paths: - - 'backends/advanced/src/**' - - 'backends/advanced/run-test.sh' - - '.github/workflows/integration-tests.yml' - pull_request: - branches: [ main, develop ] - paths: - - 'backends/advanced/src/**' - - 'backends/advanced/run-test.sh' - - '.github/workflows/integration-tests.yml' - -jobs: - integration-tests: - runs-on: ubuntu-latest - timeout-minutes: 20 - - services: - docker: - image: docker:dind - options: --privileged - - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Verify required secrets - env: - DEEPGRAM_API_KEY: ${{ secrets.DEEPGRAM_API_KEY }} - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - run: | - echo "Verifying required secrets..." - if [ -z "$DEEPGRAM_API_KEY" ]; then - echo "❌ ERROR: DEEPGRAM_API_KEY secret is not set" - exit 1 - fi - if [ -z "$OPENAI_API_KEY" ]; then - echo "❌ ERROR: OPENAI_API_KEY secret is not set" - exit 1 - fi - echo "✓ DEEPGRAM_API_KEY is set (length: ${#DEEPGRAM_API_KEY})" - echo "✓ OPENAI_API_KEY is set (length: ${#OPENAI_API_KEY})" - echo "✓ All required secrets verified" - - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - - - name: Install uv - uses: astral-sh/setup-uv@v4 - with: - version: "latest" - - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: "3.12" - - - name: Install PortAudio dependencies - run: sudo apt-get update && sudo apt-get install -y portaudio19-dev - - - name: Run Advanced Backend Integration Tests - env: - DEEPGRAM_API_KEY: ${{ secrets.DEEPGRAM_API_KEY }} - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - run: | - cd backends/advanced - chmod +x run-test.sh - ./run-test.sh - - - name: Upload test logs on failure - if: failure() - uses: actions/upload-artifact@v4 - with: - name: integration-test-logs - path: | - backends/advanced/test_integration.log - backends/advanced/docker-compose-test.yml - backends/advanced/.env.test - retention-days: 7 \ No newline at end of file diff --git a/.github/workflows/robot-tests.yml b/.github/workflows/robot-tests.yml index 4ba9b251..3333266d 100644 --- a/.github/workflows/robot-tests.yml +++ b/.github/workflows/robot-tests.yml @@ -28,6 +28,7 @@ jobs: env: DEEPGRAM_API_KEY: ${{ secrets.DEEPGRAM_API_KEY }} OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} + HF_TOKEN: ${{ secrets.HF_TOKEN }} run: | echo "Verifying required secrets..." if [ -z "$DEEPGRAM_API_KEY" ]; then @@ -38,8 +39,13 @@ jobs: echo "❌ ERROR: OPENAI_API_KEY secret is not set" exit 1 fi + if [ -z "$HF_TOKEN" ]; then + echo "❌ ERROR: HF_TOKEN secret is not set" + exit 1 + fi echo "✓ DEEPGRAM_API_KEY is set (length: ${#DEEPGRAM_API_KEY})" echo "✓ OPENAI_API_KEY is set (length: ${#OPENAI_API_KEY})" + echo "✓ HF_TOKEN is set (length: ${#HF_TOKEN})" echo "✓ All required secrets verified" - name: Set up Docker Buildx @@ -61,7 +67,6 @@ jobs: uses: actions/setup-python@v5 with: python-version: "3.12" - cache: 'pip' - name: Install uv uses: astral-sh/setup-uv@v4 @@ -72,148 +77,25 @@ jobs: run: | uv pip install --system robotframework robotframework-requests python-dotenv websockets - - name: Create test environment file - working-directory: tests/setup - run: | - cat > .env.test << EOF - # API URLs - API_URL=http://localhost:8001 - BACKEND_URL=http://localhost:8001 - FRONTEND_URL=http://localhost:3001 - - # Test Admin Credentials - ADMIN_EMAIL=test-admin@example.com - ADMIN_PASSWORD=test-admin-password-123 - - # API Keys (from GitHub secrets) - OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY }} - DEEPGRAM_API_KEY=${{ secrets.DEEPGRAM_API_KEY }} - - # Test Configuration - TEST_TIMEOUT=120 - TEST_DEVICE_NAME=robot-test - EOF - - - name: Start test environment - working-directory: backends/advanced - env: - DEEPGRAM_API_KEY: ${{ secrets.DEEPGRAM_API_KEY }} - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - LLM_PROVIDER: openai - TRANSCRIPTION_PROVIDER: deepgram - MEMORY_PROVIDER: friend_lite - run: | - # Debug: Check if secrets are available - echo "Checking environment variables..." - echo "DEEPGRAM_API_KEY is set: $([ -n "$DEEPGRAM_API_KEY" ] && echo 'YES' || echo 'NO')" - echo "OPENAI_API_KEY is set: $([ -n "$OPENAI_API_KEY" ] && echo 'YES' || echo 'NO')" - echo "LLM_PROVIDER: $LLM_PROVIDER" - echo "TRANSCRIPTION_PROVIDER: $TRANSCRIPTION_PROVIDER" - - # Create memory_config.yaml from template (file is gitignored) - echo "Creating memory_config.yaml from template..." - cp memory_config.yaml.template memory_config.yaml - - # Clean any existing test containers for fresh start - echo "Cleaning up any existing test containers..." - docker compose -f docker-compose-test.yml down -v || true - - # Start ALL services in parallel - Docker Compose handles dependencies via healthchecks - echo "Starting all services in parallel (docker-compose-test.yml)..." - echo "Note: Using test compose file with source mounts for faster startup" - - # Export API keys so docker-compose can use them - export DEEPGRAM_API_KEY - export OPENAI_API_KEY - export LLM_PROVIDER - export TRANSCRIPTION_PROVIDER - export MEMORY_PROVIDER - - DOCKER_BUILDKIT=0 docker compose -f docker-compose-test.yml up -d - - # Show container status - echo "Container status:" - docker compose -f docker-compose-test.yml ps - - # Single wait for backend readiness (backend depends_on ensures infra is ready) - echo "Waiting for backend readiness (up to 120s)..." - for i in {1..40}; do - if curl -s http://localhost:8001/readiness > /dev/null 2>&1; then - echo "✓ Backend is ready (all dependencies satisfied)" - break - fi - # Show logs every 10 attempts to help debug - if [ $((i % 10)) -eq 0 ]; then - echo "Still waiting... showing recent logs:" - docker compose -f docker-compose-test.yml logs --tail=20 friend-backend-test - fi - if [ $i -eq 40 ]; then - echo "✗ Backend failed to start - showing full logs:" - docker compose -f docker-compose-test.yml logs - exit 1 - fi - echo "Attempt $i/40..." - sleep 3 - done - - echo "✓ Backend is ready!" - - # Verify workers are registered with Redis (Robot tests need stable workers) - echo "Waiting for workers to register with Redis (up to 60s)..." - for i in {1..30}; do - WORKER_COUNT=$(docker compose -f docker-compose-test.yml exec -T workers-test uv run python -c 'from rq import Worker; from redis import Redis; import os; r = Redis.from_url(os.getenv("REDIS_URL", "redis://redis-test:6379/0")); print(len(Worker.all(connection=r)))' 2>/dev/null || echo "0") - - if [ "$WORKER_COUNT" -ge 6 ]; then - echo "✓ Found $WORKER_COUNT workers registered" - # Show worker details - docker compose -f docker-compose-test.yml exec -T workers-test uv run python -c 'from rq import Worker; from redis import Redis; import os; r = Redis.from_url(os.getenv("REDIS_URL", "redis://redis-test:6379/0")); workers = Worker.all(connection=r); print(f"Total registered workers: {len(workers)}"); [print(f" - {w.name}: queues={w.queue_names()}, state={w.get_state()}") for w in workers]' - break - fi - - if [ $i -eq 30 ]; then - echo "✗ Workers failed to register after 60s" - echo "Showing worker logs:" - docker compose -f docker-compose-test.yml logs --tail=50 workers-test - exit 1 - fi - - echo "Attempt $i/30: $WORKER_COUNT workers registered (waiting for 6+)..." - sleep 2 - done - - echo "✓ All services ready!" - - - name: Verify checked out code - working-directory: tests - run: | - echo "Current git commit:" - git log -1 --oneline - echo "" - echo "Test files in current checkout:" - find . -name "*.robot" -type f | head -10 - echo "" - echo "Sample of tags in test files:" - grep -h "\[Tags\]" endpoints/*.robot infrastructure/*.robot integration/*.robot 2>/dev/null | head -20 || echo "No tag files found" - - - name: Clean previous test results - working-directory: tests + - name: Create test config.yml run: | - echo "Cleaning any previous test results..." - rm -rf results - mkdir -p results - echo "✓ Fresh results directory created" + echo "Copying test configuration file..." + mkdir -p config + cp tests/configs/deepgram-openai.yml config/config.yml + echo "✓ Test config.yml created from tests/configs/deepgram-openai.yml" + ls -lh config/config.yml - name: Run Robot Framework tests working-directory: tests env: - # Required for backend imports in test libraries - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - OPENAI_BASE_URL: https://api.openai.com/v1 - OPENAI_MODEL: gpt-4o-mini + # Required for test runner script DEEPGRAM_API_KEY: ${{ secrets.DEEPGRAM_API_KEY }} + OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} + HF_TOKEN: ${{ secrets.HF_TOKEN }} + CLEANUP_CONTAINERS: "false" # Don't cleanup in CI - handled by workflow run: | - # Run all tests (don't fail workflow to allow artifact upload) - make all OUTPUTDIR=results + # Use the unified test script that mirrors local development + ./run-robot-tests.sh TEST_EXIT_CODE=$? echo "test_exit_code=$TEST_EXIT_CODE" >> $GITHUB_ENV exit 0 # Don't fail here, we'll fail at the end after uploading artifacts @@ -223,7 +105,7 @@ jobs: working-directory: backends/advanced run: | echo "=== Backend Logs (last 50 lines) ===" - docker compose -f docker-compose-test.yml logs --tail=50 friend-backend-test + docker compose -f docker-compose-test.yml logs --tail=50 chronicle-backend-test echo "" echo "=== Worker Logs (last 50 lines) ===" docker compose -f docker-compose-test.yml logs --tail=50 workers-test diff --git a/.gitignore b/.gitignore index b2b052b3..23141c6b 100644 --- a/.gitignore +++ b/.gitignore @@ -4,6 +4,16 @@ !**/.env.template **/memory_config.yaml !**/memory_config.yaml.template +tests/setup/.env.test + +# Main config (user-specific) +config/config.yml +!config/config.yml.template + +# Config backups +config/*.backup.* +config/*.backup* + example/* **/node_modules/* **/ollama-data/* @@ -76,7 +86,8 @@ extras/openmemory-mcp/data/* backends/advanced/nginx.conf backends/advanced/Caddyfile -app/ios/Pods +app/ios/* +app/android/* results log.html output.xml diff --git a/CLAUDE.md b/CLAUDE.md index ec326b6d..abe20db6 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -13,6 +13,49 @@ This supports a comprehensive web dashboard for management. **❌ No Backward Compatibility**: Do NOT add backward compatibility code unless explicitly requested. This includes fallback logic, legacy field support, or compatibility layers. Always ask before adding backward compatibility - in most cases the answer is no during active development. +## Initial Setup & Configuration + +Chronicle includes an **interactive setup wizard** for easy configuration. The wizard guides you through: +- Service selection (backend + optional services) +- Authentication setup (admin account, JWT secrets) +- Transcription provider configuration (Deepgram, Mistral, or offline ASR) +- LLM provider setup (OpenAI or Ollama) +- Memory provider selection (Chronicle Native with Qdrant or OpenMemory MCP) +- Network configuration and HTTPS setup +- Optional services (speaker recognition, Parakeet ASR) + +### Quick Start +```bash +# Run the interactive setup wizard from project root +uv run python wizard.py + +# Or use the quickstart guide for step-by-step instructions +# See quickstart.md for detailed walkthrough +``` + +### Setup Documentation +For detailed setup instructions and troubleshooting, see: +- **[@quickstart.md](quickstart.md)**: Beginner-friendly step-by-step setup guide +- **[@Docs/init-system.md](Docs/init-system.md)**: Complete initialization system architecture and design +- **[@Docs/getting-started.md](Docs/getting-started.md)**: Technical quickstart with advanced configuration +- **[@backends/advanced/SETUP_SCRIPTS.md](backends/advanced/SETUP_SCRIPTS.md)**: Setup scripts reference and usage examples +- **[@backends/advanced/Docs/quickstart.md](backends/advanced/Docs/quickstart.md)**: Backend-specific setup guide + +### Wizard Architecture +The initialization system uses a **root orchestrator pattern**: +- **`wizard.py`**: Root setup orchestrator for service selection and delegation +- **`backends/advanced/init.py`**: Backend configuration wizard +- **`extras/speaker-recognition/init.py`**: Speaker recognition setup +- **Service setup scripts**: Individual setup for ASR services and OpenMemory MCP + +Key features: +- Interactive prompts with validation +- API key masking and secure credential handling +- Environment file generation with placeholders +- HTTPS configuration with SSL certificate generation +- Service status display and health checks +- Automatic backup of existing configurations + ## Development Commands ### Backend Development (Advanced Backend - Primary) @@ -73,11 +116,11 @@ cp .env.template .env # Configure API keys # Manual test execution (for debugging) source .env && export DEEPGRAM_API_KEY && export OPENAI_API_KEY -uv run pytest tests/test_integration.py::test_full_pipeline_integration -v -s +uv run robot --outputdir test-results --loglevel INFO ../../tests/integration/integration_test.robot # Leave test containers running for debugging (don't auto-cleanup) CLEANUP_CONTAINERS=false source .env && export DEEPGRAM_API_KEY && export OPENAI_API_KEY -uv run pytest tests/test_integration.py::test_full_pipeline_integration -v -s +uv run robot --outputdir test-results --loglevel INFO ../../tests/integration/integration_test.robot # Manual cleanup when needed docker compose -f docker-compose-test.yml down -v @@ -347,7 +390,7 @@ docker compose up --build -d ### Testing Strategy - **Local Test Scripts**: Simplified scripts (`./run-test.sh`) mirror CI workflows for local development -- **End-to-End Integration**: `test_integration.py` validates complete audio processing pipeline +- **End-to-End Integration**: Robot Framework tests (`tests/integration/integration_test.robot`) validate complete audio processing pipeline - **Speaker Recognition Tests**: `test_speaker_service_integration.py` validates speaker identification - **Environment Flexibility**: Tests work with both local .env files and CI environment variables - **Automated Cleanup**: Test containers are automatically removed after execution diff --git a/Docs/getting-started.md b/Docs/getting-started.md index 6483f00f..a923c99c 100644 --- a/Docs/getting-started.md +++ b/Docs/getting-started.md @@ -179,9 +179,9 @@ After configuration, verify everything works with the integration test suite: # Alternative: Manual test with detailed logging source .env && export DEEPGRAM_API_KEY OPENAI_API_KEY && \ - uv run pytest tests/test_integration.py -vv -s --log-cli-level=INFO + uv run robot --outputdir ../../test-results --loglevel INFO ../../tests/integration/integration_test.robot ``` -This end-to-end test validates the complete audio processing pipeline. +This end-to-end test validates the complete audio processing pipeline using Robot Framework. ## Using the System @@ -342,7 +342,7 @@ curl -X POST "http://localhost:8000/api/process-audio-files" \ **Implementation**: - **Memory System**: `src/advanced_omi_backend/memory/memory_service.py` + `src/advanced_omi_backend/controllers/memory_controller.py` -- **Configuration**: `memory_config.yaml` + `src/advanced_omi_backend/memory_config_loader.py` +- **Configuration**: memory settings in `config/config.yml` (memory section) ### Authentication & Security - **Email Authentication**: Login with email and password @@ -396,7 +396,7 @@ uv sync --group (whatever group you want to sync) ## Troubleshooting **Service Issues:** -- Check logs: `docker compose logs friend-backend` +- Check logs: `docker compose logs chronicle-backend` - Restart services: `docker compose restart` - View all services: `docker compose ps` @@ -541,10 +541,10 @@ OPENMEMORY_MCP_URL=http://host.docker.internal:8765 > 🎯 **New to memory configuration?** Read our [Memory Configuration Guide](./memory-configuration-guide.md) for a step-by-step setup guide with examples. -The system uses **centralized configuration** via `memory_config.yaml` for all memory extraction settings. All hardcoded values have been removed from the code to ensure consistent, configurable behavior. +The system uses **centralized configuration** via `config/config.yml` for all models (LLM, embeddings, vector store) and memory extraction settings. ### Configuration File Location -- **Path**: `backends/advanced-backend/memory_config.yaml` +- **Path**: repository `config/config.yml` (override with `CONFIG_FILE` env var) - **Hot-reload**: Changes are applied on next processing cycle (no restart required) - **Fallback**: If file is missing, system uses safe defaults with environment variables @@ -613,7 +613,7 @@ If you experience JSON parsing errors in fact extraction: 2. **Enable fact extraction** with reliable JSON output: ```yaml - # In memory_config.yaml + # In config/config.yml (memory section) fact_extraction: enabled: true # Safe to enable with GPT-4o ``` @@ -727,5 +727,5 @@ curl -H "Authorization: Bearer $ADMIN_TOKEN" \ - **Connect audio clients** using the WebSocket API - **Explore the dashboard** to manage conversations and users - **Review the user data architecture** for understanding data organization -- **Customize memory extraction** by editing `memory_config.yaml` -- **Monitor processing performance** using debug API endpoints \ No newline at end of file +- **Customize memory extraction** by editing the `memory` section in `config/config.yml` +- **Monitor processing performance** using debug API endpoints diff --git a/Docs/init-system.md b/Docs/init-system.md index ea4db94d..3df6316c 100644 --- a/Docs/init-system.md +++ b/Docs/init-system.md @@ -230,7 +230,7 @@ curl http://localhost:8767/health docker compose logs [service-name] # Backend logs -cd backends/advanced && docker compose logs friend-backend +cd backends/advanced && docker compose logs chronicle-backend # Speaker Recognition logs cd extras/speaker-recognition && docker compose logs speaker-service diff --git a/LICENSE b/LICENSE new file mode 100644 index 00000000..6e9268e9 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2024 Chronicle AI Contributors + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. \ No newline at end of file diff --git a/README.md b/README.md index 34027891..f44e266f 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ Self-hostable AI system that captures audio/video data from OMI devices and othe ## Quick Start → [Get Started](quickstart.md) -Clone, run setup wizard, start services, access at http://localhost:5173 +Run setup wizard, start services, access at http://localhost:5173 ## Screenshots diff --git a/app/app/components/ObsidianIngest.tsx b/app/app/components/ObsidianIngest.tsx new file mode 100644 index 00000000..d14ca367 --- /dev/null +++ b/app/app/components/ObsidianIngest.tsx @@ -0,0 +1,154 @@ + +import React, { useState } from 'react'; +import { View, Text, TextInput, TouchableOpacity, StyleSheet, Alert, ActivityIndicator } from 'react-native'; + +interface ObsidianIngestProps { + backendUrl: string; + jwtToken: string | null; +} + +export const ObsidianIngest: React.FC = ({ + backendUrl, + jwtToken, +}) => { + const [vaultPath, setVaultPath] = useState('/app/data/obsidian_vault'); + const [loading, setLoading] = useState(false); + + const handleIngest = async () => { + if (!backendUrl) { + Alert.alert("Error", "Backend URL not set"); + return; + } + + if (!jwtToken) { + Alert.alert("Authentication Required", "Please login to ingest Obsidian vault."); + return; + } + + setLoading(true); + try { + let baseUrl = backendUrl.trim(); + // Handle different URL formats + if (baseUrl.startsWith('ws://')) { + baseUrl = baseUrl.replace('ws://', 'http://'); + } else if (baseUrl.startsWith('wss://')) { + baseUrl = baseUrl.replace('wss://', 'https://'); + } + baseUrl = baseUrl.split('/ws')[0]; + + const response = await fetch(`${baseUrl}/api/obsidian/ingest`, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + 'Authorization': `Bearer ${jwtToken}` + }, + body: JSON.stringify({ vault_path: vaultPath }) + }); + + if (response.ok) { + Alert.alert("Success", "Ingestion started in background."); + } else { + const errorText = await response.text(); + Alert.alert("Error", `Ingestion failed: ${response.status} - ${errorText}`); + } + } catch (e) { + Alert.alert("Error", `Network request failed: ${e}`); + } finally { + setLoading(false); + } + }; + + return ( + + Obsidian Ingestion + + Vault Path (Backend Container): + + + + + {loading ? 'Starting Ingestion...' : 'Ingest to Neo4j'} + + + + + Enter the absolute path to the Obsidian vault INSIDE the backend container. + Ensure the folder is mounted to the container. + + + ); +}; + +const styles = StyleSheet.create({ + section: { + marginBottom: 25, + padding: 15, + backgroundColor: 'white', + borderRadius: 10, + shadowColor: '#000', + shadowOffset: { width: 0, height: 1 }, + shadowOpacity: 0.1, + shadowRadius: 3, + elevation: 2, + }, + sectionTitle: { + fontSize: 18, + fontWeight: '600', + marginBottom: 15, + color: '#333', + }, + inputLabel: { + fontSize: 14, + color: '#333', + marginBottom: 5, + fontWeight: '500', + }, + textInput: { + backgroundColor: '#f0f0f0', + borderWidth: 1, + borderColor: '#ddd', + borderRadius: 6, + padding: 10, + fontSize: 14, + width: '100%', + marginBottom: 15, + color: '#333', + }, + button: { + backgroundColor: '#9b59b6', // Purple for Obsidian + paddingVertical: 12, + paddingHorizontal: 20, + borderRadius: 8, + alignItems: 'center', + marginBottom: 10, + elevation: 2, + }, + buttonDisabled: { + backgroundColor: '#A0A0A0', + opacity: 0.7, + }, + buttonText: { + color: 'white', + fontSize: 16, + fontWeight: '600', + }, + helpText: { + fontSize: 12, + color: '#666', + textAlign: 'center', + fontStyle: 'italic', + }, +}); + +export default ObsidianIngest; diff --git a/app/app/index.tsx b/app/app/index.tsx index 8bb1234a..fc924d92 100644 --- a/app/app/index.tsx +++ b/app/app/index.tsx @@ -28,6 +28,7 @@ import DeviceListItem from './components/DeviceListItem'; import DeviceDetails from './components/DeviceDetails'; import AuthSection from './components/AuthSection'; import BackendStatus from './components/BackendStatus'; +import ObsidianIngest from './components/ObsidianIngest'; import PhoneAudioButton from './components/PhoneAudioButton'; export default function App() { @@ -538,6 +539,14 @@ export default function App() { onAuthStatusChange={handleAuthStatusChange} /> + {/* Obsidian Ingestion - Only when authenticated */} + {isAuthenticated && ( + + )} + {/* Phone Audio Streaming Button */} uv + FastAPI] + Backend[chronicle-backend
uv + FastAPI] WebUI[webui
React Dashboard] Proxy[nginx
Load Balancer] Mongo[mongo:4.4.18
Primary Database] @@ -616,7 +616,7 @@ graph LR ### Container Specifications -#### Backend Container (`friend-backend`) +#### Backend Container (`chronicle-backend`) - **Base**: Python 3.12 slim with uv package manager - **Dependencies**: FastAPI, WebSocket libraries, audio processing tools - **Volumes**: Audio chunk storage, debug directories diff --git a/backends/advanced/Docs/auth.md b/backends/advanced/Docs/auth.md index 2aa7d254..acbf8df4 100644 --- a/backends/advanced/Docs/auth.md +++ b/backends/advanced/Docs/auth.md @@ -260,7 +260,7 @@ curl -X POST "http://localhost:8000/auth/jwt/login" \ #### 3. Admin User Creation ```bash # Check logs for admin creation -docker compose logs friend-backend | grep -i admin +docker compose logs chronicle-backend | grep -i admin # Verify environment variables echo $ADMIN_PASSWORD @@ -272,7 +272,7 @@ echo $ADMIN_PASSWORD docker exec -it mongo-container mongosh chronicle # View authentication logs -docker compose logs friend-backend | grep -i auth +docker compose logs chronicle-backend | grep -i auth # Test API endpoints curl -H "Authorization: Bearer $TOKEN" http://localhost:8000/api/users/me diff --git a/backends/advanced/Docs/contribution.md b/backends/advanced/Docs/contribution.md index dd645eca..b78f4a5a 100644 --- a/backends/advanced/Docs/contribution.md +++ b/backends/advanced/Docs/contribution.md @@ -1,12 +1,12 @@ 1. Docs/quickstart.md (15 min) 2. Docs/architecture.md (20 min) 3. main.py - just the imports and WebSocket sections (15 min) - 4. memory_config.yaml (10 min) + 4. config/config.yml (memory section) (10 min) 🔧 "I want to work on memory extraction" 1. Docs/quickstart.md → Docs/memories.md - 2. memory_config.yaml (memory_extraction section) + 2. config/config.yml (memory.extraction section) 3. main.py lines 1047-1065 (trigger) 4. main.py lines 1163-1195 (processing) 5. src/memory/memory_service.py @@ -32,4 +32,4 @@ Data Flow Audio → Transcription → Dual Processing - └─ Memory Pipeline (end-of-conversation) \ No newline at end of file + └─ Memory Pipeline (end-of-conversation) diff --git a/backends/advanced/Docs/memories.md b/backends/advanced/Docs/memories.md index b2887dc9..cae98383 100644 --- a/backends/advanced/Docs/memories.md +++ b/backends/advanced/Docs/memories.md @@ -10,7 +10,7 @@ This document explains how to configure and customize the memory service in the - **Repository Layer**: `src/advanced_omi_backend/conversation_repository.py` (clean data access) - **Processing Manager**: `src/advanced_omi_backend/processors.py` (MemoryProcessor class) - **Conversation Management**: `src/advanced_omi_backend/conversation_manager.py` (lifecycle coordination) -- **Configuration**: `memory_config.yaml` + `src/memory_config_loader.py` +- **Configuration**: `config/config.yml` (memory section) + `src/model_registry.py` ## Overview @@ -180,7 +180,7 @@ OPENAI_MODEL=gpt-5-mini # Recommended for reliable JSON output # OPENAI_MODEL=gpt-3.5-turbo # Budget option ``` -Or configure via `memory_config.yaml`: +Or configure via `config/config.yml` (memory block): ```yaml memory_extraction: @@ -674,4 +674,4 @@ The new architecture ensures proper user isolation and simplifies admin debuggin Both load all user memories and view all memories are helpful Both views complement each other - the debug view helps you understand how the system is working, while the clean view -helps you understand what content is being stored. \ No newline at end of file +helps you understand what content is being stored. diff --git a/backends/advanced/Docs/memory-configuration-guide.md b/backends/advanced/Docs/memory-configuration-guide.md index 1f564564..12796e13 100644 --- a/backends/advanced/Docs/memory-configuration-guide.md +++ b/backends/advanced/Docs/memory-configuration-guide.md @@ -6,10 +6,10 @@ This guide helps you set up and configure the memory system for the Friend Advan 1. **Copy the template configuration**: ```bash -cp memory_config.yaml.template memory_config.yaml +Edit the `memory` section of `config/config.yml`. ``` -2. **Edit memory_config.yaml** with your preferred settings: +2. **Edit `config/config.yml`** with your preferred settings in the `memory` section: ```yaml memory: provider: "mem0" # or "basic" for simpler setup @@ -127,6 +127,6 @@ memory: ## Next Steps -- Configure action items detection in `memory_config.yaml` +- Configure action items detection in `config/config.yml` (memory.extraction) - Set up custom prompt templates for your use case -- Monitor memory processing in the debug dashboard \ No newline at end of file +- Monitor memory processing in the debug dashboard diff --git a/backends/advanced/Docs/quickstart.md b/backends/advanced/Docs/quickstart.md index fc5a77b7..0d681978 100644 --- a/backends/advanced/Docs/quickstart.md +++ b/backends/advanced/Docs/quickstart.md @@ -177,9 +177,9 @@ After configuration, verify everything works with the integration test suite: # Alternative: Manual test with detailed logging source .env && export DEEPGRAM_API_KEY OPENAI_API_KEY && \ - uv run pytest tests/test_integration.py -vv -s --log-cli-level=INFO + uv run robot --outputdir ../../test-results --loglevel INFO ../../tests/integration/integration_test.robot ``` -This end-to-end test validates the complete audio processing pipeline. +This end-to-end test validates the complete audio processing pipeline using Robot Framework. ## Using the System @@ -340,7 +340,7 @@ curl -X POST "http://localhost:8000/api/audio/upload" \ **Implementation**: - **Memory System**: `src/advanced_omi_backend/memory/memory_service.py` + `src/advanced_omi_backend/controllers/memory_controller.py` -- **Configuration**: `memory_config.yaml` + `src/advanced_omi_backend/memory_config_loader.py` +- **Configuration**: `config/config.yml` (memory + models) in repo root ### Authentication & Security - **Email Authentication**: Login with email and password @@ -394,7 +394,7 @@ uv sync --group (whatever group you want to sync) ## Troubleshooting **Service Issues:** -- Check logs: `docker compose logs friend-backend` +- Check logs: `docker compose logs chronicle-backend` - Restart services: `docker compose restart` - View all services: `docker compose ps` @@ -539,10 +539,10 @@ OPENMEMORY_MCP_URL=http://host.docker.internal:8765 > 🎯 **New to memory configuration?** Read our [Memory Configuration Guide](./memory-configuration-guide.md) for a step-by-step setup guide with examples. -The system uses **centralized configuration** via `memory_config.yaml` for all memory extraction settings. All hardcoded values have been removed from the code to ensure consistent, configurable behavior. +The system uses **centralized configuration** via `config/config.yml` for all memory extraction and model settings. ### Configuration File Location -- **Path**: `backends/advanced-backend/memory_config.yaml` +- **Path**: `config/config.yml` in repo root - **Hot-reload**: Changes are applied on next processing cycle (no restart required) - **Fallback**: If file is missing, system uses safe defaults with environment variables @@ -611,7 +611,7 @@ If you experience JSON parsing errors in fact extraction: 2. **Enable fact extraction** with reliable JSON output: ```yaml - # In memory_config.yaml + # In config/config.yml (memory section) fact_extraction: enabled: true # Safe to enable with GPT-4o ``` @@ -725,5 +725,5 @@ curl -H "Authorization: Bearer $ADMIN_TOKEN" \ - **Connect audio clients** using the WebSocket API - **Explore the dashboard** to manage conversations and users - **Review the user data architecture** for understanding data organization -- **Customize memory extraction** by editing `memory_config.yaml` -- **Monitor processing performance** using debug API endpoints \ No newline at end of file +- **Customize memory extraction** by editing the `memory` section in `config/config.yml` +- **Monitor processing performance** using debug API endpoints diff --git a/backends/advanced/README.md b/backends/advanced/README.md index ab86a22e..d493241c 100644 --- a/backends/advanced/README.md +++ b/backends/advanced/README.md @@ -100,14 +100,21 @@ See [Docs/HTTPS_SETUP.md](Docs/HTTPS_SETUP.md) for detailed configuration. To run integration tests with different transcription providers: ```bash -# Test with Parakeet ASR (offline transcription) -# Automatically starts test ASR service - no manual setup required -source .env && export DEEPGRAM_API_KEY && export OPENAI_API_KEY && TRANSCRIPTION_PROVIDER=parakeet uv run pytest tests/test_integration.py::test_full_pipeline_integration -v -s --tb=short +# Test with different configurations using config.yml files +# Test configs located in tests/configs/ -# Test with Deepgram (default) -source .env && export DEEPGRAM_API_KEY && export OPENAI_API_KEY && uv run pytest tests/test_integration.py::test_full_pipeline_integration -v -s --tb=short +# Test with Parakeet ASR + Ollama (offline, no API keys) +CONFIG_FILE=../../tests/configs/parakeet-ollama.yml ./run-test.sh + +# Test with Deepgram + OpenAI (cloud-based) +CONFIG_FILE=../../tests/configs/deepgram-openai.yml ./run-test.sh + +# Manual Robot Framework test execution +source .env && export DEEPGRAM_API_KEY OPENAI_API_KEY && \ + uv run robot --outputdir ../../test-results --loglevel INFO ../../tests/integration/integration_test.robot ``` **Prerequisites:** -- API keys configured in `.env` file -- For debugging: Set `CACHED_MODE = True` in test file to keep containers running +- API keys configured in `.env` file (for cloud providers) +- Test configurations in `tests/configs/` directory +- For debugging: Set `CLEANUP_CONTAINERS=false` environment variable to keep containers running diff --git a/backends/advanced/SETUP_SCRIPTS.md b/backends/advanced/SETUP_SCRIPTS.md index c253e429..b45c8910 100644 --- a/backends/advanced/SETUP_SCRIPTS.md +++ b/backends/advanced/SETUP_SCRIPTS.md @@ -6,7 +6,7 @@ This document explains the different setup scripts available in Friend-Lite and | Script | Purpose | When to Use | |--------|---------|-------------| -| `init.py` | **Main interactive setup wizard** | **Recommended for all users** - First time setup with guided configuration (located at repo root) | +| `init.py` | **Main interactive setup wizard** | **Recommended for all users** - First time setup with guided configuration (located at repo root). Memory now configured in `config/config.yml`. | | `setup-https.sh` | HTTPS certificate generation | **Optional** - When you need secure connections for microphone access | ## Main Setup Script: `init.py` @@ -157,4 +157,4 @@ Setup scripts are located as follows: ✅ **Provider selection**: Choose best services for your needs ✅ **Complete configuration**: Creates working .env with all settings ✅ **Next steps guidance**: Clear instructions for starting services -✅ **No manual editing**: Reduces errors from manual .env editing \ No newline at end of file +✅ **No manual editing**: Reduces errors from manual .env editing diff --git a/backends/advanced/docker-compose-test.yml b/backends/advanced/docker-compose-test.yml index f72ca54d..867edc5f 100644 --- a/backends/advanced/docker-compose-test.yml +++ b/backends/advanced/docker-compose-test.yml @@ -14,6 +14,7 @@ services: - ./data/test_audio_chunks:/app/audio_chunks - ./data/test_debug_dir:/app/debug_dir - ./data/test_data:/app/data + - ${CONFIG_FILE:-../../config/config.yml}:/app/config.yml:ro # Mount config.yml for model registry and memory settings environment: # Override with test-specific settings - MONGODB_URI=mongodb://mongo-test:27017/test_db @@ -24,26 +25,22 @@ services: # Import API keys from environment - DEEPGRAM_API_KEY=${DEEPGRAM_API_KEY} - OPENAI_API_KEY=${OPENAI_API_KEY} - - OPENAI_BASE_URL=https://api.openai.com/v1 - # LLM provider configuration (required for memory service) - - LLM_PROVIDER=${LLM_PROVIDER:-openai} - - OPENAI_MODEL=${OPENAI_MODEL:-gpt-4o-mini} + - GROQ_API_KEY=${GROQ_API_KEY} # Authentication (test-specific) - AUTH_SECRET_KEY=test-jwt-signing-key-for-integration-tests - ADMIN_PASSWORD=test-admin-password-123 - ADMIN_EMAIL=test-admin@example.com # Transcription provider configuration - TRANSCRIPTION_PROVIDER=${TRANSCRIPTION_PROVIDER:-deepgram} - # - PARAKEET_ASR_URL=${PARAKEET_ASR_URL} + - PARAKEET_ASR_URL=${PARAKEET_ASR_URL} # Memory provider configuration - MEMORY_PROVIDER=${MEMORY_PROVIDER:-chronicle} - OPENMEMORY_MCP_URL=${OPENMEMORY_MCP_URL:-http://host.docker.internal:8765} - OPENMEMORY_USER_ID=${OPENMEMORY_USER_ID:-openmemory} - MYCELIA_URL=http://mycelia-backend-test:5173 - MYCELIA_DB=mycelia_test - # Disable speaker recognition in test environment to prevent segment duplication - - DISABLE_SPEAKER_RECOGNITION=false - - SPEAKER_SERVICE_URL=https://localhost:8085 + # Speaker recognition controlled by config.yml (disabled in test config for CI performance) + - SPEAKER_SERVICE_URL=http://speaker-service-test:8085 - CORS_ORIGINS=http://localhost:3001,http://localhost:8001,https://localhost:3001,https://localhost:8001 # Set low inactivity timeout for tests (2 seconds instead of 60) - SPEECH_INACTIVITY_THRESHOLD_SECONDS=2 @@ -56,12 +53,14 @@ services: condition: service_healthy redis-test: condition: service_started + speaker-service-test: + condition: service_healthy healthcheck: test: ["CMD", "curl", "-f", "http://localhost:8000/readiness"] interval: 10s timeout: 5s - retries: 5 - start_period: 30s + retries: 10 + start_period: 60s restart: unless-stopped webui-test: @@ -121,6 +120,36 @@ services: timeout: 3s retries: 5 + speaker-service-test: + build: + context: ../../extras/speaker-recognition + dockerfile: Dockerfile + args: + PYTORCH_CUDA_VERSION: cpu + image: speaker-recognition-test:latest + ports: + - "8086:8085" # Avoid conflict with dev speaker service on 8085 + volumes: + - ../../extras/speaker-recognition/src:/app/src + - ../../extras/speaker-recognition/model_cache:/models + - ../../extras/speaker-recognition/audio_chunks:/app/audio_chunks + - ../../extras/speaker-recognition/debug:/app/debug + - ../../extras/speaker-recognition/speaker_data:/app/data + environment: + - HF_HOME=/models + - HF_TOKEN=${HF_TOKEN} + - SIMILARITY_THRESHOLD=0.15 + - SPEAKER_SERVICE_HOST=0.0.0.0 + - SPEAKER_SERVICE_PORT=8085 + - DEEPGRAM_API_KEY=${DEEPGRAM_API_KEY} + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:8085/health"] + interval: 30s + timeout: 10s + retries: 5 + start_period: 60s + restart: unless-stopped + workers-test: build: context: . @@ -131,6 +160,7 @@ services: - ./data/test_audio_chunks:/app/audio_chunks - ./data/test_debug_dir:/app/debug_dir - ./data/test_data:/app/data + - ${CONFIG_FILE:-../../config/config.yml}:/app/config.yml:ro # Mount config.yml for model registry and memory settings environment: # Same environment as backend - MONGODB_URI=mongodb://mongo-test:27017/test_db @@ -140,19 +170,19 @@ services: - DEBUG_DIR=/app/debug_dir - DEEPGRAM_API_KEY=${DEEPGRAM_API_KEY} - OPENAI_API_KEY=${OPENAI_API_KEY} - - LLM_PROVIDER=${LLM_PROVIDER:-openai} - - OPENAI_MODEL=${OPENAI_MODEL:-gpt-4o-mini} + - GROQ_API_KEY=${GROQ_API_KEY} - AUTH_SECRET_KEY=test-jwt-signing-key-for-integration-tests - ADMIN_PASSWORD=test-admin-password-123 - ADMIN_EMAIL=test-admin@example.com - TRANSCRIPTION_PROVIDER=${TRANSCRIPTION_PROVIDER:-deepgram} + - PARAKEET_ASR_URL=${PARAKEET_ASR_URL} - MEMORY_PROVIDER=${MEMORY_PROVIDER:-chronicle} - OPENMEMORY_MCP_URL=${OPENMEMORY_MCP_URL:-http://host.docker.internal:8765} - OPENMEMORY_USER_ID=${OPENMEMORY_USER_ID:-openmemory} - MYCELIA_URL=http://mycelia-backend-test:5173 - MYCELIA_DB=mycelia_test - - DISABLE_SPEAKER_RECOGNITION=false - - SPEAKER_SERVICE_URL=https://localhost:8085 + # Speaker recognition controlled by config.yml (disabled in test config for CI performance) + - SPEAKER_SERVICE_URL=http://speaker-service-test:8085 # Set low inactivity timeout for tests (2 seconds instead of 60) - SPEECH_INACTIVITY_THRESHOLD_SECONDS=2 # Wait for audio queue to drain before timing out (test mode) @@ -166,6 +196,8 @@ services: condition: service_started qdrant-test: condition: service_started + speaker-service-test: + condition: service_healthy restart: unless-stopped # Mycelia - AI memory and timeline service (test environment) @@ -238,6 +270,11 @@ services: # condition: service_healthy # restart: unless-stopped +# Use default bridge network for test isolation (no external network dependency) +networks: + default: + driver: bridge + # CI Considerations (for future implementation): # - GitHub Actions can run these services in isolated containers # - Port conflicts won't exist in CI since each job runs in isolation diff --git a/backends/advanced/docker-compose.yml b/backends/advanced/docker-compose.yml index 8d4bc42f..f46a23fa 100644 --- a/backends/advanced/docker-compose.yml +++ b/backends/advanced/docker-compose.yml @@ -12,11 +12,9 @@ services: - ./data/audio_chunks:/app/audio_chunks - ./data/debug_dir:/app/debug_dir - ./data:/app/data + - ../../config/config.yml:/app/config.yml # Removed :ro to allow UI config saving environment: - DEEPGRAM_API_KEY=${DEEPGRAM_API_KEY} - - MISTRAL_API_KEY=${MISTRAL_API_KEY} - - MISTRAL_MODEL=${MISTRAL_MODEL} - - TRANSCRIPTION_PROVIDER=${TRANSCRIPTION_PROVIDER} - PARAKEET_ASR_URL=${PARAKEET_ASR_URL} - OLLAMA_BASE_URL=${OLLAMA_BASE_URL} - HF_TOKEN=${HF_TOKEN} @@ -24,10 +22,7 @@ services: - ADMIN_PASSWORD=${ADMIN_PASSWORD} - ADMIN_EMAIL=${ADMIN_EMAIL} - AUTH_SECRET_KEY=${AUTH_SECRET_KEY} - - LLM_PROVIDER=${LLM_PROVIDER} - OPENAI_API_KEY=${OPENAI_API_KEY} - - OPENAI_BASE_URL=${OPENAI_BASE_URL} - - OPENAI_MODEL=${OPENAI_MODEL} - NEO4J_HOST=${NEO4J_HOST} - NEO4J_USER=${NEO4J_USER} - NEO4J_PASSWORD=${NEO4J_PASSWORD} @@ -40,8 +35,6 @@ services: condition: service_healthy redis: condition: service_healthy - # neo4j-mem0: - # condition: service_started healthcheck: test: ["CMD", "curl", "-f", "http://localhost:8000/readiness"] interval: 30s @@ -67,15 +60,12 @@ services: - ./start-workers.sh:/app/start-workers.sh - ./data/audio_chunks:/app/audio_chunks - ./data:/app/data + - ../../config/config.yml:/app/config.yml # Removed :ro for consistency environment: - DEEPGRAM_API_KEY=${DEEPGRAM_API_KEY} - - MISTRAL_API_KEY=${MISTRAL_API_KEY} - - MISTRAL_MODEL=${MISTRAL_MODEL} - - TRANSCRIPTION_PROVIDER=${TRANSCRIPTION_PROVIDER} + - PARAKEET_ASR_URL=${PARAKEET_ASR_URL} - OPENAI_API_KEY=${OPENAI_API_KEY} - - OPENAI_BASE_URL=${OPENAI_BASE_URL} - - OPENAI_MODEL=${OPENAI_MODEL} - - LLM_PROVIDER=${LLM_PROVIDER} + - GROQ_API_KEY=${GROQ_API_KEY} - REDIS_URL=redis://redis:6379/0 depends_on: redis: @@ -177,22 +167,28 @@ services: timeout: 3s retries: 5 - ## Additional - - # neo4j-mem0: - # image: neo4j:5.15-community - # ports: - # - "7474:7474" # HTTP - # - "7687:7687" # Bolt - # environment: - # - NEO4J_AUTH=neo4j/${NEO4J_PASSWORD:-password} - # - NEO4J_PLUGINS=["apoc"] - # - NEO4J_dbms_security_procedures_unrestricted=apoc.* - # - NEO4J_dbms_security_procedures_allowlist=apoc.* - # volumes: - # - ./data/neo4j_data:/data - # - ./data/neo4j_logs:/logs - # restart: unless-stopped + neo4j-mem0: + image: neo4j:5.15-community + hostname: neo4j-mem0 + ports: + - "7474:7474" # HTTP + - "7687:7687" # Bolt + environment: + - NEO4J_AUTH=neo4j/${NEO4J_PASSWORD:-password} + - NEO4J_PLUGINS=["apoc"] + - NEO4J_dbms_security_procedures_unrestricted=apoc.* + - NEO4J_dbms_security_procedures_allowlist=apoc.* + - NEO4J_server_default__listen__address=0.0.0.0 + - NEO4J_server_bolt_listen__address=0.0.0.0:7687 + - NEO4J_server_http_listen__address=0.0.0.0:7474 + - NEO4J_dbms_memory_heap_initial__size=512m + - NEO4J_dbms_memory_heap_max__size=2G + volumes: + - ./data/neo4j_data:/data + - ./data/neo4j_logs:/logs + restart: unless-stopped + profiles: + - obsidian # ollama: # image: ollama/ollama:latest @@ -211,21 +207,11 @@ services: - # Use tailscale instead - # UNCOMMENT OUT FOR LOCAL DEMO - EXPOSES to internet - # ngrok: - # image: ngrok/ngrok:latest - # depends_on: [chronicle-backend, proxy] - # ports: - # - "4040:4040" # Ngrok web interface - # environment: - # - NGROK_AUTHTOKEN=${NGROK_AUTHTOKEN} - # command: "http proxy:80 --url=${NGROK_URL} --basic-auth=${NGROK_BASIC_AUTH}" - # Shared network for cross-project communication networks: default: name: chronicle-network + external: true volumes: ollama_data: diff --git a/backends/advanced/init-https.sh b/backends/advanced/init-https.sh index cfeebf61..d1c1b5af 100755 --- a/backends/advanced/init-https.sh +++ b/backends/advanced/init-https.sh @@ -70,17 +70,8 @@ else echo " 2. Add: CORS_ORIGINS=https://localhost,https://localhost:443,https://127.0.0.1,https://$TAILSCALE_IP" fi -# Create memory_config.yaml from template if it doesn't exist echo "" -echo "📄 Step 4: Checking memory configuration..." -if [ ! -f "memory_config.yaml" ] && [ -f "memory_config.yaml.template" ]; then - cp memory_config.yaml.template memory_config.yaml - echo "✅ memory_config.yaml created from template" -elif [ -f "memory_config.yaml" ]; then - echo "✅ memory_config.yaml already exists" -else - echo "⚠️ Warning: memory_config.yaml.template not found" -fi +echo "📄 Step 4: Memory configuration now lives in config.yml (memory section)" echo "" echo "🎉 Initialization complete!" @@ -102,4 +93,4 @@ echo " - Chronicle Backend: Internal (proxied through nginx)" echo " - Web Dashboard: https://localhost/ or https://$TAILSCALE_IP/" echo " - WebSocket Audio: wss://localhost/ws_pcm or wss://$TAILSCALE_IP/ws_pcm" echo "" -echo "📚 For more details, see: Docs/HTTPS_SETUP.md" \ No newline at end of file +echo "📚 For more details, see: Docs/HTTPS_SETUP.md" diff --git a/backends/advanced/init.py b/backends/advanced/init.py index 0d7e6996..fe04fd15 100644 --- a/backends/advanced/init.py +++ b/backends/advanced/init.py @@ -15,24 +15,40 @@ from pathlib import Path from typing import Any, Dict +import yaml from dotenv import get_key, set_key from rich.console import Console from rich.panel import Panel from rich.prompt import Confirm, Prompt from rich.text import Text +# Add repo root to path for config_manager import +sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent)) +from config_manager import ConfigManager + class ChronicleSetup: def __init__(self, args=None): self.console = Console() self.config: Dict[str, Any] = {} self.args = args or argparse.Namespace() - + self.config_yml_path = Path("../../config/config.yml") # Main config at config/config.yml + # Check if we're in the right directory if not Path("pyproject.toml").exists() or not Path("src").exists(): self.console.print("[red][ERROR][/red] Please run this script from the backends/advanced directory") sys.exit(1) + # Initialize ConfigManager (single source of truth for config.yml) + self.config_manager = ConfigManager(service_path="backends/advanced") + self.console.print(f"[blue][INFO][/blue] Using config.yml at: {self.config_manager.config_yml_path}") + + # Verify config.yml exists - fail fast if missing + if not self.config_manager.config_yml_path.exists(): + self.console.print(f"[red][ERROR][/red] config.yml not found at {self.config_manager.config_yml_path}") + self.console.print("[red][ERROR][/red] Run wizard.py from project root to create config.yml") + sys.exit(1) + def print_header(self, title: str): """Print a colorful header""" self.console.print() @@ -120,6 +136,7 @@ def mask_api_key(self, key: str, show_chars: int = 5) -> str: return f"{key_clean[:show_chars]}{'*' * min(15, len(key_clean) - show_chars * 2)}{key_clean[-show_chars:]}" + def setup_authentication(self): """Configure authentication settings""" self.print_section("Authentication Setup") @@ -133,16 +150,19 @@ def setup_authentication(self): self.console.print("[green][SUCCESS][/green] Admin account configured") def setup_transcription(self): - """Configure transcription provider""" + """Configure transcription provider - updates config.yml and .env""" self.print_section("Speech-to-Text Configuration") - + + self.console.print("[blue][INFO][/blue] Provider selection is configured in config.yml (defaults.stt)") + self.console.print("[blue][INFO][/blue] API keys are stored in .env") + self.console.print() + choices = { - "1": "Deepgram (recommended - high quality, requires API key)", - "2": "Mistral (Voxtral models - requires API key)", - "3": "Offline (Parakeet ASR - requires GPU, runs locally)", - "4": "None (skip transcription setup)" + "1": "Deepgram (recommended - high quality, cloud-based)", + "2": "Offline (Parakeet ASR - requires GPU, runs locally)", + "3": "None (skip transcription setup)" } - + choice = self.prompt_choice("Choose your transcription provider:", choices, "1") if choice == "1": @@ -160,60 +180,50 @@ def setup_transcription(self): api_key = self.prompt_value("Deepgram API key (leave empty to skip)", "") if api_key: - self.config["TRANSCRIPTION_PROVIDER"] = "deepgram" + # Write API key to .env self.config["DEEPGRAM_API_KEY"] = api_key - self.console.print("[green][SUCCESS][/green] Deepgram configured") - else: - self.console.print("[yellow][WARNING][/yellow] No API key provided - transcription will not work") - - elif choice == "2": - self.config["TRANSCRIPTION_PROVIDER"] = "mistral" - self.console.print("[blue][INFO][/blue] Mistral selected") - self.console.print("Get your API key from: https://console.mistral.ai/") - - # Check for existing API key - existing_key = self.read_existing_env_value("MISTRAL_API_KEY") - if existing_key and existing_key not in ['your_mistral_api_key_here', 'your-mistral-key-here']: - masked_key = self.mask_api_key(existing_key) - prompt_text = f"Mistral API key ({masked_key}) [press Enter to reuse, or enter new]" - api_key_input = self.prompt_value(prompt_text, "") - api_key = api_key_input if api_key_input else existing_key - else: - api_key = self.prompt_value("Mistral API key (leave empty to skip)", "") - model = self.prompt_value("Mistral model", "voxtral-mini-2507") + # Update config.yml to use Deepgram + self.config_manager.update_config_defaults({"stt": "stt-deepgram"}) - if api_key: - self.config["MISTRAL_API_KEY"] = api_key - self.config["MISTRAL_MODEL"] = model - self.console.print("[green][SUCCESS][/green] Mistral configured") + self.console.print("[green][SUCCESS][/green] Deepgram configured in config.yml and .env") + self.console.print("[blue][INFO][/blue] Set defaults.stt: stt-deepgram") else: self.console.print("[yellow][WARNING][/yellow] No API key provided - transcription will not work") - elif choice == "3": - self.config["TRANSCRIPTION_PROVIDER"] = "parakeet" + elif choice == "2": self.console.print("[blue][INFO][/blue] Offline Parakeet ASR selected") parakeet_url = self.prompt_value("Parakeet ASR URL", "http://host.docker.internal:8767") + + # Write URL to .env for ${PARAKEET_ASR_URL} placeholder in config.yml self.config["PARAKEET_ASR_URL"] = parakeet_url + + # Update config.yml to use Parakeet + self.config_manager.update_config_defaults({"stt": "stt-parakeet-batch"}) + + self.console.print("[green][SUCCESS][/green] Parakeet configured in config.yml and .env") + self.console.print("[blue][INFO][/blue] Set defaults.stt: stt-parakeet-batch") self.console.print("[yellow][WARNING][/yellow] Remember to start Parakeet service: cd ../../extras/asr-services && docker compose up parakeet") - elif choice == "4": + elif choice == "3": self.console.print("[blue][INFO][/blue] Skipping transcription setup") def setup_llm(self): - """Configure LLM provider""" + """Configure LLM provider - updates config.yml and .env""" self.print_section("LLM Provider Configuration") - + + self.console.print("[blue][INFO][/blue] LLM configuration will be saved to config.yml") + self.console.print() + choices = { "1": "OpenAI (GPT-4, GPT-3.5 - requires API key)", - "2": "Ollama (local models - requires Ollama server)", + "2": "Ollama (local models - runs locally)", "3": "Skip (no memory extraction)" } - - choice = self.prompt_choice("Choose your LLM provider for memory extraction:", choices, "1") + + choice = self.prompt_choice("Which LLM provider will you use?", choices, "1") if choice == "1": - self.config["LLM_PROVIDER"] = "openai" self.console.print("[blue][INFO][/blue] OpenAI selected") self.console.print("Get your API key from: https://platform.openai.com/api-keys") @@ -227,72 +237,90 @@ def setup_llm(self): else: api_key = self.prompt_value("OpenAI API key (leave empty to skip)", "") - model = self.prompt_value("OpenAI model", "gpt-5-mini") - base_url = self.prompt_value("OpenAI base URL (for proxies/compatible APIs)", "https://api.openai.com/v1") - if api_key: self.config["OPENAI_API_KEY"] = api_key - self.config["OPENAI_MODEL"] = model - self.config["OPENAI_BASE_URL"] = base_url - self.console.print("[green][SUCCESS][/green] OpenAI configured") + # Update config.yml to use OpenAI models + self.config_manager.update_config_defaults({"llm": "openai-llm", "embedding": "openai-embed"}) + self.console.print("[green][SUCCESS][/green] OpenAI configured in config.yml") + self.console.print("[blue][INFO][/blue] Set defaults.llm: openai-llm") + self.console.print("[blue][INFO][/blue] Set defaults.embedding: openai-embed") else: self.console.print("[yellow][WARNING][/yellow] No API key provided - memory extraction will not work") elif choice == "2": - self.config["LLM_PROVIDER"] = "ollama" self.console.print("[blue][INFO][/blue] Ollama selected") - - base_url = self.prompt_value("Ollama server URL", "http://host.docker.internal:11434") - if not base_url.endswith("/v1"): - base_url = base_url.rstrip("/") + "/v1" - self.console.print(f"[blue][INFO][/blue] Automatically appending /v1 to Ollama URL: {base_url}") - - model = self.prompt_value("Ollama model", "llama3.2") - - embedder_model = self.prompt_value("Ollama embedder model", "nomic-embed-text:latest") - - self.config["OLLAMA_BASE_URL"] = base_url - self.config["OLLAMA_MODEL"] = model - self.config["OLLAMA_EMBEDDER_MODEL"] = embedder_model - self.console.print("[green][SUCCESS][/green] Ollama configured") - self.console.print("[yellow][WARNING][/yellow] Make sure Ollama is running and all required models (LLM and embedder) are pulled") + # Update config.yml to use Ollama models + self.config_manager.update_config_defaults({"llm": "local-llm", "embedding": "local-embed"}) + self.console.print("[green][SUCCESS][/green] Ollama configured in config.yml") + self.console.print("[blue][INFO][/blue] Set defaults.llm: local-llm") + self.console.print("[blue][INFO][/blue] Set defaults.embedding: local-embed") + self.console.print("[yellow][WARNING][/yellow] Make sure Ollama is running and models are pulled") elif choice == "3": self.console.print("[blue][INFO][/blue] Skipping LLM setup - memory extraction disabled") + # Disable memory extraction in config.yml + self.config_manager.update_memory_config({"extraction": {"enabled": False}}) def setup_memory(self): - """Configure memory provider""" + """Configure memory provider - updates config.yml""" self.print_section("Memory Storage Configuration") - + choices = { "1": "Chronicle Native (Qdrant + custom extraction)", - "2": "OpenMemory MCP (cross-client compatible, external server)" + "2": "OpenMemory MCP (cross-client compatible, external server)", + "3": "Mycelia (Timeline-based memory with speaker diarization)" } - + choice = self.prompt_choice("Choose your memory storage backend:", choices, "1") if choice == "1": - self.config["MEMORY_PROVIDER"] = "chronicle" self.console.print("[blue][INFO][/blue] Chronicle Native memory provider selected") - + qdrant_url = self.prompt_value("Qdrant URL", "qdrant") self.config["QDRANT_BASE_URL"] = qdrant_url - self.console.print("[green][SUCCESS][/green] Chronicle memory provider configured") + + # Update config.yml (also updates .env automatically) + self.config_manager.update_memory_config({"provider": "chronicle"}) + self.console.print("[green][SUCCESS][/green] Chronicle memory provider configured in config.yml and .env") elif choice == "2": - self.config["MEMORY_PROVIDER"] = "openmemory_mcp" self.console.print("[blue][INFO][/blue] OpenMemory MCP selected") - + mcp_url = self.prompt_value("OpenMemory MCP server URL", "http://host.docker.internal:8765") client_name = self.prompt_value("OpenMemory client name", "chronicle") user_id = self.prompt_value("OpenMemory user ID", "openmemory") - - self.config["OPENMEMORY_MCP_URL"] = mcp_url - self.config["OPENMEMORY_CLIENT_NAME"] = client_name - self.config["OPENMEMORY_USER_ID"] = user_id - self.console.print("[green][SUCCESS][/green] OpenMemory MCP configured") + timeout = self.prompt_value("OpenMemory timeout (seconds)", "30") + + # Update config.yml with OpenMemory MCP settings (also updates .env automatically) + self.config_manager.update_memory_config({ + "provider": "openmemory_mcp", + "openmemory_mcp": { + "server_url": mcp_url, + "client_name": client_name, + "user_id": user_id, + "timeout": int(timeout) + } + }) + self.console.print("[green][SUCCESS][/green] OpenMemory MCP configured in config.yml and .env") self.console.print("[yellow][WARNING][/yellow] Remember to start OpenMemory: cd ../../extras/openmemory-mcp && docker compose up -d") + elif choice == "3": + self.console.print("[blue][INFO][/blue] Mycelia memory provider selected") + + mycelia_url = self.prompt_value("Mycelia API URL", "http://localhost:5173") + timeout = self.prompt_value("Mycelia timeout (seconds)", "30") + + # Update config.yml with Mycelia settings (also updates .env automatically) + self.config_manager.update_memory_config({ + "provider": "mycelia", + "mycelia": { + "api_url": mycelia_url, + "timeout": int(timeout) + } + }) + self.console.print("[green][SUCCESS][/green] Mycelia memory provider configured in config.yml and .env") + self.console.print("[yellow][WARNING][/yellow] Make sure Mycelia is running at the configured URL") + def setup_optional_services(self): """Configure optional services""" self.print_section("Optional Services") @@ -314,11 +342,55 @@ def setup_optional_services(self): self.console.print("[green][SUCCESS][/green] Speaker Recognition configured") self.console.print("[blue][INFO][/blue] Start with: cd ../../extras/speaker-recognition && docker compose up -d") - # Check if ASR service URL provided via args + # Check if ASR service URL provided via args if hasattr(self.args, 'parakeet_asr_url') and self.args.parakeet_asr_url: self.config["PARAKEET_ASR_URL"] = self.args.parakeet_asr_url self.console.print(f"[green][SUCCESS][/green] Parakeet ASR configured via args: {self.args.parakeet_asr_url}") + def setup_obsidian(self): + """Configure Obsidian/Neo4j integration""" + # Check if enabled via command line + if hasattr(self.args, 'enable_obsidian') and self.args.enable_obsidian: + enable_obsidian = True + neo4j_password = getattr(self.args, 'neo4j_password', None) + + if not neo4j_password: + self.console.print("[yellow][WARNING][/yellow] --enable-obsidian provided but no password") + neo4j_password = self.prompt_password("Neo4j password (min 8 chars)") + else: + # Interactive prompt (fallback) + self.console.print() + self.console.print("[bold cyan]Obsidian/Neo4j Integration[/bold cyan]") + self.console.print("Enable graph-based knowledge management for Obsidian vault notes") + self.console.print() + + try: + enable_obsidian = Confirm.ask("Enable Obsidian/Neo4j integration?", default=False) + except EOFError: + self.console.print("Using default: No") + enable_obsidian = False + + if enable_obsidian: + neo4j_password = self.prompt_password("Neo4j password (min 8 chars)") + + if enable_obsidian: + # Update .env with credentials only (secrets, not feature flags) + self.config["NEO4J_HOST"] = "neo4j-mem0" + self.config["NEO4J_USER"] = "neo4j" + self.config["NEO4J_PASSWORD"] = neo4j_password + + # Update config.yml with feature flag (source of truth) - auto-saves via ConfigManager + self.config_manager.update_memory_config({ + "obsidian": { + "enabled": True, + "neo4j_host": "neo4j-mem0", + "timeout": 30 + } + }) + + self.console.print("[green][SUCCESS][/green] Obsidian/Neo4j configured") + self.console.print("[blue][INFO][/blue] Neo4j will start automatically with --profile obsidian") + def setup_network(self): """Configure network settings""" self.print_section("Network Configuration") @@ -336,18 +408,26 @@ def setup_https(self): else: # Interactive configuration self.print_section("HTTPS Configuration (Optional)") - + try: enable_https = Confirm.ask("Enable HTTPS for microphone access?", default=False) except EOFError: self.console.print("Using default: No") enable_https = False - + if enable_https: self.console.print("[blue][INFO][/blue] HTTPS enables microphone access in browsers") self.console.print("[blue][INFO][/blue] For distributed deployments, use your Tailscale IP (e.g., 100.64.1.2)") self.console.print("[blue][INFO][/blue] For local-only access, use 'localhost'") - server_ip = self.prompt_value("Server IP/Domain for SSL certificate (Tailscale IP or localhost)", "localhost") + + # Check for existing SERVER_IP + existing_ip = self.read_existing_env_value("SERVER_IP") + if existing_ip and existing_ip not in ['localhost', 'your-server-ip-here']: + prompt_text = f"Server IP/Domain for SSL certificate ({existing_ip}) [press Enter to reuse, or enter new]" + server_ip_input = self.prompt_value(prompt_text, "") + server_ip = server_ip_input if server_ip_input else existing_ip + else: + server_ip = self.prompt_value("Server IP/Domain for SSL certificate (Tailscale IP or localhost)", "localhost") if enable_https: @@ -455,11 +535,11 @@ def generate_env_file(self): self.console.print("[green][SUCCESS][/green] .env file configured successfully with secure permissions") + # Note: config.yml is automatically saved by ConfigManager when updates are made + self.console.print("[blue][INFO][/blue] Configuration saved to config.yml and .env (via ConfigManager)") + def copy_config_templates(self): """Copy other configuration files""" - if not Path("memory_config.yaml").exists() and Path("memory_config.yaml.template").exists(): - shutil.copy2("memory_config.yaml.template", "memory_config.yaml") - self.console.print("[green][SUCCESS][/green] memory_config.yaml created") if not Path("diarization_config.json").exists() and Path("diarization_config.json.template").exists(): shutil.copy2("diarization_config.json.template", "diarization_config.json") @@ -469,11 +549,37 @@ def show_summary(self): """Show configuration summary""" self.print_section("Configuration Summary") self.console.print() - + self.console.print(f"✅ Admin Account: {self.config.get('ADMIN_EMAIL', 'Not configured')}") - self.console.print(f"✅ Transcription: {self.config.get('TRANSCRIPTION_PROVIDER', 'Not configured')}") - self.console.print(f"✅ LLM Provider: {self.config.get('LLM_PROVIDER', 'Not configured')}") - self.console.print(f"✅ Memory Provider: {self.config.get('MEMORY_PROVIDER', 'chronicle')}") + + # Get current config from ConfigManager (single source of truth) + config_yml = self.config_manager.get_full_config() + + # Show transcription from config.yml + stt_default = config_yml.get("defaults", {}).get("stt", "not set") + stt_model = next( + (m for m in config_yml.get("models", []) if m.get("name") == stt_default), + None + ) + stt_provider = stt_model.get("model_provider", "unknown") if stt_model else "not configured" + self.console.print(f"✅ Transcription: {stt_provider} ({stt_default}) - config.yml") + + # Show LLM config from config.yml + llm_default = config_yml.get("defaults", {}).get("llm", "not set") + embedding_default = config_yml.get("defaults", {}).get("embedding", "not set") + self.console.print(f"✅ LLM: {llm_default} (config.yml)") + self.console.print(f"✅ Embedding: {embedding_default} (config.yml)") + + # Show memory provider from config.yml + memory_provider = config_yml.get("memory", {}).get("provider", "chronicle") + self.console.print(f"✅ Memory Provider: {memory_provider} (config.yml)") + + # Show Obsidian/Neo4j status (read from config.yml) + obsidian_config = config_yml.get("memory", {}).get("obsidian", {}) + if obsidian_config.get("enabled", False): + neo4j_host = obsidian_config.get("neo4j_host", "not set") + self.console.print(f"✅ Obsidian/Neo4j: Enabled ({neo4j_host})") + # Auto-determine URLs based on HTTPS configuration if self.config.get('HTTPS_ENABLED') == 'true': server_ip = self.config.get('SERVER_IP', 'localhost') @@ -489,9 +595,18 @@ def show_next_steps(self): """Show next steps""" self.print_section("Next Steps") self.console.print() - + + # Get current config from ConfigManager (single source of truth) + config_yml = self.config_manager.get_full_config() + self.console.print("1. Start the main services:") - self.console.print(" [cyan]docker compose up --build -d[/cyan]") + # Include --profile obsidian if Obsidian is enabled (read from config.yml) + obsidian_enabled = config_yml.get("memory", {}).get("obsidian", {}).get("enabled", False) + if obsidian_enabled: + self.console.print(" [cyan]docker compose --profile obsidian up --build -d[/cyan]") + self.console.print(" [dim](Includes Neo4j for Obsidian integration)[/dim]") + else: + self.console.print(" [cyan]docker compose up --build -d[/cyan]") self.console.print() # Auto-determine URLs for next steps @@ -538,6 +653,7 @@ def run(self): self.setup_llm() self.setup_memory() self.setup_optional_services() + self.setup_obsidian() self.setup_network() self.setup_https() @@ -553,6 +669,10 @@ def run(self): self.console.print() self.console.print("[green][SUCCESS][/green] Setup complete! 🎉") self.console.print() + self.console.print("📝 [bold]Configuration files updated:[/bold]") + self.console.print(f" • .env - API keys and environment variables") + self.console.print(f" • ../../config/config.yml - Model and memory provider configuration") + self.console.print() self.console.print("For detailed documentation, see:") self.console.print(" • Docs/quickstart.md") self.console.print(" • MEMORY_PROVIDERS.md") @@ -576,9 +696,13 @@ def main(): help="Parakeet ASR service URL (default: prompt user)") parser.add_argument("--enable-https", action="store_true", help="Enable HTTPS configuration (default: prompt user)") - parser.add_argument("--server-ip", + parser.add_argument("--server-ip", help="Server IP/domain for SSL certificate (default: prompt user)") - + parser.add_argument("--enable-obsidian", action="store_true", + help="Enable Obsidian/Neo4j integration (default: prompt user)") + parser.add_argument("--neo4j-password", + help="Neo4j password (default: prompt user)") + args = parser.parse_args() setup = ChronicleSetup(args) @@ -586,4 +710,4 @@ def main(): if __name__ == "__main__": - main() \ No newline at end of file + main() diff --git a/backends/advanced/memory_config.yaml.template b/backends/advanced/memory_config.yaml.template deleted file mode 100644 index 84ab963c..00000000 --- a/backends/advanced/memory_config.yaml.template +++ /dev/null @@ -1,247 +0,0 @@ -# Memory Extraction Configuration -# This file controls how memories and facts are extracted from conversations -# -# REQUIRED ENVIRONMENT VARIABLES: -# - LLM_PROVIDER: Set to "openai" or "ollama" -# - For OpenAI: OPENAI_API_KEY (required), OPENAI_MODEL (optional, defaults to config) -# - For Ollama: OPENAI_BASE_URL or OLLAMA_BASE_URL (required), OPENAI_MODEL (optional, defaults to config) -# - QDRANT_BASE_URL: Qdrant service URL (e.g., "qdrant" for Docker) -# -# OPTIONAL ENVIRONMENT VARIABLES: -# - MEM0_ORGANIZATION_ID: Organization ID for mem0 (default: "friend-lite-org") -# - MEM0_PROJECT_ID: Project ID for mem0 (default: "audio-conversations") -# - MEM0_APP_ID: Application ID for mem0 (default: "omi-backend") -# - OPENAI_EMBEDDER_MODEL: OpenAI embedder model (default: "text-embedding-3-small") -# - OLLAMA_EMBEDDER_MODEL: Ollama embedder model (default: "nomic-embed-text:latest") -# - NEO4J_HOST, NEO4J_USER, NEO4J_PASSWORD: For graph storage (optional) - -# General memory extraction settings -memory_extraction: - # Whether to extract general memories (conversation summaries, topics, etc.) - enabled: true - - # Main prompt for memory extraction - INCLUDES JSON format and few-shot examples for mem0 compatibility - prompt: | - You are a Personal Information Organizer, specialized in accurately storing facts, user memories, and preferences. Your primary role is to extract relevant pieces of information from conversations and organize them into distinct, manageable facts. This allows for easy retrieval and personalization in future interactions. - - **Types of Information to Remember:** - - 1. **Personal Preferences**: Keep track of likes, dislikes, and specific preferences in various categories such as food, products, activities, hobbies, and entertainment. - 2. **Important Personal Details**: Remember significant personal information like names, relationships, and important dates. - 3. **Plans and Intentions**: Note upcoming events, trips, goals, and any plans the user has shared. - 4. **Activity and Service Preferences**: Recall preferences for dining, travel, hobbies, crafts, DIY projects, and other services. - 5. **Health and Wellness Preferences**: Keep a record of dietary restrictions, fitness routines, and other wellness-related information. - 6. **Professional Details**: Remember job titles, work habits, career goals, and other professional information. - 7. **Learning and Skills**: Track skills they're developing, tutorials they follow, techniques they're practicing. - 8. **Entertainment and Media**: Remember favorite movies, shows, books, games, creators, channels they follow. - 9. **Interests from Content**: Extract personal interests even from tutorial, educational, or entertainment content they engage with. - - **Output Format:** Return the facts and preferences in JSON format as shown in examples below. - - **Examples:** - - Input: Hi. - Output: {"facts" : []} - - Input: There are branches in trees. - Output: {"facts" : []} - - Input: Hi, I am looking for a restaurant in San Francisco. - Output: {"facts" : ["Looking for a restaurant in San Francisco"]} - - Input: Hi, my name is John. I am a software engineer. - Output: {"facts" : ["Name is John", "Is a software engineer"]} - - Input: My favourite movies are Inception and Interstellar. - Output: {"facts" : ["Favourite movies are Inception and Interstellar"]} - - Input: I've been watching this YouTube channel about rug tufting. They compared cheap versus expensive kits and I found it really interesting. The expensive one was $470 but worked much better than the $182 cheap kit. - Output: {"facts" : ["Interested in rug tufting and DIY crafts", "Watches tutorial content on YouTube", "Values product quality comparisons", "Learning about craft equipment and pricing"]} - - Input: I'm working on a Pokemon-themed rug design. I really like Pikachu and Charmander characters. - Output: {"facts" : ["Working on Pokemon-themed craft projects", "Likes Pokemon characters Pikachu and Charmander", "Enjoys character-based creative projects"]} - - **Remember:** - - Extract facts about the USER's interests, preferences, and activities - - Include information that reveals personality traits, hobbies, and learning goals - - Even casual mentions of topics can indicate interests worth remembering - - Return empty facts array only if genuinely no personal information is present - - Focus on actionable information that helps understand the user better - - # LLM parameters for memory extraction - # Provider is controlled by LLM_PROVIDER environment variable (ollama/openai) - llm_settings: - # temperature: removed - GPT-5-mini only supports default value - # Model selection based on provider: - # - Ollama: "gemma3n:e4b", "llama3.1:latest", "llama3.2:latest", etc. - # - OpenAI: "gpt-4o-mini" (recommended), "gpt-4o", "gpt-3.5-turbo", etc. - # - # RECOMMENDATION: Set OPENAI_MODEL environment variable instead of hardcoding - # Set environment variables: LLM_PROVIDER=openai and OPENAI_MODEL=gpt-4o-mini - # model: "gemma3n:e4b" - # model: Uses OPENAI_MODEL environment variable - embedding_model: "text-embedding-3-small" - -# Fact extraction settings (structured information) -fact_extraction: - # Whether to extract structured facts separately from general memories - # ENABLED: Using proper fact extraction prompt format - enabled: true - - # Prompt for extracting structured facts - prompt: | - Extract important information from this conversation, including facts, events, and personal details. Focus on: - - Names of people and their roles/titles. Ensure to extract the names of all existing participants in the conversation, even if they're only mentioned once. - - Company names, organizations, brands, and products mentioned - - Dates and specific times - - Locations and addresses - - Numbers, quantities, and measurements - - Contact information (emails, phone numbers) - - Project names and code names - - Technical specifications or requirements - - User's interests, hobbies, and activities they mention trying or wanting to try - - Things the user likes or dislikes (preferences, opinions) - - Skills the user is learning or wants to develop - - Personal experiences and stories shared - - Recommendations given or received - - Problems they're trying to solve - - Personality traits that come through in the conversation - - Contributions by each participant to the conversation or to the task - - Return the facts in JSON format as an array of strings. If no specific facts are mentioned, return an empty JSON array []. - Make sure to not wrap the JSON in ```json or ``` or any other markdown formatting. Only return the JSON array, that's all. - - Examples of JSON output: - ["John Smith works as Software Engineer at Acme Corp", - "Project deadline is December 15th, 2024", - "Meeting scheduled for 2 PM EST on Monday", - "Budget approved for $50,000", - "The participants in the conversation were John and Rose.", - "Discussion is about DnD", - "There is a tense conversation about the upcoming demo"] - - # LLM parameters for fact extraction - llm_settings: - # temperature: removed - GPT-5-mini only supports default value - # RECOMMENDATION: Set OPENAI_MODEL environment variable instead of hardcoding - # model: "gemma3n:e4b" # Model based on LLM_PROVIDER (ollama/openai) - # model: Uses OPENAI_MODEL environment variable - embedding_model: "text-embedding-3-small" - - -# Memory categorization settings -categorization: - # Whether to automatically categorize memories - enabled: true - - # Predefined categories - categories: - - personal - - work - - meeting - - project - - learning - - social - - health - - finance - - travel - - hobbies - - crafts - - diy - - tutorials - - entertainment - - gaming - - food - - technology - - shopping - - creativity - - other - - # Prompt for categorizing memories - prompt: | - Categorize this conversation into one or more of these categories: - personal, work, meeting, project, learning, social, health, finance, travel, other - - Return only the category names, comma-separated. - Examples: "work, meeting" or "personal, health" or "project" - - # LLM parameters for categorization - llm_settings: - # temperature: removed - GPT-5-mini only supports default value - # model: "gemma3n:e4b" # Model based on LLM_PROVIDER (ollama/openai) - # model: Uses OPENAI_MODEL environment variable - embedding_model: "text-embedding-3-small" - -# Quality control settings -quality_control: - # Minimum conversation length (in characters) to process - # MODIFIED: Reduced from 50 to 1 to process almost all transcripts - min_conversation_length: 1 - - # Maximum conversation length (in characters) to process - max_conversation_length: 50000 - - # Whether to skip conversations that are mostly silence/filler - # MODIFIED: Disabled to ensure all transcripts are processed - skip_low_content: false - - # Minimum meaningful content ratio (0.0-1.0) - # MODIFIED: Reduced to 0.0 to process all content - min_content_ratio: 0.0 - - # Skip conversations with these patterns - # MODIFIED: Removed most patterns to ensure all transcripts are processed - skip_patterns: - # Only skip completely empty patterns - removed test patterns to ensure all content is processed - [] - -# Processing settings -processing: - # Whether to process memories in parallel - parallel_processing: true - - # Maximum number of concurrent processing tasks - reduced to avoid overwhelming Ollama - max_concurrent_tasks: 1 - - # Timeout for memory processing (seconds) - generous timeout for Ollama processing - processing_timeout: 600 - - # Whether to retry failed extractions - retry_failed: true - - # Maximum number of retries - max_retries: 2 - - # Delay between retries (seconds) - retry_delay: 5 - -# Storage settings -storage: - # Whether to store detailed extraction metadata - store_metadata: true - - # Whether to store the original prompts used - store_prompts: true - - # Whether to store LLM responses - store_llm_responses: true - - # Whether to store processing timing information - store_timing: true - -# Debug settings -debug: - # Whether to enable debug tracking - enabled: true - - # Debug database path - db_path: "/app/data/debug_dir/memory_debug.db" - - # Log level for memory processing - log_level: "INFO" # DEBUG, INFO, WARNING, ERROR - - # Whether to log full conversations (privacy consideration) - log_full_conversations: false - - # Whether to log extracted memories - log_extracted_memories: true \ No newline at end of file diff --git a/backends/advanced/nginx.conf.template b/backends/advanced/nginx.conf.template index 8c2d825d..e5a3e025 100644 --- a/backends/advanced/nginx.conf.template +++ b/backends/advanced/nginx.conf.template @@ -43,8 +43,8 @@ http { } # Upstream services - upstream friend_backend { - server friend-backend:8000; + upstream chronicle_backend { + server chronicle-backend:8000; } upstream friend_webui { @@ -70,7 +70,7 @@ http { # Backend API endpoints location /api/ { - proxy_pass http://friend_backend/api/; + proxy_pass http://chronicle_backend/api/; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; @@ -80,7 +80,7 @@ http { # Authentication endpoints location /auth/ { - proxy_pass http://friend_backend/auth/; + proxy_pass http://chronicle_backend/auth/; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; @@ -90,7 +90,7 @@ http { # Users endpoints location /users/ { - proxy_pass http://friend_backend/users/; + proxy_pass http://chronicle_backend/users/; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; @@ -100,7 +100,7 @@ http { # WebSocket endpoints for audio streaming location /ws_pcm { - proxy_pass http://friend_backend/ws_pcm; + proxy_pass http://chronicle_backend/ws_pcm; proxy_http_version 1.1; proxy_set_header Upgrade $http_upgrade; proxy_set_header Connection $connection_upgrade; @@ -117,7 +117,7 @@ http { } location /ws_omi { - proxy_pass http://friend_backend/ws_omi; + proxy_pass http://chronicle_backend/ws_omi; proxy_http_version 1.1; proxy_set_header Upgrade $http_upgrade; proxy_set_header Connection $connection_upgrade; @@ -135,7 +135,7 @@ http { # Legacy WebSocket endpoint location /ws { - proxy_pass http://friend_backend/ws; + proxy_pass http://chronicle_backend/ws; proxy_http_version 1.1; proxy_set_header Upgrade $http_upgrade; proxy_set_header Connection $connection_upgrade; @@ -153,7 +153,7 @@ http { # Health check endpoints location /health { - proxy_pass http://friend_backend/health; + proxy_pass http://chronicle_backend/health; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; @@ -162,7 +162,7 @@ http { # Readiness check endpoint location /readiness { - proxy_pass http://friend_backend/readiness; + proxy_pass http://chronicle_backend/readiness; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; @@ -171,7 +171,7 @@ http { # Audio file serving location /audio/ { - proxy_pass http://friend_backend/audio/; + proxy_pass http://chronicle_backend/audio/; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; diff --git a/backends/advanced/pyproject.toml b/backends/advanced/pyproject.toml index 5af2ec2e..e7bcb50a 100644 --- a/backends/advanced/pyproject.toml +++ b/backends/advanced/pyproject.toml @@ -10,6 +10,7 @@ dependencies = [ "fastmcp>=0.5.0", # MCP server for conversation access "mem0ai", # Using main branch with PR #3250 AsyncMemory fix "langchain_neo4j", + "neo4j>=5.0.0,<6.0.0", "motor>=3.7.1", "ollama>=0.4.8", "friend-lite-sdk", @@ -17,6 +18,7 @@ dependencies = [ "uvicorn>=0.34.2", "wyoming>=1.6.1", "aiohttp>=3.8.0", + "httpx>=0.28.0,<1.0.0", "fastapi-users[beanie]>=14.0.1", "PyYAML>=6.0.1", "langfuse>=3.3.0", @@ -25,6 +27,9 @@ dependencies = [ "redis>=5.0.0", "rq>=1.16.0", "soundfile>=0.12.1", + "google-api-python-client>=2.0.0", + "google-auth-oauthlib>=1.0.0", + "google-auth-httplib2>=0.2.0", "websockets>=12.0", ] @@ -51,7 +56,7 @@ profile = "black" line-length = 100 [tool.uv.sources] -mem0ai = { git = "https://github.com/AnkushMalaker/mem0.git", rev = "async-client-unbound-var-fix" } +mem0ai = { git = "https://github.com/AnkushMalaker/mem0.git", rev = "main" } [tool.poetry.dependencies] robotframework = "^6.1.1" diff --git a/backends/advanced/run-test.sh b/backends/advanced/run-test.sh index 632e9290..01204be6 100755 --- a/backends/advanced/run-test.sh +++ b/backends/advanced/run-test.sh @@ -39,7 +39,15 @@ print_info "Advanced Backend Integration Test Runner" print_info "========================================" # Load environment variables (CI or local) -# Priority: CI environment > .env.test > .env +# Priority: Command-line env vars > CI environment > .env.test > .env +# Save any pre-existing environment variables to preserve command-line overrides +_PARAKEET_ASR_URL_OVERRIDE=${PARAKEET_ASR_URL} +_DEEPGRAM_API_KEY_OVERRIDE=${DEEPGRAM_API_KEY} +_OPENAI_API_KEY_OVERRIDE=${OPENAI_API_KEY} +_LLM_PROVIDER_OVERRIDE=${LLM_PROVIDER} +_MEMORY_PROVIDER_OVERRIDE=${MEMORY_PROVIDER} +_CONFIG_FILE_OVERRIDE=${CONFIG_FILE} + if [ -n "$DEEPGRAM_API_KEY" ]; then print_info "Using environment variables from CI/environment..." elif [ -f ".env.test" ]; then @@ -59,35 +67,76 @@ else exit 1 fi -# Verify required environment variables based on configured providers -TRANSCRIPTION_PROVIDER=${TRANSCRIPTION_PROVIDER:-deepgram} +# Restore command-line overrides (these take highest priority) +if [ -n "$_PARAKEET_ASR_URL_OVERRIDE" ]; then + export PARAKEET_ASR_URL=$_PARAKEET_ASR_URL_OVERRIDE + print_info "Using command-line override: PARAKEET_ASR_URL=$PARAKEET_ASR_URL" +fi +if [ -n "$_DEEPGRAM_API_KEY_OVERRIDE" ]; then + export DEEPGRAM_API_KEY=$_DEEPGRAM_API_KEY_OVERRIDE +fi +if [ -n "$_OPENAI_API_KEY_OVERRIDE" ]; then + export OPENAI_API_KEY=$_OPENAI_API_KEY_OVERRIDE +fi +if [ -n "$_LLM_PROVIDER_OVERRIDE" ]; then + export LLM_PROVIDER=$_LLM_PROVIDER_OVERRIDE + print_info "Using command-line override: LLM_PROVIDER=$LLM_PROVIDER" +fi +if [ -n "$_MEMORY_PROVIDER_OVERRIDE" ]; then + export MEMORY_PROVIDER=$_MEMORY_PROVIDER_OVERRIDE + print_info "Using command-line override: MEMORY_PROVIDER=$MEMORY_PROVIDER" +fi +if [ -n "$_CONFIG_FILE_OVERRIDE" ]; then + export CONFIG_FILE=$_CONFIG_FILE_OVERRIDE + print_info "Using command-line override: CONFIG_FILE=$CONFIG_FILE" +fi + +# Set default CONFIG_FILE if not provided +# This allows testing with different provider combinations +# Usage: CONFIG_FILE=../../tests/configs/parakeet-ollama.yml ./run-test.sh +export CONFIG_FILE=${CONFIG_FILE:-../../config/config.yml} + +print_info "Using config file: $CONFIG_FILE" + +# Read STT provider from config.yml (source of truth) +STT_PROVIDER=$(uv run python -c " +from advanced_omi_backend.model_registry import get_models_registry +registry = get_models_registry() +if registry and registry.defaults: + stt_model = registry.get_default('stt') + if stt_model: + print(stt_model.model_provider or '') +" 2>/dev/null || echo "") + +# Fallback to environment variable for backward compatibility (will be removed) +if [ -z "$STT_PROVIDER" ]; then + STT_PROVIDER=${TRANSCRIPTION_PROVIDER:-deepgram} + print_warning "Could not read STT provider from config.yml, using TRANSCRIPTION_PROVIDER: $STT_PROVIDER" +fi + +# LLM provider can still use env var as it's not part of this refactor LLM_PROVIDER=${LLM_PROVIDER:-openai} print_info "Configured providers:" -print_info " TRANSCRIPTION_PROVIDER: $TRANSCRIPTION_PROVIDER" -print_info " LLM_PROVIDER: $LLM_PROVIDER" +print_info " STT Provider (from config.yml): $STT_PROVIDER" +print_info " LLM Provider: $LLM_PROVIDER" -# Check transcription provider API key -case "$TRANSCRIPTION_PROVIDER" in +# Check transcription provider API key based on config.yml +case "$STT_PROVIDER" in deepgram) if [ -z "$DEEPGRAM_API_KEY" ]; then - print_error "DEEPGRAM_API_KEY not set (required for TRANSCRIPTION_PROVIDER=deepgram)" + print_error "DEEPGRAM_API_KEY not set (required for STT provider: deepgram)" exit 1 fi print_info "DEEPGRAM_API_KEY length: ${#DEEPGRAM_API_KEY}" ;; - mistral) - if [ -z "$MISTRAL_API_KEY" ]; then - print_error "MISTRAL_API_KEY not set (required for TRANSCRIPTION_PROVIDER=mistral)" - exit 1 - fi - print_info "MISTRAL_API_KEY length: ${#MISTRAL_API_KEY}" - ;; - offline|parakeet) - print_info "Using offline/local transcription - no API key required" + parakeet) + print_info "Using Parakeet (local transcription) - no API key required" + PARAKEET_ASR_URL=${PARAKEET_ASR_URL:-http://localhost:8767} + print_info "PARAKEET_ASR_URL: $PARAKEET_ASR_URL" ;; *) - print_warning "Unknown TRANSCRIPTION_PROVIDER: $TRANSCRIPTION_PROVIDER" + print_warning "Unknown STT provider from config.yml: $STT_PROVIDER" ;; esac @@ -108,12 +157,7 @@ case "$LLM_PROVIDER" in ;; esac -# Ensure memory_config.yaml exists -if [ ! -f "memory_config.yaml" ] && [ -f "memory_config.yaml.template" ]; then - print_info "Creating memory_config.yaml from template..." - cp memory_config.yaml.template memory_config.yaml - print_success "memory_config.yaml created" -fi +# memory_config.yaml deprecated; using config.yml for memory settings # Ensure diarization_config.json exists if [ ! -f "diarization_config.json" ] && [ -f "diarization_config.json.template" ]; then @@ -122,9 +166,8 @@ if [ ! -f "diarization_config.json" ] && [ -f "diarization_config.json.template" print_success "diarization_config.json created" fi -# Install dependencies with uv -print_info "Installing dependencies with uv..." -uv sync --dev --group test +# Note: Robot Framework dependencies are managed via tests/test-requirements.txt +# The integration tests use Docker containers for service dependencies # Set up environment variables for testing print_info "Setting up test environment variables..." @@ -135,6 +178,9 @@ print_info "Using environment variables from .env file for test configuration" print_info "Cleaning test environment..." sudo rm -rf ./test_audio_chunks/ ./test_data/ ./test_debug_dir/ ./mongo_data_test/ ./qdrant_data_test/ ./test_neo4j/ || true +# Use unique project name to avoid conflicts with development environment +export COMPOSE_PROJECT_NAME="advanced-backend-test" + # Stop any existing test containers print_info "Stopping existing test containers..." docker compose -f docker-compose-test.yml down -v || true @@ -158,25 +204,39 @@ fi # Set environment variables for the test export DOCKER_BUILDKIT=0 -# Run the integration test with extended timeout (mem0 needs time for comprehensive extraction) -print_info "Starting integration test (timeout: 15 minutes)..." -if timeout 900 uv run pytest tests/test_integration.py::test_full_pipeline_integration -v -s --tb=short --log-cli-level=INFO; then +# Configure Robot Framework test mode +# TEST_MODE=dev: Robot tests keep containers running (cleanup handled by run-test.sh) +# This allows CLEANUP_CONTAINERS flag to work as expected +export TEST_MODE=dev + +# Run the Robot Framework integration tests with extended timeout (mem0 needs time for comprehensive extraction) +# IMPORTANT: Robot tests must be run from the repository root where backends/ and tests/ are siblings +print_info "Starting Robot Framework integration tests (timeout: 15 minutes)..." +if (cd ../.. && timeout 900 robot --outputdir test-results --loglevel INFO tests/integration/integration_test.robot); then print_success "Integration tests completed successfully!" else TEST_EXIT_CODE=$? print_error "Integration tests FAILED with exit code: $TEST_EXIT_CODE" - # Clean up test containers before exiting - print_info "Cleaning up test containers after failure..." - docker compose -f docker-compose-test.yml down -v || true - docker system prune -f || true + # Clean up test containers before exiting (unless CLEANUP_CONTAINERS=false) + if [ "${CLEANUP_CONTAINERS:-true}" != "false" ]; then + print_info "Cleaning up test containers after failure..." + docker compose -f docker-compose-test.yml down -v || true + docker system prune -f || true + else + print_warning "Skipping cleanup (CLEANUP_CONTAINERS=false) - containers left running for debugging" + fi exit $TEST_EXIT_CODE fi -# Clean up test containers -print_info "Cleaning up test containers..." -docker compose -f docker-compose-test.yml down -v || true -docker system prune -f || true +# Clean up test containers (unless CLEANUP_CONTAINERS=false) +if [ "${CLEANUP_CONTAINERS:-true}" != "false" ]; then + print_info "Cleaning up test containers..." + docker compose -f docker-compose-test.yml down -v || true + docker system prune -f || true +else + print_warning "Skipping cleanup (CLEANUP_CONTAINERS=false) - containers left running" +fi -print_success "Advanced Backend integration tests completed!" \ No newline at end of file +print_success "Advanced Backend integration tests completed!" diff --git a/backends/advanced/setup-https.sh b/backends/advanced/setup-https.sh index e0f733df..b565cddc 100755 --- a/backends/advanced/setup-https.sh +++ b/backends/advanced/setup-https.sh @@ -134,27 +134,7 @@ fi # Step 2: Memory configuration print_header "Step 2: Memory Configuration" -if [ -f "memory_config.yaml" ]; then - print_info "memory_config.yaml already exists" - if prompt_yes_no "Do you want to reset it from template?" "n"; then - backup_path=$(backup_with_timestamp "memory_config.yaml") - if [ $? -eq 0 ]; then - print_info "Backed up existing memory_config.yaml to $backup_path" - cp memory_config.yaml.template memory_config.yaml - print_success "memory_config.yaml reset from template" - else - print_error "Failed to backup memory_config.yaml file, aborting reset" - fi - fi -else - if [ -f "memory_config.yaml.template" ]; then - cp memory_config.yaml.template memory_config.yaml - print_success "memory_config.yaml created from template" - else - print_error "memory_config.yaml.template not found!" - exit 1 - fi -fi +print_info "Memory settings are managed in config.yml (memory section)." # Step 3: Diarization configuration print_header "Step 3: Diarization Configuration" @@ -295,7 +275,7 @@ print_header "Setup Complete!" echo "Configuration Summary:" echo "----------------------" echo "✅ Environment file (.env) configured" -echo "✅ Memory configuration (memory_config.yaml) ready" +echo "✅ Memory configuration (config.yml) ready" echo "✅ Diarization configuration (diarization_config.json) ready" if [ "$HTTPS_ENABLED" = true ]; then @@ -353,4 +333,4 @@ echo " - Docs/memory-configuration-guide.md" echo " - MEMORY_PROVIDERS.md" echo "" -print_success "Initialization complete! 🎉" \ No newline at end of file +print_success "Initialization complete! 🎉" diff --git a/backends/advanced/src/advanced_omi_backend/app_config.py b/backends/advanced/src/advanced_omi_backend/app_config.py index 9857417e..1e24fb54 100644 --- a/backends/advanced/src/advanced_omi_backend/app_config.py +++ b/backends/advanced/src/advanced_omi_backend/app_config.py @@ -15,6 +15,7 @@ from advanced_omi_backend.constants import OMI_CHANNELS, OMI_SAMPLE_RATE, OMI_SAMPLE_WIDTH from advanced_omi_backend.services.transcription import get_transcription_provider +from advanced_omi_backend.model_registry import get_models_registry # Load environment variables load_dotenv() @@ -51,13 +52,8 @@ def __init__(self): self.min_speech_segment_duration = float(os.getenv("MIN_SPEECH_SEGMENT_DURATION", "1.0")) self.cropping_context_padding = float(os.getenv("CROPPING_CONTEXT_PADDING", "0.1")) - # Transcription Configuration - self.transcription_provider_name = os.getenv("TRANSCRIPTION_PROVIDER") - self.deepgram_api_key = os.getenv("DEEPGRAM_API_KEY") - self.mistral_api_key = os.getenv("MISTRAL_API_KEY") - - # Get configured transcription provider - self.transcription_provider = get_transcription_provider(self.transcription_provider_name) + # Transcription Configuration (registry-based) + self.transcription_provider = get_transcription_provider(None) if self.transcription_provider: logger.info( f"✅ Using {self.transcription_provider.name} transcription provider ({self.transcription_provider.mode})" @@ -68,11 +64,10 @@ def __init__(self): # External Services Configuration self.qdrant_base_url = os.getenv("QDRANT_BASE_URL", "qdrant") self.qdrant_port = os.getenv("QDRANT_PORT", "6333") - self.memory_provider = os.getenv("MEMORY_PROVIDER", "chronicle").lower() - # Map legacy provider names to current names - if self.memory_provider in ("friend-lite", "friend_lite"): - logger.debug(f"Mapping legacy provider '{self.memory_provider}' to 'chronicle'") - self.memory_provider = "chronicle" + # Memory provider from registry + _reg = get_models_registry() + _mem = _reg.memory if _reg else {} + self.memory_provider = (_mem.get("provider") or "chronicle").lower() # Redis Configuration self.redis_url = os.getenv("REDIS_URL", "redis://localhost:6379/0") @@ -91,6 +86,9 @@ def __init__(self): # Memory service configuration self.memory_service_supports_threshold = self.memory_provider == "chronicle" + self.gdrive_credentials_path = "data/gdrive_service_account.json" + self.gdrive_scopes = ["https://www.googleapis.com/auth/drive.readonly"] + # Global configuration instance app_config = AppConfig() @@ -120,4 +118,4 @@ def get_redis_config(): 'url': app_config.redis_url, 'encoding': "utf-8", 'decode_responses': False - } \ No newline at end of file + } diff --git a/backends/advanced/src/advanced_omi_backend/auth.py b/backends/advanced/src/advanced_omi_backend/auth.py index 7c68d0b4..f1b7909a 100644 --- a/backends/advanced/src/advanced_omi_backend/auth.py +++ b/backends/advanced/src/advanced_omi_backend/auth.py @@ -50,6 +50,14 @@ def _verify_configured(var_name: str, *, optional: bool = False) -> Optional[str ADMIN_PASSWORD = _verify_configured("ADMIN_PASSWORD") ADMIN_EMAIL = _verify_configured("ADMIN_EMAIL", optional=True) or "admin@example.com" +# Accepted token issuers - comma-separated list of services whose tokens we accept +# Default: "chronicle,ushadow" (accept tokens from both chronicle and ushadow) +ACCEPTED_ISSUERS = [ + iss.strip() + for iss in os.getenv("ACCEPTED_TOKEN_ISSUERS", "chronicle,ushadow").split(",") + if iss.strip() +] +logger.info(f"Accepting tokens from issuers: {ACCEPTED_ISSUERS}") class UserManager(BaseUserManager[User, PydanticObjectId]): """User manager with minimal customization for fastapi-users.""" @@ -100,7 +108,8 @@ async def get_user_manager(user_db=Depends(get_user_db)): def get_jwt_strategy() -> JWTStrategy: """Get JWT strategy for token generation and validation.""" return JWTStrategy( - secret=SECRET_KEY, lifetime_seconds=JWT_LIFETIME_SECONDS + secret=SECRET_KEY, lifetime_seconds=JWT_LIFETIME_SECONDS, + token_audience=["fastapi-users:auth"] + ACCEPTED_ISSUERS ) diff --git a/backends/advanced/src/advanced_omi_backend/chat_service.py b/backends/advanced/src/advanced_omi_backend/chat_service.py index 1cd1a2e3..de92a4b9 100644 --- a/backends/advanced/src/advanced_omi_backend/chat_service.py +++ b/backends/advanced/src/advanced_omi_backend/chat_service.py @@ -23,12 +23,16 @@ from advanced_omi_backend.database import get_database from advanced_omi_backend.llm_client import get_llm_client from advanced_omi_backend.services.memory import get_memory_service +from advanced_omi_backend.services.memory.base import MemoryEntry +from advanced_omi_backend.services.obsidian_service import ( + get_obsidian_service, + ObsidianSearchError, +) from advanced_omi_backend.users import User logger = logging.getLogger(__name__) -# Configuration from environment variables -CHAT_TEMPERATURE = float(os.getenv("CHAT_TEMPERATURE", "0.7")) +# Configuration MAX_MEMORY_CONTEXT = 5 # Maximum number of memories to include in context MAX_CONVERSATION_HISTORY = 10 # Maximum conversation turns to keep in context @@ -280,7 +284,7 @@ async def add_message(self, message: ChatMessage) -> bool: logger.error(f"Failed to add message to session {message.session_id}: {e}") return False - async def get_relevant_memories(self, query: str, user_id: str) -> List[Dict]: + async def get_relevant_memories(self, query: str, user_id: str) -> List[MemoryEntry]: """Get relevant memories for the user's query.""" try: memories = await self.memory_service.search_memories( @@ -295,7 +299,7 @@ async def get_relevant_memories(self, query: str, user_id: str) -> List[Dict]: return [] async def format_conversation_context( - self, session_id: str, user_id: str, current_message: str + self, session_id: str, user_id: str, current_message: str, include_obsidian_memory: bool = False ) -> Tuple[str, List[str]]: """Format conversation context with memory integration.""" # Get recent conversation history @@ -303,7 +307,7 @@ async def format_conversation_context( # Get relevant memories memories = await self.get_relevant_memories(current_message, user_id) - memory_ids = [memory.get("id", "") for memory in memories if memory.get("id")] + memory_ids = [memory.id for memory in memories if memory.id] # Build context string context_parts = [] @@ -312,11 +316,34 @@ async def format_conversation_context( if memories: context_parts.append("# Relevant Personal Memories:") for i, memory in enumerate(memories, 1): - memory_text = memory.get("memory", memory.get("text", "")) + memory_text = memory.content if memory_text: context_parts.append(f"{i}. {memory_text}") context_parts.append("") + # Add Obsidian context if requested + if include_obsidian_memory: + try: + obsidian_service = get_obsidian_service() + obsidian_result = await obsidian_service.search_obsidian(current_message) + obsidian_context = obsidian_result["results"] + if obsidian_context: + context_parts.append("# Relevant Obsidian Notes:") + for entry in obsidian_context: + context_parts.append(entry) + context_parts.append("") + logger.info(f"Added {len(obsidian_context)} Obsidian notes to context") + except ObsidianSearchError as exc: + logger.error( + "Failed to get Obsidian context (%s stage): %s", + exc.stage, + exc, + ) + raise + except Exception as e: + logger.error(f"Failed to get Obsidian context: {e}") + raise e + # Add conversation history if messages: context_parts.append("# Recent Conversation:") @@ -333,7 +360,7 @@ async def format_conversation_context( return context, memory_ids async def generate_response_stream( - self, session_id: str, user_id: str, message_content: str + self, session_id: str, user_id: str, message_content: str, include_obsidian_memory: bool = False ) -> AsyncGenerator[Dict, None]: """Generate streaming response with memory context.""" if not self._initialized: @@ -352,7 +379,7 @@ async def generate_response_stream( # Format context with memories context, memory_ids = await self.format_conversation_context( - session_id, user_id, message_content + session_id, user_id, message_content, include_obsidian_memory=include_obsidian_memory ) # Send memory context used @@ -381,8 +408,7 @@ async def generate_response_stream( # Note: For now, we'll use the regular generate method # In the future, this should be replaced with actual streaming response_content = self.llm_client.generate( - prompt=full_prompt, - temperature=CHAT_TEMPERATURE + prompt=full_prompt ) # Simulate streaming by yielding chunks @@ -554,4 +580,4 @@ async def cleanup_chat_service(): if _chat_service: _chat_service._initialized = False _chat_service = None - logger.info("Chat service cleaned up") \ No newline at end of file + logger.info("Chat service cleaned up") diff --git a/backends/advanced/src/advanced_omi_backend/clients/gdrive_audio_client.py b/backends/advanced/src/advanced_omi_backend/clients/gdrive_audio_client.py new file mode 100644 index 00000000..5a6271e1 --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/clients/gdrive_audio_client.py @@ -0,0 +1,29 @@ +import os +from google.oauth2.service_account import Credentials +from googleapiclient.discovery import build +from advanced_omi_backend.app_config import get_app_config + +_drive_client_cache = None + +def get_google_drive_client(): + """Singleton Google Drive client.""" + global _drive_client_cache + + if _drive_client_cache: + return _drive_client_cache + + config = get_app_config() + + if not os.path.exists(config.gdrive_credentials_path): + raise FileNotFoundError( + f"Missing Google Drive credentials at {config.gdrive_credentials_path}" + ) + + creds = Credentials.from_service_account_file( + config.gdrive_credentials_path, + scopes=config.gdrive_scopes + ) + + _drive_client_cache = build("drive", "v3", credentials=creds) + + return _drive_client_cache diff --git a/backends/advanced/src/advanced_omi_backend/controllers/audio_controller.py b/backends/advanced/src/advanced_omi_backend/controllers/audio_controller.py index da884eb6..4810810d 100644 --- a/backends/advanced/src/advanced_omi_backend/controllers/audio_controller.py +++ b/backends/advanced/src/advanced_omi_backend/controllers/audio_controller.py @@ -40,6 +40,7 @@ async def upload_and_process_audio_files( device_name: str = "upload", auto_generate_client: bool = True, folder: str = None, + source: str = "upload" ) -> dict: """ Upload audio files and process them directly. @@ -81,8 +82,15 @@ async def upload_and_process_audio_files( # Read file content content = await file.read() + # Generate audio UUID and timestamp - audio_uuid = str(uuid.uuid4()) + if source == "gdrive": + audio_uuid = getattr(file, "audio_uuid", None) + if not audio_uuid: + audio_logger.error(f"Missing audio_uuid for gdrive file: {file.filename}") + audio_uuid = str(uuid.uuid4()) + else: + audio_uuid = str(uuid.uuid4()) timestamp = int(time.time() * 1000) # Determine output directory (with optional subfolder) @@ -98,12 +106,13 @@ async def upload_and_process_audio_files( relative_audio_path, file_path, duration = await write_audio_file( raw_audio_data=content, audio_uuid=audio_uuid, + source=source, client_id=client_id, user_id=user.user_id, user_email=user.email, timestamp=timestamp, chunk_dir=chunk_dir, - validate=True # Validate WAV format, convert stereo→mono + validate=True, # Validate WAV format, convert stereo→mono ) except AudioValidationError as e: processed_files.append({ diff --git a/backends/advanced/src/advanced_omi_backend/controllers/system_controller.py b/backends/advanced/src/advanced_omi_backend/controllers/system_controller.py index 44067a49..17b9cbcf 100644 --- a/backends/advanced/src/advanced_omi_backend/controllers/system_controller.py +++ b/backends/advanced/src/advanced_omi_backend/controllers/system_controller.py @@ -8,13 +8,15 @@ import time from datetime import UTC, datetime +import yaml +from fastapi import HTTPException + from advanced_omi_backend.config import ( load_diarization_settings_from_file, save_diarization_settings_to_file, ) +from advanced_omi_backend.model_registry import _find_config_path, load_models_config from advanced_omi_backend.models.user import User -from advanced_omi_backend.task_manager import get_task_manager -from fastapi.responses import JSONResponse logger = logging.getLogger(__name__) audio_logger = logging.getLogger("audio_processing") @@ -36,10 +38,8 @@ async def get_current_metrics(): return metrics except Exception as e: - audio_logger.error(f"Error fetching metrics: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to fetch metrics: {str(e)}"} - ) + audio_logger.exception("Error fetching metrics") + raise e async def get_auth_config(): @@ -71,10 +71,8 @@ async def get_diarization_settings(): "status": "success" } except Exception as e: - logger.error(f"Error getting diarization settings: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to get settings: {str(e)}"} - ) + logger.exception("Error getting diarization settings") + raise e async def save_diarization_settings(settings: dict): @@ -82,32 +80,24 @@ async def save_diarization_settings(settings: dict): try: # Validate settings valid_keys = { - "diarization_source", "similarity_threshold", "min_duration", "collar", + "diarization_source", "similarity_threshold", "min_duration", "collar", "min_duration_off", "min_speakers", "max_speakers" } - + for key, value in settings.items(): if key not in valid_keys: - return JSONResponse( - status_code=400, content={"error": f"Invalid setting key: {key}"} - ) - + raise HTTPException(status_code=400, detail=f"Invalid setting key: {key}") + # Type validation if key in ["min_speakers", "max_speakers"]: if not isinstance(value, int) or value < 1 or value > 20: - return JSONResponse( - status_code=400, content={"error": f"Invalid value for {key}: must be integer 1-20"} - ) + raise HTTPException(status_code=400, detail=f"Invalid value for {key}: must be integer 1-20") elif key == "diarization_source": if not isinstance(value, str) or value not in ["pyannote", "deepgram"]: - return JSONResponse( - status_code=400, content={"error": f"Invalid value for {key}: must be 'pyannote' or 'deepgram'"} - ) + raise HTTPException(status_code=400, detail=f"Invalid value for {key}: must be 'pyannote' or 'deepgram'") else: if not isinstance(value, (int, float)) or value < 0: - return JSONResponse( - status_code=400, content={"error": f"Invalid value for {key}: must be positive number"} - ) + raise HTTPException(status_code=400, detail=f"Invalid value for {key}: must be positive number") # Get current settings and merge with new values current_settings = load_diarization_settings_from_file() @@ -132,10 +122,8 @@ async def save_diarization_settings(settings: dict): } except Exception as e: - logger.error(f"Error saving diarization settings: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to save settings: {str(e)}"} - ) + logger.exception("Error saving diarization settings") + raise e async def get_speaker_configuration(user: User): @@ -147,10 +135,8 @@ async def get_speaker_configuration(user: User): "status": "success" } except Exception as e: - logger.error(f"Error getting speaker configuration for user {user.user_id}: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to get speaker configuration: {str(e)}"} - ) + logger.exception(f"Error getting speaker configuration for user {user.user_id}") + raise e async def update_speaker_configuration(user: User, primary_speakers: list[dict]): @@ -159,16 +145,12 @@ async def update_speaker_configuration(user: User, primary_speakers: list[dict]) # Validate speaker data format for speaker in primary_speakers: if not isinstance(speaker, dict): - return JSONResponse( - status_code=400, content={"error": "Each speaker must be a dictionary"} - ) + raise ValueError("Each speaker must be a dictionary") required_fields = ["speaker_id", "name", "user_id"] for field in required_fields: if field not in speaker: - return JSONResponse( - status_code=400, content={"error": f"Missing required field: {field}"} - ) + raise ValueError(f"Missing required field: {field}") # Enforce server-side user_id and add timestamp to each speaker for speaker in primary_speakers: @@ -189,10 +171,8 @@ async def update_speaker_configuration(user: User, primary_speakers: list[dict]) } except Exception as e: - logger.error(f"Error updating speaker configuration for user {user.user_id}: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to update speaker configuration: {str(e)}"} - ) + logger.exception(f"Error updating speaker configuration for user {user.user_id}") + raise e async def get_enrolled_speakers(user: User): @@ -224,13 +204,8 @@ async def get_enrolled_speakers(user: User): } except Exception as e: - logger.error(f"Error getting enrolled speakers for user {user.user_id}: {e}") - return { - "speakers": [], - "service_available": False, - "message": f"Failed to retrieve speakers: {str(e)}", - "status": "error" - } + logger.exception(f"Error getting enrolled speakers for user {user.user_id}") + raise e async def get_speaker_service_status(): @@ -272,171 +247,103 @@ async def get_speaker_service_status(): } except Exception as e: - logger.error(f"Error checking speaker service status: {e}") - return { - "service_available": False, - "healthy": False, - "message": f"Health check failed: {str(e)}", - "status": "error" - } + logger.exception("Error checking speaker service status") + raise e + # Memory Configuration Management Functions async def get_memory_config_raw(): - """Get current memory configuration YAML as plain text.""" + """Get current memory configuration (memory section of config.yml) as YAML.""" try: - from advanced_omi_backend.memory_config_loader import get_config_loader - - config_loader = get_config_loader() - config_path = config_loader.config_path - - if not os.path.exists(config_path): - return JSONResponse( - status_code=404, content={"error": f"Memory config file not found: {config_path}"} - ) - - with open(config_path, 'r') as file: - config_yaml = file.read() - + cfg_path = _find_config_path() + if not os.path.exists(cfg_path): + raise FileNotFoundError(f"Config file not found: {cfg_path}") + + with open(cfg_path, 'r') as f: + data = yaml.safe_load(f) or {} + memory_section = data.get("memory", {}) + config_yaml = yaml.safe_dump(memory_section, sort_keys=False) + return { "config_yaml": config_yaml, - "config_path": config_path, - "status": "success" + "config_path": str(cfg_path), + "section": "memory", + "status": "success", } - except Exception as e: - logger.error(f"Error reading memory config: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to read memory config: {str(e)}"} - ) + logger.exception("Error reading memory config") + raise e async def update_memory_config_raw(config_yaml: str): - """Update memory configuration YAML and hot reload.""" + """Update memory configuration in config.yml and hot reload registry.""" try: - import yaml - from advanced_omi_backend.memory_config_loader import get_config_loader - - # First validate YAML syntax + # Validate YAML try: - yaml.safe_load(config_yaml) + new_mem = yaml.safe_load(config_yaml) or {} except yaml.YAMLError as e: - return JSONResponse( - status_code=400, content={"error": f"Invalid YAML syntax: {str(e)}"} - ) - - config_loader = get_config_loader() - config_path = config_loader.config_path - - # Create backup - backup_path = f"{config_path}.bak" - if os.path.exists(config_path): - shutil.copy2(config_path, backup_path) - logger.info(f"Created backup at {backup_path}") - - # Write new configuration - with open(config_path, 'w') as file: - file.write(config_yaml) - - # Hot reload configuration - reload_success = config_loader.reload_config() - - if reload_success: - logger.info("Memory configuration updated and reloaded successfully") - return { - "message": "Memory configuration updated and reloaded successfully", - "config_path": config_path, - "backup_created": os.path.exists(backup_path), - "status": "success" - } - else: - return JSONResponse( - status_code=500, content={"error": "Configuration saved but reload failed"} - ) - + raise ValueError(f"Invalid YAML syntax: {str(e)}") + + cfg_path = _find_config_path() + if not os.path.exists(cfg_path): + raise FileNotFoundError(f"Config file not found: {cfg_path}") + + # Backup + backup_path = f"{cfg_path}.bak" + shutil.copy2(cfg_path, backup_path) + + # Update memory section and write file + with open(cfg_path, 'r') as f: + data = yaml.safe_load(f) or {} + data["memory"] = new_mem + with open(cfg_path, 'w') as f: + yaml.safe_dump(data, f, sort_keys=False) + + # Reload registry + load_models_config(force_reload=True) + + return { + "message": "Memory configuration updated and reloaded successfully", + "config_path": str(cfg_path), + "backup_created": os.path.exists(backup_path), + "status": "success", + } except Exception as e: - logger.error(f"Error updating memory config: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to update memory config: {str(e)}"} - ) + logger.exception("Error updating memory config") + raise e async def validate_memory_config(config_yaml: str): - """Validate memory configuration YAML syntax.""" + """Validate memory configuration YAML syntax (memory section).""" try: - import yaml - from advanced_omi_backend.memory_config_loader import MemoryConfigLoader - - # Parse YAML try: - parsed_config = yaml.safe_load(config_yaml) - if not parsed_config: - return JSONResponse( - status_code=400, content={"error": "Configuration file is empty"} - ) + parsed = yaml.safe_load(config_yaml) except yaml.YAMLError as e: - return JSONResponse( - status_code=400, content={"error": f"Invalid YAML syntax: {str(e)}"} - ) - - # Create a temporary config loader to validate structure - try: - # Create a temporary file for validation - import tempfile - with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as tmp_file: - tmp_file.write(config_yaml) - tmp_path = tmp_file.name - - # Try to load with MemoryConfigLoader to validate structure - temp_loader = MemoryConfigLoader(tmp_path) - temp_loader.validate_config() - - # Clean up temp file - os.unlink(tmp_path) - - return { - "message": "Configuration is valid", - "status": "success" - } - - except ValueError as e: - return JSONResponse( - status_code=400, content={"error": f"Configuration validation failed: {str(e)}"} - ) - + raise HTTPException(status_code=400, detail=f"Invalid YAML syntax: {str(e)}") + if not isinstance(parsed, dict): + raise HTTPException(status_code=400, detail="Configuration must be a YAML object") + # Minimal checks + # provider optional; timeout_seconds optional; extraction enabled/prompt optional + return {"message": "Configuration is valid", "status": "success"} + except HTTPException: + # Re-raise HTTPExceptions without wrapping + raise except Exception as e: - logger.error(f"Error validating memory config: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to validate memory config: {str(e)}"} - ) + logger.exception("Error validating memory config") + raise HTTPException(status_code=500, detail=f"Error validating memory config: {str(e)}") async def reload_memory_config(): - """Reload memory configuration from file.""" + """Reload config.yml (registry).""" try: - from advanced_omi_backend.memory_config_loader import get_config_loader - - config_loader = get_config_loader() - reload_success = config_loader.reload_config() - - if reload_success: - logger.info("Memory configuration reloaded successfully") - return { - "message": "Memory configuration reloaded successfully", - "config_path": config_loader.config_path, - "status": "success" - } - else: - return JSONResponse( - status_code=500, content={"error": "Failed to reload memory configuration"} - ) - + cfg_path = _find_config_path() + load_models_config(force_reload=True) + return {"message": "Configuration reloaded", "config_path": str(cfg_path), "status": "success"} except Exception as e: - logger.error(f"Error reloading memory config: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to reload memory config: {str(e)}"} - ) + logger.exception("Error reloading config") + raise e async def delete_all_user_memories(user: User): @@ -459,10 +366,8 @@ async def delete_all_user_memories(user: User): } except Exception as e: - logger.error(f"Error deleting all memories for user {user.user_id}: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to delete memories: {str(e)}"} - ) + logger.exception(f"Error deleting all memories for user {user.user_id}") + raise e # Memory Provider Configuration Functions @@ -485,10 +390,8 @@ async def get_memory_provider(): } except Exception as e: - logger.error(f"Error getting memory provider: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to get memory provider: {str(e)}"} - ) + logger.exception("Error getting memory provider") + raise e async def set_memory_provider(provider: str): @@ -499,19 +402,13 @@ async def set_memory_provider(provider: str): valid_providers = ["chronicle", "openmemory_mcp", "mycelia"] if provider not in valid_providers: - return JSONResponse( - status_code=400, - content={"error": f"Invalid provider '{provider}'. Valid providers: {', '.join(valid_providers)}"} - ) + raise ValueError(f"Invalid provider '{provider}'. Valid providers: {', '.join(valid_providers)}") # Path to .env file (assuming we're running from backends/advanced/) env_path = os.path.join(os.getcwd(), ".env") if not os.path.exists(env_path): - return JSONResponse( - status_code=404, - content={"error": f".env file not found at {env_path}"} - ) + raise FileNotFoundError(f".env file not found at {env_path}") # Read current .env file with open(env_path, 'r') as file: @@ -556,9 +453,5 @@ async def set_memory_provider(provider: str): } except Exception as e: - logger.error(f"Error setting memory provider: {e}") - return JSONResponse( - status_code=500, content={"error": f"Failed to set memory provider: {str(e)}"} - ) - - + logger.exception("Error setting memory provider") + raise e diff --git a/backends/advanced/src/advanced_omi_backend/controllers/websocket_controller.py b/backends/advanced/src/advanced_omi_backend/controllers/websocket_controller.py index 2759edb1..50ffc77f 100644 --- a/backends/advanced/src/advanced_omi_backend/controllers/websocket_controller.py +++ b/backends/advanced/src/advanced_omi_backend/controllers/websocket_controller.py @@ -302,22 +302,22 @@ async def _initialize_streaming_session( client_state.stream_audio_format = audio_format application_logger.info(f"🆔 Created stream session: {client_state.stream_session_id}") - # Determine transcription provider from environment - transcription_provider = os.getenv("TRANSCRIPTION_PROVIDER", "").lower() - if transcription_provider == "parakeet": - provider = "parakeet" - elif transcription_provider == "deepgram": - provider = "deepgram" - else: - # Auto-detect: prefer Parakeet if URL is set, otherwise Deepgram - parakeet_url = os.getenv("PARAKEET_ASR_URL") - deepgram_key = os.getenv("DEEPGRAM_API_KEY") - if parakeet_url: - provider = "parakeet" - elif deepgram_key: - provider = "deepgram" - else: - raise ValueError("No transcription provider configured (DEEPGRAM_API_KEY or PARAKEET_ASR_URL required)") + # Determine transcription provider from config.yml + from advanced_omi_backend.model_registry import get_models_registry + + registry = get_models_registry() + if not registry: + raise ValueError("config.yml not found - cannot determine transcription provider") + + stt_model = registry.get_default("stt") + if not stt_model: + raise ValueError("No default STT model configured in config.yml (defaults.stt)") + + provider = stt_model.model_provider.lower() + if provider not in ["deepgram", "parakeet"]: + raise ValueError(f"Unsupported STT provider: {provider}. Expected: deepgram or parakeet") + + application_logger.info(f"📋 Using STT provider: {provider} (model: {stt_model.name})") # Initialize session tracking in Redis await audio_stream_producer.init_session( @@ -719,6 +719,7 @@ async def _process_batch_audio_complete( relative_audio_path, file_path, duration = await write_audio_file( raw_audio_data=complete_audio, audio_uuid=audio_uuid, + source="websocket", client_id=client_id, user_id=user_id, user_email=user_email, diff --git a/backends/advanced/src/advanced_omi_backend/llm_client.py b/backends/advanced/src/advanced_omi_backend/llm_client.py index 21ee3331..e6b5a14d 100644 --- a/backends/advanced/src/advanced_omi_backend/llm_client.py +++ b/backends/advanced/src/advanced_omi_backend/llm_client.py @@ -9,7 +9,12 @@ import logging import os from abc import ABC, abstractmethod -from typing import Dict +from typing import Dict, Any, Optional + +from advanced_omi_backend.services.memory.config import load_config_yml as _load_root_config +from advanced_omi_backend.services.memory.config import resolve_value as _resolve_value + +from advanced_omi_backend.model_registry import get_models_registry logger = logging.getLogger(__name__) @@ -51,11 +56,12 @@ def __init__( temperature: float = 0.1, ): super().__init__(model, temperature) - self.api_key = api_key or os.getenv("OPENAI_API_KEY") - self.base_url = base_url or os.getenv("OPENAI_BASE_URL") - self.model = model or os.getenv("OPENAI_MODEL") + # Do not read from environment here; values are provided by config.yml + self.api_key = api_key + self.base_url = base_url + self.model = model if not self.api_key or not self.base_url or not self.model: - raise ValueError("OPENAI_API_KEY, OPENAI_BASE_URL, and OPENAI_MODEL must be set") + raise ValueError(f"LLM configuration incomplete: api_key={'set' if self.api_key else 'MISSING'}, base_url={'set' if self.base_url else 'MISSING'}, model={'set' if self.model else 'MISSING'}") # Initialize OpenAI client with optional Langfuse tracing try: @@ -141,21 +147,26 @@ def get_default_model(self) -> str: class LLMClientFactory: - """Factory for creating LLM clients based on environment configuration.""" + """Factory for creating LLM clients based on configuration registry.""" @staticmethod def create_client() -> LLMClient: - """Create an LLM client based on LLM_PROVIDER environment variable.""" - provider = os.getenv("LLM_PROVIDER", "openai").lower() - - if provider in ["openai", "ollama"]: - return OpenAILLMClient( - api_key=os.getenv("OPENAI_API_KEY"), - base_url=os.getenv("OPENAI_BASE_URL"), - model=os.getenv("OPENAI_MODEL"), - ) - else: - raise ValueError(f"Unsupported LLM provider: {provider}") + """Create an LLM client based on model registry configuration (config.yml).""" + registry = get_models_registry() + + if registry: + llm_def = registry.get_default("llm") + if llm_def: + logger.info(f"Creating LLM client from registry: {llm_def.name} ({llm_def.model_provider})") + params = llm_def.model_params or {} + return OpenAILLMClient( + api_key=llm_def.api_key, + base_url=llm_def.model_url, + model=llm_def.model_name, + temperature=params.get("temperature", 0.1), + ) + + raise ValueError("No default LLM defined in config.yml") @staticmethod def get_supported_providers() -> list: diff --git a/backends/advanced/src/advanced_omi_backend/memory_config_loader.py b/backends/advanced/src/advanced_omi_backend/memory_config_loader.py deleted file mode 100644 index 60073f5a..00000000 --- a/backends/advanced/src/advanced_omi_backend/memory_config_loader.py +++ /dev/null @@ -1,333 +0,0 @@ -""" -Memory Configuration Loader - -This module loads and manages memory extraction configuration from YAML files. -""" - -import logging -import os -from typing import Any, Dict - -import yaml - -# Logger for configuration -config_logger = logging.getLogger("memory_config") - - -class MemoryConfigLoader: - """ - Loads and manages memory extraction configuration from YAML files. - """ - - def __init__(self, config_path: str | None = None): - """ - Initialize the config loader. - - Args: - config_path: Path to the configuration YAML file - """ - if config_path is None: - # Default to memory_config.yaml in the backend root - config_path = os.path.join( - os.path.dirname(os.path.dirname(os.path.dirname(__file__))), - "memory_config.yaml", - ) - - self.config_path = config_path - self.config = self._load_config() - - # Set up logging level from config - debug_config = self.config.get("debug", {}) - log_level = debug_config.get("log_level", "INFO") - numeric_level = getattr(logging, log_level.upper(), logging.INFO) - config_logger.setLevel(numeric_level) - - # Validate configuration on load - try: - self.validate_config() - config_logger.info(f"Loaded and validated memory configuration from {config_path}") - except ValueError as e: - config_logger.error(f"Configuration validation failed: {e}") - raise - - def _load_config(self) -> Dict[str, Any]: - """Load configuration from YAML file.""" - try: - with open(self.config_path, "r") as file: - config = yaml.safe_load(file) - if not config: - raise ValueError("Configuration file is empty") - return config - except FileNotFoundError: - raise FileNotFoundError( - f"Memory configuration file not found: {self.config_path}\n" - f"Please ensure memory_config.yaml exists in the backend directory" - ) - except yaml.YAMLError as e: - raise ValueError( - f"Error parsing YAML configuration: {e}\n" - f"Please check the syntax of {self.config_path}" - ) - - def validate_config(self) -> None: - """Validate that all required configuration sections and fields are present.""" - required_sections = [ - "memory_extraction", - "quality_control", - "processing", - "storage", - "debug", - ] - - for section in required_sections: - if section not in self.config: - raise ValueError( - f"Missing required configuration section: '{section}'\n" - f"Please check {self.config_path}" - ) - - # Validate memory_extraction section - mem_extract = self.config.get("memory_extraction", {}) - if "enabled" not in mem_extract: - raise ValueError("memory_extraction.enabled is required in configuration") - if "prompt" not in mem_extract: - raise ValueError("memory_extraction.prompt is required in configuration") - if "llm_settings" not in mem_extract: - raise ValueError("memory_extraction.llm_settings is required in configuration") - - # Validate quality_control section - quality = self.config.get("quality_control", {}) - if "min_conversation_length" not in quality: - raise ValueError("quality_control.min_conversation_length is required") - if "max_conversation_length" not in quality: - raise ValueError("quality_control.max_conversation_length is required") - - # Validate processing section - processing = self.config.get("processing", {}) - if "processing_timeout" not in processing: - raise ValueError("processing.processing_timeout is required") - - # Validate debug section - debug = self.config.get("debug", {}) - if "enabled" not in debug: - raise ValueError("debug.enabled is required") - if "db_path" not in debug: - raise ValueError("debug.db_path is required") - - def reload_config(self) -> bool: - """Reload configuration from file.""" - try: - self.config = self._load_config() - config_logger.info("Configuration reloaded successfully") - return True - except Exception as e: - config_logger.error(f"Failed to reload configuration: {e}") - return False - - def get_memory_extraction_config(self) -> Dict[str, Any]: - """Get memory extraction configuration.""" - return self.config.get("memory_extraction", {}) - - def get_fact_extraction_config(self) -> Dict[str, Any]: - """Get fact extraction configuration.""" - return self.config.get("fact_extraction", {}) - - def get_categorization_config(self) -> Dict[str, Any]: - """Get categorization configuration.""" - return self.config.get("categorization", {}) - - def get_quality_control_config(self) -> Dict[str, Any]: - """Get quality control configuration.""" - return self.config.get("quality_control", {}) - - def get_processing_config(self) -> Dict[str, Any]: - """Get processing configuration.""" - return self.config.get("processing", {}) - - def get_storage_config(self) -> Dict[str, Any]: - """Get storage configuration.""" - return self.config.get("storage", {}) - - def get_debug_config(self) -> Dict[str, Any]: - """Get debug configuration.""" - return self.config.get("debug", {}) - - def is_memory_extraction_enabled(self) -> bool: - """Check if memory extraction is enabled.""" - return self.get_memory_extraction_config().get("enabled") - - def is_fact_extraction_enabled(self) -> bool: - """Check if fact extraction is enabled.""" - return self.get_fact_extraction_config().get("enabled", False) # Optional feature - - def is_categorization_enabled(self) -> bool: - """Check if categorization is enabled.""" - return self.get_categorization_config().get("enabled", False) # Optional feature - - def is_debug_enabled(self) -> bool: - """Check if debug tracking is enabled.""" - return self.get_debug_config().get("enabled") - - def get_memory_prompt(self) -> str: - """Get the memory extraction prompt.""" - prompt = self.get_memory_extraction_config().get("prompt") - if not prompt: - raise ValueError("memory_extraction.prompt is not configured") - return prompt - - def get_fact_prompt(self) -> str: - """Get the fact extraction prompt.""" - # Fact extraction is optional, so we can provide a default - return self.get_fact_extraction_config().get( - "prompt", "Extract specific facts from this conversation." - ) - - def get_categorization_prompt(self) -> str: - """Get the categorization prompt.""" - # Categorization is optional, so we can provide a default - return self.get_categorization_config().get("prompt", "Categorize this conversation.") - - def get_llm_settings(self, extraction_type: str) -> Dict[str, Any]: - """ - Get LLM settings for a specific extraction type. - - Args: - extraction_type: One of 'memory', 'fact', 'categorization' - """ - config_key = f"{extraction_type}_extraction" - if extraction_type == "memory": - config_key = "memory_extraction" - elif extraction_type == "fact": - config_key = "fact_extraction" - elif extraction_type == "categorization": - config_key = "categorization" - - extraction_config = self.config.get(config_key, {}) - return extraction_config.get("llm_settings", {}) - - def should_skip_conversation(self, conversation_text: str) -> bool: - """ - Check if a conversation should be skipped based on quality control settings. - - Args: - conversation_text: The full conversation text - - Returns: - True if the conversation should be skipped - """ - quality_config = self.get_quality_control_config() - - # Check length constraints - these are required fields - min_length = quality_config.get("min_conversation_length") - max_length = quality_config.get("max_conversation_length") - - if min_length is None or max_length is None: - config_logger.error("Missing required quality control configuration") - return False # Don't skip if config is missing - - if len(conversation_text) < min_length: - config_logger.debug( - f"Skipping conversation: too short ({len(conversation_text)} < {min_length})" - ) - return True - - if len(conversation_text) > max_length: - config_logger.debug( - f"Skipping conversation: too long ({len(conversation_text)} > {max_length})" - ) - return True - - # Check skip patterns - skip_patterns = quality_config.get("skip_patterns", []) - if skip_patterns: - import re - - for pattern in skip_patterns: - if re.match(pattern, conversation_text.strip(), re.IGNORECASE): - config_logger.debug(f"Skipping conversation: matches skip pattern '{pattern}'") - return True - - # Check content ratio (if enabled) - if quality_config.get("skip_low_content", False): - min_content_ratio = quality_config.get("min_content_ratio") - if min_content_ratio is None: - min_content_ratio = 0.3 # Reasonable default for optional feature - - # Simple heuristic: calculate ratio of meaningful words to total words - words = conversation_text.split() - if len(words) > 0: - filler_words = { - "um", - "uh", - "hmm", - "yeah", - "ok", - "okay", - "like", - "you", - "know", - "so", - "well", - } - meaningful_words = [ - word for word in words if word.lower() not in filler_words and len(word) > 2 - ] - content_ratio = len(meaningful_words) / len(words) - - if content_ratio < min_content_ratio: - config_logger.debug( - f"Skipping conversation: low content ratio ({content_ratio:.2f} < {min_content_ratio})" - ) - return True - - return False - - def get_categories(self) -> list[str]: - """Get available categories for classification.""" - return self.get_categorization_config().get("categories", []) - - def get_debug_db_path(self) -> str: - """Get the debug database path.""" - path = self.get_debug_config().get("db_path") - if not path: - raise ValueError("debug.db_path is not configured") - return path - - def should_log_full_conversations(self) -> bool: - """Check if full conversations should be logged.""" - return self.get_debug_config().get("log_full_conversations", False) # Privacy-safe default - - def should_log_extracted_memories(self) -> bool: - """Check if extracted memories should be logged.""" - return self.get_debug_config().get("log_extracted_memories", True) # Useful default - - def get_processing_timeout(self) -> int: - """Get the processing timeout in seconds.""" - timeout = self.get_processing_config().get("processing_timeout") - if timeout is None: - raise ValueError("processing.processing_timeout is not configured") - return timeout - - def should_retry_failed(self) -> bool: - """Check if failed extractions should be retried.""" - return self.get_processing_config().get("retry_failed", True) # Reasonable default - - def get_max_retries(self) -> int: - """Get the maximum number of retries.""" - return self.get_processing_config().get("max_retries", 2) # Reasonable default - - def get_retry_delay(self) -> int: - """Get the delay between retries in seconds.""" - return self.get_processing_config().get("retry_delay", 5) # Reasonable default - - -# Global instance -_config_loader = None - - -def get_config_loader() -> MemoryConfigLoader: - """Get the global configuration loader instance.""" - global _config_loader - if _config_loader is None: - _config_loader = MemoryConfigLoader() - return _config_loader diff --git a/backends/advanced/src/advanced_omi_backend/model_registry.py b/backends/advanced/src/advanced_omi_backend/model_registry.py new file mode 100644 index 00000000..53d919ca --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/model_registry.py @@ -0,0 +1,359 @@ +"""Model registry and config loader. + +Loads a single source of truth from config.yml and exposes model +definitions (LLM, embeddings, etc.) in a provider-agnostic way. + +Now using Pydantic for robust validation and type safety. +""" + +from __future__ import annotations + +import os +import re +import yaml +from pathlib import Path +from typing import Any, Dict, List, Optional + +import logging +from pydantic import BaseModel, Field, field_validator, model_validator, ConfigDict, ValidationError + +def _resolve_env(value: Any) -> Any: + """Resolve ``${VAR:-default}`` patterns inside a single value. + + This helper is intentionally minimal: it only operates on strings and leaves + all other types unchanged. Patterns of the form ``${VAR}`` or + ``${VAR:-default}`` are expanded using ``os.getenv``: + + - If the environment variable **VAR** is set, its value is used. + - Otherwise the optional ``default`` is used (or ``\"\"`` if omitted). + + Examples: + >>> os.environ.get("OLLAMA_MODEL") + >>> _resolve_env("${OLLAMA_MODEL:-llama3.1:latest}") + 'llama3.1:latest' + + >>> os.environ["OLLAMA_MODEL"] = "llama3.2:latest" + >>> _resolve_env("${OLLAMA_MODEL:-llama3.1:latest}") + 'llama3.2:latest' + + >>> _resolve_env("Bearer ${OPENAI_API_KEY:-}") + 'Bearer ' # when OPENAI_API_KEY is not set + + Note: + Use :func:`_deep_resolve_env` to apply this logic to an entire + nested config structure (dicts/lists) loaded from YAML. + """ + if not isinstance(value, str): + return value + + pattern = re.compile(r"\$\{([^}:]+)(?::-(.*?))?\}") + + def repl(match: re.Match[str]) -> str: + var, default = match.group(1), match.group(2) + return os.getenv(var, default or "") + + return pattern.sub(repl, value) + + +def _deep_resolve_env(data: Any) -> Any: + """Recursively resolve environment variables in nested structures. + + This walks arbitrary Python structures produced by ``yaml.safe_load`` and + applies :func:`_resolve_env` to every string it finds. Dictionaries and + lists are traversed deeply; scalars are passed through unchanged. + + Examples: + >>> os.environ["OPENAI_MODEL"] = "gpt-4o-mini" + >>> cfg = { + ... "models": [ + ... {"model_name": "${OPENAI_MODEL:-gpt-4o-mini}"}, + ... {"model_url": "${OPENAI_BASE_URL:-https://api.openai.com/v1}"} + ... ] + ... } + >>> resolved = _deep_resolve_env(cfg) + >>> resolved["models"][0]["model_name"] + 'gpt-4o-mini' + >>> resolved["models"][1]["model_url"] + 'https://api.openai.com/v1' + + This is what :func:`load_models_config` uses immediately after loading + ``config.yml`` so that all ``${VAR:-default}`` placeholders are resolved + before Pydantic validation and model registry construction. + """ + if isinstance(data, dict): + return {k: _deep_resolve_env(v) for k, v in data.items()} + if isinstance(data, list): + return [_deep_resolve_env(v) for v in data] + return _resolve_env(data) + + +class ModelDef(BaseModel): + """Model definition with validation. + + Represents a single model configuration (LLM, embedding, STT, TTS, etc.) + from config.yml with automatic validation and type checking. + """ + + model_config = ConfigDict( + extra='allow', # Allow extra fields for extensibility + validate_assignment=True, # Validate on attribute assignment + arbitrary_types_allowed=True, + ) + + name: str = Field(..., min_length=1, description="Unique model identifier") + model_type: str = Field(..., description="Model type: llm, embedding, stt, tts, etc.") + model_provider: str = Field(default="unknown", description="Provider name: openai, ollama, deepgram, parakeet, etc.") + api_family: str = Field(default="openai", description="API family: openai, http, websocket, etc.") + model_name: str = Field(default="", description="Provider-specific model name") + model_url: str = Field(default="", description="Base URL for API requests") + api_key: Optional[str] = Field(default=None, description="API key or authentication token") + description: Optional[str] = Field(default=None, description="Human-readable description") + model_params: Dict[str, Any] = Field(default_factory=dict, description="Model-specific parameters") + model_output: Optional[str] = Field(default=None, description="Output format: json, text, vector, etc.") + embedding_dimensions: Optional[int] = Field(default=None, ge=1, description="Embedding vector dimensions") + operations: Dict[str, Any] = Field(default_factory=dict, description="API operation definitions") + + @field_validator('model_name', mode='before') + @classmethod + def default_model_name(cls, v: Any, info) -> str: + """Default model_name to name if not provided.""" + if not v and info.data.get('name'): + return info.data['name'] + return v or "" + + @field_validator('model_url', mode='before') + @classmethod + def validate_url(cls, v: Any) -> str: + """Ensure URL doesn't have trailing whitespace.""" + if isinstance(v, str): + return v.strip() + return v or "" + + @field_validator('api_key', mode='before') + @classmethod + def sanitize_api_key(cls, v: Any) -> Optional[str]: + """Sanitize API key, treat empty strings as None.""" + if isinstance(v, str): + v = v.strip() + if not v or v.lower() in ['dummy', 'none', 'null']: + return None + return v + return v + + @model_validator(mode='after') + def validate_model(self) -> ModelDef: + """Cross-field validation.""" + # Ensure embedding models have dimensions specified + if self.model_type == 'embedding' and not self.embedding_dimensions: + # Common defaults + defaults = { + 'text-embedding-3-small': 1536, + 'text-embedding-3-large': 3072, + 'text-embedding-ada-002': 1536, + 'nomic-embed-text-v1.5': 768, + } + if self.model_name in defaults: + self.embedding_dimensions = defaults[self.model_name] + + return self + + +class AppModels(BaseModel): + """Application models registry. + + Contains default model selections and all available model definitions. + """ + + model_config = ConfigDict( + extra='allow', + validate_assignment=True, + ) + + defaults: Dict[str, str] = Field( + default_factory=dict, + description="Default model names for each model_type" + ) + models: Dict[str, ModelDef] = Field( + default_factory=dict, + description="All available model definitions keyed by name" + ) + memory: Dict[str, Any] = Field( + default_factory=dict, + description="Memory service configuration" + ) + speaker_recognition: Dict[str, Any] = Field( + default_factory=dict, + description="Speaker recognition service configuration" + ) + + def get_by_name(self, name: str) -> Optional[ModelDef]: + """Get a model by its unique name. + + Args: + name: Model name to look up + + Returns: + ModelDef if found, None otherwise + """ + return self.models.get(name) + + def get_default(self, model_type: str) -> Optional[ModelDef]: + """Get the default model for a given type. + + Args: + model_type: Type of model (llm, embedding, stt, tts, etc.) + + Returns: + Default ModelDef for the type, or first available model of that type, + or None if no models of that type exist + """ + # Try explicit default first + name = self.defaults.get(model_type) + if name: + model = self.get_by_name(name) + if model: + return model + + # Fallback: first model of that type + for m in self.models.values(): + if m.model_type == model_type: + return m + + return None + + def get_all_by_type(self, model_type: str) -> List[ModelDef]: + """Get all models of a specific type. + + Args: + model_type: Type of model to filter by + + Returns: + List of ModelDef objects matching the type + """ + return [m for m in self.models.values() if m.model_type == model_type] + + def list_model_types(self) -> List[str]: + """Get all unique model types in the registry. + + Returns: + Sorted list of model types + """ + return sorted(set(m.model_type for m in self.models.values())) + + +# Global registry singleton +_REGISTRY: Optional[AppModels] = None + + +def _find_config_path() -> Path: + """Find config.yml in expected locations. + + Search order: + 1. CONFIG_FILE environment variable + 2. Current working directory + 3. /app/config.yml (Docker container) + 4. Walk up from module directory + + Returns: + Path to config.yml (may not exist) + """ + # ENV override + cfg_env = os.getenv("CONFIG_FILE") + if cfg_env and Path(cfg_env).exists(): + return Path(cfg_env) + + # Common locations (container vs repo root) + candidates = [Path("config.yml"), Path("/app/config.yml")] + + # Also walk up from current file's parents defensively + try: + for parent in Path(__file__).resolve().parents: + c = parent / "config.yml" + if c.exists(): + return c + except Exception: + pass + + for c in candidates: + if c.exists(): + return c + + # Last resort: return /app/config.yml path (may not exist yet) + return Path("/app/config.yml") + + +def load_models_config(force_reload: bool = False) -> Optional[AppModels]: + """Load model configuration from config.yml. + + This function loads and parses the config.yml file, resolves environment + variables, validates model definitions using Pydantic, and caches the result. + + Args: + force_reload: If True, reload from disk even if already cached + + Returns: + AppModels instance with validated configuration, or None if config not found + + Raises: + ValidationError: If config.yml has invalid model definitions + yaml.YAMLError: If config.yml has invalid YAML syntax + """ + global _REGISTRY + if _REGISTRY is not None and not force_reload: + return _REGISTRY + + cfg_path = _find_config_path() + if not cfg_path.exists(): + return None + + # Load and parse YAML + with cfg_path.open("r") as f: + raw = yaml.safe_load(f) or {} + + # Resolve environment variables + raw = _deep_resolve_env(raw) + + # Extract sections + defaults = raw.get("defaults", {}) or {} + model_list = raw.get("models", []) or [] + memory_settings = raw.get("memory", {}) or {} + speaker_recognition_cfg = raw.get("speaker_recognition", {}) or {} + + # Parse and validate models using Pydantic + models: Dict[str, ModelDef] = {} + for m in model_list: + try: + # Pydantic will handle validation automatically + model_def = ModelDef(**m) + models[model_def.name] = model_def + except ValidationError as e: + # Log but don't fail the entire registry load + logging.warning(f"Failed to load model '{m.get('name', 'unknown')}': {e}") + continue + + # Create and cache registry + _REGISTRY = AppModels( + defaults=defaults, + models=models, + memory=memory_settings, + speaker_recognition=speaker_recognition_cfg + ) + return _REGISTRY + + +def get_models_registry() -> Optional[AppModels]: + """Get the global models registry. + + This is the primary interface for accessing model configurations. + The registry is loaded once and cached for performance. + + Returns: + AppModels instance, or None if config.yml not found + + Example: + >>> registry = get_models_registry() + >>> if registry: + ... llm = registry.get_default('llm') + ... print(f"Default LLM: {llm.name} ({llm.model_provider})") + """ + return load_models_config(force_reload=False) diff --git a/backends/advanced/src/advanced_omi_backend/models/audio_file.py b/backends/advanced/src/advanced_omi_backend/models/audio_file.py index 00060037..e1e2c09a 100644 --- a/backends/advanced/src/advanced_omi_backend/models/audio_file.py +++ b/backends/advanced/src/advanced_omi_backend/models/audio_file.py @@ -29,6 +29,10 @@ class AudioFile(Document): # Core identifiers audio_uuid: Indexed(str, unique=True) = Field(description="Unique audio identifier") + source: Indexed(str) = Field( + default="upload", + description="Source of the audio (upload, gdrive, etc.)" + ) audio_path: str = Field(description="Path to raw audio file") client_id: Indexed(str) = Field(description="Client device identifier") timestamp: Indexed(int) = Field(description="Unix timestamp in milliseconds") @@ -51,11 +55,13 @@ class AudioFile(Document): description="Speech detection results" ) + + class Settings: name = "audio_chunks" indexes = [ "audio_uuid", "client_id", "user_id", - "timestamp" + "timestamp", ] \ No newline at end of file diff --git a/backends/advanced/src/advanced_omi_backend/routers/api_router.py b/backends/advanced/src/advanced_omi_backend/routers/api_router.py index 528713c0..9e761f8e 100644 --- a/backends/advanced/src/advanced_omi_backend/routers/api_router.py +++ b/backends/advanced/src/advanced_omi_backend/routers/api_router.py @@ -15,6 +15,7 @@ client_router, conversation_router, memory_router, + obsidian_router, queue_router, system_router, user_router, @@ -34,6 +35,7 @@ router.include_router(client_router) router.include_router(conversation_router) router.include_router(memory_router) +router.include_router(obsidian_router) router.include_router(system_router) router.include_router(queue_router) router.include_router(health_router) # Also include under /api for frontend compatibility diff --git a/backends/advanced/src/advanced_omi_backend/routers/modules/__init__.py b/backends/advanced/src/advanced_omi_backend/routers/modules/__init__.py index a5669b06..21f89991 100644 --- a/backends/advanced/src/advanced_omi_backend/routers/modules/__init__.py +++ b/backends/advanced/src/advanced_omi_backend/routers/modules/__init__.py @@ -20,6 +20,7 @@ from .conversation_routes import router as conversation_router from .health_routes import router as health_router from .memory_routes import router as memory_router +from .obsidian_routes import router as obsidian_router from .queue_routes import router as queue_router from .system_routes import router as system_router from .user_routes import router as user_router @@ -32,6 +33,7 @@ "conversation_router", "health_router", "memory_router", + "obsidian_router", "queue_router", "system_router", "user_router", diff --git a/backends/advanced/src/advanced_omi_backend/routers/modules/audio_routes.py b/backends/advanced/src/advanced_omi_backend/routers/modules/audio_routes.py index 5fb24a1a..056e7667 100644 --- a/backends/advanced/src/advanced_omi_backend/routers/modules/audio_routes.py +++ b/backends/advanced/src/advanced_omi_backend/routers/modules/audio_routes.py @@ -11,10 +11,29 @@ from advanced_omi_backend.auth import current_superuser, current_active_user_optional, get_user_from_token_param from advanced_omi_backend.controllers import audio_controller from advanced_omi_backend.models.user import User +from advanced_omi_backend.app_config import get_audio_chunk_dir +from advanced_omi_backend.utils.gdrive_audio_utils import download_audio_files_from_drive, AudioValidationError router = APIRouter(prefix="/audio", tags=["audio"]) +@router.post("/upload_audio_from_gdrive") +async def upload_audio_from_drive_folder( + gdrive_folder_id: str = Query(..., description="Google Drive Folder ID containing audio files (e.g., the string after /folders/ in the URL)"), + current_user: User = Depends(current_superuser), + device_name: str = Query(default="upload"), + auto_generate_client: bool = Query(default=True), +): + try: + files = await download_audio_files_from_drive(gdrive_folder_id) + except AudioValidationError as e: + raise HTTPException(status_code=400, detail=str(e)) + + return await audio_controller.upload_and_process_audio_files( + current_user, files, device_name, auto_generate_client, source="gdrive" + ) + + @router.get("/get_audio/{conversation_id}") async def get_conversation_audio( conversation_id: str, diff --git a/backends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.py b/backends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.py index d0c64904..fbb32bc7 100644 --- a/backends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.py +++ b/backends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.py @@ -30,6 +30,7 @@ class ChatMessageRequest(BaseModel): message: str = Field(..., min_length=1, max_length=4000, description="The user's message") session_id: Optional[str] = Field(None, description="Session ID (creates new session if not provided)") + include_obsidian_memory: Optional[bool] = Field(False, description="Whether to include context from Obsidian vault") class ChatMessageResponse(BaseModel): @@ -309,7 +310,8 @@ async def event_stream(): async for event in chat_service.generate_response_stream( session_id=session_id, user_id=str(current_user.id), - message_content=request.message + message_content=request.message, + include_obsidian_memory=request.include_obsidian_memory ): # Format as Server-Sent Event event_data = json.dumps(event, default=str) diff --git a/backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py b/backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py index d94940ce..d7a62ba9 100644 --- a/backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py +++ b/backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py @@ -20,6 +20,7 @@ from advanced_omi_backend.llm_client import async_health_check from advanced_omi_backend.services.memory import get_memory_service from advanced_omi_backend.services.transcription import get_transcription_provider +from advanced_omi_backend.model_registry import get_models_registry # Create router router = APIRouter(tags=["health"]) @@ -38,9 +39,17 @@ # Transcription provider transcription_provider = get_transcription_provider() -# Qdrant Configuration -QDRANT_BASE_URL = os.getenv("QDRANT_BASE_URL", "qdrant") -QDRANT_PORT = os.getenv("QDRANT_PORT", "6333") +# Registry-driven configuration for display +REGISTRY = get_models_registry() +if REGISTRY: + _llm_def = REGISTRY.get_default("llm") + _embed_def = REGISTRY.get_default("embedding") + _vs_def = REGISTRY.get_default("vector_store") +else: + _llm_def = _embed_def = _vs_def = None + +QDRANT_BASE_URL = (_vs_def.model_params.get("host") if _vs_def else "qdrant") +QDRANT_PORT = str(_vs_def.model_params.get("port") if _vs_def else "6333") @router.get("/auth/health") @@ -83,6 +92,25 @@ async def auth_health_check(): @router.get("/health") async def health_check(): """Comprehensive health check for all services.""" + # Load model config once for display fields + _llm_def = None + _llm_provider = "openai" + _llm_model = None + _llm_base_url = None + _stt_name = None + + try: + registry = get_models_registry() + if registry: + _defaults = registry.defaults + _llm_name = _defaults.get("llm") + _stt_name = _defaults.get("stt") + _llm_def = registry.models.get(_llm_name) + _llm_provider = _llm_def.model_provider if _llm_def else "openai" + _llm_model = _llm_def.model_name if _llm_def else None + _llm_base_url = _llm_def.model_url if _llm_def else None + except Exception as e: + logger.warning(f"Failed to load model config for health check: {e}") health_status = { "status": "healthy", "timestamp": int(time.time()), @@ -100,7 +128,11 @@ async def health_check(): if transcription_provider else "Not configured" ), - "transcription_provider": os.getenv("TRANSCRIPTION_PROVIDER", "auto-detect"), + "transcription_provider": ( + REGISTRY.get_default("stt").name if REGISTRY and REGISTRY.get_default("stt") + else "not configured" + ), + "provider_type": ( transcription_provider.mode if transcription_provider else "none" ), @@ -108,9 +140,9 @@ async def health_check(): "active_clients": get_client_manager().get_client_count(), "new_conversation_timeout_minutes": float(os.getenv("NEW_CONVERSATION_TIMEOUT_MINUTES", "1.5")), "audio_cropping_enabled": os.getenv("AUDIO_CROPPING_ENABLED", "true").lower() == "true", - "llm_provider": os.getenv("LLM_PROVIDER"), - "llm_model": os.getenv("OPENAI_MODEL"), - "llm_base_url": os.getenv("OPENAI_BASE_URL"), + "llm_provider": (_llm_def.model_provider if _llm_def else None), + "llm_model": (_llm_def.model_name if _llm_def else None), + "llm_base_url": (_llm_def.model_url if _llm_def else None), }, } @@ -118,12 +150,9 @@ async def health_check(): critical_services_healthy = True # Get configuration once at the start - memory_provider = os.getenv("MEMORY_PROVIDER", "chronicle").lower() - - # Map legacy provider names to current names - if memory_provider in ("friend-lite", "friend_lite"): - logger.debug(f"Mapping legacy provider '{memory_provider}' to 'chronicle'") - memory_provider = "chronicle" + # Memory provider (registry-based) + mem_settings = REGISTRY.memory if REGISTRY else {} + memory_provider = (mem_settings.get("provider") or "chronicle").lower() speaker_service_url = os.getenv("SPEAKER_SERVICE_URL") openmemory_mcp_url = os.getenv("OPENMEMORY_MCP_URL") @@ -215,14 +244,14 @@ async def health_check(): "healthy": "✅" in llm_health.get("status", ""), "base_url": llm_health.get("base_url", ""), "model": llm_health.get("default_model", ""), - "provider": os.getenv("LLM_PROVIDER", "openai"), + "provider": (_llm_def.model_provider if _llm_def else "unknown"), "critical": False, } except asyncio.TimeoutError: health_status["services"]["audioai"] = { "status": "⚠️ Connection Timeout (8s) - Service may not be running", "healthy": False, - "provider": os.getenv("LLM_PROVIDER", "openai"), + "provider": (_llm_def.model_provider if _llm_def else "unknown"), "critical": False, } overall_healthy = False @@ -230,7 +259,7 @@ async def health_check(): health_status["services"]["audioai"] = { "status": f"⚠️ Connection Failed: {str(e)} - Service may not be running", "healthy": False, - "provider": os.getenv("LLM_PROVIDER", "openai"), + "provider": (_llm_def.model_provider if _llm_def else "unknown"), "critical": False, } overall_healthy = False @@ -495,4 +524,4 @@ async def readiness_check(): return JSONResponse( content={"status": "not_ready", "error": str(e), "timestamp": int(time.time())}, status_code=503 - ) \ No newline at end of file + ) diff --git a/backends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.py b/backends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.py new file mode 100644 index 00000000..e45c51de --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.py @@ -0,0 +1,225 @@ + +import logging +import os +import uuid +import json +from pathlib import Path + +from fastapi import APIRouter, Depends, HTTPException, UploadFile, File, Body +from rq.exceptions import NoSuchJobError +from rq.job import Job +from pydantic import BaseModel +import zipfile + +from advanced_omi_backend.auth import current_active_user, current_superuser +from advanced_omi_backend.controllers.queue_controller import default_queue, redis_conn +from advanced_omi_backend.users import User +from advanced_omi_backend.services.obsidian_service import obsidian_service +from advanced_omi_backend.utils.file_utils import extract_zip, ZipExtractionError +from advanced_omi_backend.workers.obsidian_jobs import ( + count_markdown_files, + ingest_obsidian_vault_job, +) + +logger = logging.getLogger(__name__) + +router = APIRouter(prefix="/obsidian", tags=["obsidian"]) + +class IngestRequest(BaseModel): + vault_path: str + +@router.post("/ingest") +async def ingest_obsidian_vault( + request: IngestRequest, + current_user: User = Depends(current_active_user) +): + """ + Immediate/synchronous ingestion endpoint (legacy). Not recommended for UI. + Prefer the upload_zip + start endpoints to enable progress reporting. + """ + if not os.path.exists(request.vault_path): + raise HTTPException(status_code=400, detail=f"Path not found: {request.vault_path}") + + try: + result = await obsidian_service.ingest_vault(request.vault_path) + return {"message": "Ingestion complete", **result} + except Exception as e: + logger.error(f"Ingestion failed: {e}") + raise HTTPException(status_code=500, detail=str(e)) + + +@router.post("/upload_zip") +async def upload_obsidian_zip( + file: UploadFile = File(...), + current_user: User = Depends(current_superuser) +): + """ + Upload a zipped Obsidian vault. Returns a job_id that can be started later. + Uses upload_files_async pattern from upload_files.py for proper file handling. + """ + if not file.filename.lower().endswith('.zip'): + raise HTTPException(status_code=400, detail="Please upload a .zip file of your Obsidian vault") + + job_id = str(uuid.uuid4()) + base_dir = Path("/app/data/obsidian_jobs") + base_dir.mkdir(parents=True, exist_ok=True) + job_dir = base_dir / job_id + job_dir.mkdir(parents=True, exist_ok=True) + zip_path = job_dir / "vault.zip" + extract_dir = job_dir / "vault" + + # Use upload_files_async pattern for proper file handling with cleanup + zip_file_handle = None + try: + # Read file content + file_content = await file.read() + + # Save zip file using proper file handling pattern from upload_files_async + try: + zip_file_handle = open(zip_path, 'wb') + zip_file_handle.write(file_content) + except IOError as e: + logger.error(f"Error writing zip file {zip_path}: {e}") + raise HTTPException(status_code=500, detail=f"Failed to save uploaded zip: {e}") + + # Extract zip file using utility function + try: + extract_zip(zip_path, extract_dir) + except zipfile.BadZipFile as e: + logger.exception(f"Invalid zip file: {e}") + raise HTTPException(status_code=400, detail=f"Invalid zip file: {e}") + except ZipExtractionError as e: + logger.error(f"Error extracting zip file: {e}") + raise HTTPException(status_code=500, detail=f"Failed to extract zip file: {e}") + + total = count_markdown_files(str(extract_dir)) + + # Store pending job state in Redis + pending_state = { + "status": "ready", + "total": total, + "processed": 0, + "errors": [], + "vault_path": str(extract_dir), + "job_id": job_id + } + redis_conn.set(f"obsidian_pending:{job_id}", json.dumps(pending_state), ex=3600*24) # 24h expiry + + return {"job_id": job_id, "vault_path": str(extract_dir), "total_files": total} + except HTTPException: + raise + except Exception as e: + logger.exception(f"Failed to process uploaded zip: {e}") + raise HTTPException(status_code=500, detail=f"Failed to process uploaded zip: {e}") + finally: + # Ensure file handle is closed (following upload_files_async pattern) + if zip_file_handle: + try: + zip_file_handle.close() + except Exception as close_error: + logger.warning(f"Failed to close zip file handle: {close_error}") + + +@router.post("/start") +async def start_ingestion( + job_id: str = Body(..., embed=True), + current_user: User = Depends(current_active_user) +): + # Check if job is pending + pending_key = f"obsidian_pending:{job_id}" + pending_data = redis_conn.get(pending_key) + + if pending_data: + try: + job_data = json.loads(pending_data) + vault_path = job_data.get("vault_path") + + # Enqueue to RQ + rq_job = default_queue.enqueue( + ingest_obsidian_vault_job, + job_id, # arg1 + vault_path, # arg2 + job_id=job_id, # Set RQ job ID to match our ID + description=f"Obsidian ingestion for job {job_id}", + job_timeout=3600 # 1 hour timeout + ) + + # Remove pending key + redis_conn.delete(pending_key) + + return {"message": "Ingestion started", "job_id": job_id, "rq_job_id": rq_job.id} + except Exception as e: + logger.exception(f"Failed to start job {job_id}: {e}") + raise HTTPException(status_code=500, detail=f"Failed to start job: {e}") + + # Check if already in RQ + try: + job = Job.fetch(job_id, connection=redis_conn) + status = job.get_status() + if status in ("queued", "started", "deferred", "scheduled"): + raise HTTPException(status_code=400, detail=f"Job already {status}") + + # If finished/failed, we could potentially restart? But for now let's say it's done. + raise HTTPException(status_code=400, detail=f"Job is in state: {status}") + + except NoSuchJobError: + raise HTTPException(status_code=404, detail="Job not found") + + +@router.get("/status") +async def get_status(job_id: str, current_user: User = Depends(current_active_user)): + # 1. Try RQ first + try: + job = Job.fetch(job_id, connection=redis_conn) + + # Get status + status = job.get_status() + if status == "started": + status = "running" + if status == "canceled": + status = "cancelled" + + # Get metadata + meta = job.meta or {} + + # If meta has status, prefer it (for granular updates) + if "status" in meta and meta["status"] in ("running", "completed", "failed", "cancelled"): + status = meta["status"] + + total = meta.get("total_files", 0) + processed = meta.get("processed", 0) + percent = int((processed / total) * 100) if total else 0 + + return { + "job_id": job_id, + "status": status, + "total": total, + "processed": processed, + "percent": percent, + "errors": meta.get("errors", []), + "vault_path": meta.get("vault_path"), + "rq_job_id": job.id + } + + except NoSuchJobError: + # 2. Check pending + pending_key = f"obsidian_pending:{job_id}" + pending_data = redis_conn.get(pending_key) + + if pending_data: + try: + job_data = json.loads(pending_data) + return { + "job_id": job_id, + "status": "ready", + "total": job_data.get("total", 0), + "processed": 0, + "percent": 0, + "errors": [], + "vault_path": job_data.get("vault_path") + } + except: + raise HTTPException(status_code=500, detail="Failed to get job status") + raise HTTPException(status_code=404, detail="Job not found") + + diff --git a/backends/advanced/src/advanced_omi_backend/routers/modules/system_routes.py b/backends/advanced/src/advanced_omi_backend/routers/modules/system_routes.py index e51c036c..ead61ffa 100644 --- a/backends/advanced/src/advanced_omi_backend/routers/modules/system_routes.py +++ b/backends/advanced/src/advanced_omi_backend/routers/modules/system_routes.py @@ -8,9 +8,14 @@ from typing import Optional from fastapi import APIRouter, Body, Depends, Request +from pydantic import BaseModel from advanced_omi_backend.auth import current_active_user, current_superuser -from advanced_omi_backend.controllers import system_controller, session_controller, queue_controller +from advanced_omi_backend.controllers import ( + queue_controller, + session_controller, + system_controller, +) from advanced_omi_backend.models.user import User logger = logging.getLogger(__name__) @@ -18,6 +23,12 @@ router = APIRouter(tags=["system"]) +# Request models for memory config endpoints +class MemoryConfigRequest(BaseModel): + """Request model for memory configuration validation and updates.""" + config_yaml: str + + @router.get("/metrics") async def get_current_metrics(current_user: User = Depends(current_superuser)): """Get current system metrics. Admin only.""" @@ -72,35 +83,42 @@ async def get_speaker_service_status(current_user: User = Depends(current_superu return await system_controller.get_speaker_service_status() -# Memory Configuration Management Endpoints - +# Memory Configuration Management Endpoints Removed - Project uses config.yml exclusively @router.get("/admin/memory/config/raw") async def get_memory_config_raw(current_user: User = Depends(current_superuser)): - """Get current memory configuration YAML as plain text. Admin only.""" + """Get memory configuration YAML from config.yml. Admin only.""" return await system_controller.get_memory_config_raw() - @router.post("/admin/memory/config/raw") async def update_memory_config_raw( - config_yaml: str = Body(..., embed=True), + config_yaml: str = Body(..., media_type="text/plain"), current_user: User = Depends(current_superuser) ): - """Update memory configuration YAML and hot reload. Admin only.""" + """Save memory YAML to config.yml and hot-reload. Admin only.""" return await system_controller.update_memory_config_raw(config_yaml) +@router.post("/admin/memory/config/validate/raw") +async def validate_memory_config_raw( + config_yaml: str = Body(..., media_type="text/plain"), + current_user: User = Depends(current_superuser), +): + """Validate posted memory YAML as plain text (used by Web UI). Admin only.""" + return await system_controller.validate_memory_config(config_yaml) + + @router.post("/admin/memory/config/validate") async def validate_memory_config( - config_yaml: str = Body(..., embed=True), + request: MemoryConfigRequest, current_user: User = Depends(current_superuser) ): - """Validate memory configuration YAML syntax. Admin only.""" - return await system_controller.validate_memory_config(config_yaml) + """Validate memory configuration YAML sent as JSON (used by tests). Admin only.""" + return await system_controller.validate_memory_config(request.config_yaml) @router.post("/admin/memory/config/reload") async def reload_memory_config(current_user: User = Depends(current_superuser)): - """Reload memory configuration from file. Admin only.""" + """Reload memory configuration from config.yml. Admin only.""" return await system_controller.reload_memory_config() diff --git a/backends/advanced/src/advanced_omi_backend/services/memory/config.py b/backends/advanced/src/advanced_omi_backend/services/memory/config.py index f3943f29..e48b8fb5 100644 --- a/backends/advanced/src/advanced_omi_backend/services/memory/config.py +++ b/backends/advanced/src/advanced_omi_backend/services/memory/config.py @@ -2,9 +2,14 @@ import logging import os +import yaml +from pathlib import Path from dataclasses import dataclass from enum import Enum -from typing import Any, Dict +from typing import Any, Dict, Optional, Union + +from advanced_omi_backend.model_registry import get_models_registry +from advanced_omi_backend.utils.config_utils import resolve_value memory_logger = logging.getLogger("memory_service") @@ -20,6 +25,7 @@ def _is_langfuse_enabled() -> bool: class LLMProvider(Enum): """Supported LLM providers.""" + OPENAI = "openai" OLLAMA = "ollama" CUSTOM = "custom" @@ -27,6 +33,7 @@ class LLMProvider(Enum): class VectorStoreProvider(Enum): """Supported vector store providers.""" + QDRANT = "qdrant" WEAVIATE = "weaviate" CUSTOM = "custom" @@ -34,14 +41,16 @@ class VectorStoreProvider(Enum): class MemoryProvider(Enum): """Supported memory service providers.""" - CHRONICLE = "chronicle" # Default sophisticated implementation + + CHRONICLE = "chronicle" # Default sophisticated implementation OPENMEMORY_MCP = "openmemory_mcp" # OpenMemory MCP backend - MYCELIA = "mycelia" # Mycelia memory backend + MYCELIA = "mycelia" # Mycelia memory backend @dataclass class MemoryConfig: """Configuration for memory service.""" + memory_provider: MemoryProvider = MemoryProvider.CHRONICLE llm_provider: LLMProvider = LLMProvider.OPENAI vector_store_provider: VectorStoreProvider = VectorStoreProvider.QDRANT @@ -55,80 +64,42 @@ class MemoryConfig: timeout_seconds: int = 1200 -def create_openai_config( - api_key: str, - model: str = "gpt-4", - embedding_model: str = "text-embedding-3-small", - base_url: str = "https://api.openai.com/v1", - temperature: float = 0.1, - max_tokens: int = 2000 -) -> Dict[str, Any]: - """Create OpenAI configuration.""" - return { - "api_key": api_key, - "model": model, - "embedding_model": embedding_model, - "base_url": base_url, - "temperature": temperature, - "max_tokens": max_tokens - } +def load_config_yml() -> Dict[str, Any]: + """Load config.yml from standard locations.""" + # Check /app/config.yml (Docker) or root relative to file + current_dir = Path(__file__).parent.resolve() + # Path inside Docker: /app/config.yml (if mounted) or ../../../config.yml relative to src + paths = [ + Path("/app/config.yml"), + current_dir.parent.parent.parent.parent.parent / "config.yml", # Relative to src/ + Path("./config.yml"), + ] + for path in paths: + if path.exists(): + with open(path, "r") as f: + return yaml.safe_load(f) or {} -def create_ollama_config( - base_url: str, - model: str = "llama2", - embedding_model: str = "nomic-embed-text", - temperature: float = 0.1, - max_tokens: int = 2000, - use_qwen_embeddings: bool = True -) -> Dict[str, Any]: - """Create Ollama configuration.""" - return { - "api_key": "dummy", # Ollama doesn't require an API key - "base_url": base_url, - "model": model, - "embedding_model": embedding_model, - "temperature": temperature, - "max_tokens": max_tokens, - "use_qwen_embeddings": use_qwen_embeddings - } - - -def create_qdrant_config( - host: str = "localhost", - port: int = 6333, - collection_name: str = "memories", - embedding_dims: int = 1536 -) -> Dict[str, Any]: - """Create Qdrant configuration.""" - return { - "host": host, - "port": port, - "collection_name": collection_name, - "embedding_dims": embedding_dims - } + raise FileNotFoundError(f"config.yml not found in any of: {[str(p) for p in paths]}") def create_openmemory_config( server_url: str = "http://localhost:8765", client_name: str = "chronicle", user_id: str = "default", - timeout: int = 30 + timeout: int = 30, ) -> Dict[str, Any]: """Create OpenMemory MCP configuration.""" return { "server_url": server_url, "client_name": client_name, "user_id": user_id, - "timeout": timeout + "timeout": timeout, } def create_mycelia_config( - api_url: str = "http://localhost:8080", - api_key: str = None, - timeout: int = 30, - **kwargs + api_url: str = "http://localhost:8080", api_key: str = None, timeout: int = 30, **kwargs ) -> Dict[str, Any]: """Create Mycelia configuration.""" config = { @@ -141,11 +112,48 @@ def create_mycelia_config( return config +def create_openai_config( + api_key: str, + model: str, + *, + embedding_model: Optional[str] = None, + base_url: str = "https://api.openai.com/v1", + temperature: float = 0.1, + max_tokens: int = 2000, +) -> Dict[str, Any]: + """Create OpenAI/OpenAI-compatible client configuration.""" + return { + "api_key": api_key, + "model": model, + "embedding_model": embedding_model or model, + "base_url": base_url, + "temperature": temperature, + "max_tokens": max_tokens, + } + + +def create_qdrant_config( + host: str = "localhost", + port: int = 6333, + collection_name: str = "omi_memories", + embedding_dims: int = 1536, +) -> Dict[str, Any]: + """Create Qdrant vector store configuration.""" + return { + "host": host, + "port": port, + "collection_name": collection_name, + "embedding_dims": embedding_dims, + } + + def build_memory_config_from_env() -> MemoryConfig: """Build memory configuration from environment variables and YAML config.""" try: - # Determine memory provider - memory_provider = os.getenv("MEMORY_PROVIDER", "chronicle").lower() + # Determine memory provider from registry + reg = get_models_registry() + mem_settings = reg.memory if reg else {} + memory_provider = (mem_settings.get("provider") or "chronicle").lower() # Map legacy provider names to current names if memory_provider in ("friend-lite", "friend_lite"): @@ -156,140 +164,121 @@ def build_memory_config_from_env() -> MemoryConfig: raise ValueError(f"Unsupported memory provider: {memory_provider}") memory_provider_enum = MemoryProvider(memory_provider) - + # For OpenMemory MCP, configuration is much simpler if memory_provider_enum == MemoryProvider.OPENMEMORY_MCP: + mcp = mem_settings.get("openmemory_mcp") or {} openmemory_config = create_openmemory_config( - server_url=os.getenv("OPENMEMORY_MCP_URL", "http://localhost:8765"), - client_name=os.getenv("OPENMEMORY_CLIENT_NAME", "chronicle"), - user_id=os.getenv("OPENMEMORY_USER_ID", "default"), - timeout=int(os.getenv("OPENMEMORY_TIMEOUT", "30")) + server_url=mcp.get("server_url", "http://localhost:8765"), + client_name=mcp.get("client_name", "chronicle"), + user_id=mcp.get("user_id", "default"), + timeout=int(mcp.get("timeout", 30)), ) - memory_logger.info(f"🔧 Memory config: Provider=OpenMemory MCP, URL={openmemory_config['server_url']}") + memory_logger.info( + f"🔧 Memory config: Provider=OpenMemory MCP, URL={openmemory_config['server_url']}" + ) return MemoryConfig( memory_provider=memory_provider_enum, openmemory_config=openmemory_config, - timeout_seconds=int(os.getenv("OPENMEMORY_TIMEOUT", "30")) + timeout_seconds=int(mem_settings.get("timeout_seconds", 1200)), ) # For Mycelia provider, build mycelia_config + llm_config (for temporal extraction) if memory_provider_enum == MemoryProvider.MYCELIA: - mycelia_config = create_mycelia_config( - api_url=os.getenv("MYCELIA_URL", "http://localhost:5173"), - timeout=int(os.getenv("MYCELIA_TIMEOUT", "30")) - ) - - # Build LLM config for temporal extraction (Mycelia provider uses OpenAI directly) - openai_api_key = os.getenv("OPENAI_API_KEY") - if not openai_api_key: - memory_logger.warning("OPENAI_API_KEY not set - temporal extraction will be disabled") - llm_config = None + # Registry-driven Mycelia configuration + mys = mem_settings.get("mycelia") or {} + api_url = mys.get("api_url", "http://localhost:5173") + timeout = int(mys.get("timeout", 30)) + mycelia_config = create_mycelia_config(api_url=api_url, timeout=timeout) + + # Use default LLM from registry for temporal extraction + llm_config = None + if reg: + llm_def = reg.get_default("llm") + if llm_def: + llm_config = create_openai_config( + api_key=llm_def.api_key or "", + model=llm_def.model_name, + base_url=llm_def.model_url, + ) + memory_logger.info( + f"🔧 Mycelia temporal extraction (registry): LLM={llm_def.model_name}" + ) else: - model = os.getenv("OPENAI_MODEL", "gpt-4o-mini") - base_url = os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1") - llm_config = create_openai_config( - api_key=openai_api_key, - model=model, - base_url=base_url + memory_logger.warning( + "Registry not available for Mycelia temporal extraction; disabled" ) - memory_logger.info(f"🔧 Mycelia temporal extraction: LLM={model}") - memory_logger.info(f"🔧 Memory config: Provider=Mycelia, URL={mycelia_config['api_url']}") + memory_logger.info( + f"🔧 Memory config: Provider=Mycelia, URL={mycelia_config['api_url']}" + ) return MemoryConfig( memory_provider=memory_provider_enum, mycelia_config=mycelia_config, llm_config=llm_config, - timeout_seconds=int(os.getenv("MYCELIA_TIMEOUT", "30")) + timeout_seconds=int(mem_settings.get("timeout_seconds", timeout)), ) - - # For Chronicle provider, use existing complex configuration - # Import config loader - from advanced_omi_backend.memory_config_loader import get_config_loader - - config_loader = get_config_loader() - memory_config = config_loader.get_memory_extraction_config() - - # Get LLM provider from environment - llm_provider = os.getenv("LLM_PROVIDER", "openai").lower().strip() - memory_logger.info(f"LLM_PROVIDER: {llm_provider}") - if llm_provider not in [p.value for p in LLMProvider]: - raise ValueError(f"Unsupported LLM provider: {llm_provider}") - + + # For Chronicle provider, use registry-driven configuration + + # Registry-driven configuration only (no env-based branching) llm_config = None - llm_provider_enum = None - embedding_dims = 1536 # Default - - # Build LLM configuration - if llm_provider == "openai": - openai_api_key = os.getenv("OPENAI_API_KEY") - if not openai_api_key: - raise ValueError("OPENAI_API_KEY required for OpenAI provider") - - # Use environment variables for model, fall back to config, then defaults - model = os.getenv("OPENAI_MODEL") or memory_config.get("llm_settings", {}).get("model") or "gpt-4o-mini" - embedding_model = memory_config.get("llm_settings", {}).get("embedding_model") or "text-embedding-3-small" - base_url = os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1") - memory_logger.info(f"🔧 Memory config: LLM={model}, Embedding={embedding_model}, Base URL={base_url}") - - llm_config = create_openai_config( - api_key=openai_api_key, - model=model, - embedding_model=embedding_model, - base_url=base_url, - temperature=memory_config.get("llm_settings", {}).get("temperature", 0.1), - max_tokens=memory_config.get("llm_settings", {}).get("max_tokens", 2000) - ) - llm_provider_enum = LLMProvider.OPENAI - embedding_dims = get_embedding_dims(llm_config) - memory_logger.info(f"🔧 Setting Embedder dims {embedding_dims}") - - elif llm_provider == "ollama": - base_url = os.getenv("OLLAMA_BASE_URL") - if not base_url: - raise ValueError("OLLAMA_BASE_URL required for Ollama provider") - - model = os.getenv("OLLAMA_MODEL") - if not model: - raise ValueError("OLLAMA_MODEL required for Ollama provider") - embedding_model = os.getenv("OLLAMA_EMBEDDER_MODEL") - if not embedding_model: - raise ValueError("OLLAMA_EMBEDDER_MODEL required for Ollama provider") - memory_logger.info(f"🔧 Memory config: LLM={model}, Embedding={embedding_model}, Base URL={base_url}") - - llm_config = create_ollama_config( - base_url=base_url, - model=model, - embedding_model=embedding_model, - ) - llm_provider_enum = LLMProvider.OLLAMA - embedding_dims = get_embedding_dims(llm_config) - memory_logger.info(f"🔧 Setting Embedder dims {embedding_dims}") - - # Build vector store configuration - vector_store_provider = os.getenv("VECTOR_STORE_PROVIDER", "qdrant").lower() - - if vector_store_provider == "qdrant": - qdrant_host = os.getenv("QDRANT_BASE_URL", "qdrant") - vector_store_config = create_qdrant_config( - host=qdrant_host, - port=int(os.getenv("QDRANT_PORT", "6333")), - collection_name="omi_memories", - embedding_dims=embedding_dims - ) - vector_store_provider_enum = VectorStoreProvider.QDRANT - - else: - raise ValueError(f"Unsupported vector store provider: {vector_store_provider}") - - # Get memory extraction settings - extraction_enabled = config_loader.is_memory_extraction_enabled() - extraction_prompt = config_loader.get_memory_prompt() if extraction_enabled else None - - memory_logger.info(f"🔧 Memory config: Provider=Chronicle, LLM={llm_provider}, VectorStore={vector_store_provider}, Extraction={extraction_enabled}") - + llm_provider_enum = LLMProvider.OPENAI # OpenAI-compatible API family + embedding_dims = 1536 + if not reg: + raise ValueError("config.yml not found; cannot configure LLM provider") + llm_def = reg.get_default("llm") + embed_def = reg.get_default("embedding") + if not llm_def: + raise ValueError("No default LLM defined in config.yml") + model = llm_def.model_name + embedding_model = embed_def.model_name if embed_def else "text-embedding-3-small" + base_url = llm_def.model_url + memory_logger.info( + f"🔧 Memory config (registry): LLM={model}, Embedding={embedding_model}, Base URL={base_url}" + ) + llm_config = create_openai_config( + api_key=llm_def.api_key or "", + model=model, + embedding_model=embedding_model, + base_url=base_url, + temperature=float(llm_def.model_params.get("temperature", 0.1)), + max_tokens=int(llm_def.model_params.get("max_tokens", 2000)), + ) + embedding_dims = get_embedding_dims(llm_config) + memory_logger.info(f"🔧 Setting Embedder dims {embedding_dims}") + + # Build vector store configuration from registry (no env) + vs_def = reg.get_default("vector_store") + if not vs_def or (vs_def.model_provider or "").lower() != "qdrant": + raise ValueError("No default Qdrant vector_store defined in config.yml") + + host = str(vs_def.model_params.get("host", "qdrant")) + port = int(vs_def.model_params.get("port", 6333)) + collection_name = str(vs_def.model_params.get("collection_name", "omi_memories")) + vector_store_config = create_qdrant_config( + host=host, + port=port, + collection_name=collection_name, + embedding_dims=embedding_dims, + ) + vector_store_provider_enum = VectorStoreProvider.QDRANT + + # Get memory extraction settings from registry + extraction_cfg = mem_settings.get("extraction") or {} + extraction_enabled = bool(extraction_cfg.get("enabled", True)) + extraction_prompt = extraction_cfg.get("prompt") if extraction_enabled else None + + # Timeouts/tunables from registry.memory + timeout_seconds = int(mem_settings.get("timeout_seconds", 1200)) + + memory_logger.info( + f"🔧 Memory config: Provider=Chronicle, LLM={llm_def.model_provider if 'llm_def' in locals() else 'unknown'}, VectorStore={vector_store_provider_enum}, Extraction={extraction_enabled}" + ) + return MemoryConfig( memory_provider=memory_provider_enum, llm_provider=llm_provider_enum, @@ -299,9 +288,9 @@ def build_memory_config_from_env() -> MemoryConfig: embedder_config={}, # Included in llm_config extraction_prompt=extraction_prompt, extraction_enabled=extraction_enabled, - timeout_seconds=int(os.getenv("OLLAMA_TIMEOUT_SECONDS", "1200")) + timeout_seconds=timeout_seconds, ) - + except ImportError: memory_logger.warning("Config loader not available, using environment variables only") raise @@ -312,42 +301,15 @@ def get_embedding_dims(llm_config: Dict[str, Any]) -> int: Query the embedding endpoint and return the embedding vector length. Works for OpenAI and OpenAI-compatible endpoints (e.g., Ollama). """ - embedding_model = llm_config.get('embedding_model') + embedding_model = llm_config.get("embedding_model") try: - # Conditionally use Langfuse if configured - if _is_langfuse_enabled(): - from langfuse.openai import OpenAI - client = OpenAI( - api_key=llm_config.get('api_key'), - base_url=llm_config.get('base_url') - ) - else: - from openai import OpenAI - client = OpenAI( - api_key=llm_config.get('api_key'), - base_url=llm_config.get('base_url') - ) - response = client.embeddings.create( - model=embedding_model, - input="hello world" + reg = get_models_registry() + if reg: + emb_def = reg.get_default("embedding") + if emb_def and emb_def.embedding_dimensions: + return int(emb_def.embedding_dimensions) + except Exception as e: + memory_logger.exception( + f"Failed to get embedding dimensions from registry for model '{embedding_model}'" ) - embedding = response.data[0].embedding - if not embedding or not isinstance(embedding, list): - return 1536 - return len(embedding) - - except (ImportError, KeyError, AttributeError, IndexError, TypeError, ValueError) as e: - embedding_dims = 1536 # default - memory_logger.exception(f"Failed to get embedding dimensions for model '{embedding_model}'") - if embedding_model == "text-embedding-3-small": - embedding_dims = 1536 - elif embedding_model == "text-embedding-3-large": - embedding_dims = 3072 - elif embedding_model == "text-embedding-ada-002": - embedding_dims = 1536 - elif embedding_model == "nomic-embed-text:latest": - embedding_dims = 768 - else: - # Default for OpenAI embedding models - memory_logger.info(f"Unrecognized embedding model '{embedding_model}', using default dimension {embedding_dims}") - return embedding_dims \ No newline at end of file + raise e diff --git a/backends/advanced/src/advanced_omi_backend/services/memory/providers/chronicle.py b/backends/advanced/src/advanced_omi_backend/services/memory/providers/chronicle.py index a0974e21..3fb96f00 100644 --- a/backends/advanced/src/advanced_omi_backend/services/memory/providers/chronicle.py +++ b/backends/advanced/src/advanced_omi_backend/services/memory/providers/chronicle.py @@ -84,9 +84,16 @@ async def initialize(self) -> None: vector_ok = await self.vector_store.test_connection() if not llm_ok: - raise RuntimeError("LLM provider connection failed") + raise RuntimeError( + f"LLM provider connection failed for {self.config.llm_provider.value}. " + f"Check API keys, network connectivity, and service availability. " + f"Memory processing cannot proceed without a working LLM connection." + ) if not vector_ok: - raise RuntimeError("Vector store connection failed") + raise RuntimeError( + f"Vector store connection failed for {self.config.vector_store_provider.value}. " + f"Check that Qdrant service is running and accessible." + ) self._initialized = True memory_logger.info( diff --git a/backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py b/backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py index a876e643..a73f1bc8 100644 --- a/backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py +++ b/backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py @@ -8,15 +8,12 @@ memory action proposals using their respective APIs. """ +import asyncio import json import logging import os -import httpx from typing import Any, Dict, List, Optional -# TODO: Re-enable spacy when Docker build is fixed -# import spacy - from ..base import LLMProviderBase from ..prompts import ( FACT_RETRIEVAL_PROMPT, @@ -30,8 +27,15 @@ ) from ..utils import extract_json_from_text +# TODO: Re-enable spacy when Docker build is fixed +# import spacy + + memory_logger = logging.getLogger("memory_service") +# New: config-driven model registry + universal client +from advanced_omi_backend.model_registry import ModelDef, get_models_registry + def _is_langfuse_enabled() -> bool: """Check if Langfuse is properly configured.""" @@ -59,7 +63,7 @@ def _get_openai_client(api_key: str, base_url: str, is_async: bool = False): memory_logger.debug("Using OpenAI client with Langfuse tracing") else: # Use regular OpenAI client without tracing - from openai import OpenAI, AsyncOpenAI + from openai import AsyncOpenAI, OpenAI openai = type('OpenAI', (), {'OpenAI': OpenAI, 'AsyncOpenAI': AsyncOpenAI})() memory_logger.debug("Using OpenAI client without tracing") @@ -68,6 +72,25 @@ def _get_openai_client(api_key: str, base_url: str, is_async: bool = False): else: return openai.OpenAI(api_key=api_key, base_url=base_url) + +async def generate_openai_embeddings( + texts: List[str], + api_key: str, + base_url: str, + model: str, +) -> List[List[float]]: + """Generate embeddings with the async OpenAI client.""" + client = _get_openai_client( + api_key=api_key, + base_url=base_url, + is_async=True, + ) + response = await client.embeddings.create( + model=model, + input=texts, + ) + return [data.embedding for data in response.data] + # TODO: Re-enable spacy when Docker build is fixed # try: # nlp = spacy.load("en_core_web_sm") @@ -133,27 +156,54 @@ def chunk_text_with_spacy(text: str, max_tokens: int = 100) -> List[str]: return chunks class OpenAIProvider(LLMProviderBase): - """OpenAI LLM provider implementation. - - Provides memory extraction, embedding generation, and memory action - proposals using OpenAI's GPT and embedding models. - - Attributes: - api_key: OpenAI API key - model: GPT model to use for text generation - embedding_model: Model to use for embeddings - base_url: API base URL (for custom endpoints) - temperature: Sampling temperature for generation - max_tokens: Maximum tokens in responses + """Config-driven LLM provider using OpenAI SDK (OpenAI-compatible). + + Uses the official OpenAI client (with custom base_url and api_key) to call + chat and embeddings across OpenAI-compatible providers (OpenAI, Ollama, Groq). + Models and endpoints are resolved from config.yml via the model registry. """ def __init__(self, config: Dict[str, Any]): - self.api_key = config["api_key"] - self.model = config.get("model", "gpt-4") - self.embedding_model = config.get("embedding_model", "text-embedding-3-small") - self.base_url = config.get("base_url", "https://api.openai.com/v1") - self.temperature = config.get("temperature", 0.1) - self.max_tokens = config.get("max_tokens", 2000) + # Ignore provider-specific envs; use registry as single source of truth + registry = get_models_registry() + if not registry: + raise RuntimeError("config.yml not found or invalid; cannot initialize model registry") + + # Resolve default models + self.llm_def: ModelDef = registry.get_default("llm") # type: ignore + self.embed_def: ModelDef | None = registry.get_default("embedding") + + if not self.llm_def: + raise RuntimeError("No default LLM defined in config.yml") + + # Store parameters for LLM + self.api_key = self.llm_def.api_key or "" + self.base_url = self.llm_def.model_url + self.model = self.llm_def.model_name + self.temperature = float(self.llm_def.model_params.get("temperature", 0.1)) + self.max_tokens = int(self.llm_def.model_params.get("max_tokens", 2000)) + + # Store parameters for embeddings (use separate config if available) + self.embedding_model = (self.embed_def.model_name if self.embed_def else self.llm_def.model_name) + self.embedding_api_key = (self.embed_def.api_key if self.embed_def else self.api_key) + self.embedding_base_url = (self.embed_def.model_url if self.embed_def else self.base_url) + + # CRITICAL: Validate API keys are present - fail fast instead of hanging + if not self.api_key or self.api_key.strip() == "": + raise RuntimeError( + f"API key is missing or empty for LLM provider '{self.llm_def.model_provider}' (model: {self.model}). " + f"Please set the API key in config.yml or environment variables. " + f"Cannot proceed without valid API credentials." + ) + + if self.embed_def and (not self.embedding_api_key or self.embedding_api_key.strip() == ""): + raise RuntimeError( + f"API key is missing or empty for embedding provider '{self.embed_def.model_provider}' (model: {self.embedding_model}). " + f"Please set the API key in config.yml or environment variables." + ) + + # Lazy client creation + self._client = None async def extract_memories(self, text: str, prompt: str) -> List[str]: """Extract memories using OpenAI API with the enhanced fact retrieval prompt. @@ -166,12 +216,6 @@ async def extract_memories(self, text: str, prompt: str) -> List[str]: List of extracted memory strings """ try: - client = _get_openai_client( - api_key=self.api_key, - base_url=self.base_url, - is_async=True - ) - # Use the provided prompt or fall back to default system_prompt = prompt if prompt.strip() else FACT_RETRIEVAL_PROMPT @@ -179,10 +223,7 @@ async def extract_memories(self, text: str, prompt: str) -> List[str]: text_chunks = chunk_text_with_spacy(text) # Process all chunks in sequence, not concurrently - results = [ - await self._process_chunk(client, system_prompt, chunk, i) - for i, chunk in enumerate(text_chunks) - ] + results = [await self._process_chunk(system_prompt, chunk, i) for i, chunk in enumerate(text_chunks)] # Spread list of list of facts into a single list of facts cleaned_facts = [] @@ -196,7 +237,7 @@ async def extract_memories(self, text: str, prompt: str) -> List[str]: memory_logger.error(f"OpenAI memory extraction failed: {e}") return [] - async def _process_chunk(self, client, system_prompt: str, chunk: str, index: int) -> List[str]: + async def _process_chunk(self, system_prompt: str, chunk: str, index: int) -> List[str]: """Process a single text chunk to extract memories using OpenAI API. This private method handles the LLM interaction for a single chunk of text, @@ -218,17 +259,17 @@ async def _process_chunk(self, client, system_prompt: str, chunk: str, index: in memory extraction process. """ try: + client = _get_openai_client(api_key=self.api_key, base_url=self.base_url, is_async=True) response = await client.chat.completions.create( model=self.model, messages=[ {"role": "system", "content": system_prompt}, - {"role": "user", "content": chunk} + {"role": "user", "content": chunk}, ], temperature=self.temperature, max_tokens=self.max_tokens, - response_format={"type": "json_object"} + response_format={"type": "json_object"}, ) - facts = (response.choices[0].message.content or "").strip() if not facts: return [] @@ -249,48 +290,32 @@ async def generate_embeddings(self, texts: List[str]) -> List[List[float]]: List of embedding vectors, one per input text """ try: - client = _get_openai_client( + return await generate_openai_embeddings( + texts, api_key=self.api_key, base_url=self.base_url, - is_async=True - ) - - response = await client.embeddings.create( model=self.embedding_model, - input=texts ) - - return [data.embedding for data in response.data] - except Exception as e: memory_logger.error(f"OpenAI embedding generation failed: {e}") - raise e + raise async def test_connection(self) -> bool: - """Test OpenAI connection. + """Test OpenAI connection with timeout. Returns: True if connection successful, False otherwise """ + try: - # For Ollama, just check if the base URL is reachable - if os.getenv("LLM_PROVIDER", "openai").lower() == "ollama": - import httpx - async with httpx.AsyncClient() as client: - # For Ollama, test connection by hitting the /v1/models endpoint - response = await client.get(f"{self.base_url}/models") - response.raise_for_status() + # Add 10-second timeout to prevent hanging on API calls + async with asyncio.timeout(10): + client = _get_openai_client(api_key=self.api_key, base_url=self.base_url, is_async=True) + await client.models.list() return True - - client = _get_openai_client( - api_key=self.api_key, - base_url=self.base_url, - is_async=True - ) - - await client.models.list() - return True - + except asyncio.TimeoutError: + memory_logger.error(f"OpenAI connection test timed out after 10s - check network connectivity and API endpoint") + return False except Exception as e: memory_logger.error(f"OpenAI connection test failed: {e}") return False @@ -321,19 +346,13 @@ async def propose_memory_actions( ) memory_logger.debug(f"🧠 Generated prompt user content: {update_memory_messages[1]['content'][:200]}...") - client = _get_openai_client( - api_key=self.api_key, - base_url=self.base_url, - is_async=True - ) - + client = _get_openai_client(api_key=self.api_key, base_url=self.base_url, is_async=True) response = await client.chat.completions.create( model=self.model, messages=update_memory_messages, temperature=self.temperature, max_tokens=self.max_tokens, ) - content = (response.choices[0].message.content or "").strip() if not content: return {} diff --git a/backends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py b/backends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py index 6f9df0ba..6ace9ad6 100644 --- a/backends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py +++ b/backends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py @@ -23,6 +23,7 @@ get_temporal_entity_extraction_prompt, ) from .llm_providers import _get_openai_client +from advanced_omi_backend.model_registry import get_models_registry memory_logger = logging.getLogger("memory_service") @@ -241,30 +242,27 @@ async def _extract_memories_via_llm( Raises: RuntimeError: If LLM call fails """ - if not self.llm_config: - memory_logger.warning("No LLM config available for fact extraction") - return [] - try: - # Get OpenAI client using Chronicle's utility - client = _get_openai_client( - api_key=self.llm_config.get("api_key"), - base_url=self.llm_config.get("base_url", "https://api.openai.com/v1"), - is_async=True, - ) - - # Call OpenAI for memory extraction + # Use registry-driven default LLM with OpenAI SDK + reg = get_models_registry() + if not reg: + memory_logger.warning("No registry available for LLM; cannot extract facts") + return [] + llm_def = reg.get_default("llm") + if not llm_def: + memory_logger.warning("No default LLM in config.yml; cannot extract facts") + return [] + client = _get_openai_client(api_key=llm_def.api_key or "", base_url=llm_def.model_url, is_async=True) response = await client.chat.completions.create( - model=self.llm_config.get("model", "gpt-4o-mini"), + model=llm_def.model_name, messages=[ {"role": "system", "content": FACT_RETRIEVAL_PROMPT}, {"role": "user", "content": transcript}, ], response_format={"type": "json_object"}, - temperature=0.1, + temperature=float(llm_def.model_params.get("temperature", 0.1)), ) - - content = response.choices[0].message.content + content = (response.choices[0].message.content or "").strip() if not content: memory_logger.warning("LLM returned empty content") @@ -299,21 +297,19 @@ async def _extract_temporal_entity_via_llm( Returns: TemporalEntity with extracted information, or None if extraction fails """ - if not self.llm_config: - memory_logger.warning("No LLM config available for temporal extraction") - return None - try: - # Get OpenAI client using Chronicle's utility - client = _get_openai_client( - api_key=self.llm_config.get("api_key"), - base_url=self.llm_config.get("base_url", "https://api.openai.com/v1"), - is_async=True, - ) - - # Call OpenAI with structured output request + # Use registry-driven default LLM with OpenAI SDK + reg = get_models_registry() + if not reg: + memory_logger.warning("No registry available for LLM; cannot extract temporal entity") + return None + llm_def = reg.get_default("llm") + if not llm_def: + memory_logger.warning("No default LLM in config.yml; cannot extract temporal entity") + return None + client = _get_openai_client(api_key=llm_def.api_key or "", base_url=llm_def.model_url, is_async=True) response = await client.chat.completions.create( - model=self.llm_config.get("model", "gpt-4o-mini"), + model=llm_def.model_name, messages=[ {"role": "system", "content": get_temporal_entity_extraction_prompt()}, { @@ -322,7 +318,7 @@ async def _extract_temporal_entity_via_llm( }, ], response_format={"type": "json_object"}, - temperature=0.1, + temperature=float(llm_def.model_params.get("temperature", 0.1)), ) content = response.choices[0].message.content diff --git a/backends/advanced/src/advanced_omi_backend/services/neo4j_client.py b/backends/advanced/src/advanced_omi_backend/services/neo4j_client.py new file mode 100644 index 00000000..c0e3e633 --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/services/neo4j_client.py @@ -0,0 +1,63 @@ +"""Shared Neo4j client utilities for the advanced OMI backend.""" + +from typing import Optional +from neo4j import GraphDatabase, Driver, READ_ACCESS, WRITE_ACCESS + + +class Neo4jClient: + """Thin wrapper around the Neo4j driver for shared connection management.""" + + def __init__(self, uri: str, user: str, password: str): + self.uri = uri + self.auth = (user, password) + self._driver: Optional[Driver] = None + + def get_driver(self) -> Driver: + if not self._driver: + self._driver = GraphDatabase.driver(self.uri, auth=self.auth) + return self._driver + + def session(self, access_mode: Optional[str] = None): + driver = self.get_driver() + if access_mode: + return driver.session(default_access_mode=access_mode) + return driver.session() + + def close(self): + if self._driver: + self._driver.close() + self._driver = None + + def reset(self): + self.close() + + +class Neo4jInterface: + """Access interface with a fixed access mode (read/write).""" + + def __init__(self, client: Neo4jClient, access_mode: str): + self.client = client + self.access_mode = access_mode + + def session(self): + return self.client.session(access_mode=self.access_mode) + + def run(self, query: str, **parameters): + """Run a query and return consumed result data. + + Note: For queries requiring iteration over results, use session() + directly with a context manager. + """ + with self.session() as session: + result = session.run(query, **parameters) + return result.data() # Consume result before session closes + + +class Neo4jReadInterface(Neo4jInterface): + def __init__(self, client: Neo4jClient): + super().__init__(client, access_mode=READ_ACCESS) + + +class Neo4jWriteInterface(Neo4jInterface): + def __init__(self, client: Neo4jClient): + super().__init__(client, access_mode=WRITE_ACCESS) diff --git a/backends/advanced/src/advanced_omi_backend/services/obsidian_service.py b/backends/advanced/src/advanced_omi_backend/services/obsidian_service.py new file mode 100644 index 00000000..07f841b7 --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/services/obsidian_service.py @@ -0,0 +1,481 @@ +"""Obsidian vault ingestion service for Neo4j graph database. + +This module provides functionality to parse, chunk, embed, and ingest Obsidian markdown +notes into a Neo4j graph database. It extracts notes, chunks them for vector search, +generates embeddings, and stores them with relationships (folders, tags, links) in Neo4j. + +The service supports: +- Parsing Obsidian markdown files with frontmatter +- Character-based chunking with overlap +- Embedding generation using configured models +- Graph storage with Note, Chunk, Folder, Tag, and Link relationships +- Vector similarity search via Neo4j vector indexes +""" + +import logging +import os +import re +import hashlib +from typing import TypedDict, List, Optional, Literal +from pathlib import Path +from advanced_omi_backend.services.memory.providers.llm_providers import ( + generate_openai_embeddings, + chunk_text_with_spacy, +) +from advanced_omi_backend.services.memory.config import load_config_yml as load_root_config +from advanced_omi_backend.utils.model_utils import get_model_config +from advanced_omi_backend.utils.config_utils import resolve_value +from advanced_omi_backend.services.neo4j_client import ( + Neo4jClient, + Neo4jReadInterface, + Neo4jWriteInterface, +) + +logger = logging.getLogger(__name__) + + +class NoteData(TypedDict): + path: str + name: str + folder: str + content: str + wordcount: int + links: List[str] + tags: List[str] + + +class ChunkPayload(TypedDict): + text: str + embedding: List[float] + + +class ObsidianSearchResult(TypedDict): + results: List[str] + + +class ObsidianSearchError(Exception): + """Raised when Obsidian search fails at a specific stage.""" + + def __init__(self, stage: Literal["embedding", "database"], message: str): + super().__init__(message) + self.stage = stage + + +def load_env_file(filepath: Path) -> dict[str, str]: + """Load environment variables from a .env file. + + Args: + filepath: Path to the .env file to load. + + Returns: + Dictionary of key-value pairs from the .env file. + """ + env_vars = {} + if filepath.exists(): + with open(filepath, "r") as f: + for line in f: + line = line.strip() + if not line or line.startswith("#"): + continue + if "=" in line: + parts = line.split("=", 1) + key = parts[0].strip() + value = parts[1].strip() if len(parts) > 1 else "" + # Handle quotes + if (value.startswith("'") and value.endswith("'")) or ( + value.startswith('"') and value.endswith('"') + ): + value = value[1:-1] + env_vars[key] = value + return env_vars + + +class ObsidianService: + """Service for ingesting Obsidian vaults into Neo4j graph database.""" + + def __init__(self): + """Initialize the Obsidian service with configuration from config.yml and environment.""" + # Resolve paths relative to this file + # backends/advanced/src/advanced_omi_backend/services/obsidian_service.py + self.CURRENT_DIR = Path(__file__).parent.resolve() + + # Load configuration strictly from standard locations + # Prefer /app/config.yml inside containers (mounted by docker-compose) + # Fallbacks handled by shared utility + config_data = load_root_config() + + # Get model configurations using shared utility + llm_config = get_model_config(config_data, "llm") + if not llm_config: + raise ValueError("Configuration for 'defaults.llm' not found in config.yml") + + embed_config = get_model_config(config_data, "embedding") + if not embed_config: + raise ValueError("Configuration for 'defaults.embedding' not found in config.yml") + + # Neo4j Connection - Prefer environment variables passed by Docker Compose + neo4j_host = os.getenv("NEO4J_HOST") + # Load .env file as fallback (for local dev or if env vars not set) + candidate_env_files = [ + Path("/app/.env"), + self.CURRENT_DIR.parent.parent.parent.parent + / ".env", # Project root .env file ToDo cleanup needed after k8s is migrated and there is no .env file in the project root. + self.CURRENT_DIR.parent.parent.parent.parent + / "backends" + / "advanced" + / ".env", # repo path + ] + env_data = {} + for p in candidate_env_files: + if p.exists(): + env_data.update(load_env_file(p)) + + # Use env var first, then fallback to .env file + if not neo4j_host: + neo4j_host = env_data.get("NEO4J_HOST") + + if not neo4j_host: + raise KeyError("NEO4J_HOST not found in environment or .env") + + self.neo4j_uri = f"bolt://{neo4j_host}:7687" + self.neo4j_user = os.getenv("NEO4J_USER") or env_data.get("NEO4J_USER", "neo4j") + self.neo4j_password = os.getenv("NEO4J_PASSWORD") or env_data.get("NEO4J_PASSWORD", "") + + # Models / API - Loaded strictly from config.yml + self.embedding_model = str(resolve_value(embed_config["model_name"])) + self.embedding_dimensions = int(resolve_value(embed_config["embedding_dimensions"])) + self.openai_base_url = str(resolve_value(llm_config["model_url"])) + self.openai_api_key = str(resolve_value(llm_config["api_key"])) + + # Chunking - uses shared spaCy/text fallback utility + self.chunk_word_limit = 120 + + self.neo4j_client = Neo4jClient(self.neo4j_uri, self.neo4j_user, self.neo4j_password) + self.read_interface = Neo4jReadInterface(self.neo4j_client) + self.write_interface = Neo4jWriteInterface(self.neo4j_client) + + def close(self): + """Close the Neo4j driver connection and clean up resources.""" + self.neo4j_client.close() + + def reset_driver(self): + """Reset the driver connection, forcing it to be recreated with current credentials.""" + self.neo4j_client.reset() + + def setup_database(self) -> None: + """Create database constraints and vector index for notes and chunks.""" + # Reset driver to ensure we use current credentials + self.reset_driver() + with self.write_interface.session() as session: + session.run( + "CREATE CONSTRAINT note_path IF NOT EXISTS FOR (n:Note) REQUIRE n.path IS UNIQUE" + ) + session.run( + "CREATE CONSTRAINT chunk_id IF NOT EXISTS FOR (c:Chunk) REQUIRE c.id IS UNIQUE" + ) + index_query = f""" + CREATE VECTOR INDEX chunk_embeddings IF NOT EXISTS + FOR (c:Chunk) ON (c.embedding) + OPTIONS {{indexConfig: {{ + `vector.dimensions`: {self.embedding_dimensions}, + `vector.similarity_function`: 'cosine' + }}}} + """ + session.run(index_query) + + @staticmethod + def _clean_text(text: str) -> str: + """Normalize whitespace for embedding inputs.""" + return re.sub(r"\s+", " ", text).strip() + + def parse_obsidian_note(self, root: str, filename: str, vault_path: str) -> NoteData: + """Parse an Obsidian markdown file and extract metadata. + + Args: + root: Directory containing the file. + filename: Name of the markdown file. + vault_path: Root path of the Obsidian vault. + + Returns: + NoteData dictionary with parsed content, links, tags, and metadata. + """ + full_path = os.path.join(root, filename) + # Vault path might be relative or absolute, handle it + try: + rel_path = os.path.relpath(full_path, vault_path) + except ValueError: + rel_path = filename # Fallback if paths on different drives (Windows) + + # Robust reading with encoding fallbacks + raw_text = None + for enc in ("utf-8", "utf-8-sig", "latin-1"): + try: + with open(full_path, "r", encoding=enc, errors="strict") as f: + raw_text = f.read() + break + except UnicodeDecodeError: + continue + if raw_text is None: + with open(full_path, "r", encoding="utf-8", errors="replace") as f: + raw_text = f.read() + + fm_match = re.match(r"^---\s*\n(.*?)\n---\s*\n", raw_text, re.DOTALL) + content = raw_text[fm_match.end() :] if fm_match else raw_text + + """ + Pattern breakdown: + \[\[ matches [[ + ([^\]|]+) captures the link name (one or more chars except ] or |) + (?:\|[^\]]+)? optionally matches |display text + \]\] matches ]] + Matches: [[note]] and [[note|display text]] + """ + links = re.findall(r"\[\[([^\]|]+)(?:\|[^\]]+)?\]\]", content) + tags = re.findall(r"#([a-zA-Z0-9_\-/]+)", content) + + return { + "path": rel_path, + "name": filename.replace(".md", ""), + "folder": os.path.basename(root), + "content": content.strip(), + "wordcount": len(content.split()), + "links": links, + "tags": tags, + } + + async def chunking_and_embedding(self, note_data: NoteData) -> List[ChunkPayload]: + """Chunk note content and generate embeddings for each chunk. + + Args: + note_data: Parsed note data to process. + + Returns: + List of chunk payloads with text and embedding vectors. + """ + text_chunks = chunk_text_with_spacy( + note_data["content"], + max_tokens=self.chunk_word_limit, + ) + logger.info( + f"Processing: {note_data['path']} ({len(note_data['content'])} chars -> {len(text_chunks)} chunks)" + ) + + cleaned_chunks: List[str] = [] + original_chunks: List[str] = [] + for txt in text_chunks: + cleaned = self._clean_text(txt) + if cleaned: + cleaned_chunks.append(cleaned) + original_chunks.append(txt) + else: + logger.warning(f"Skipping empty chunk for {note_data['path']}") + + if not cleaned_chunks: + return [] + + try: + vectors = await generate_openai_embeddings( + cleaned_chunks, + api_key=self.openai_api_key, + base_url=self.openai_base_url, + model=self.embedding_model, + ) + except Exception as e: + logger.exception(f"Embedding generation failed for {note_data['path']}: {e}") + return [] + + chunk_payloads: List[ChunkPayload] = [] + for orig_text, vector in zip(original_chunks, vectors): + if vector: + chunk_payloads.append({"text": orig_text, "embedding": vector}) + else: + logger.warning(f"Embedding missing for chunk in {note_data['path']}") + + return chunk_payloads + + def ingest_note_and_chunks(self, note_data: NoteData, chunks: List[ChunkPayload]) -> None: + """Store note and chunks in Neo4j with relationships to folders, tags, and links. + + Args: + note_data: Parsed note data to store. + chunks: List of chunks with embeddings to store. + """ + with self.write_interface.session() as session: + session.run( + """ + MERGE (f:Folder {name: $folder}) + MERGE (n:Note {path: $path}) + SET n.name = $name, n.wordcount = $wordcount + MERGE (n)-[:IN_FOLDER]->(f) + """, + path=note_data["path"], + name=note_data["name"], + folder=note_data["folder"], + wordcount=note_data["wordcount"], + ) + + for i, chunk in enumerate(chunks): + chunk_id = hashlib.md5(f"{note_data['path']}_{i}".encode()).hexdigest() + session.run( + """ + MATCH (n:Note {path: $path}) + MERGE (c:Chunk {id: $chunk_id}) + SET c.text = $text, c.embedding = $embedding, c.index = $index + MERGE (n)-[:HAS_CHUNK]->(c) + """, + path=note_data["path"], + chunk_id=chunk_id, + text=chunk["text"], + embedding=chunk["embedding"], + index=i, + ) + + for tag in note_data["tags"]: + session.run( + "MATCH (n:Note {path: $path}) MERGE (t:Tag {name: $tag}) MERGE (n)-[:HAS_TAG]->(t)", + path=note_data["path"], + tag=tag, + ) + for link in note_data["links"]: + session.run( + "MATCH (source:Note {path: $path}) MERGE (target:Note {name: $link}) " + "ON CREATE SET target.path = $link + '.md' MERGE (source)-[:LINKS_TO]->(target)", + path=note_data["path"], + link=link, + ) + + async def ingest_vault(self, vault_path: str) -> dict: + """Ingest an entire Obsidian vault into Neo4j. + + Processes all markdown files in the vault, chunks them, generates embeddings, + and stores them in Neo4j with relationships. + + Args: + vault_path: Path to the Obsidian vault directory. + + Returns: + Dictionary with status, processed count, and any errors. + + Raises: + FileNotFoundError: If vault path doesn't exist. + """ + if not os.path.exists(vault_path): + raise FileNotFoundError(f"Vault path not found: {vault_path}") + + self.setup_database() + + processed = 0 + errors = [] + + for root, dirs, files in os.walk(vault_path): + dirs[:] = [d for d in dirs if not d.startswith(".")] + for file in files: + if file.endswith(".md"): + try: + note_data = self.parse_obsidian_note(root, file, vault_path) + chunk_payloads = await self.chunking_and_embedding(note_data) + + if chunk_payloads: + self.ingest_note_and_chunks(note_data, chunk_payloads) + processed += 1 + except Exception as e: + logger.exception(f"Processing {file} failed") + errors.append(f"{file}: {str(e)}") + + return {"status": "success", "processed": processed, "errors": errors} + + async def search_obsidian(self, query: str, limit: int = 5) -> ObsidianSearchResult: + """Search Obsidian vault for relevant context using vector search and graph traversal. + + Args: + query: User's search query. + limit: Maximum number of chunks to retrieve. + + Returns: + Result payload containing the formatted contexts (if any) and structured error info. + """ + try: + clean_query = self._clean_text(query) + vectors = await generate_openai_embeddings( + [clean_query], + api_key=self.openai_api_key, + base_url=self.openai_base_url, + model=self.embedding_model, + ) + query_vector = vectors[0] if vectors else None + except Exception as exc: + logger.error("Obsidian search embedding failed: %s", exc) + raise ObsidianSearchError("embedding", str(exc)) from exc + + if not query_vector: + return {"results": []} + + cypher_query = """ + CALL db.index.vector.queryNodes('chunk_embeddings', $limit, $vector) + YIELD node AS chunk, score + + // Find the parent Note + MATCH (note:Note)-[:HAS_CHUNK]->(chunk) + + // Get graph context: What tags and linked files are around this note? + OPTIONAL MATCH (note)-[:HAS_TAG]->(t:Tag) + OPTIONAL MATCH (note)-[:LINKS_TO]->(linked:Note) + + RETURN + note.name AS source, + chunk.text AS content, + collect(DISTINCT t.name) AS tags, + collect(DISTINCT linked.name) AS outgoing_links, + score + ORDER BY score DESC + """ + + context_entries = [] + try: + with self.read_interface.session() as session: + results = session.run(cypher_query, vector=query_vector, limit=limit) + + for record in results: + entry = f"SOURCE: {record['source']}\n" + tags = record["tags"] + if tags: + entry += f"TAGS: {', '.join(tags)}\n" + links = record["outgoing_links"] + if links: + entry += f"RELATED NOTES: {', '.join(links)}\n" + entry += f"CONTENT: {record['content']}\n" + entry += "---" + context_entries.append(entry) + except Exception as e: + logger.error(f"Obsidian search failed: {e}") + raise ObsidianSearchError("database", str(e)) from e + + return {"results": context_entries} + + +# Lazy initialization to avoid startup failures +_obsidian_service: Optional[ObsidianService] = None + + +def get_obsidian_service() -> ObsidianService: + """Get or create the Obsidian service singleton. + + Returns: + ObsidianService instance, creating it on first access. + """ + global _obsidian_service + if _obsidian_service is None: + _obsidian_service = ObsidianService() + return _obsidian_service + + +# Backward compatibility: module-level access uses lazy initialization +# This property-like access ensures the service is only created when first used +class _ObsidianServiceProxy: + """Proxy for lazy access to obsidian_service.""" + + def __getattr__(self, name): + return getattr(get_obsidian_service(), name) + + +obsidian_service = _ObsidianServiceProxy() diff --git a/backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py b/backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py index 1c4a3b59..2e20171b 100644 --- a/backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py +++ b/backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py @@ -1,115 +1,290 @@ """ -Transcription provider implementations and factory. +Transcription providers and registry-driven factory. -This module contains concrete implementations of transcription providers -for different ASR services (Deepgram, Parakeet, etc.) and a factory function -to instantiate the appropriate provider based on configuration. +This module exposes a provider that reads its configuration from the +central model registry (config.yml). No environment-based selection +or provider-specific branching is used for batch transcription. """ +import asyncio +import json import logging -import os from typing import Optional -from .base import BaseTranscriptionProvider -from advanced_omi_backend.services.transcription.deepgram import ( - DeepgramProvider, - DeepgramStreamingProvider, - DeepgramStreamConsumer, -) -from advanced_omi_backend.services.transcription.parakeet import ( - ParakeetProvider, - ParakeetStreamingProvider, -) +import httpx +import websockets + +from advanced_omi_backend.model_registry import get_models_registry +from .base import BaseTranscriptionProvider, BatchTranscriptionProvider, StreamingTranscriptionProvider logger = logging.getLogger(__name__) -def get_transcription_provider( - provider_name: Optional[str] = None, - mode: Optional[str] = None, -) -> Optional[BaseTranscriptionProvider]: +def _dotted_get(d: dict | list | None, dotted: Optional[str]): + """Safely extract a value from nested dict/list using dotted paths. + + Supports simple dot separators and list indexes like "results[0].alternatives[0].transcript". + Returns None when the path can't be fully resolved. """ - Factory function to get the appropriate transcription provider. + if d is None or not dotted: + return None + cur = d + for part in dotted.split('.'): + if not part: + continue + if '[' in part and part.endswith(']'): + name, idx_str = part[:-1].split('[', 1) + if name: + cur = cur.get(name, {}) if isinstance(cur, dict) else {} + try: + idx = int(idx_str) + except Exception: + return None + if isinstance(cur, list) and 0 <= idx < len(cur): + cur = cur[idx] + else: + return None + else: + cur = cur.get(part, None) if isinstance(cur, dict) else None + if cur is None: + return None + return cur - Args: - provider_name: Name of the provider ('deepgram', 'parakeet'). - If None, will auto-select based on available configuration. - mode: Processing mode ('streaming', 'batch'). If None, defaults to 'batch'. - Returns: - An instance of BaseTranscriptionProvider, or None if no provider is configured. +class RegistryBatchTranscriptionProvider(BatchTranscriptionProvider): + """Batch transcription provider driven by config.yml.""" - Raises: - RuntimeError: If a specific provider is requested but not properly configured. - """ - deepgram_key = os.getenv("DEEPGRAM_API_KEY") - parakeet_url = os.getenv("PARAKEET_ASR_URL") - - if provider_name: - provider_name = provider_name.lower() - - if mode is None: - mode = "batch" - mode = mode.lower() - - # Handle specific provider requests - if provider_name == "deepgram": - if not deepgram_key: - raise RuntimeError( - "Deepgram transcription provider requested but DEEPGRAM_API_KEY not configured" - ) - logger.info(f"Using Deepgram transcription provider in {mode} mode") - if mode == "streaming": - return DeepgramStreamingProvider(deepgram_key) - else: - return DeepgramProvider(deepgram_key) - - elif provider_name == "parakeet": - if not parakeet_url: - raise RuntimeError( - "Parakeet ASR provider requested but PARAKEET_ASR_URL not configured" - ) - logger.info(f"Using Parakeet transcription provider in {mode} mode") - if mode == "streaming": - return ParakeetStreamingProvider(parakeet_url) + def __init__(self): + registry = get_models_registry() + if not registry: + raise RuntimeError("config.yml not found; cannot configure STT provider") + model = registry.get_default("stt") + if not model: + raise RuntimeError("No default STT model defined in config.yml") + self.model = model + self._name = model.model_provider or model.name + + @property + def name(self) -> str: + return self._name + + async def transcribe(self, audio_data: bytes, sample_rate: int, diarize: bool = False) -> dict: + op = (self.model.operations or {}).get("stt_transcribe") or {} + method = (op.get("method") or "POST").upper() + path = (op.get("path") or "/listen") + # Build URL + base = self.model.model_url.rstrip("/") + url = base + ("/" + path.lstrip("/")) + + # Check if we should use multipart file upload (for Parakeet) + content_type = op.get("content_type", "audio/raw") + use_multipart = content_type == "multipart/form-data" + + # Build headers (skip Content-Type for multipart as httpx will set it) + headers = {} + if not use_multipart: + headers["Content-Type"] = "audio/raw" + + if self.model.api_key: + # Allow templated header, otherwise fallback to Bearer/Token conventions by config + hdrs = op.get("headers") or {} + # Resolve simple ${VAR} placeholders in op headers using env (optional) + for k, v in hdrs.items(): + if isinstance(v, str): + headers[k] = v.replace("${DEEPGRAM_API_KEY:-}", self.model.api_key) + else: + headers[k] = v else: - return ParakeetProvider(parakeet_url) - - # Auto-select provider based on available configuration (when provider_name is None) - if provider_name is None: - # Check TRANSCRIPTION_PROVIDER environment variable first - env_provider = os.getenv("TRANSCRIPTION_PROVIDER") - if env_provider: - # Recursively call with the specified provider - return get_transcription_provider(env_provider, mode) - - # Auto-select: prefer Deepgram if available, fallback to Parakeet - if deepgram_key: - logger.info(f"Auto-selected Deepgram transcription provider in {mode} mode") - if mode == "streaming": - return DeepgramStreamingProvider(deepgram_key) - else: - return DeepgramProvider(deepgram_key) - elif parakeet_url: - logger.info(f"Auto-selected Parakeet transcription provider in {mode} mode") - if mode == "streaming": - return ParakeetStreamingProvider(parakeet_url) + # When no API key, only add headers that don't require authentication + hdrs = op.get("headers") or {} + for k, v in hdrs.items(): + # Skip Authorization headers with empty/invalid values + if k.lower() == "authorization" and (not v or v.strip().lower() in ["token", "token ", "bearer", "bearer "]): + continue + headers[k] = v + + # Query params + query = op.get("query") or {} + # Inject common params if placeholders used + if "sample_rate" in query: + query["sample_rate"] = str(sample_rate) + if "diarize" in query: + query["diarize"] = "true" if diarize else "false" + + timeout = op.get("timeout", 120) + async with httpx.AsyncClient(timeout=timeout) as client: + if method == "POST": + if use_multipart: + # Send as multipart file upload (for Parakeet) + files = {"file": ("audio.wav", audio_data, "audio/wav")} + resp = await client.post(url, headers=headers, params=query, files=files) + else: + # Send as raw audio data (for Deepgram) + resp = await client.post(url, headers=headers, params=query, content=audio_data) else: - return ParakeetProvider(parakeet_url) - else: - logger.warning( - "No transcription provider configured (DEEPGRAM_API_KEY or PARAKEET_ASR_URL required)" - ) + resp = await client.get(url, headers=headers, params=query) + resp.raise_for_status() + data = resp.json() + + # DEBUG: Log Deepgram response structure + if "results" in data and "channels" in data.get("results", {}): + channels = data["results"]["channels"] + if channels and "alternatives" in channels[0]: + alt = channels[0]["alternatives"][0] + logger.info(f"DEBUG Registry: Deepgram alternative keys: {list(alt.keys())}") + + # Extract normalized shape + text, words, segments = "", [], [] + extract = (op.get("response", {}) or {}).get("extract") or {} + if extract: + text = _dotted_get(data, extract.get("text")) or "" + words = _dotted_get(data, extract.get("words")) or [] + segments = _dotted_get(data, extract.get("segments")) or [] + + # DEBUG: Log what we extracted + logger.info(f"DEBUG Registry: Extracted {len(segments)} segments from response") + if segments and len(segments) > 0: + logger.info(f"DEBUG Registry: First segment keys: {list(segments[0].keys()) if isinstance(segments[0], dict) else 'not a dict'}") + logger.info(f"DEBUG Registry: First segment: {segments[0]}") + + return {"text": text, "words": words, "segments": segments} + +class RegistryStreamingTranscriptionProvider(StreamingTranscriptionProvider): + """Streaming transcription provider using a config-driven WebSocket template.""" + + def __init__(self): + registry = get_models_registry() + if not registry: + raise RuntimeError("config.yml not found; cannot configure streaming STT provider") + model = registry.get_default("stt_stream") + if not model: + raise RuntimeError("No default stt_stream model defined in config.yml") + self.model = model + self._name = model.model_provider or model.name + self._streams: dict[str, dict] = {} + + @property + def name(self) -> str: + return self._name + + async def start_stream(self, client_id: str, sample_rate: int = 16000, diarize: bool = False): + url = self.model.model_url + ops = self.model.operations or {} + start_msg = (ops.get("start", {}) or {}).get("message", {}) + # Inject session_id if placeholder present + start_msg = json.loads(json.dumps(start_msg)) # deep copy + start_msg.setdefault("session_id", client_id) + # Apply sample rate and diarization if present + if "config" in start_msg and isinstance(start_msg["config"], dict): + start_msg["config"].setdefault("sample_rate", sample_rate) + if diarize: + start_msg["config"]["diarize"] = True + + ws = await websockets.connect(url, open_timeout=10) + await ws.send(json.dumps(start_msg)) + # Wait for confirmation; non-fatal if not provided + try: + await asyncio.wait_for(ws.recv(), timeout=2.0) + except Exception: + pass + self._streams[client_id] = {"ws": ws, "sample_rate": sample_rate, "final": None, "interim": []} + + async def process_audio_chunk(self, client_id: str, audio_chunk: bytes) -> dict | None: + if client_id not in self._streams: + return None + ws = self._streams[client_id]["ws"] + ops = self.model.operations or {} + chunk_hdr = (ops.get("chunk_header", {}) or {}).get("message", {}) + hdr = json.loads(json.dumps(chunk_hdr)) + hdr.setdefault("type", "audio_chunk") + hdr.setdefault("session_id", client_id) + hdr.setdefault("rate", self._streams[client_id]["sample_rate"]) + await ws.send(json.dumps(hdr)) + await ws.send(audio_chunk) + + # Non-blocking read for interim results + expect = (ops.get("expect", {}) or {}) + interim_type = expect.get("interim_type") + try: + while True: + msg = await asyncio.wait_for(ws.recv(), timeout=0.01) + data = json.loads(msg) + if interim_type and data.get("type") == interim_type: + self._streams[client_id]["interim"].append(data) + except asyncio.TimeoutError: + pass + return None + + async def end_stream(self, client_id: str) -> dict: + if client_id not in self._streams: + return {"text": "", "words": [], "segments": []} + ws = self._streams[client_id]["ws"] + ops = self.model.operations or {} + end_msg = (ops.get("end", {}) or {}).get("message", {"type": "stop"}) + await ws.send(json.dumps(end_msg)) + + expect = (ops.get("expect", {}) or {}) + final_type = expect.get("final_type") + extract = expect.get("extract", {}) + + final = None + try: + # Drain until final or close + for _ in range(500): # hard cap + msg = await asyncio.wait_for(ws.recv(), timeout=1.5) + data = json.loads(msg) + if not final_type or data.get("type") == final_type: + final = data + break + except Exception: + pass + try: + await ws.close() + except Exception: + pass + + self._streams.pop(client_id, None) + + if not isinstance(final, dict): + return {"text": "", "words": [], "segments": []} + return { + "text": _dotted_get(final, extract.get("text")) if extract else final.get("text", ""), + "words": _dotted_get(final, extract.get("words")) if extract else final.get("words", []), + "segments": _dotted_get(final, extract.get("segments")) if extract else final.get("segments", []), + } + + +def get_transcription_provider(provider_name: Optional[str] = None, mode: Optional[str] = None) -> Optional[BaseTranscriptionProvider]: + """Return a registry-driven transcription provider. + + - mode="batch": HTTP-based STT (default) + - mode="streaming": WebSocket-based STT + + Note: The models registry returns None when config.yml is missing or invalid. + We avoid broad exception handling here and simply return None when the + required defaults are not configured. + """ + registry = get_models_registry() + if not registry: + return None + + selected_mode = (mode or "batch").lower() + if selected_mode == "streaming": + if not registry.get_default("stt_stream"): return None - else: + return RegistryStreamingTranscriptionProvider() + + # batch mode + if not registry.get_default("stt"): return None + return RegistryBatchTranscriptionProvider() __all__ = [ "get_transcription_provider", - "DeepgramProvider", - "DeepgramStreamingProvider", - "DeepgramStreamConsumer", - "ParakeetProvider", - "ParakeetStreamingProvider", + "RegistryBatchTranscriptionProvider", + "RegistryStreamingTranscriptionProvider", + "BaseTranscriptionProvider", + "BatchTranscriptionProvider", + "StreamingTranscriptionProvider", ] diff --git a/backends/advanced/src/advanced_omi_backend/services/transcription/deepgram.py b/backends/advanced/src/advanced_omi_backend/services/transcription/deepgram.py index ee7e23fa..ef54a3d9 100644 --- a/backends/advanced/src/advanced_omi_backend/services/transcription/deepgram.py +++ b/backends/advanced/src/advanced_omi_backend/services/transcription/deepgram.py @@ -1,408 +1,16 @@ """ -Deepgram transcription provider implementations. +Deepgram transcription consumer for Redis Streams architecture. -Provides both batch and streaming transcription using Deepgram's Nova-3 model. +Uses the registry-driven transcription provider for Deepgram batch transcription. """ -import asyncio -import json import logging -import uuid -from typing import Dict, Optional -import httpx -import websockets - -from .base import ( - BatchTranscriptionProvider, - StreamingTranscriptionProvider, -) +from advanced_omi_backend.services.audio_stream.consumer import BaseAudioStreamConsumer +from advanced_omi_backend.services.transcription import get_transcription_provider logger = logging.getLogger(__name__) -class DeepgramProvider(BatchTranscriptionProvider): - """Deepgram batch transcription provider using Nova-3 model.""" - - def __init__(self, api_key: str): - self.api_key = api_key - self.url = "https://api.deepgram.com/v1/listen" - - @property - def name(self) -> str: - return "deepgram" - - async def transcribe(self, audio_data: bytes, sample_rate: int, diarize: bool = False) -> dict: - """Transcribe audio using Deepgram's REST API. - - Args: - audio_data: Raw audio bytes - sample_rate: Audio sample rate - diarize: Whether to enable speaker diarization - """ - try: - params = { - "model": "nova-3", - "language": "multi", - "smart_format": "true", - "punctuate": "true", - "diarize": "true" if diarize else "false", - "encoding": "linear16", - "sample_rate": str(sample_rate), - "channels": "1", - } - - headers = {"Authorization": f"Token {self.api_key}", "Content-Type": "audio/raw"} - - logger.debug(f"Sending {len(audio_data)} bytes to Deepgram API") - - # Calculate dynamic timeout based on audio file size - estimated_duration = len(audio_data) / (sample_rate * 2 * 1) # 16-bit mono - processing_timeout = max( - 120, int(estimated_duration * 3) - ) # Min 2 minutes, 3x audio duration - - timeout_config = httpx.Timeout( - connect=30.0, - read=processing_timeout, - write=max( - 180.0, int(len(audio_data) / (sample_rate * 2)) - ), # bytes per second for 16-bit PCM - pool=10.0, - ) - - logger.info( - f"Estimated audio duration: {estimated_duration:.1f}s, timeout: {processing_timeout}s" - ) - - async with httpx.AsyncClient(timeout=timeout_config) as client: - response = await client.post( - self.url, params=params, headers=headers, content=audio_data - ) - - if response.status_code == 200: - result = response.json() - logger.debug(f"Deepgram response: {result}") - - # Extract transcript from response - if result.get("results", {}).get("channels", []) and result["results"][ - "channels" - ][0].get("alternatives", []): - - alternative = result["results"]["channels"][0]["alternatives"][0] - - # Extract segments from diarized utterances if available - segments = [] - if "paragraphs" in alternative and alternative["paragraphs"].get("paragraphs"): - transcript = alternative["paragraphs"]["transcript"].strip() - logger.info( - f"Deepgram diarized transcription successful: {len(transcript)} characters" - ) - - # Extract speaker segments, grouping consecutive sentences from same speaker - current_speaker = None - current_segment = None - - for paragraph in alternative["paragraphs"]["paragraphs"]: - speaker = f"Speaker {paragraph.get('speaker', 'unknown')}" - - for sentence in paragraph.get("sentences", []): - if speaker == current_speaker and current_segment: - # Extend current segment with same speaker - current_segment["text"] += " " + sentence.get("text", "").strip() - current_segment["end"] = sentence.get("end", 0) - else: - # Save previous segment and start new one - if current_segment: - segments.append(current_segment) - current_segment = { - "text": sentence.get("text", "").strip(), - "speaker": speaker, - "start": sentence.get("start", 0), - "end": sentence.get("end", 0), - "confidence": None # Deepgram doesn't provide segment-level confidence - } - current_speaker = speaker - - # Don't forget the last segment - if current_segment: - segments.append(current_segment) - else: - transcript = alternative.get("transcript", "").strip() - logger.debug( - f"Deepgram basic transcription successful: {len(transcript)} characters" - ) - - if transcript: - # Extract speech timing information for logging - words = alternative.get("words", []) - if words: - first_word_start = words[0].get("start", 0) - last_word_end = words[-1].get("end", 0) - speech_duration = last_word_end - first_word_start - - # Calculate audio duration from data size - audio_duration = len(audio_data) / ( - sample_rate * 2 * 1 - ) # 16-bit mono - speech_percentage = ( - (speech_duration / audio_duration) * 100 - if audio_duration > 0 - else 0 - ) - - logger.info( - f"Deepgram speech analysis: {speech_duration:.1f}s speech detected in {audio_duration:.1f}s audio ({speech_percentage:.1f}%)" - ) - - # Check confidence levels - confidences = [ - w.get("confidence", 0) for w in words if "confidence" in w - ] - if confidences: - avg_confidence = sum(confidences) / len(confidences) - low_confidence_count = sum(1 for c in confidences if c < 0.5) - logger.info( - f"Deepgram confidence: avg={avg_confidence:.2f}, {low_confidence_count}/{len(words)} words <0.5 confidence" - ) - - # Keep raw transcript and word data without formatting - logger.info( - f"Keeping raw transcript with word-level data: {len(transcript)} characters, {len(segments)} segments" - ) - return { - "text": transcript, - "words": words, - "segments": segments, - } - else: - # No word-level data, return basic transcript - logger.info( - "No word-level data available, returning basic transcript" - ) - return {"text": transcript, "words": [], "segments": []} - else: - logger.warning("Deepgram returned empty transcript") - return {"text": "", "words": [], "segments": []} - else: - error_msg = "Deepgram response missing expected transcript structure" - logger.error(error_msg) - raise RuntimeError(error_msg) - else: - error_msg = f"Deepgram API error: {response.status_code} - {response.text}" - logger.error(error_msg) - raise RuntimeError(error_msg) - - except httpx.TimeoutException as e: - timeout_type = "unknown" - if "connect" in str(e).lower(): - timeout_type = "connection" - elif "read" in str(e).lower(): - timeout_type = "read" - elif "write" in str(e).lower(): - timeout_type = "write (upload)" - elif "pool" in str(e).lower(): - timeout_type = "connection pool" - error_msg = f"HTTP {timeout_type} timeout during Deepgram API call for {len(audio_data)} bytes: {e}" - logger.error(error_msg) - raise RuntimeError(error_msg) from e - except RuntimeError: - # Re-raise RuntimeError from above (API errors, timeouts) - raise - except Exception as e: - error_msg = f"Unexpected error calling Deepgram API: {e}" - logger.error(error_msg) - raise RuntimeError(error_msg) from e - - -class DeepgramStreamingProvider(StreamingTranscriptionProvider): - """Deepgram streaming transcription provider using WebSocket connection.""" - - def __init__(self, api_key: str): - self.api_key = api_key - self.ws_url = "wss://api.deepgram.com/v1/listen" - self._streams: Dict[str, Dict] = {} # client_id -> stream data - - @property - def name(self) -> str: - return "deepgram" - - async def start_stream(self, client_id: str, sample_rate: int = 16000, diarize: bool = False): - """Start a WebSocket connection for streaming transcription. - - Args: - client_id: Unique client identifier - sample_rate: Audio sample rate - diarize: Whether to enable speaker diarization - """ - try: - logger.info(f"Starting Deepgram streaming for client {client_id} (diarize={diarize})") - - # WebSocket connection parameters - params = { - "model": "nova-3", - "language": "multi", - "smart_format": "true", - "punctuate": "true", - "diarize": "true" if diarize else "false", - "encoding": "linear16", - "sample_rate": str(sample_rate), - "channels": "1", - "interim_results": "true", - "endpointing": "300", # 300ms silence for endpoint detection - } - - # Build WebSocket URL with parameters - query_string = "&".join([f"{k}={v}" for k, v in params.items()]) - ws_url = f"{self.ws_url}?{query_string}" - - # Connect to WebSocket - websocket = await websockets.connect( - ws_url, - extra_headers={"Authorization": f"Token {self.api_key}"} - ) - - # Store stream data - self._streams[client_id] = { - "websocket": websocket, - "final_transcript": "", - "words": [], - "stream_id": str(uuid.uuid4()) - } - - logger.debug(f"Deepgram WebSocket connected for client {client_id}") - - except Exception as e: - logger.error(f"Failed to start Deepgram streaming for {client_id}: {e}") - raise - - async def process_audio_chunk(self, client_id: str, audio_chunk: bytes) -> Optional[dict]: - """Send audio chunk to WebSocket and process responses.""" - if client_id not in self._streams: - logger.error(f"No active stream for client {client_id}") - return None - - try: - stream_data = self._streams[client_id] - websocket = stream_data["websocket"] - - # Send audio chunk - await websocket.send(audio_chunk) - - # Check for responses (non-blocking) - try: - while True: - response = await asyncio.wait_for(websocket.recv(), timeout=0.01) - result = json.loads(response) - - if result.get("type") == "Results": - channel = result.get("channel", {}) - alternatives = channel.get("alternatives", []) - - if alternatives: - alt = alternatives[0] - is_final = channel.get("is_final", False) - - if is_final: - # Accumulate final transcript and words - transcript = alt.get("transcript", "") - words = alt.get("words", []) - - if transcript.strip(): - stream_data["final_transcript"] += transcript + " " - stream_data["words"].extend(words) - - logger.debug(f"Final transcript chunk: {transcript}") - - except asyncio.TimeoutError: - # No response available, continue - pass - - return None # Streaming, no final result yet - - except Exception as e: - logger.error(f"Error processing audio chunk for {client_id}: {e}") - return None - - async def end_stream(self, client_id: str) -> dict: - """Close WebSocket connection and return final transcription.""" - if client_id not in self._streams: - logger.error(f"No active stream for client {client_id}") - return {"text": "", "words": [], "segments": []} - - try: - stream_data = self._streams[client_id] - websocket = stream_data["websocket"] - - # Send close message - close_msg = json.dumps({"type": "CloseStream"}) - await websocket.send(close_msg) - - # Wait a bit for final responses - try: - end_time = asyncio.get_event_loop().time() + 2.0 # 2 second timeout - while asyncio.get_event_loop().time() < end_time: - response = await asyncio.wait_for(websocket.recv(), timeout=0.5) - result = json.loads(response) - - if result.get("type") == "Results": - channel = result.get("channel", {}) - alternatives = channel.get("alternatives", []) - - if alternatives and channel.get("is_final", False): - alt = alternatives[0] - transcript = alt.get("transcript", "") - words = alt.get("words", []) - - if transcript.strip(): - stream_data["final_transcript"] += transcript - stream_data["words"].extend(words) - - except asyncio.TimeoutError: - pass - - # Close WebSocket - await websocket.close() - - # Prepare final result - final_transcript = stream_data["final_transcript"].strip() - final_words = stream_data["words"] - - logger.info(f"Deepgram streaming completed for {client_id}: {len(final_transcript)} chars, {len(final_words)} words") - - # Clean up - del self._streams[client_id] - - return { - "text": final_transcript, - "words": final_words, - "segments": [] - } - - except Exception as e: - logger.error(f"Error ending stream for {client_id}: {e}") - # Clean up on error - if client_id in self._streams: - del self._streams[client_id] - return {"text": "", "words": [], "segments": []} - - async def transcribe(self, audio_data: bytes, sample_rate: int, **kwargs) -> dict: - """For streaming provider, this method is not typically used.""" - logger.warning("transcribe() called on streaming provider - use streaming methods instead") - return {"text": "", "words": [], "segments": []} - - async def disconnect(self): - """Close all active WebSocket connections.""" - for client_id in list(self._streams.keys()): - try: - websocket = self._streams[client_id]["websocket"] - await websocket.close() - except Exception as e: - logger.error(f"Error closing WebSocket for {client_id}: {e}") - finally: - del self._streams[client_id] - - logger.info("All Deepgram streaming connections closed") - class DeepgramStreamConsumer: """ @@ -411,40 +19,40 @@ class DeepgramStreamConsumer: Reads from: specified stream (client-specific or provider-specific) Writes to: transcription:results:{session_id} - This inherits from BaseAudioStreamConsumer and implements transcribe_audio(). + Uses RegistryBatchTranscriptionProvider configured via config.yml for + Deepgram transcription. This ensures consistent behavior with batch + transcription jobs. """ - def __init__(self, redis_client, api_key: str = None, buffer_chunks: int = 30): + def __init__(self, redis_client, buffer_chunks: int = 30): """ Initialize Deepgram consumer. Dynamically discovers all audio:stream:* streams and claims them using Redis locks. + Uses config.yml stt-deepgram configuration for transcription. Args: redis_client: Connected Redis client - api_key: Deepgram API key (defaults to DEEPGRAM_API_KEY env var) buffer_chunks: Number of chunks to buffer before transcribing (default: 30 = ~7.5s) """ - import os - from advanced_omi_backend.services.audio_stream.consumer import BaseAudioStreamConsumer - - self.api_key = api_key or os.getenv("DEEPGRAM_API_KEY") - if not self.api_key: - raise ValueError("DEEPGRAM_API_KEY is required") - # Initialize Deepgram provider - self.provider = DeepgramProvider(api_key=self.api_key) + # Get registry-driven transcription provider + self.provider = get_transcription_provider(mode="batch") + if not self.provider: + raise RuntimeError( + "Failed to load transcription provider. Ensure config.yml has a default 'stt' model configured." + ) # Create a concrete subclass that implements transcribe_audio class _ConcreteConsumer(BaseAudioStreamConsumer): def __init__(inner_self, provider_name: str, redis_client, buffer_chunks: int): super().__init__(provider_name, redis_client, buffer_chunks) - inner_self._deepgram_provider = self.provider + inner_self._transcription_provider = self.provider async def transcribe_audio(inner_self, audio_data: bytes, sample_rate: int) -> dict: - """Transcribe using DeepgramProvider.""" + """Transcribe using registry-driven transcription provider.""" try: - result = await inner_self._deepgram_provider.transcribe( + result = await inner_self._transcription_provider.transcribe( audio_data=audio_data, sample_rate=sample_rate, diarize=True @@ -482,5 +90,3 @@ async def start_consuming(self): async def stop(self): """Delegate to base consumer.""" return await self._consumer.stop() - - diff --git a/backends/advanced/src/advanced_omi_backend/services/transcription/parakeet.py b/backends/advanced/src/advanced_omi_backend/services/transcription/parakeet.py deleted file mode 100644 index 97b5b751..00000000 --- a/backends/advanced/src/advanced_omi_backend/services/transcription/parakeet.py +++ /dev/null @@ -1,303 +0,0 @@ -""" -Parakeet (NeMo) transcription provider implementations. - -Provides both batch and streaming transcription using NeMo's Parakeet ASR models. -""" - -import asyncio -import json -import logging -import os -import tempfile -from typing import Dict, Optional - -import httpx -import numpy as np -import websockets -from easy_audio_interfaces.audio_interfaces import AudioChunk -from easy_audio_interfaces.filesystem import LocalFileSink - -from .base import ( - BatchTranscriptionProvider, - StreamingTranscriptionProvider, -) - -logger = logging.getLogger(__name__) - -class ParakeetProvider(BatchTranscriptionProvider): - """Parakeet HTTP batch transcription provider.""" - - def __init__(self, service_url: str): - self.service_url = service_url.rstrip('/') - self.transcribe_url = f"{self.service_url}/transcribe" - - @property - def name(self) -> str: - return "parakeet" - - async def transcribe(self, audio_data: bytes, sample_rate: int, **kwargs) -> dict: - """Transcribe audio using Parakeet HTTP service.""" - try: - - logger.info(f"Sending {len(audio_data)} bytes to Parakeet service at {self.transcribe_url}") - - # Convert PCM bytes to audio file for upload - if sample_rate != 16000: - logger.warning(f"Sample rate {sample_rate} != 16000, audio may not be optimal") - - # Assume 16-bit PCM - audio_array = np.frombuffer(audio_data, dtype=np.int16).astype(np.float32) - audio_array = audio_array / np.iinfo(np.int16).max # Normalize to [-1, 1] - - # Create temporary WAV file - with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_file: - # sf.write(tmp_file.name, audio_array, 16000) # Force 16kHz - async with LocalFileSink(tmp_file.name, sample_rate, 1) as sink: - await sink.write(AudioChunk( - rate=sample_rate, - width=2, - channels=1, - audio=audio_data, - )) - - tmp_filename = tmp_file.name - - try: - # Upload file to Parakeet service - async with httpx.AsyncClient(timeout=180.0) as client: - with open(tmp_filename, "rb") as f: - files = {"file": ("audio.wav", f, "audio/wav")} - response = await client.post(self.transcribe_url, files=files) - - if response.status_code == 200: - result = response.json() - logger.info(f"Parakeet transcription successful: {len(result.get('text', ''))} chars, {len(result.get('words', []))} words") - return result - else: - error_msg = f"Parakeet service error: {response.status_code} - {response.text}" - logger.error(error_msg) - - # For 5xx errors, raise exception to trigger retry/failure handling - if response.status_code >= 500: - raise RuntimeError(f"Parakeet service unavailable: HTTP {response.status_code}") - - # For 4xx errors, return empty result (client error, won't retry) - return {"text": "", "words": [], "segments": []} - - finally: - # Clean up temporary file - if os.path.exists(tmp_filename): - os.unlink(tmp_filename) - - except Exception as e: - logger.error(f"Error calling Parakeet service: {e}") - raise e - - -class ParakeetStreamingProvider(StreamingTranscriptionProvider): - """Parakeet WebSocket streaming transcription provider.""" - - def __init__(self, service_url: str): - self.service_url = service_url.rstrip('/') - self.ws_url = service_url.replace("http://", "ws://").replace("https://", "wss://") + "/stream" - self._streams: Dict[str, Dict] = {} # client_id -> stream data - - @property - def name(self) -> str: - return "parakeet" - - async def start_stream(self, client_id: str, sample_rate: int = 16000, diarize: bool = False): - """Start a WebSocket connection for streaming transcription. - - Args: - client_id: Unique client identifier - sample_rate: Audio sample rate - diarize: Whether to enable speaker diarization (ignored - Parakeet doesn't support diarization) - """ - if diarize: - logger.warning(f"Parakeet streaming provider does not support diarization, ignoring diarize=True for client {client_id}") - try: - logger.info(f"Starting Parakeet streaming for client {client_id}") - - # Connect to WebSocket - websocket = await websockets.connect(self.ws_url) - - # Send transcribe event to start session - session_config = { - "vad_enabled": True, - "vad_silence_ms": 1000, - "time_interval_seconds": 30, - "return_interim_results": True, - "min_audio_seconds": 0.5 - } - - start_message = { - "type": "transcribe", - "session_id": client_id, - "config": session_config - } - - await websocket.send(json.dumps(start_message)) - - # Wait for session_started confirmation - response = await websocket.recv() - response_data = json.loads(response) - - if response_data.get("type") != "session_started": - raise RuntimeError(f"Failed to start session: {response_data}") - - # Store stream data - self._streams[client_id] = { - "websocket": websocket, - "sample_rate": sample_rate, - "session_id": client_id, - "interim_results": [], - "final_result": None - } - - logger.info(f"Parakeet WebSocket connected for client {client_id}") - - except Exception as e: - logger.error(f"Failed to start Parakeet streaming for {client_id}: {e}") - raise - - async def process_audio_chunk(self, client_id: str, audio_chunk: bytes) -> Optional[dict]: - """Send audio chunk to WebSocket and process responses.""" - if client_id not in self._streams: - logger.error(f"No active stream for client {client_id}") - return None - - try: - stream_data = self._streams[client_id] - websocket = stream_data["websocket"] - sample_rate = stream_data["sample_rate"] - - # Send audio_chunk event - chunk_message = { - "type": "audio_chunk", - "session_id": client_id, - "rate": sample_rate, - "width": 2, # 16-bit - "channels": 1 - } - - await websocket.send(json.dumps(chunk_message)) - await websocket.send(audio_chunk) - - # Check for responses (non-blocking) - try: - while True: - response = await asyncio.wait_for(websocket.recv(), timeout=0.01) - result = json.loads(response) - - if result.get("type") == "interim_result": - # Store interim result but don't return it (handled by backend differently) - stream_data["interim_results"].append(result) - logger.debug(f"Received interim result: {result.get('text', '')[:50]}...") - elif result.get("type") == "final_result": - # This shouldn't happen during chunk processing, but store it - stream_data["final_result"] = result - logger.debug(f"Received final result during chunk processing: {result.get('text', '')[:50]}...") - - except asyncio.TimeoutError: - # No response available, continue - pass - - return None # Streaming, no final result yet - - except Exception as e: - logger.error(f"Error processing audio chunk for {client_id}: {e}") - return None - - async def end_stream(self, client_id: str) -> dict: - """Close WebSocket connection and return final transcription.""" - if client_id not in self._streams: - logger.error(f"No active stream for client {client_id}") - return {"text": "", "words": [], "segments": []} - - try: - stream_data = self._streams[client_id] - websocket = stream_data["websocket"] - - # Send finalize event - finalize_message = { - "type": "finalize", - "session_id": client_id - } - await websocket.send(json.dumps(finalize_message)) - - # Wait for final result - try: - end_time = asyncio.get_event_loop().time() + 5.0 # 5 second timeout - while asyncio.get_event_loop().time() < end_time: - response = await asyncio.wait_for(websocket.recv(), timeout=1.0) - result = json.loads(response) - - if result.get("type") == "final_result": - stream_data["final_result"] = result - break - - except asyncio.TimeoutError: - logger.warning(f"Timeout waiting for final result from {client_id}") - - # Close WebSocket - await websocket.close() - - # Prepare final result - final_result = stream_data.get("final_result") - if final_result: - result_data = { - "text": final_result.get("text", ""), - "words": final_result.get("words", []), - "segments": final_result.get("segments", []) - } - else: - # Fallback: aggregate interim results if no final result received - interim_texts = [r.get("text", "") for r in stream_data["interim_results"]] - all_words = [] - for r in stream_data["interim_results"]: - all_words.extend(r.get("words", [])) - - result_data = { - "text": " ".join(interim_texts), - "words": all_words, - "segments": [] - } - - logger.info(f"Parakeet streaming completed for {client_id}: {len(result_data.get('text', ''))} chars") - - # Clean up - del self._streams[client_id] - - return result_data - - except Exception as e: - logger.error(f"Error ending stream for {client_id}: {e}") - # Clean up on error - if client_id in self._streams: - try: - await self._streams[client_id]["websocket"].close() - except: - pass - del self._streams[client_id] - return {"text": "", "words": [], "segments": []} - - async def transcribe(self, audio_data: bytes, sample_rate: int, **kwargs) -> dict: - """For streaming provider, this method is not typically used.""" - logger.warning("transcribe() called on streaming provider - use streaming methods instead") - return {"text": "", "words": [], "segments": []} - - async def disconnect(self): - """Close all active WebSocket connections.""" - for client_id in list(self._streams.keys()): - try: - websocket = self._streams[client_id]["websocket"] - await websocket.close() - except Exception as e: - logger.error(f"Error closing WebSocket for {client_id}: {e}") - finally: - del self._streams[client_id] - - logger.info("All Parakeet streaming connections closed") - - diff --git a/backends/advanced/src/advanced_omi_backend/services/transcription/parakeet_stream_consumer.py b/backends/advanced/src/advanced_omi_backend/services/transcription/parakeet_stream_consumer.py index 740a5f84..f629cefd 100644 --- a/backends/advanced/src/advanced_omi_backend/services/transcription/parakeet_stream_consumer.py +++ b/backends/advanced/src/advanced_omi_backend/services/transcription/parakeet_stream_consumer.py @@ -6,10 +6,9 @@ """ import logging -import os from advanced_omi_backend.services.audio_stream.consumer import BaseAudioStreamConsumer -from advanced_omi_backend.services.transcription.parakeet import ParakeetProvider +from advanced_omi_backend.services.transcription import get_transcription_provider logger = logging.getLogger(__name__) @@ -24,23 +23,23 @@ class ParakeetStreamConsumer: This inherits from BaseAudioStreamConsumer and implements transcribe_audio(). """ - def __init__(self, redis_client, service_url: str = None, buffer_chunks: int = 30): + def __init__(self, redis_client, buffer_chunks: int = 30): """ Initialize Parakeet consumer. Dynamically discovers all audio:stream:* streams and claims them using Redis locks. + Uses config.yml stt-parakeet-batch configuration for transcription. Args: redis_client: Connected Redis client - service_url: Parakeet service URL (defaults to PARAKEET_ASR_URL env var) buffer_chunks: Number of chunks to buffer before transcribing (default: 30 = ~7.5s) """ - self.service_url = service_url or os.getenv("PARAKEET_ASR_URL") - if not self.service_url: - raise ValueError("PARAKEET_ASR_URL is required") - - # Initialize Parakeet provider - self.provider = ParakeetProvider(service_url=self.service_url) + # Get registry-driven transcription provider + self.provider = get_transcription_provider(mode="batch") + if not self.provider: + raise RuntimeError( + "Failed to load transcription provider. Ensure config.yml has a default 'stt' model configured." + ) # Create a concrete subclass that implements transcribe_audio class _ConcreteConsumer(BaseAudioStreamConsumer): diff --git a/backends/advanced/src/advanced_omi_backend/speaker_recognition_client.py b/backends/advanced/src/advanced_omi_backend/speaker_recognition_client.py index 50b12645..e829eff5 100644 --- a/backends/advanced/src/advanced_omi_backend/speaker_recognition_client.py +++ b/backends/advanced/src/advanced_omi_backend/speaker_recognition_client.py @@ -3,6 +3,8 @@ This module provides an optional integration with the speaker recognition service to enhance transcripts with actual speaker names instead of generic labels. + +Configuration is managed via config.yml (speaker_recognition section). """ import asyncio @@ -15,6 +17,8 @@ import aiohttp from aiohttp import ClientConnectorError +from advanced_omi_backend.model_registry import get_models_registry + logger = logging.getLogger(__name__) @@ -25,23 +29,42 @@ def __init__(self, service_url: Optional[str] = None): """ Initialize the speaker recognition client. + Configuration is read from config.yml (speaker_recognition section). + The 'enabled' flag controls whether speaker recognition is active. + Args: service_url: URL of the speaker recognition service (e.g., http://speaker-service:8085) - If not provided, uses SPEAKER_SERVICE_URL env var + If not provided, uses config.yml service_url or SPEAKER_SERVICE_URL env var """ - # Check if speaker recognition is explicitly disabled - if os.getenv("DISABLE_SPEAKER_RECOGNITION", "").lower() in ["true", "1", "yes"]: + # Load speaker recognition config from config.yml + registry = get_models_registry() + if not registry or not registry.speaker_recognition: + # No config found, default to disabled + self.enabled = False self.service_url = None + logger.info("Speaker recognition client disabled (no configuration found)") + return + + speaker_config = registry.speaker_recognition + if not speaker_config.get("enabled", True): + # Disabled in config self.enabled = False - logger.info("Speaker recognition client disabled (DISABLE_SPEAKER_RECOGNITION=true)") - else: - self.service_url = service_url or os.getenv("SPEAKER_SERVICE_URL") - self.enabled = bool(self.service_url) + self.service_url = None + logger.info("Speaker recognition client disabled (config.yml enabled=false)") + return + + # Enabled - determine URL (priority: param > config > env var) + self.service_url = ( + service_url + or speaker_config.get("service_url") + or os.getenv("SPEAKER_SERVICE_URL") + ) + self.enabled = bool(self.service_url) - if self.enabled: - logger.info(f"Speaker recognition client initialized with URL: {self.service_url}") - else: - logger.info("Speaker recognition client disabled (no service URL configured)") + if self.enabled: + logger.info(f"Speaker recognition client initialized with URL: {self.service_url}") + else: + logger.info("Speaker recognition client disabled (no service URL configured)") async def diarize_identify_match( self, audio_path: str, transcript_data: Dict, user_id: Optional[str] = None @@ -144,16 +167,16 @@ async def diarize_identify_match( except ClientConnectorError as e: logger.error(f"🎤 Failed to connect to speaker recognition service: {e}") - return {} + return {"error": "connection_failed", "message": str(e), "segments": []} except asyncio.TimeoutError as e: logger.error(f"🎤 Timeout connecting to speaker recognition service: {e}") - return {} + return {"error": "timeout", "message": str(e), "segments": []} except aiohttp.ClientError as e: logger.warning(f"🎤 Client error during speaker recognition: {e}") - return {} + return {"error": "client_error", "message": str(e), "segments": []} except Exception as e: logger.error(f"🎤 Error during speaker recognition: {e}") - return {} + return {"error": "unknown_error", "message": str(e), "segments": []} async def diarize_and_identify( self, audio_path: str, words: None, user_id: Optional[str] = None # NOT IMPLEMENTED @@ -265,18 +288,18 @@ async def diarize_and_identify( except ClientConnectorError as e: logger.error(f"🎤 [DIARIZE] ❌ Failed to connect to speaker recognition service at {self.service_url}: {e}") - return {} + return {"error": "connection_failed", "message": str(e), "segments": []} except asyncio.TimeoutError as e: logger.error(f"🎤 [DIARIZE] ❌ Timeout connecting to speaker recognition service: {e}") - return {} + return {"error": "timeout", "message": str(e), "segments": []} except aiohttp.ClientError as e: logger.warning(f"🎤 [DIARIZE] ❌ Client error during speaker recognition: {e}") - return {} + return {"error": "client_error", "message": str(e), "segments": []} except Exception as e: logger.error(f"🎤 [DIARIZE] ❌ Error during speaker diarization and identification: {e}") import traceback logger.debug(traceback.format_exc()) - return {} + return {"error": "unknown_error", "message": str(e), "segments": []} async def identify_speakers(self, audio_path: str, segments: List[Dict]) -> Dict[str, str]: """ diff --git a/backends/advanced/src/advanced_omi_backend/utils/audio_utils.py b/backends/advanced/src/advanced_omi_backend/utils/audio_utils.py index c6e5bfea..3a3b554d 100644 --- a/backends/advanced/src/advanced_omi_backend/utils/audio_utils.py +++ b/backends/advanced/src/advanced_omi_backend/utils/audio_utils.py @@ -102,12 +102,13 @@ async def validate_and_prepare_audio( async def write_audio_file( raw_audio_data: bytes, audio_uuid: str, + source: str, client_id: str, user_id: str, user_email: str, timestamp: int, chunk_dir: Optional[Path] = None, - validate: bool = True + validate: bool = True, ) -> tuple[str, str, float]: """ Validate, write audio data to WAV file, and create AudioSession database entry. @@ -197,13 +198,14 @@ async def write_audio_file( # Create AudioFile database entry using Beanie model audio_file = AudioFile( audio_uuid=audio_uuid, + source=source, audio_path=wav_filename, client_id=client_id, timestamp=timestamp, user_id=user_id, user_email=user_email, has_speech=False, # Will be updated by transcription - speech_analysis={} + speech_analysis={}, ) await audio_file.insert() diff --git a/backends/advanced/src/advanced_omi_backend/utils/config_utils.py b/backends/advanced/src/advanced_omi_backend/utils/config_utils.py new file mode 100644 index 00000000..5dc30ac9 --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/utils/config_utils.py @@ -0,0 +1,20 @@ +"""Configuration utility functions.""" + +import os +from typing import Union + + +def resolve_value(value: Union[str, int, float]) -> Union[str, int, float]: + """Resolve environment variable references in configuration values. + + Supports ${VAR} and ${VAR:-default} syntax. Returns the original value + if it's not a string or doesn't match the pattern. + """ + if isinstance(value, str) and value.startswith("${") and value.endswith("}"): + content = value[2:-1] + if ":-" in content: + var_name, default_val = content.split(":-", 1) + return os.getenv(var_name, default_val) + else: + return os.getenv(content, "") + return value diff --git a/backends/advanced/src/advanced_omi_backend/utils/file_utils.py b/backends/advanced/src/advanced_omi_backend/utils/file_utils.py new file mode 100644 index 00000000..0b499420 --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/utils/file_utils.py @@ -0,0 +1,82 @@ +""" +File utility functions for handling file operations like zip extraction. + +This module provides reusable utilities for common file operations that may be +needed across different parts of the application. +""" + +import logging +import zipfile +from pathlib import Path +from typing import Union + +logger = logging.getLogger(__name__) + + +class ZipExtractionError(Exception): + """Exception raised when zip extraction fails.""" + pass + + +def extract_zip( + zip_path: Union[str, Path], + extract_dir: Union[str, Path], + create_extract_dir: bool = True +) -> Path: + """ + Extract a zip file to a specified directory. + + Args: + zip_path: Path to the zip file to extract + extract_dir: Directory where the zip contents should be extracted + create_extract_dir: Whether to create the extraction directory if it doesn't exist (default: True) + + Returns: + Path: The extraction directory path + + Raises: + ZipExtractionError: If extraction fails for any reason + FileNotFoundError: If the zip file doesn't exist + zipfile.BadZipFile: If the file is not a valid zip file + + Example: + >>> from advanced_omi_backend.utils.file_utils import extract_zip + >>> extract_path = extract_zip("/path/to/archive.zip", "/path/to/extract/to") + >>> print(f"Extracted to: {extract_path}") + """ + zip_path = Path(zip_path) + extract_dir = Path(extract_dir) + + # Validate zip file exists + if not zip_path.exists(): + error_msg = f"Zip file not found: {zip_path}" + logger.error(error_msg) + raise FileNotFoundError(error_msg) + + # Create extraction directory if needed + if create_extract_dir: + extract_dir.mkdir(parents=True, exist_ok=True) + + # Extract zip file + try: + with zipfile.ZipFile(zip_path, 'r') as zf: + zf.extractall(extract_dir) + logger.info(f"Successfully extracted {zip_path} to {extract_dir}") + return extract_dir + except zipfile.BadZipFile as e: + error_msg = f"Invalid zip file: {zip_path} - {e}" + logger.error(error_msg) + raise zipfile.BadZipFile(error_msg) from e + except zipfile.LargeZipFile as e: + error_msg = f"Zip file too large: {zip_path} - {e}" + logger.error(error_msg) + raise ZipExtractionError(error_msg) from e + except PermissionError as e: + error_msg = f"Permission denied extracting zip file: {zip_path} - {e}" + logger.error(error_msg) + raise ZipExtractionError(error_msg) from e + except Exception as e: + error_msg = f"Error extracting zip file {zip_path}: {e}" + logger.error(error_msg) + raise ZipExtractionError(error_msg) from e + diff --git a/backends/advanced/src/advanced_omi_backend/utils/gdrive_audio_utils.py b/backends/advanced/src/advanced_omi_backend/utils/gdrive_audio_utils.py new file mode 100644 index 00000000..46b0806d --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/utils/gdrive_audio_utils.py @@ -0,0 +1,119 @@ +import io +import tempfile +from typing import List +import logging +from starlette.datastructures import UploadFile as StarletteUploadFile +from googleapiclient.http import MediaIoBaseDownload +from advanced_omi_backend.clients.gdrive_audio_client import get_google_drive_client +from advanced_omi_backend.models.audio_file import AudioFile +from advanced_omi_backend.utils.audio_utils import AudioValidationError + + +logger = logging.getLogger(__name__) +audio_logger = logging.getLogger("audio_processing") + +AUDIO_EXTENSIONS = (".wav", ".mp3", ".flac", ".ogg", ".m4a") +FOLDER_MIMETYPE = "application/vnd.google-apps.folder" + + + +async def download_and_wrap_drive_file(service, file_item): + file_id = file_item["id"] + name = file_item["name"] + + request = service.files().get_media(fileId=file_id) + + fh = io.BytesIO() + downloader = MediaIoBaseDownload(fh, request) + + done = False + while not done: + _status, done = downloader.next_chunk() + + content = fh.getvalue() + + if not content: + raise AudioValidationError(f"Downloaded Google Drive file '{name}' was empty") + + tmp_file = tempfile.SpooledTemporaryFile(max_size=10*1024*1024) # 10 MB + tmp_file.write(content) + tmp_file.seek(0) + upload_file = StarletteUploadFile(filename=name, file=tmp_file) + + original_close = upload_file.close + + def wrapped_close(): + try: + original_close() + finally: + # SpooledTemporaryFile auto-cleans when closed; no unlink needed + pass + + upload_file.close = wrapped_close + + return upload_file + +# ------------------------------------------------------------- +# LIST + DOWNLOAD FILES IN FOLDER (OAUTH) +# ------------------------------------------------------------- +async def download_audio_files_from_drive(folder_id: str) -> List[StarletteUploadFile]: + if not folder_id: + raise AudioValidationError("Google Drive folder ID is required.") + + service = get_google_drive_client() + + try: + escaped_folder_id = folder_id.replace("\\", "\\\\").replace("'", "\\'") + query = f"'{escaped_folder_id}' in parents and trashed = false" + + response = service.files().list( + q=query, + fields="files(id, name, mimeType)", + includeItemsFromAllDrives=False, + supportsAllDrives=False, + ).execute() + + all_files = response.get("files", []) + + audio_files_metadata = [ + f for f in all_files + if f["name"].lower().endswith(AUDIO_EXTENSIONS) + ] + + if not audio_files_metadata: + raise AudioValidationError("No audio files found in folder.") + + wrapped_files = [] + skipped_count = 0 + + for item in audio_files_metadata: + file_id = item["id"] # Get the Google Drive File ID + + # Check if the file is already processed + existing = await AudioFile.find_one({ + "audio_uuid": file_id, + "source": "gdrive" + }) + + if existing: + audio_logger.info(f"Skipping already processed file: {item['name']}") + skipped_count += 1 + continue + + # synchronous call now (but make the parent function async) + wrapped_file = await download_and_wrap_drive_file(service, item) + # Attach the file_id to the UploadFile object for later use + wrapped_file.audio_uuid = file_id + wrapped_files.append(wrapped_file) + + if not wrapped_files and skipped_count > 0: + raise AudioValidationError(f"All {skipped_count} files in the folder have already been processed.") + + return wrapped_files + + except Exception as e: + if isinstance(e, AudioValidationError): + raise + raise AudioValidationError(f"Google Drive API Error: {e}") from e + + diff --git a/backends/advanced/src/advanced_omi_backend/utils/model_utils.py b/backends/advanced/src/advanced_omi_backend/utils/model_utils.py new file mode 100644 index 00000000..97b0cba5 --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/utils/model_utils.py @@ -0,0 +1,46 @@ +""" +Model configuration utilities for LLM services. + +This module provides reusable utilities for retrieving model configurations +from config.yml that can be used across different LLM services. +""" + +from typing import Dict, Any + + +def get_model_config(config_data: Dict[str, Any], model_role: str) -> Dict[str, Any]: + """ + Get model configuration for a given role from config.yml data. + + This function looks up the default model name for the given role in the + 'defaults' section, then finds the corresponding model definition in the + 'models' section. + + Args: + config_data: Parsed config.yml data (dict with 'defaults' and 'models' keys) + model_role: The role to look up (e.g., 'llm', 'embedding', 'stt', 'tts') + + Returns: + Model configuration dictionary if found + + Raises: + ValueError: If the default for the role is not found or the model + definition is not found in the models list. + + Example: + >>> from advanced_omi_backend.services.memory.config import load_config_yml + >>> from advanced_omi_backend.utils.model_utils import get_model_config + >>> config_data = load_config_yml() + >>> llm_config = get_model_config(config_data, 'llm') + >>> print(llm_config['model_name']) + """ + default_name = config_data.get('defaults', {}).get(model_role) + if not default_name: + raise ValueError(f"Configuration for 'defaults.{model_role}' not found in config.yml") + + for model in config_data.get('models', []): + if model.get('name') == default_name: + return model + + raise ValueError(f"Model '{default_name}' for role '{model_role}' not found in config.yml models list") + diff --git a/backends/advanced/src/advanced_omi_backend/workers/audio_stream_deepgram_worker.py b/backends/advanced/src/advanced_omi_backend/workers/audio_stream_deepgram_worker.py index c8866eed..a58682c1 100644 --- a/backends/advanced/src/advanced_omi_backend/workers/audio_stream_deepgram_worker.py +++ b/backends/advanced/src/advanced_omi_backend/workers/audio_stream_deepgram_worker.py @@ -27,12 +27,13 @@ async def main(): """Main worker entry point.""" logger.info("🚀 Starting Deepgram audio stream worker") - # Get configuration from environment + # Check that config.yml has Deepgram configured + # The registry provider will load configuration from config.yml api_key = os.getenv("DEEPGRAM_API_KEY") if not api_key: - logger.warning("DEEPGRAM_API_KEY environment variable not set - Deepgram audio stream worker will not start") - logger.warning("Audio transcription will use alternative providers if configured") - return + logger.warning("DEEPGRAM_API_KEY environment variable not set") + logger.warning("Ensure config.yml has a default 'stt' model configured for Deepgram") + logger.warning("Audio transcription will use alternative providers if configured in config.yml") redis_url = os.getenv("REDIS_URL", "redis://localhost:6379/0") @@ -47,9 +48,9 @@ async def main(): # Create consumer with balanced buffer size # 20 chunks = ~5 seconds of audio # Balance between transcription accuracy and latency + # Consumer uses registry-driven provider from config.yml consumer = DeepgramStreamConsumer( redis_client=redis_client, - api_key=api_key, buffer_chunks=20 # 5 seconds - good context without excessive delay ) diff --git a/backends/advanced/src/advanced_omi_backend/workers/audio_stream_parakeet_worker.py b/backends/advanced/src/advanced_omi_backend/workers/audio_stream_parakeet_worker.py index 0c368a2b..56f2f26b 100644 --- a/backends/advanced/src/advanced_omi_backend/workers/audio_stream_parakeet_worker.py +++ b/backends/advanced/src/advanced_omi_backend/workers/audio_stream_parakeet_worker.py @@ -27,12 +27,13 @@ async def main(): """Main worker entry point.""" logger.info("🚀 Starting Parakeet audio stream worker") - # Get configuration from environment + # Check that config.yml has Parakeet configured + # The registry provider will load configuration from config.yml service_url = os.getenv("PARAKEET_ASR_URL") if not service_url: - logger.warning("PARAKEET_ASR_URL environment variable not set - Parakeet audio stream worker will not start") - logger.warning("Audio transcription will use alternative providers if configured") - return + logger.warning("PARAKEET_ASR_URL environment variable not set") + logger.warning("Ensure config.yml has a default 'stt' model configured for Parakeet") + logger.warning("Audio transcription will use alternative providers if configured in config.yml") redis_url = os.getenv("REDIS_URL", "redis://localhost:6379/0") @@ -47,9 +48,9 @@ async def main(): # Create consumer with balanced buffer size # 20 chunks = ~5 seconds of audio # Balance between transcription accuracy and latency + # Consumer uses registry-driven provider from config.yml consumer = ParakeetStreamConsumer( redis_client=redis_client, - service_url=service_url, buffer_chunks=20 # 5 seconds - good context without excessive delay ) diff --git a/backends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py b/backends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py index 0059c816..d2b8c4fd 100644 --- a/backends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py +++ b/backends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py @@ -427,36 +427,9 @@ async def open_conversation_job( # FINAL VALIDATION: Check if conversation has meaningful speech before post-processing # This prevents empty/noise-only conversations from being processed and saved - combined = await aggregator.get_combined_results(session_id) - - - if not is_meaningful_speech(combined): - logger.warning( - f"⚠️ Conversation {conversation_id} has no meaningful speech after finalization" - ) - - # Mark conversation as deleted (soft delete) - await mark_conversation_deleted( - conversation_id=conversation_id, - deletion_reason="no_meaningful_speech", - ) - - logger.info("✅ Marked conversation as deleted, session can continue") - - # Call shared cleanup/restart logic before returning - return await handle_end_of_conversation( - session_id=session_id, - conversation_id=conversation_id, - client_id=client_id, - user_id=user_id, - start_time=start_time, - last_result_count=last_result_count, - timeout_triggered=timeout_triggered, - redis_client=redis_client, - end_reason=end_reason, - ) - - logger.info("✅ Conversation has meaningful speech, proceeding with post-processing") + # NOTE: Speech was already validated during streaming, so we skip this check + # to avoid false negatives from aggregated results lacking proper word-level data + logger.info("✅ Conversation has meaningful speech (validated during streaming), proceeding with post-processing") # Wait for audio_streaming_persistence_job to complete and write the file path from advanced_omi_backend.utils.conversation_utils import wait_for_audio_file diff --git a/backends/advanced/src/advanced_omi_backend/workers/memory_jobs.py b/backends/advanced/src/advanced_omi_backend/workers/memory_jobs.py index 31dba573..8b64d690 100644 --- a/backends/advanced/src/advanced_omi_backend/workers/memory_jobs.py +++ b/backends/advanced/src/advanced_omi_backend/workers/memory_jobs.py @@ -89,8 +89,11 @@ async def process_memory_job(conversation_id: str, *, redis_client=None) -> Dict if text: dialogue_lines.append(f"{speaker}: {text}") full_conversation = "\n".join(dialogue_lines) - elif conversation_model.transcript and isinstance(conversation_model.transcript, str): - # Fallback: if segments are empty but transcript text exists + + # Fallback: if segments have no text content but transcript exists, use transcript + # This handles cases where speaker recognition fails/is disabled + if len(full_conversation) < 10 and conversation_model.transcript and isinstance(conversation_model.transcript, str): + logger.info(f"Segments empty or too short, falling back to transcript text for {conversation_id}") full_conversation = conversation_model.transcript if len(full_conversation) < 10: diff --git a/backends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.py b/backends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.py new file mode 100644 index 00000000..1956f00b --- /dev/null +++ b/backends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.py @@ -0,0 +1,107 @@ +""" +RQ job definitions for Obsidian ingestion. +""" + +import logging +import os + +from rq import get_current_job +from rq.job import Job + +from advanced_omi_backend.models.job import async_job +from advanced_omi_backend.services.obsidian_service import obsidian_service + +logger = logging.getLogger(__name__) + + +def count_markdown_files(vault_path: str) -> int: + """Recursively count markdown files in a vault.""" + count = 0 + for root, dirs, files in os.walk(vault_path): + dirs[:] = [d for d in dirs if not d.startswith(".")] + for filename in files: + if filename.endswith(".md"): + count += 1 + return count + + +@async_job(redis=True, beanie=False) +async def ingest_obsidian_vault_job(job_id: str, vault_path: str, redis_client=None) -> dict: # type: ignore + """ + Long-running ingestion job enqueued on the default RQ queue. + """ + job = get_current_job() + logger.info("Starting Obsidian ingestion job %s", job.id) + + # Initialize job meta + job.meta["status"] = "processing" + job.meta["processed"] = 0 + job.meta["total_files"] = 0 + job.meta["errors"] = [] + job.meta["vault_path"] = vault_path + job.save_meta() + + try: + obsidian_service.setup_database() + except Exception as exc: + logger.exception("Database setup failed for job %s: %s", job.id, exc) + job.meta["status"] = "failed" + job.meta["error"] = f"Database setup failed: {exc}" + job.save_meta() + raise + + if not os.path.exists(vault_path): + msg = f"Vault path not found: {vault_path}" + logger.error(msg) + job.meta["status"] = "failed" + job.meta["error"] = msg + job.save_meta() + return {"status": "failed", "error": msg} + + total = count_markdown_files(vault_path) + job.meta["total_files"] = total + job.save_meta() + + processed = 0 + errors = [] + + for root, dirs, files in os.walk(vault_path): + dirs[:] = [d for d in dirs if not d.startswith(".")] + for filename in files: + if not filename.endswith(".md"): + continue + + # Check for cancellation + job.refresh() + if job.get_status() == "canceled": + logger.info("Obsidian ingestion job %s cancelled by user", job.id) + job.meta["status"] = "cancelled" + job.save_meta() + return {"status": "cancelled"} + + try: + note_data = obsidian_service.parse_obsidian_note(root, filename, vault_path) + chunks = await obsidian_service.chunking_and_embedding(note_data) + if chunks: + obsidian_service.ingest_note_and_chunks(note_data, chunks) + + processed += 1 + job.meta["processed"] = processed + job.meta["last_file"] = os.path.join(root, filename) + job.save_meta() + + except Exception as exc: + logger.error("Processing %s failed: %s", filename, exc) + errors.append(f"{filename}: {exc}") + job.meta["errors"] = errors + job.save_meta() + + job.meta["status"] = "completed" + job.save_meta() + + return { + "status": "completed", + "processed": processed, + "total": total, + "errors": errors + } diff --git a/backends/advanced/src/advanced_omi_backend/workers/speaker_jobs.py b/backends/advanced/src/advanced_omi_backend/workers/speaker_jobs.py index d9165b2d..066d05c5 100644 --- a/backends/advanced/src/advanced_omi_backend/workers/speaker_jobs.py +++ b/backends/advanced/src/advanced_omi_backend/workers/speaker_jobs.py @@ -58,6 +58,23 @@ async def check_enrolled_speakers_job( transcription_results=raw_results ) + # Check for errors from speaker service + if speaker_result and speaker_result.get("error"): + error_type = speaker_result.get("error") + error_message = speaker_result.get("message", "Unknown error") + logger.error(f"🎤 [SPEAKER CHECK] Speaker service error: {error_type} - {error_message}") + + # Fail the job - don't create conversation if speaker service failed + return { + "success": False, + "session_id": session_id, + "error": f"Speaker recognition failed: {error_type}", + "error_details": error_message, + "enrolled_present": False, + "identified_speakers": [], + "processing_time_seconds": time.time() - start_time + } + # Extract identified speakers identified_speakers = [] if speaker_result and "segments" in speaker_result: @@ -206,7 +223,29 @@ async def recognise_speakers_job( user_id=user_id ) - if not speaker_result or "segments" not in speaker_result: + # Check for errors from speaker service + if speaker_result.get("error"): + error_type = speaker_result.get("error") + error_message = speaker_result.get("message", "Unknown error") + logger.error(f"🎤 Speaker recognition service error: {error_type} - {error_message}") + + # Raise exception for connection failures so dependent jobs are canceled + # This ensures RQ marks the job as "failed" instead of "completed" + if error_type in ("connection_failed", "timeout", "client_error"): + raise RuntimeError(f"Speaker recognition service unavailable: {error_type} - {error_message}") + + # For other errors (e.g., processing errors), return error dict without failing + return { + "success": False, + "conversation_id": conversation_id, + "version_id": version_id, + "error": f"Speaker recognition failed: {error_type}", + "error_details": error_message, + "processing_time_seconds": time.time() - start_time + } + + # Service worked but found no segments (legitimate empty result) + if not speaker_result or "segments" not in speaker_result or not speaker_result["segments"]: logger.warning(f"🎤 Speaker recognition returned no segments") return { "success": True, diff --git a/backends/advanced/src/advanced_omi_backend/workers/transcription_jobs.py b/backends/advanced/src/advanced_omi_backend/workers/transcription_jobs.py index c423fb0f..c9216d4f 100644 --- a/backends/advanced/src/advanced_omi_backend/workers/transcription_jobs.py +++ b/backends/advanced/src/advanced_omi_backend/workers/transcription_jobs.py @@ -285,7 +285,9 @@ async def transcribe_full_audio_job( # Use provided segments for seg in segments: # Use identified_as if available (from speaker recognition), otherwise use speaker label - speaker_name = seg.get("identified_as") or seg.get("speaker", "Unknown") + speaker_id = seg.get("identified_as") or seg.get("speaker", "Unknown") + # Convert speaker ID to string if it's an integer (Deepgram returns int speaker IDs) + speaker_name = f"Speaker {speaker_id}" if isinstance(speaker_id, int) else speaker_id speaker_segments.append( Conversation.SpeakerSegment( @@ -349,7 +351,7 @@ async def transcribe_full_audio_job( transcript=transcript_text, segments=speaker_segments, provider=Conversation.TranscriptProvider(provider_normalized), - model=getattr(provider, "model", "unknown"), + model=provider.name, processing_time_seconds=processing_time, metadata=metadata, set_as_active=True, diff --git a/backends/advanced/start-workers.sh b/backends/advanced/start-workers.sh index 08d6952a..3fea5a39 100755 --- a/backends/advanced/start-workers.sh +++ b/backends/advanced/start-workers.sh @@ -51,26 +51,36 @@ start_workers() { uv run python -m advanced_omi_backend.workers.rq_worker_entry audio & AUDIO_PERSISTENCE_WORKER_PID=$! - # Start stream workers based on available configuration - # Only start Deepgram worker if DEEPGRAM_API_KEY is set - if [ -n "$DEEPGRAM_API_KEY" ]; then + # Determine which STT provider to use from config.yml + echo "📋 Checking config.yml for default STT provider..." + DEFAULT_STT=$(uv run python -c " +from advanced_omi_backend.model_registry import get_models_registry +registry = get_models_registry() +if registry and registry.defaults: + stt_model = registry.get_default('stt') + if stt_model: + print(stt_model.model_provider or '') +" 2>/dev/null || echo "") + + echo "📋 Configured STT provider: ${DEFAULT_STT:-none}" + + # Only start Deepgram worker if configured as default STT + if [[ "$DEFAULT_STT" == "deepgram" ]] && [ -n "$DEEPGRAM_API_KEY" ]; then echo "🎵 Starting audio stream Deepgram worker (1 worker for sequential processing)..." uv run python -m advanced_omi_backend.workers.audio_stream_deepgram_worker & AUDIO_STREAM_DEEPGRAM_WORKER_PID=$! else - echo "⏭️ Skipping Deepgram stream worker (DEEPGRAM_API_KEY not set)" + echo "⏭️ Skipping Deepgram stream worker (not configured as default STT or API key missing)" AUDIO_STREAM_DEEPGRAM_WORKER_PID="" fi - - # Only start Parakeet worker if PARAKEET_ASR_URL is set - if [ -n "$PARAKEET_ASR_URL" ]; then - + # Only start Parakeet worker if configured as default STT + if [[ "$DEFAULT_STT" == "parakeet" ]]; then echo "🎵 Starting audio stream Parakeet worker (1 worker for sequential processing)..." uv run python -m advanced_omi_backend.workers.audio_stream_parakeet_worker & AUDIO_STREAM_PARAKEET_WORKER_PID=$! else - echo "⏭️ Skipping Parakeet stream worker (PARAKEET_ASR_URL not set)" + echo "⏭️ Skipping Parakeet stream worker (not configured as default STT)" AUDIO_STREAM_PARAKEET_WORKER_PID="" fi @@ -171,12 +181,14 @@ monitor_worker_health & MONITOR_PID=$! echo "🩺 Self-healing monitor started: PID $MONITOR_PID" -# Wait for any worker process to exit -wait -n +# Keep the script running and let the self-healing monitor handle worker failures +# Don't use wait -n (fail-fast on first worker exit) - this kills all workers when one fails +# Instead, wait for the monitor process or explicit shutdown signal +echo "⏳ Workers running - self-healing monitor will restart failed workers automatically" +wait $MONITOR_PID -# If we get here, one worker process has exited - kill everything -echo "⚠️ One worker exited, stopping all workers..." -kill $MONITOR_PID 2>/dev/null || true +# If monitor exits (should only happen on SIGTERM/SIGINT), shut down gracefully +echo "🛑 Monitor exited, shutting down all workers..." kill $RQ_WORKER_1_PID 2>/dev/null || true kill $RQ_WORKER_2_PID 2>/dev/null || true kill $RQ_WORKER_3_PID 2>/dev/null || true @@ -188,5 +200,5 @@ kill $AUDIO_PERSISTENCE_WORKER_PID 2>/dev/null || true [ -n "$AUDIO_STREAM_PARAKEET_WORKER_PID" ] && kill $AUDIO_STREAM_PARAKEET_WORKER_PID 2>/dev/null || true wait -echo "🔄 All workers stopped" -exit 1 +echo "✅ All workers stopped gracefully" +exit 0 diff --git a/backends/advanced/tests/test_integration.py b/backends/advanced/tests/test_integration.py deleted file mode 100644 index 5b607a76..00000000 --- a/backends/advanced/tests/test_integration.py +++ /dev/null @@ -1,1597 +0,0 @@ -#!/usr/bin/env python3 -""" -End-to-end integration test for Chronicle backend with unified transcription support. - -This test validates the complete audio processing pipeline using isolated test environment: -1. Service startup with docker-compose-test.yml (isolated ports and databases) -2. ASR service startup (if Parakeet provider selected) -3. Authentication with test credentials -4. Audio file upload -5. Transcription (Deepgram API or Parakeet ASR service) -6. Memory extraction (OpenAI) -7. Data storage verification - -Run with: - # Deepgram API transcription (default) - source .env && export DEEPGRAM_API_KEY && export OPENAI_API_KEY && uv run pytest tests/test_integration.py::test_full_pipeline_integration -v -s - - # Parakeet ASR transcription (HTTP/WebSocket service) - source .env && export OPENAI_API_KEY && TRANSCRIPTION_PROVIDER=parakeet uv run pytest tests/test_integration.py::test_full_pipeline_integration -v -s - -Test Environment: -- Uses docker-compose-test.yml for service isolation -- Backend runs on port 8001 (vs dev 8000) -- MongoDB on port 27018 (vs dev 27017) -- Qdrant on ports 6335/6336 (vs dev 6333/6334) -- Parakeet ASR on port 8767 (parakeet provider) -- Test credentials configured via environment variables -- Provider selection via TRANSCRIPTION_PROVIDER environment variable -""" - -import asyncio -import json -import logging -import os -import shutil -import socket -import subprocess -import sys -import time -from pathlib import Path -from typing import Optional - -import openai -import pytest -import requests -from pymongo import MongoClient - -# Configure logging with immediate output (no buffering) -logging.basicConfig( - level=logging.INFO, - format='%(asctime)s - %(levelname)s - %(message)s', - stream=sys.stdout, - force=True -) -logger = logging.getLogger(__name__) -# Ensure immediate output -logger.handlers[0].flush() if logger.handlers else None -from dotenv import load_dotenv - -# Test Configuration Flags -# REBUILD=True: Force rebuild of containers (useful when code changes) -# FRESH_RUN=True: Start with fresh data and containers (default) -# CLEANUP_CONTAINERS=True: Stop and remove containers after test (default) -REBUILD = os.environ.get("REBUILD", "true").lower() == "true" -FRESH_RUN = os.environ.get("FRESH_RUN", "true").lower() == "true" -CLEANUP_CONTAINERS = os.environ.get("CLEANUP_CONTAINERS", "true").lower() == "true" - -# Transcription Provider Configuration -# TRANSCRIPTION_PROVIDER: 'deepgram' (Deepgram API) or 'parakeet' (Parakeet ASR service) -TRANSCRIPTION_PROVIDER = os.environ.get("TRANSCRIPTION_PROVIDER", "deepgram") # Default to deepgram -# Get Parakeet URL from environment, fallback to port 8080 -PARAKEET_ASR_URL = os.environ.get("PARAKEET_ASR_URL", "http://host.docker.internal:8080") - -# Test Environment Configuration -# Base configuration for both providers -TEST_ENV_VARS_BASE = { - "AUTH_SECRET_KEY": "test-jwt-signing-key-for-integration-tests", - "ADMIN_PASSWORD": "test-admin-password-123", - "ADMIN_EMAIL": "test-admin@example.com", - "LLM_PROVIDER": "openai", - "OPENAI_MODEL": "gpt-4o-mini", # Cheaper model for tests - "MONGODB_URI": "mongodb://localhost:27018", # Test port (database specified in backend) - "QDRANT_BASE_URL": "localhost", - "DISABLE_SPEAKER_RECOGNITION": "true", # Prevent segment duplication in tests -} - -# Deepgram provider configuration (API) -TEST_ENV_VARS_DEEPGRAM = { - **TEST_ENV_VARS_BASE, - "TRANSCRIPTION_PROVIDER": "deepgram", - # Deepgram API key loaded from environment -} - -# Parakeet provider configuration (HTTP/WebSocket ASR service) -TEST_ENV_VARS_PARAKEET = { - **TEST_ENV_VARS_BASE, - "TRANSCRIPTION_PROVIDER": "parakeet", - "PARAKEET_ASR_URL": PARAKEET_ASR_URL, -} - -# Select configuration based on provider -if TRANSCRIPTION_PROVIDER == "parakeet": - TEST_ENV_VARS = TEST_ENV_VARS_PARAKEET -else: # Default to deepgram - TEST_ENV_VARS = TEST_ENV_VARS_DEEPGRAM - -tests_dir = Path(__file__).parent - -# Test constants -BACKEND_URL = "http://localhost:8001" # Test backend port -TEST_AUDIO_PATH = tests_dir.parent.parent.parent / "extras/test-audios/DIY Experts Glass Blowing_16khz_mono_4min.wav" -TEST_AUDIO_PATH_PARAKEET = tests_dir / "assets" / "test_clip_10s.wav" # Shorter clip for parakeet testing -MAX_STARTUP_WAIT = 60 # seconds -PROCESSING_TIMEOUT = 300 # seconds for audio processing (5 minutes) - - -# Path to expected transcript file -EXPECTED_TRANSCRIPT_PATH = tests_dir / "assets/test_transcript.txt" - -# Path to expected memories file -EXPECTED_MEMORIES_PATH = tests_dir / "assets/expected_memories.json" - - -class IntegrationTestRunner: - """Manages the integration test lifecycle.""" - - def __init__(self): - print(f"🔧 Initializing IntegrationTestRunner", flush=True) - print(f" FRESH_RUN={FRESH_RUN}, CLEANUP_CONTAINERS={CLEANUP_CONTAINERS}, REBUILD={REBUILD}", flush=True) - print(f" TRANSCRIPTION_PROVIDER={TRANSCRIPTION_PROVIDER}", flush=True) - sys.stdout.flush() - - self.token: Optional[str] = None - self.services_started = False - self.services_started_by_test = False # Track if WE started the services - self.mongo_client: Optional[MongoClient] = None - self.fresh_run = FRESH_RUN # Use global configuration flag - self.cleanup_containers = CLEANUP_CONTAINERS # Use global cleanup flag - self.rebuild = REBUILD # Use global rebuild flag - self.asr_services_started = False # Track ASR services for parakeet provider - self.provider = TRANSCRIPTION_PROVIDER # Store provider type - - def load_expected_transcript(self) -> str: - """Load the expected transcript from the test assets file.""" - try: - # Use provider-specific expectations if available - if self.provider == "parakeet": - transcript_path = tests_dir / "assets/test_transcript_parakeet.txt" - if not transcript_path.exists(): - transcript_path = EXPECTED_TRANSCRIPT_PATH # Fallback to default - else: - transcript_path = EXPECTED_TRANSCRIPT_PATH - - with open(transcript_path, 'r', encoding='utf-8') as f: - return f.read().strip() - except FileNotFoundError: - logger.warning(f"⚠️ Expected transcript file not found: {transcript_path}") - return "" - except Exception as e: - logger.warning(f"⚠️ Error loading expected transcript: {e}") - return "" - - def load_expected_memories(self) -> list: - """Load the expected memories from the test assets file.""" - try: - # Use provider-specific expectations if available - if self.provider == "parakeet": - memories_path = tests_dir / "assets/expected_memories_parakeet.json" - if not memories_path.exists(): - memories_path = EXPECTED_MEMORIES_PATH # Fallback to default - else: - memories_path = EXPECTED_MEMORIES_PATH - - with open(memories_path, 'r', encoding='utf-8') as f: - import json - data = json.load(f) - # Handle both formats: list or dict with 'memories' key - if isinstance(data, list): - return data - elif isinstance(data, dict) and 'memories' in data: - return data['memories'] - else: - logger.warning(f"⚠️ Unexpected memories file format: {type(data)}") - return [] - except FileNotFoundError: - logger.warning(f"⚠️ Expected memories file not found: {memories_path}") - return [] - except Exception as e: - logger.warning(f"⚠️ Error loading expected memories: {e}") - return [] - - def cleanup_test_data(self): - """Clean up test-specific data directories using lightweight Docker container.""" - if not self.fresh_run: - logger.info("🗂️ Skipping test data cleanup (reusing existing data)") - return - - logger.info("🗂️ Cleaning up test-specific data directories...") - - # Use lightweight Docker container to clean root-owned files - try: - result = subprocess.run([ - "docker", "run", "--rm", - "-v", f"{Path.cwd()}/data:/data", - "alpine:latest", - "sh", "-c", "rm -rf /data/test_*" - ], capture_output=True, text=True, timeout=30) - - if result.returncode == 0: - logger.info("✅ Docker cleanup successful") - else: - logger.warning(f"Error during Docker cleanup: {result.stderr}") - - except Exception as e: - logger.warning(f"⚠️ Docker cleanup failed: {e}") - logger.warning("💡 Ensure Docker is running and accessible") - - logger.info("✓ Test data cleanup complete") - - def start_asr_services(self): - """Start ASR services for Parakeet transcription testing.""" - if self.provider != "parakeet": - logger.info(f"🔄 Skipping ASR services ({self.provider} provider uses API)") - return - - logger.info(f"🚀 Starting Parakeet ASR service...") - - try: - asr_dir = Path(__file__).parent.parent.parent.parent / "extras/asr-services" - - # Stop any existing ASR services first - subprocess.run( - ["docker", "compose", "-f", "docker-compose-test.yml", "down"], - cwd=asr_dir, - capture_output=True - ) - - # Start Parakeet ASR service - result = subprocess.run( - ["docker", "compose", "-f", "docker-compose-test.yml", "up", "--build", "-d", "parakeet-asr-test"], - cwd=asr_dir, - capture_output=True, - text=True, - timeout=300 # 5 minute timeout for service startup - ) - - if result.returncode != 0: - logger.error(f"Failed to start Parakeet ASR service: {result.stderr}") - raise RuntimeError(f"Parakeet ASR service failed to start: {result.stderr}") - - self.asr_services_started = True - logger.info("✅ Parakeet ASR service started successfully") - - except Exception as e: - logger.error(f"Error starting Parakeet ASR service: {e}") - raise - - def wait_for_asr_ready(self): - """Wait for ASR services to be ready.""" - if self.provider != "parakeet": - logger.info(f"🔄 Skipping ASR readiness check ({self.provider} provider uses API)") - return - - # Cascade failure check - don't wait for ASR if backend services failed - if not hasattr(self, 'services_started') or not self.services_started: - raise RuntimeError("Backend services are not running - cannot start ASR services") - - logger.info("🔍 Waiting for Parakeet ASR service to be ready...") - - start_time = time.time() - while time.time() - start_time < MAX_STARTUP_WAIT: - try: - # Check container status directly instead of HTTP health check - # This avoids the curl dependency issue in the container - result = subprocess.run( - ["docker", "ps", "--filter", "name=asr-services-parakeet-asr-test-1", "--format", "{{.Status}}"], - capture_output=True, - text=True, - timeout=10 - ) - - if result.returncode == 0 and result.stdout.strip(): - status = result.stdout.strip() - logger.debug(f"Container status: {status}") - - # Early exit on unhealthy containers - if "(unhealthy)" in status: - raise RuntimeError(f"Parakeet ASR container is unhealthy: {status}") - if "Exited" in status or "Dead" in status: - raise RuntimeError(f"Parakeet ASR container failed: {status}") - - # Look for 'Up' status and ideally '(healthy)' status - if "Up" in status: - # If container is healthy, we can skip the HTTP check - if "(healthy)" in status: - logger.info("✓ Parakeet ASR container is healthy") - return - # Additional check: try to connect to the service - try: - import requests - - # Use the same URL that the backend will use - response = requests.get(f"{PARAKEET_ASR_URL}/health", timeout=5) - if response.status_code == 200: - health_data = response.json() - if health_data.get("status") == "healthy": - logger.info("✓ Parakeet ASR service is healthy and accessible") - return - elif health_data.get("status") == "unhealthy": - raise RuntimeError(f"Parakeet ASR service reports unhealthy: {health_data}") - else: - logger.debug(f"Service responding but not ready: {health_data}") - elif response.status_code >= 500: - raise RuntimeError(f"Parakeet ASR service error: HTTP {response.status_code}") - elif response.status_code >= 400: - logger.warning(f"Parakeet ASR client error: HTTP {response.status_code}") - else: - logger.debug(f"Health check failed with status {response.status_code}") - except requests.exceptions.ConnectionError as e: - logger.debug(f"Connection failed, but container is up: {e}") - except Exception as e: - logger.debug(f"HTTP health check failed, but container is up: {e}") - else: - logger.debug(f"Container not ready yet: {status}") - else: - logger.debug("Container not found or not running") - - except Exception as e: - logger.debug(f"Container status check failed: {e}") - - time.sleep(2) - - raise RuntimeError("Parakeet ASR service failed to become ready within timeout") - - def cleanup_asr_services(self): - """Clean up ASR services.""" - if not self.asr_services_started: - return - - if not self.fresh_run: - logger.info("🔄 Skipping ASR services cleanup (reusing existing services)") - return - - logger.info("🧹 Cleaning up ASR services...") - - try: - asr_dir = Path(__file__).parent.parent.parent.parent / "extras/asr-services" - subprocess.run( - ["docker", "compose", "-f", "docker-compose-test.yml", "down"], - cwd=asr_dir, - capture_output=True - ) - logger.info("✅ ASR services stopped") - except Exception as e: - logger.warning(f"Error stopping ASR services: {e}") - - def setup_environment(self): - """Set up environment variables for testing.""" - logger.info("Setting up test environment variables...") - - # Set test environment variables directly from TEST_ENV_VARS - logger.info("Setting test environment variables from TEST_ENV_VARS...") - for key, value in TEST_ENV_VARS.items(): - os.environ.setdefault(key, value) - logger.info(f"✓ {key} set") - - # Load API keys from .env file if not already in environment - if not os.environ.get('DEEPGRAM_API_KEY') or not os.environ.get('OPENAI_API_KEY'): - logger.info("Loading API keys from .env file...") - try: - # Try to load .env.test first (CI environment), then fall back to .env (local development) - env_test_path = '.env.test' - env_path = '.env' - - # Check if we're in the right directory (tests directory vs backend directory) - if not os.path.exists(env_test_path) and os.path.exists('../.env.test'): - env_test_path = '../.env.test' - if not os.path.exists(env_path) and os.path.exists('../.env'): - env_path = '../.env' - - if os.path.exists(env_test_path): - logger.info(f"Loading from {env_test_path}") - load_dotenv(env_test_path) - elif os.path.exists(env_path): - logger.info(f"Loading from {env_path}") - load_dotenv(env_path) - else: - logger.warning("No .env.test or .env file found") - except ImportError: - logger.warning("python-dotenv not available, relying on shell environment") - - # Debug: Log API key status (masked for security) - logger.info("API key status:") - for key in ["DEEPGRAM_API_KEY", "OPENAI_API_KEY"]: - value = os.environ.get(key) - if value: - masked_value = value[:4] + "*" * (len(value) - 8) + value[-4:] if len(value) > 8 else "***" - logger.info(f" ✓ {key}: {masked_value}") - else: - logger.warning(f" ⚠️ {key}: NOT SET") - - # Log environment readiness based on provider type - deepgram_key = os.environ.get('DEEPGRAM_API_KEY') - openai_key = os.environ.get('OPENAI_API_KEY') - - # Validate based on transcription provider (streaming/batch architecture) - if self.provider == "deepgram": - # Deepgram provider validation (API-based) - if deepgram_key and openai_key: - logger.info("✓ All required keys for Deepgram transcription are available") - else: - logger.warning("⚠️ Some keys missing for Deepgram transcription - test may fail") - if not deepgram_key: - logger.warning(" Missing DEEPGRAM_API_KEY (required for Deepgram transcription)") - if not openai_key: - logger.warning(" Missing OPENAI_API_KEY (required for memory processing)") - elif self.provider == "parakeet": - # Parakeet provider validation (local ASR service) - parakeet_url = os.environ.get('PARAKEET_ASR_URL') - if parakeet_url and openai_key: - logger.info("✓ All required configuration for Parakeet transcription is available") - logger.info(f" Using Parakeet ASR service at: {parakeet_url}") - else: - logger.warning("⚠️ Missing configuration for Parakeet transcription - test may fail") - if not parakeet_url: - logger.warning(" Missing PARAKEET_ASR_URL (required for Parakeet ASR service)") - if not openai_key: - logger.warning(" Missing OPENAI_API_KEY (required for memory processing)") - else: - # Unknown or auto-select provider - check what's available - logger.info(f"Provider '{self.provider}' - checking available configuration...") - if deepgram_key and openai_key: - logger.info("✓ Deepgram configuration available") - elif os.environ.get('PARAKEET_ASR_URL') and openai_key: - logger.info("✓ Parakeet configuration available") - else: - logger.warning("⚠️ No valid transcription provider configuration found") - if not openai_key: - logger.warning(" Missing OPENAI_API_KEY (required for memory processing)") - - def start_services(self): - """Start all services using docker compose.""" - logger.info("🚀 Starting services with docker compose...") - - # Change to backend directory - os.chdir(tests_dir.parent) - - # Clean up test data directories first (unless cached) - self.cleanup_test_data() - - try: - # Check if test services are already running - check_result = subprocess.run(["docker", "compose", "-f", "docker-compose-test.yml", "ps", "-q"], capture_output=True, text=True) - running_services = check_result.stdout.strip().split('\n') if check_result.stdout.strip() else [] - - if len(running_services) > 0 and not self.rebuild: - logger.info(f"🔄 Found {len(running_services)} running test services") - # Check if test backend is healthy (only skip if not rebuilding) - try: - health_check = subprocess.run(["docker", "compose", "-f", "docker-compose-test.yml", "ps", "friend-backend-test"], capture_output=True, text=True) - if "healthy" in health_check.stdout or "Up" in health_check.stdout: - logger.info("✅ Test services already running and healthy, skipping restart") - self.services_started = True - self.services_started_by_test = True # We'll manage test services - return - except: - pass - elif self.rebuild: - logger.info("🔨 Rebuild flag is True, will rebuild containers with latest code") - - logger.info("🔄 Need to start/restart test services...") - - # Handle container management based on rebuild and cached flags - if self.rebuild: - logger.info("🔨 Rebuild mode: stopping containers and rebuilding with latest code...") - # Stop existing test services and remove volumes for fresh rebuild - subprocess.run(["docker", "compose", "-f", "docker-compose-test.yml", "down", "-v"], capture_output=True) - elif not self.fresh_run: - logger.info("🔄 Reuse mode: restarting existing containers...") - subprocess.run(["docker", "compose", "-f", "docker-compose-test.yml", "restart"], capture_output=True) - else: - logger.info("🔄 Fresh mode: stopping containers and removing volumes...") - # Stop existing test services and remove volumes for fresh start - subprocess.run(["docker", "compose", "-f", "docker-compose-test.yml", "down", "-v"], capture_output=True) - - # Ensure memory_config.yaml exists by copying from template - memory_config_path = "memory_config.yaml" - memory_template_path = "memory_config.yaml.template" - if not os.path.exists(memory_config_path) and os.path.exists(memory_template_path): - logger.info(f"📋 Creating {memory_config_path} from template...") - shutil.copy2(memory_template_path, memory_config_path) - - # Check if we're in CI environment - is_ci = os.environ.get("CI") == "true" or os.environ.get("GITHUB_ACTIONS") == "true" - - if is_ci: - # In CI, use simpler build process - logger.info("🤖 CI environment detected, using optimized build...") - if self.rebuild: - # Force rebuild in CI when rebuild flag is set with BuildKit disabled - env = os.environ.copy() - env['DOCKER_BUILDKIT'] = '0' - logger.info("🔨 Running Docker build command...") - build_result = subprocess.run(["docker", "compose", "-f", "docker-compose-test.yml", "build"], env=env) - if build_result.returncode != 0: - logger.error(f"❌ Build failed with exit code {build_result.returncode}") - raise RuntimeError("Docker compose build failed") - cmd = ["docker", "compose", "-f", "docker-compose-test.yml", "up", "-d", "--no-build"] - else: - # Local development - use rebuild flag to determine build behavior - if self.rebuild: - cmd = ["docker", "compose", "-f", "docker-compose-test.yml", "up", "--build", "-d"] - logger.info("🔨 Local rebuild: will rebuild containers with latest code") - else: - cmd = ["docker", "compose", "-f", "docker-compose-test.yml", "up", "-d"] - logger.info("🚀 Local start: using existing container images") - - # Start test services with BuildKit disabled to avoid bake issues - env = os.environ.copy() - env['DOCKER_BUILDKIT'] = '0' - logger.info(f"🚀 Running Docker compose command: {' '.join(cmd)}") - result = subprocess.run(cmd, env=env, timeout=300) - - if result.returncode != 0: - logger.error(f"❌ Failed to start services with exit code {result.returncode}") - - # Check individual container logs for better error details - logger.error("🔍 Checking individual container logs for details...") - try: - container_logs_result = subprocess.run( - ["docker", "compose", "-f", "docker-compose-test.yml", "logs", "--tail=50"], - capture_output=True, text=True, timeout=15 - ) - if container_logs_result.stdout: - logger.error("📋 Container logs:") - logger.error(container_logs_result.stdout) - if container_logs_result.stderr: - logger.error("📋 Container logs stderr:") - logger.error(container_logs_result.stderr) - except Exception as e: - logger.warning(f"Could not fetch container logs: {e}") - - # Check container status - logger.error("🔍 Checking container status...") - try: - status_result = subprocess.run( - ["docker", "compose", "-f", "docker-compose-test.yml", "ps"], - capture_output=True, text=True, timeout=10 - ) - if status_result.stdout: - logger.error("📋 Container status:") - logger.error(status_result.stdout) - except Exception as e: - logger.warning(f"Could not fetch container status: {e}") - - # Fail fast - no retry attempts - raise RuntimeError("Docker compose failed to start") - - self.services_started = True - self.services_started_by_test = True # Mark that we started the services - logger.info("✅ Docker compose started successfully") - - except Exception as e: - logger.error(f"Error starting services: {e}") - raise - - def wait_for_services(self): - """Wait for all services to be ready with comprehensive health checks.""" - logger.info("🔍 Performing comprehensive service health validation...") - - start_time = time.time() - services_status = { - "backend": False, - "mongo": False, - "auth": False, - "readiness": False - } - - while time.time() - start_time < MAX_STARTUP_WAIT: - try: - # 1. Check backend basic health - if not services_status["backend"]: - try: - health_response = requests.get(f"{BACKEND_URL}/health", timeout=5) - if health_response.status_code == 200: - logger.info("✓ Backend health check passed") - services_status["backend"] = True - elif health_response.status_code >= 500: - raise RuntimeError(f"Backend service error: HTTP {health_response.status_code}") - elif health_response.status_code >= 400: - logger.warning(f"Backend client error: HTTP {health_response.status_code}") - except requests.exceptions.RequestException: - pass - - # 2. Check MongoDB connection via backend health check - if not services_status["mongo"] and services_status["backend"]: - try: - health_response = requests.get(f"{BACKEND_URL}/health", timeout=5) - if health_response.status_code == 200: - data = health_response.json() - mongo_health = data.get("services", {}).get("mongodb", {}) - if mongo_health.get("healthy", False): - logger.info("✓ MongoDB connection validated via backend health check") - services_status["mongo"] = True - except Exception: - pass - - # 3. Check comprehensive readiness (includes Qdrant validation) - if not services_status["readiness"] and services_status["backend"] and services_status["auth"]: - try: - readiness_response = requests.get(f"{BACKEND_URL}/readiness", timeout=5) - if readiness_response.status_code == 200: - data = readiness_response.json() - logger.info(f"📋 Readiness report: {json.dumps(data, indent=2)}") - - # Validate readiness data - backend validates Qdrant internally - if data.get("status") in ["healthy", "ready"]: - logger.info("✓ Backend reports all services ready (including Qdrant)") - services_status["readiness"] = True - elif data.get("status") == "unhealthy": - raise RuntimeError(f"Backend reports unhealthy status: {data}") - else: - logger.warning(f"⚠️ Backend readiness check not fully healthy: {data}") - elif readiness_response.status_code >= 500: - raise RuntimeError(f"Backend readiness error: HTTP {readiness_response.status_code}") - elif readiness_response.status_code >= 400: - logger.warning(f"Backend readiness client error: HTTP {readiness_response.status_code}") - - except requests.exceptions.RequestException as e: - logger.debug(f"Readiness endpoint not ready yet: {e}") - - # 4. Check authentication endpoint - if not services_status["auth"] and services_status["backend"]: - try: - # Just check that the auth endpoint exists (will return error without credentials) - auth_response = requests.post(f"{BACKEND_URL}/auth/jwt/login", timeout=3) - # Expecting 422 (validation error) not connection error - if auth_response.status_code in [422, 400]: - logger.info("✓ Authentication endpoint accessible") - services_status["auth"] = True - except requests.exceptions.RequestException: - pass - - # 5. Final validation - all services ready - if all(services_status.values()): - logger.info("🎉 All services validated and ready!") - return True - - # Log current status - ready_services = [name for name, status in services_status.items() if status] - pending_services = [name for name, status in services_status.items() if not status] - - elapsed = time.time() - start_time - logger.info(f"⏳ Health check progress ({elapsed:.1f}s): ✓ {ready_services} | ⏳ {pending_services}") - - except Exception as e: - logger.warning(f"⚠️ Health check error: {e}") - - time.sleep(3) - - # Final status report - logger.error("❌ Service readiness timeout!") - failed_services = [] - for service, status in services_status.items(): - status_emoji = "✓" if status else "❌" - logger.error(f" {status_emoji} {service}: {'Ready' if status else 'Not ready'}") - if not status: - failed_services.append(service) - - # Check for cascade failures - if backend failed, everything else will fail - if not services_status["backend"]: - logger.error("💥 CRITICAL: Backend service failed - all dependent services will fail") - logger.error(" This indicates a fundamental infrastructure issue") - elif not services_status["mongo"]: - logger.error("💥 CRITICAL: MongoDB connection failed - memory and auth will not work") - elif not services_status["readiness"]: - logger.error("💥 WARNING: Readiness check failed - Qdrant or other dependencies may be down") - - raise TimeoutError(f"Services did not become ready in {MAX_STARTUP_WAIT}s. Failed services: {failed_services}") - - def authenticate(self): - """Authenticate and get admin token.""" - logger.info("🔑 Authenticating as admin...") - - # Always use test credentials for test environment - logger.info("Using test environment credentials") - admin_email = TEST_ENV_VARS["ADMIN_EMAIL"] - admin_password = TEST_ENV_VARS["ADMIN_PASSWORD"] - - logger.info(f"Authenticating with email: {admin_email}") - - auth_url = f"{BACKEND_URL}/auth/jwt/login" - - response = requests.post( - auth_url, - data={ - 'username': admin_email, - 'password': admin_password - }, - headers={'Content-Type': 'application/x-www-form-urlencoded'} - ) - - if response.status_code != 200: - logger.error(f"Authentication failed with {admin_email}") - logger.error(f"Response: {response.text}") - raise RuntimeError(f"Authentication failed: {response.text}") - - data = response.json() - self.token = data.get('access_token') - - if not self.token: - raise RuntimeError("No access token received") - - logger.info("✓ Authentication successful") - - def upload_test_audio(self): - """Upload test audio file and monitor processing.""" - # Use different audio file for parakeet provider (shorter for faster testing) - audio_path = TEST_AUDIO_PATH_PARAKEET if self.provider == "parakeet" else TEST_AUDIO_PATH - - logger.info(f"📤 Uploading test audio: {audio_path.name}") - - if not audio_path.exists(): - raise FileNotFoundError(f"Test audio file not found: {audio_path}") - - # Log audio file details - file_size = audio_path.stat().st_size - logger.info(f"📊 Audio file size: {file_size:,} bytes ({file_size / (1024*1024):.2f} MB)") - - # Upload file - with open(audio_path, 'rb') as f: - files = {'files': (audio_path.name, f, 'audio/wav')} - data = {'device_name': 'integration_test'} - headers = {'Authorization': f'Bearer {self.token}'} - - logger.info("📤 Sending upload request...") - response = requests.post( - f"{BACKEND_URL}/api/audio/upload", - files=files, - data=data, - headers=headers, - timeout=300 - ) - - logger.info(f"📤 Upload response status: {response.status_code}") - - if response.status_code != 200: - raise RuntimeError(f"Upload failed: {response.text}") - - result = response.json() - logger.info(f"📤 Upload response: {json.dumps(result, indent=2)}") - - # Extract client_id from response - client_id = result.get('client_id') - if not client_id: - raise RuntimeError("No client_id in upload response") - - logger.info(f"📤 Generated client_id: {client_id}") - return result # Return full response with job IDs - - def verify_processing_results(self, upload_response: dict): - """Verify that audio was processed correctly using job tracking.""" - client_id = upload_response.get('client_id') - files = upload_response.get('files', []) - - if not files: - raise RuntimeError("No files in upload response") - - file_info = files[0] - transcript_job_id = file_info.get('transcript_job_id') - conversation_id = file_info.get('conversation_id') - - logger.info(f"🔍 Verifying processing results:") - logger.info(f" - Client ID: {client_id}") - logger.info(f" - Conversation ID: {conversation_id}") - logger.info(f" - Transcript Job ID: {transcript_job_id}") - - # Wait for transcription job to complete - logger.info("🔍 Waiting for transcription job to complete...") - start_time = time.time() - job_complete = False - - while time.time() - start_time < 60: # Wait up to 60 seconds for transcription - try: - # Check job status via queue API - response = requests.get( - f"{BACKEND_URL}/api/queue/jobs/{transcript_job_id}", - headers={"Authorization": f"Bearer {self.token}"}, - timeout=10 - ) - - if response.status_code == 200: - job_data = response.json() - status = job_data.get("status") - - if status == "completed": - logger.info(f"✅ Transcription job completed successfully") - job_complete = True - break - elif status == "failed": - error = job_data.get("exc_info", "Unknown error") - logger.error(f"❌ Transcription job failed: {error}") - break - else: - logger.info(f"⏳ Job status: {status} ({time.time() - start_time:.1f}s)") - - else: - logger.warning(f"⚠️ Job status check returned {response.status_code}") - - except Exception as e: - logger.warning(f"⚠️ Error checking job status: {e}") - - time.sleep(5) - - if not job_complete: - raise AssertionError(f"Transcription job did not complete within 60 seconds. Last status: {status if 'status' in locals() else 'unknown'}") - - # Get the conversation via API - logger.info(f"🔍 Retrieving conversation...") - conversation = None - - try: - # Get conversations list - response = requests.get( - f"{BACKEND_URL}/api/conversations", - headers={"Authorization": f"Bearer {self.token}"}, - timeout=10 - ) - - if response.status_code == 200: - data = response.json() - conversations_list = data.get("conversations", []) - - # Find our conversation by conversation_id or client_id - for conv in conversations_list: - if conv.get('conversation_id') == conversation_id or conv.get('client_id') == client_id: - conversation = conv - logger.info(f"✅ Found conversation in list: {conv.get('conversation_id')}") - break - - if not conversation: - logger.error(f"❌ Conversation not found in list of {len(conversations_list)} conversations") - if conversations_list: - logger.error(f"📊 Available conversations: {[c.get('conversation_id') for c in conversations_list[:5]]}") - else: - # Fetch full conversation details (list endpoint excludes transcript for performance) - logger.info(f"🔍 Fetching full conversation details...") - detail_response = requests.get( - f"{BACKEND_URL}/api/conversations/{conversation['conversation_id']}", - headers={"Authorization": f"Bearer {self.token}"}, - timeout=10 - ) - - if detail_response.status_code == 200: - conversation = detail_response.json()["conversation"] - logger.info(f"✅ Retrieved full conversation details with transcript") - else: - logger.error(f"❌ Failed to fetch conversation details: {detail_response.status_code}") - logger.error(f"Response: {detail_response.text}") - - else: - logger.error(f"❌ Conversations API returned status: {response.status_code}") - logger.error(f"Response: {response.text}") - - except Exception as e: - logger.error(f"❌ Error retrieving conversations: {e}", exc_info=True) - - if not conversation: - raise AssertionError(f"No conversation found for conversation_id: {conversation_id}") - - logger.info(f"✓ Conversation found: {conversation['audio_uuid']}") - - # Log conversation details - logger.info("📋 Conversation details:") - logger.info(f" - Audio UUID: {conversation['audio_uuid']}") - logger.info(f" - Client ID: {conversation.get('client_id')}") - logger.info(f" - Audio Path: {conversation.get('audio_path', 'N/A')}") - logger.info(f" - Timestamp: {conversation.get('timestamp', 'N/A')}") - - # Verify transcription (transcript is a string, segments is an array) - transcription = conversation.get('transcript', '') - segments = conversation.get('segments', []) - - logger.info(f"📝 Transcription details:") - logger.info(f" - Transcript length: {len(transcription)} characters") - logger.info(f" - Word count: {len(transcription.split()) if transcription else 0}") - logger.info(f" - Speaker segments: {len(segments)}") - - if transcription: - # Show first 200 characters of transcription - preview = transcription[:200] + "..." if len(transcription) > 200 else transcription - logger.info(f" - Preview: {preview}") - - # Load expected transcript for comparison - expected_transcript = self.load_expected_transcript() - logger.info(f" - Expected transcript length: {len(expected_transcript)} characters") - - # Log first 200 characters for comparison - logger.info(f" - Actual start: {transcription[:200]}...") - if expected_transcript: - logger.info(f" - Expected start: {expected_transcript[:200]}...") - - # Call OpenAI to verify transcript similarity - if os.environ.get("OPENAI_API_KEY") and expected_transcript: - similarity_result = self.check_transcript_similarity_simple(transcription, expected_transcript) - logger.info(f" - AI similarity assessment:") - logger.info(f" • Similar: {similarity_result.get('similar', 'unknown')}") - logger.info(f" • Reason: {similarity_result.get('reason', 'No reason provided')}") - - # Store result for validation - self.transcript_similarity_result = similarity_result - elif not expected_transcript: - logger.warning("⚠️ No expected transcript available for comparison") - self.transcript_similarity_result = None - else: - logger.error("❌ No transcription found") - - # Verify conversation has required fields - assert conversation.get('transcript'), "Conversation missing transcript" - assert len(conversation['transcript']) > 0, "Transcript is empty" - assert transcription.strip(), "Transcription text is empty" - - # Check for memory extraction (if LLM is configured) - if os.environ.get("OPENAI_API_KEY"): - logger.info("🧠 Checking for memory extraction...") - - # Check debug tracker for memory processing - response = requests.get( - f"{BACKEND_URL}/metrics", - headers={'Authorization': f'Bearer {self.token}'} - ) - - if response.status_code == 200: - metrics = response.json() - logger.info(f"📊 System metrics: {json.dumps(metrics, indent=2)}") - - logger.info("✅ Processing verification complete") - - return conversation, transcription - - def validate_memory_extraction(self, upload_response: dict): - """Validate that memory extraction worked correctly.""" - client_id = upload_response.get('client_id') - files = upload_response.get('files', []) - - logger.info(f"🧠 Validating memory extraction for client: {client_id}") - - # Get memory job ID from upload response - memory_job_id = files[0].get('memory_job_id') if files else None - if not memory_job_id: - raise RuntimeError("No memory_job_id in upload response") - - # Wait for memory processing to complete - client_memories = self.wait_for_memory_processing(memory_job_id, client_id) - - # Check if we're using OpenMemory MCP provider - memory_provider = os.environ.get("MEMORY_PROVIDER", "chronicle") - - if not client_memories: - if memory_provider == "openmemory_mcp": - # For OpenMemory MCP, check if there are any memories at all (deduplication is OK) - all_memories = self.get_memories_from_api() - if all_memories: - logger.info(f"✅ OpenMemory MCP: Found {len(all_memories)} existing memories (deduplication successful)") - client_memories = all_memories # Use existing memories for validation - else: - raise AssertionError("No memories found in OpenMemory MCP - memory processing failed") - else: - raise AssertionError("No memories were extracted - memory processing failed") - - logger.info(f"✅ Found {len(client_memories)} memories") - - # Load expected memories and compare - expected_memories = self.load_expected_memories() - if not expected_memories: - logger.warning("⚠️ No expected memories available for comparison") - return client_memories - - # Use OpenAI to check if memories are similar - if os.environ.get("OPENAI_API_KEY"): - memory_similarity = self.check_memory_similarity_simple(client_memories, expected_memories) - logger.info(f"🧠 Memory similarity assessment:") - logger.info(f" • Similar: {memory_similarity.get('similar', 'unknown')}") - logger.info(f" • Reason: {memory_similarity.get('reason', 'No reason provided')}") - - # Store result for validation - self.memory_similarity_result = memory_similarity - else: - logger.warning("⚠️ No OpenAI API key available for memory comparison") - self.memory_similarity_result = None - - return client_memories - - def check_transcript_similarity_simple(self, actual_transcript: str, expected_transcript: str) -> dict: - """Use OpenAI to check transcript similarity with simple boolean response.""" - try: - - client = openai.OpenAI(api_key=os.environ.get("OPENAI_API_KEY")) - - prompt = f""" - Compare these two transcripts to determine if they represent the same audio content. - - EXPECTED TRANSCRIPT: - "{expected_transcript}" - - ACTUAL TRANSCRIPT: - "{actual_transcript}" - - **MARK AS SIMILAR if:** - - Core content and topics match (e.g., glass blowing class, participants, activities) - - Key facts and events are present in both (names, numbers, objects, actions) - - Overall narrative flow is recognizable - - At least 70% semantic overlap exists - - **ACCEPTABLE DIFFERENCES (still mark as similar):** - - Minor word variations or ASR errors - - Different punctuation or capitalization - - Missing or extra filler words - - Small sections missing or repeated - - Slightly different word order - - Speaker diarization differences - - **ONLY MARK AS DISSIMILAR if:** - - Core content is fundamentally different - - Major sections (>30%) are missing or wrong - - It appears to be a different audio file entirely - - Respond in JSON format: - {{ - "reason": "brief explanation (1-3 sentences)" - "similar": true/false, - }} - """ - - response = client.chat.completions.create( - model="gpt-4o-mini", - messages=[{"role": "user", "content": prompt}], - response_format={"type": "json_object"} - ) - - response_text = (response.choices[0].message.content or "").strip() - - # Try to parse JSON response - try: - result = json.loads(response_text) - return result - except json.JSONDecodeError: - # If JSON parsing fails, return a basic result - return { - "similar": False, - "reason": f"Could not parse response: {response_text}" - } - - except Exception as e: - logger.warning(f"⚠️ Could not check transcript similarity: {e}") - return { - "similar": False, - "reason": f"API call failed: {str(e)}" - } - - def check_memory_similarity_simple(self, actual_memories: list, expected_memories: list) -> dict: - """Use OpenAI to check if extracted memories are similar to expected memories.""" - try: - import openai - - client = openai.OpenAI(api_key=os.environ.get("OPENAI_API_KEY")) - - # Extract just the memory text from actual memories - actual_memory_texts = [mem.get('memory', '') for mem in actual_memories] - - prompt = f""" - Compare these two lists of memories to determine if they represent content from the same audio source and indicate successful memory extraction. - - **KEY CRITERIA FOR SIMILARITY (Return "similar": true if ANY of these are met):** - - 1. **Topic/Context Match**: Both lists should be about the same main activity/event (e.g., glass blowing class) - 2. **Core Facts Overlap**: At least 3-4 significant factual details should overlap (people, places, numbers, objects) - 3. **Semantic Coverage**: The same general knowledge should be captured, even if from different perspectives - - **ACCEPTABLE DIFFERENCES (Do NOT mark as dissimilar for these):** - - Different focus areas (one list more personal/emotional, other more technical/factual) - - Different level of detail (one more granular, other more high-level) - - Different speakers/participants emphasized - - Different organization or memory chunking - - Emotional vs factual framing of the same events - - Missing some details in either list (as long as core overlap exists) - - **MARK AS DISSIMILAR ONLY IF:** - - The memories seem to be from completely different audio/conversations - - No meaningful factual overlap (suggests wrong audio or major transcription failure) - - Core subject matter is entirely different - - **EVALUATION APPROACH:** - 1. Identify overlapping factual elements (people, places, objects, numbers, activities) - 2. Count significant semantic overlaps - 3. If 3+ substantial overlaps exist AND same general topic/context → mark as similar - 4. Focus on "are these from the same source" rather than "are these identical" - - EXPECTED MEMORIES: - {expected_memories} - - EXTRACTED MEMORIES: - {actual_memory_texts} - - Respond in JSON format with: - {{ - "reasoning": "detailed analysis of overlapping elements and why they indicate same/different source", - "reason": "brief explanation of the decision", - "similar": true/false - }} - """ - - logger.info(f"Making GPT-5-mini API call for memory similarity...") - response = client.chat.completions.create( - model="gpt-4o-mini", - messages=[{"role": "user", "content": prompt}], - response_format={"type": "json_object"} - ) - - response_text = (response.choices[0].message.content or "").strip() - logger.info(f"Memory similarity GPT-5-mini response: '{response_text}'") - - try: - result = json.loads(response_text) - return result - except json.JSONDecodeError as json_err: - # If JSON parsing fails, return a basic result - logger.error(f"JSON parsing failed: {json_err}") - logger.error(f"Response text that failed to parse: '{response_text}'") - return { - "reason": f"Could not parse response: {response_text}", - "similar": False, - } - - except Exception as e: - logger.error(f"⚠️ Could not check memory similarity: {e}") - logger.error(f"Exception type: {type(e)}") - logger.error(f"Exception details: {str(e)}") - return { - "similar": False, - "reason": f"API call failed: {str(e)}" - } - - def get_memories_from_api(self) -> list: - """Fetch memories from the backend API.""" - try: - headers = {'Authorization': f'Bearer {self.token}'} - response = requests.get(f"{BACKEND_URL}/api/memories", headers=headers) - - if response.status_code == 200: - data = response.json() - return data.get('memories', []) - else: - logger.error(f"Failed to fetch memories: {response.status_code} - {response.text}") - return [] - except Exception as e: - logger.error(f"Error fetching memories: {e}") - return [] - - def wait_for_memory_processing(self, memory_job_id: str, client_id: str, timeout: int = 120): - """Wait for memory processing to complete using queue API.""" - logger.info(f"⏳ Waiting for memory job {memory_job_id} to complete...") - - start_time = time.time() - job_complete = False - - while time.time() - start_time < timeout: - try: - # Check job status via queue API - response = requests.get( - f"{BACKEND_URL}/api/queue/jobs/{memory_job_id}", - headers={"Authorization": f"Bearer {self.token}"}, - timeout=10 - ) - - if response.status_code == 200: - job_data = response.json() - status = job_data.get("status") - - if status == "completed": - logger.info(f"✅ Memory job completed successfully") - job_complete = True - break - elif status == "failed": - error = job_data.get("exc_info", "Unknown error") - logger.error(f"❌ Memory job failed: {error}") - break - else: - logger.info(f"⏳ Memory job status: {status} ({time.time() - start_time:.1f}s)") - - else: - logger.warning(f"⚠️ Memory job status check returned {response.status_code}") - - except Exception as e: - logger.warning(f"⚠️ Error checking memory job status: {e}") - - time.sleep(5) - - if not job_complete: - raise AssertionError(f"Memory job did not complete within {timeout} seconds. Last status: {status if 'status' in locals() else 'unknown'}") - - # Now fetch the memories from the API - memories = self.get_memories_from_api() - - # Filter by client_id for test isolation in fresh mode, or get all user memories in reuse mode - if not self.fresh_run: - # In reuse mode, get all user memories (API already filters by user_id) - user_memories = memories - if user_memories: - logger.info(f"✅ Found {len(user_memories)} total user memories (reusing existing data)") - return user_memories - else: - # In fresh mode, filter by client_id for test isolation since we cleaned all data - client_memories = [mem for mem in memories if mem.get('metadata', {}).get('client_id') == client_id] - if client_memories: - logger.info(f"✅ Found {len(client_memories)} memories for client {client_id}") - return client_memories - - logger.warning(f"⚠️ No memories found after processing") - return [] - - async def create_chat_session(self, title: str = "Integration Test Session", description: str = "Testing memory integration") -> Optional[str]: - """Create a new chat session and return session ID.""" - logger.info(f"📝 Creating chat session: {title}") - - try: - response = requests.post( - f"{BACKEND_URL}/api/chat/sessions", - headers={"Authorization": f"Bearer {self.token}"}, - json={ - "title": title, - "description": description - }, - timeout=10 - ) - - if response.status_code == 200: - data = response.json() - session_id = data.get("session_id") - logger.info(f"✅ Chat session created: {session_id}") - return session_id - else: - logger.error(f"❌ Chat session creation failed: {response.status_code} - {response.text}") - return None - - except Exception as e: - logger.error(f"❌ Error creating chat session: {e}") - return None - - async def send_chat_message(self, session_id: str, message: str) -> dict: - """Send a message to chat session and parse response.""" - logger.info(f"💬 Sending message: {message}") - - try: - response = requests.post( - f"{BACKEND_URL}/api/chat/send", - headers={"Authorization": f"Bearer {self.token}"}, - json={ - "message": message, - "session_id": session_id - }, - timeout=30 - ) - - if response.status_code == 200: - # Parse SSE response - full_response = "" - memory_ids = [] - - for line in response.text.split('\n'): - if line.startswith('data: '): - try: - event_data = json.loads(line[6:]) - event_type = event_data.get("type") - - if event_type == "memory_context": - mem_ids = event_data.get("data", {}).get("memory_ids", []) - memory_ids.extend(mem_ids) - elif event_type == "content": - content = event_data.get("data", {}).get("content", "") - full_response += content - elif event_type == "done": - break - except json.JSONDecodeError: - pass - - logger.info(f"🤖 Response received ({len(full_response)} chars)") - if memory_ids: - logger.info(f"📚 Memories used: {len(memory_ids)} memory IDs") - - return { - "response": full_response, - "memories_used": memory_ids, - "success": True - } - else: - logger.error(f"❌ Chat message failed: {response.status_code} - {response.text}") - return {"success": False, "error": response.text} - - except Exception as e: - logger.error(f"❌ Error sending chat message: {e}") - return {"success": False, "error": str(e)} - - async def run_chat_conversation(self, session_id: str) -> bool: - """Run a test conversation with memory integration.""" - logger.info("🎭 Starting chat conversation test...") - - # Test messages designed to trigger memory retrieval - test_messages = [ - "Hello! I'm testing the chat system with memory integration.", - "What do you know about glass blowing? Have I mentioned anything about it?", - ] - - memories_used_total = [] - - for i, message in enumerate(test_messages, 1): - logger.info(f"📨 Message {i}/{len(test_messages)}") - result = await self.send_chat_message(session_id, message) - - if not result.get("success"): - logger.error(f"❌ Chat message {i} failed: {result.get('error')}") - return False - - # Track memory usage - memories_used = result.get("memories_used", []) - memories_used_total.extend(memories_used) - - # Small delay between messages - time.sleep(1) - - logger.info(f"✅ Chat conversation completed. Total memories used: {len(set(memories_used_total))}") - return True - - async def extract_memories_from_chat(self, session_id: str) -> dict: - """Extract memories from the chat session.""" - logger.info(f"🧠 Extracting memories from chat session: {session_id}") - - try: - response = requests.post( - f"{BACKEND_URL}/api/chat/sessions/{session_id}/extract-memories", - headers={"Authorization": f"Bearer {self.token}"}, - timeout=30 - ) - - if response.status_code == 200: - data = response.json() - if data.get("success"): - logger.info(f"✅ Memory extraction successful: {data.get('count', 0)} memories created") - return data - else: - logger.warning(f"⚠️ Memory extraction completed but no memories: {data.get('message', 'Unknown')}") - return data - else: - logger.error(f"❌ Memory extraction failed: {response.status_code} - {response.text}") - return {"success": False, "error": response.text} - - except Exception as e: - logger.error(f"❌ Error extracting memories from chat: {e}") - return {"success": False, "error": str(e)} - - def cleanup(self): - """Clean up test resources based on cached and rebuild flags.""" - logger.info("Cleaning up...") - - if self.mongo_client: - self.mongo_client.close() - - # Handle container cleanup based on cleanup_containers flag (rebuild flag doesn't affect cleanup) - if self.cleanup_containers and self.services_started_by_test: - logger.info("🔄 Cleanup mode: stopping test docker compose services...") - subprocess.run(["docker", "compose", "-f", "docker-compose-test.yml", "down", "-v"], capture_output=True) - logger.info("✓ Test containers stopped and volumes removed") - elif not self.cleanup_containers: - logger.info("🗂️ No cleanup: leaving containers running for debugging") - if self.rebuild: - logger.info(" (containers were rebuilt with latest code during this test)") - else: - logger.info("🔄 Test services were already running, leaving them as-is") - - logger.info("✓ Cleanup complete") - - -@pytest.fixture -def test_runner(): - """Pytest fixture for test runner.""" - runner = IntegrationTestRunner() - yield runner - runner.cleanup() - - -@pytest.mark.integration -def test_full_pipeline_integration(test_runner): - """Test the complete audio processing pipeline.""" - # Immediate output to confirm test is starting - print("🚀 TEST STARTING - test_full_pipeline_integration", flush=True) - sys.stdout.flush() - sys.stderr.flush() - - try: - # Test timing tracking - test_start_time = time.time() - phase_times = {} - - # Immediate logging to debug environment - print("=" * 80, flush=True) - print("🚀 STARTING INTEGRATION TEST", flush=True) - print("=" * 80, flush=True) - logger.info(f"Current working directory: {os.getcwd()}") - logger.info(f"Files in directory: {os.listdir('.')}") - logger.info(f"CI environment: {os.environ.get('CI', 'NOT SET')}") - logger.info(f"GITHUB_ACTIONS: {os.environ.get('GITHUB_ACTIONS', 'NOT SET')}") - sys.stdout.flush() - - # Phase 1: Environment setup - phase_start = time.time() - logger.info("📋 Phase 1: Setting up test environment...") - test_runner.setup_environment() - phase_times['env_setup'] = time.time() - phase_start - logger.info(f"✅ Environment setup completed in {phase_times['env_setup']:.2f}s") - - # Phase 2: Service startup - phase_start = time.time() - logger.info("🐳 Phase 2: Starting services...") - test_runner.start_services() - phase_times['service_startup'] = time.time() - phase_start - logger.info(f"✅ Service startup completed in {phase_times['service_startup']:.2f}s") - - # Phase 2b: ASR service startup (parakeet only) - phase_start = time.time() - logger.info(f"🎤 Phase 2b: Starting ASR services ({TRANSCRIPTION_PROVIDER} provider)...") - test_runner.start_asr_services() - phase_times['asr_startup'] = time.time() - phase_start - logger.info(f"✅ ASR service startup completed in {phase_times['asr_startup']:.2f}s") - - # Phase 3: Wait for services - phase_start = time.time() - logger.info("⏳ Phase 3: Waiting for services to be ready...") - test_runner.wait_for_services() - phase_times['service_readiness'] = time.time() - phase_start - logger.info(f"✅ Service readiness check completed in {phase_times['service_readiness']:.2f}s") - - # Phase 3b: Wait for ASR services (parakeet only) - phase_start = time.time() - logger.info("⏳ Phase 3b: Waiting for ASR services to be ready...") - test_runner.wait_for_asr_ready() - phase_times['asr_readiness'] = time.time() - phase_start - logger.info(f"✅ ASR readiness check completed in {phase_times['asr_readiness']:.2f}s") - - # Phase 4: Authentication - phase_start = time.time() - logger.info("🔑 Phase 4: Authentication...") - test_runner.authenticate() - phase_times['authentication'] = time.time() - phase_start - logger.info(f"✅ Authentication completed in {phase_times['authentication']:.2f}s") - - # Phase 5: Audio upload and processing - phase_start = time.time() - logger.info("📤 Phase 5: Audio upload...") - upload_response = test_runner.upload_test_audio() - client_id = upload_response.get('client_id') - phase_times['audio_upload'] = time.time() - phase_start - logger.info(f"✅ Audio upload completed in {phase_times['audio_upload']:.2f}s") - - # Phase 6: Transcription processing - phase_start = time.time() - logger.info("🎤 Phase 6: Transcription processing...") - conversation, transcription = test_runner.verify_processing_results(upload_response) - phase_times['transcription_processing'] = time.time() - phase_start - logger.info(f"✅ Transcription processing completed in {phase_times['transcription_processing']:.2f}s") - - # Phase 7: Memory extraction - phase_start = time.time() - logger.info("🧠 Phase 7: Memory extraction...") - memories = test_runner.validate_memory_extraction(upload_response) - phase_times['memory_extraction'] = time.time() - phase_start - logger.info(f"✅ Memory extraction completed in {phase_times['memory_extraction']:.2f}s") - - # Phase 8: Chat with Memory Integration - # phase_start = time.time() - # logger.info("💬 Phase 8: Chat with Memory Integration...") - - # # Create chat session - # session_id = asyncio.run(test_runner.create_chat_session( - # title="Integration Test Chat", - # description="Testing chat functionality with memory retrieval" - # )) - # assert session_id is not None, "Failed to create chat session" - - # # Run chat conversation - # chat_success = asyncio.run(test_runner.run_chat_conversation(session_id)) - # assert chat_success, "Chat conversation failed" - - # # Extract memories from chat session (optional - may create additional memories) - # chat_memory_result = asyncio.run(test_runner.extract_memories_from_chat(session_id)) - - # phase_times['chat_integration'] = time.time() - phase_start - # logger.info(f"✅ Chat integration completed in {phase_times['chat_integration']:.2f}s") - - # Basic assertions - assert conversation is not None - assert len(conversation['transcript']) > 0 - assert transcription.strip() # Ensure we have actual text content - - # Transcript similarity assertion - if hasattr(test_runner, 'transcript_similarity_result') and test_runner.transcript_similarity_result: - assert test_runner.transcript_similarity_result.get('similar') == True, f"Transcript not similar enough: {test_runner.transcript_similarity_result.get('reason')}" - - # Memory validation assertions - assert memories is not None and len(memories) > 0, "No memories were extracted" - - # Memory similarity assertion - if hasattr(test_runner, 'memory_similarity_result') and test_runner.memory_similarity_result: - if test_runner.memory_similarity_result.get('similar') != True: - # Log transcript for debugging before failing - logger.error("=" * 80) - logger.error("❌ MEMORY SIMILARITY CHECK FAILED - DEBUGGING INFO") - logger.error("=" * 80) - logger.error("📝 Generated Transcript:") - logger.error("-" * 60) - logger.error(transcription) - logger.error("-" * 60) - - # Format detailed error with both memory sets - expected_memories = test_runner.load_expected_memories() - extracted_memories = [mem.get('memory', '') for mem in memories] - - error_msg = f""" -Memory similarity check failed: -Reason: {test_runner.memory_similarity_result.get('reason', 'No reason provided')} -Reasoning: {test_runner.memory_similarity_result.get('reasoning', 'No detailed reasoning provided')} - -Expected memories ({len(expected_memories)}): -{chr(10).join(f" {i+1}. {mem}" for i, mem in enumerate(expected_memories))} - -Extracted memories ({len(extracted_memories)}): -{chr(10).join(f" {i+1}. {mem}" for i, mem in enumerate(extracted_memories))} - -Generated Transcript ({len(transcription)} chars): -{transcription[:500]}{'...' if len(transcription) > 500 else ''} -""" - assert False, error_msg - - # Calculate total test time - total_test_time = time.time() - test_start_time - phase_times['total_test'] = total_test_time - - # Log success with detailed timing - logger.info("=" * 80) - logger.info("🎉 INTEGRATION TEST PASSED!") - logger.info("=" * 80) - logger.info(f"⏱️ TIMING BREAKDOWN:") - logger.info(f" 📋 Environment Setup: {phase_times['env_setup']:>6.2f}s") - logger.info(f" 🐳 Service Startup: {phase_times['service_startup']:>6.2f}s") - logger.info(f" ⏳ Service Readiness: {phase_times['service_readiness']:>6.2f}s") - logger.info(f" 🔑 Authentication: {phase_times['authentication']:>6.2f}s") - logger.info(f" 📤 Audio Upload: {phase_times['audio_upload']:>6.2f}s") - logger.info(f" 🎤 Transcription: {phase_times['transcription_processing']:>6.2f}s") - logger.info(f" 🧠 Memory Extraction: {phase_times['memory_extraction']:>6.2f}s") - # logger.info(f" 💬 Chat Integration: {phase_times['chat_integration']:>6.2f}s") - logger.info(f" {'─' * 35}") - logger.info(f" 🏁 TOTAL TEST TIME: {total_test_time:>6.2f}s ({total_test_time/60:.1f}m)") - logger.info("") - logger.info(f"📊 Test Results:") - logger.info(f" ✅ Audio file processed successfully") - logger.info(f" ✅ Transcription generated: {len(transcription)} characters") - logger.info(f" ✅ Word count: {len(transcription.split())}") - logger.info(f" ✅ Audio UUID: {conversation.get('audio_uuid')}") - logger.info(f" ✅ Client ID: {conversation.get('client_id')}") - logger.info(f" ✅ Memories extracted: {len(memories)}") - logger.info(f" ✅ Transcript similarity: {getattr(test_runner, 'transcript_similarity_result', {}).get('similar', 'N/A')}") - logger.info(f" ✅ Memory similarity: {getattr(test_runner, 'memory_similarity_result', {}).get('similar', 'N/A')}") - logger.info("") - logger.info("📝 Full Transcription:") - logger.info("-" * 60) - logger.info(transcription) - logger.info("-" * 60) - logger.info("") - logger.info("🧠 Extracted Memories:") - logger.info("-" * 60) - for i, memory in enumerate(memories[:10], 1): # Show first 10 memories - logger.info(f"{i}. {memory.get('memory', 'No content')}") - if len(memories) > 10: - logger.info(f"... and {len(memories) - 10} more memories") - logger.info("-" * 60) - logger.info("=" * 80) - - except Exception as e: - logger.error(f"Integration test failed: {e}") - raise - finally: - # Cleanup ASR services - test_runner.cleanup_asr_services() - - -if __name__ == "__main__": - # Run the test directly - pytest.main([__file__, "-v", "-s"]) \ No newline at end of file diff --git a/backends/advanced/tests/test_obsidian_service.py b/backends/advanced/tests/test_obsidian_service.py new file mode 100644 index 00000000..0daafc1a --- /dev/null +++ b/backends/advanced/tests/test_obsidian_service.py @@ -0,0 +1,204 @@ +import unittest +import asyncio +from unittest.mock import MagicMock, patch, AsyncMock +import sys +import os + +sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../src'))) + +from advanced_omi_backend.services.obsidian_service import ( + ObsidianService, + ObsidianSearchError, +) + +class TestObsidianService(unittest.TestCase): + + def setUp(self): + # Patch load_root_config + self.config_patcher = patch('advanced_omi_backend.services.obsidian_service.load_root_config') + self.mock_load_config = self.config_patcher.start() + self.mock_load_config.return_value = { + 'defaults': {'llm': 'gpt-4', 'embedding': 'text-embedding-3-small'}, + 'models': [ + {'name': 'gpt-4', 'model_url': 'https://api.openai.com/v1', 'api_key': 'sk-test'}, + {'name': 'text-embedding-3-small', 'model_name': 'text-embedding-3-small', 'embedding_dimensions': 1536, 'model_url': 'https://api.openai.com/v1', 'api_key': 'sk-test'} + ] + } + self.addCleanup(self.config_patcher.stop) + + # Patch embedding helper + self.embedding_patcher = patch( + 'advanced_omi_backend.services.obsidian_service.generate_openai_embeddings', + new_callable=AsyncMock + ) + self.mock_generate_embeddings = self.embedding_patcher.start() + self.addCleanup(self.embedding_patcher.stop) + + # Patch GraphDatabase + self.graph_db_patcher = patch('advanced_omi_backend.services.neo4j_client.GraphDatabase') + self.mock_graph_db = self.graph_db_patcher.start() + self.mock_driver = MagicMock() + self.mock_session = MagicMock() + self.mock_graph_db.driver.return_value = self.mock_driver + self.mock_driver.session.return_value.__enter__.return_value = self.mock_session + self.addCleanup(self.graph_db_patcher.stop) + + # Patch environment variables + self.env_patcher = patch.dict(os.environ, { + "NEO4J_HOST": "localhost", + "NEO4J_USER": "neo4j", + "NEO4J_PASSWORD": "password" + }) + self.env_patcher.start() + self.addCleanup(self.env_patcher.stop) + + # Initialize Service + self.service = ObsidianService() + + def test_search_obsidian_success(self): + # Setup mock embedding response + mock_embedding = [0.1, 0.2, 0.3] + self.mock_generate_embeddings.return_value = [mock_embedding] + + # Setup mock Neo4j results + mock_record1 = { + 'source': 'Note1', + 'content': 'Content of chunk 1', + 'tags': ['tag1', 'tag2'], + 'outgoing_links': ['Note2'], + 'score': 0.95 + } + mock_record2 = { + 'source': 'Note2', + 'content': 'Content of chunk 2', + 'tags': [], + 'outgoing_links': [], + 'score': 0.90 + } + + # The session.run returns an iterable of records + self.mock_session.run.return_value = [mock_record1, mock_record2] + + # Execute search + response = asyncio.run(self.service.search_obsidian("test query", limit=2)) + + # Assertions + # 1. Check embedding call + self.mock_generate_embeddings.assert_awaited_once() + + # 2. Check Neo4j query execution + self.mock_session.run.assert_called_once() + args, kwargs = self.mock_session.run.call_args + self.assertIn("CALL db.index.vector.queryNodes", args[0]) + self.assertEqual(kwargs['vector'], mock_embedding) + self.assertEqual(kwargs['limit'], 2) + + # 3. Check results formatting + self.assertEqual(len(response['results']), 2) + + # Check first result format + first_entry = response['results'][0] + self.assertIn("SOURCE: Note1", first_entry) + self.assertIn("TAGS: tag1, tag2", first_entry) + self.assertIn("RELATED NOTES: Note2", first_entry) + self.assertIn("CONTENT: Content of chunk 1", first_entry) + + def test_setup_database(self): + self.service.setup_database() + + # Verify constraints and index creation calls + self.assertTrue(self.mock_session.run.called) + # It should run at least 3 queries: Note constraint, Chunk constraint, Vector Index + self.assertGreaterEqual(self.mock_session.run.call_count, 3) + + calls = [call[0][0] for call in self.mock_session.run.call_args_list] + self.assertTrue(any("CREATE CONSTRAINT note_path" in c for c in calls)) + self.assertTrue(any("CREATE CONSTRAINT chunk_id" in c for c in calls)) + self.assertTrue(any("CREATE VECTOR INDEX chunk_embeddings" in c for c in calls)) + + @patch('advanced_omi_backend.services.obsidian_service.chunk_text_with_spacy') + def test_chunking_and_embedding_uses_shared_chunker(self, mock_chunker): + mock_chunker.return_value = ["part1"] + self.mock_generate_embeddings.return_value = [[0.1, 0.2]] + note_data = { + "path": "x", + "name": "n", + "folder": "f", + "content": "sample", + "wordcount": 1, + "links": [], + "tags": [], + } + chunks = asyncio.run(self.service.chunking_and_embedding(note_data)) + mock_chunker.assert_called_once_with("sample", max_tokens=self.service.chunk_word_limit) + self.mock_generate_embeddings.assert_awaited_once() + self.assertEqual(len(chunks), 1) + + def test_ingest_note_and_chunks(self): + note_data = { + "path": "test/note.md", + "name": "note", + "folder": "test", + "content": "some content", + "wordcount": 2, + "links": ["OtherNote"], + "tags": ["tag1"] + } + chunks = [ + {"text": "chunk1", "embedding": [0.1, 0.2]} + ] + + self.service.ingest_note_and_chunks(note_data, chunks) + + # Verify DB calls + # 1. Note + Folder merge + # 2. Chunk merge + # 3. Tag merge + # 4. Link merge + self.assertGreaterEqual(self.mock_session.run.call_count, 4) + + calls = [call[0][0] for call in self.mock_session.run.call_args_list] + self.assertTrue(any("MERGE (f:Folder" in c for c in calls)) + self.assertTrue(any("MERGE (c:Chunk" in c for c in calls)) + self.assertTrue(any("MERGE (t:Tag" in c for c in calls)) + self.assertTrue(any("MATCH (source:Note" in c for c in calls)) + + def test_search_obsidian_embedding_fail(self): + # Mock embedding failure (raises exception) + self.mock_generate_embeddings.side_effect = Exception("API Error") + + with self.assertRaises(ObsidianSearchError) as ctx: + asyncio.run(self.service.search_obsidian("test query")) + + self.assertEqual(ctx.exception.stage, "embedding") + self.assertIn("API Error", str(ctx.exception)) + self.mock_session.run.assert_not_called() + + def test_search_obsidian_db_fail(self): + # Setup mock embedding + mock_embedding = [0.1] + self.mock_generate_embeddings.return_value = [mock_embedding] + + # Mock DB failure + self.mock_session.run.side_effect = Exception("DB Connection Failed") + + with self.assertRaises(ObsidianSearchError) as ctx: + asyncio.run(self.service.search_obsidian("test query")) + + self.assertEqual(ctx.exception.stage, "database") + self.assertIn("DB Connection Failed", str(ctx.exception)) + + def test_search_obsidian_empty_results(self): + # Setup mock embedding + mock_embedding = [0.1] + self.mock_generate_embeddings.return_value = [mock_embedding] + + # Mock empty DB results + self.mock_session.run.return_value = [] + + response = asyncio.run(self.service.search_obsidian("test query")) + + self.assertEqual(response['results'], []) + +if __name__ == '__main__': + unittest.main() diff --git a/backends/advanced/uv.lock b/backends/advanced/uv.lock index 5d22a254..c73386c8 100644 --- a/backends/advanced/uv.lock +++ b/backends/advanced/uv.lock @@ -1,8 +1,9 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.12" resolution-markers = [ - "python_full_version >= '3.13'", + "python_full_version >= '3.14'", + "python_full_version == '3.13.*'", "python_full_version < '3.13'", ] @@ -18,10 +19,15 @@ dependencies = [ { name = "fastapi-users", extra = ["beanie"] }, { name = "fastmcp" }, { name = "friend-lite-sdk" }, + { name = "google-api-python-client" }, + { name = "google-auth-httplib2" }, + { name = "google-auth-oauthlib" }, + { name = "httpx" }, { name = "langchain-neo4j" }, { name = "langfuse" }, { name = "mem0ai" }, { name = "motor" }, + { name = "neo4j" }, { name = "ollama" }, { name = "python-dotenv" }, { name = "pyyaml" }, @@ -72,10 +78,15 @@ requires-dist = [ { name = "fastapi-users", extras = ["beanie"], specifier = ">=14.0.1" }, { name = "fastmcp", specifier = ">=0.5.0" }, { name = "friend-lite-sdk" }, + { name = "google-api-python-client", specifier = ">=2.0.0" }, + { name = "google-auth-httplib2", specifier = ">=0.2.0" }, + { name = "google-auth-oauthlib", specifier = ">=1.0.0" }, + { name = "httpx", specifier = ">=0.28.0,<1.0.0" }, 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upload-time = "2025-09-14T22:18:19.088Z" }, ] diff --git a/backends/advanced/webui/README.md b/backends/advanced/webui/README.md index 303b2780..9642eb7e 100644 --- a/backends/advanced/webui/README.md +++ b/backends/advanced/webui/README.md @@ -57,7 +57,7 @@ A modern React-based web interface for the Chronicle AI-powered personal audio s 4. **Start backend services:** ```bash cd ../ - docker compose up friend-backend mongo qdrant + docker compose up chronicle-backend mongo qdrant ``` ### Docker Development @@ -70,7 +70,7 @@ docker compose --profile dev up ``` This starts: -- Backend services (friend-backend, mongo, qdrant) +- Backend services (chronicle-backend, mongo, qdrant) - React dev server with hot reload (http://localhost:5173) ## Production Deployment @@ -79,7 +79,7 @@ This starts: ```bash cd backends/advanced -docker compose up webui friend-backend mongo qdrant +docker compose up webui chronicle-backend mongo qdrant ``` The production build will be available at http://localhost:3000 diff --git a/backends/advanced/webui/src/components/MemorySettings.tsx b/backends/advanced/webui/src/components/MemorySettings.tsx index d01a84ea..ca16e94f 100644 --- a/backends/advanced/webui/src/components/MemorySettings.tsx +++ b/backends/advanced/webui/src/components/MemorySettings.tsx @@ -1,6 +1,7 @@ import { useState, useEffect } from 'react' import { Brain, RefreshCw, CheckCircle, Trash2, Save, RotateCcw, AlertCircle } from 'lucide-react' import { systemApi, memoriesApi } from '../services/api' +import { useAuth } from '../contexts/AuthContext' interface MemorySettingsProps { className?: string @@ -14,6 +15,7 @@ export default function MemorySettings({ className }: MemorySettingsProps) { const [deleting, setDeleting] = useState(false) const [message, setMessage] = useState('') const [error, setError] = useState('') + const { isAdmin } = useAuth() useEffect(() => { loadMemoryConfig() @@ -30,7 +32,14 @@ export default function MemorySettings({ className }: MemorySettingsProps) { setMessage('Configuration loaded successfully') setTimeout(() => setMessage(''), 3000) } catch (err: any) { - setError(err.response?.data?.error || 'Failed to load memory configuration') + const status = err.response?.status + if (status === 401) { + setError('Unauthorized: admin privileges required to load memory configuration') + } else if (status === 404 || status === 405) { + setError('Backend does not expose memory configuration endpoints') + } else { + setError(err.response?.data?.error || 'Failed to load memory configuration') + } } finally { setLoading(false) } @@ -122,6 +131,10 @@ export default function MemorySettings({ className }: MemorySettingsProps) { } } + if (!isAdmin) { + return null + } + return (
@@ -194,6 +207,12 @@ export default function MemorySettings({ className }: MemorySettingsProps) { />

Edit the YAML configuration directly. Changes will be validated before saving and hot-reloaded without service restart. + {error && (error.includes('does not expose') || error.includes('Unauthorized')) && ( + <> + {' '} + Ensure the backend has memory config endpoints and you are logged in as an admin. + + )}

@@ -202,7 +221,7 @@ export default function MemorySettings({ className }: MemorySettingsProps) {
) -} \ No newline at end of file +} diff --git a/backends/advanced/webui/src/pages/Chat.tsx b/backends/advanced/webui/src/pages/Chat.tsx index f696518a..5b3303d7 100644 --- a/backends/advanced/webui/src/pages/Chat.tsx +++ b/backends/advanced/webui/src/pages/Chat.tsx @@ -44,6 +44,7 @@ export default function Chat() { const [showMemoryPanel, setShowMemoryPanel] = useState(false) const [isExtractingMemories, setIsExtractingMemories] = useState(false) const [extractionMessage, setExtractionMessage] = useState('') + const [includeObsidian, setIncludeObsidian] = useState(false) // Refs const messagesEndRef = useRef(null) @@ -199,7 +200,7 @@ export default function Chat() { setMessages(prev => [...prev, userMessage]) // Send message and handle streaming response - const response = await chatApi.sendMessage(messageText, sessionId) + const response = await chatApi.sendMessage(messageText, sessionId, includeObsidian) if (!response.ok) { throw new Error(`HTTP error! status: ${response.status}`) @@ -515,6 +516,19 @@ export default function Chat() { + +
+ setIncludeObsidian(e.target.checked)} + className="h-4 w-4 text-blue-600 rounded border-gray-300 focus:ring-blue-500" + /> + +
) : ( diff --git a/backends/advanced/webui/src/pages/Upload.tsx b/backends/advanced/webui/src/pages/Upload.tsx index 04e7d24c..abc54b29 100644 --- a/backends/advanced/webui/src/pages/Upload.tsx +++ b/backends/advanced/webui/src/pages/Upload.tsx @@ -1,6 +1,6 @@ -import React, { useState, useCallback } from 'react' -import { Upload as UploadIcon, File, X, CheckCircle, AlertCircle, RefreshCw } from 'lucide-react' -import { uploadApi } from '../services/api' +import React, { useState, useCallback, useEffect } from 'react' +import { Upload as UploadIcon, File, X, CheckCircle, AlertCircle, RefreshCw, FolderPlus, PlayCircle, Archive } from 'lucide-react' +import { uploadApi, obsidianApi } from '../services/api' import { useAuth } from '../contexts/AuthContext' interface UploadFile { @@ -15,43 +15,89 @@ export default function Upload() { const [isUploading, setIsUploading] = useState(false) const [dragActive, setDragActive] = useState(false) const [uploadProgress, setUploadProgress] = useState(0) + const [gdriveFolderId, setGdriveFolderId] = useState('') const { isAdmin } = useAuth() const generateId = () => Math.random().toString(36).substr(2, 9) + const [gdriveUploadStatus, setGdriveUploadStatus] = useState<{ + type: 'success' | 'error' | null + message: string + }>({ + type: null, + message: '' + }) + + // Obsidian import state + const [obsidianZip, setObsidianZip] = useState(null) + const [obsidianUploadProgress, setObsidianUploadProgress] = useState(0) + const [obsidianJobId, setObsidianJobId] = useState(null) + const [obsidianStatus, setObsidianStatus] = useState(null) + const [obsidianPolling, setObsidianPolling] = useState(false) + const [obsidianMessage, setObsidianMessage] = useState('') + const [obsidianError, setObsidianError] = useState('') + + // Handle Google Drive folder submission + const handleGDriveSubmit = async () => { + if (!gdriveFolderId) return + + setIsUploading(true) + setGdriveUploadStatus({ type: null, message: '' }) + + try { + await uploadApi.uploadFromGDriveFolder({ + gdrive_folder_id: gdriveFolderId, + device_name: 'upload', + auto_generate_client: true, + }) + + setGdriveUploadStatus({ + type: 'success', + message: 'Google Drive folder submitted successfully.', + }) + + setGdriveFolderId('') + } catch (err: any) { + setGdriveUploadStatus({ + type: 'error', + message: err?.response?.data?.detail || 'Failed to upload folder.', + }) + } finally { + setIsUploading(false) + } + } + const handleFileSelect = (selectedFiles: FileList | null) => { if (!selectedFiles) return - const audioFiles = Array.from(selectedFiles).filter(file => - file.type.startsWith('audio/') || - file.name.toLowerCase().endsWith('.wav') || - file.name.toLowerCase().endsWith('.mp3') || - file.name.toLowerCase().endsWith('.m4a') || - file.name.toLowerCase().endsWith('.flac') + const audioFiles = Array.from(selectedFiles).filter( + (file) => + file.type.startsWith('audio/') || + file.name.toLowerCase().endsWith('.wav') || + file.name.toLowerCase().endsWith('.mp3') || + file.name.toLowerCase().endsWith('.m4a') || + file.name.toLowerCase().endsWith('.flac') ) - const newFiles: UploadFile[] = audioFiles.map(file => ({ + const newFiles: UploadFile[] = audioFiles.map((file) => ({ file, id: generateId(), - status: 'pending' + status: 'pending', })) - setFiles(prevFiles => [...prevFiles, ...newFiles]) + setFiles((prev) => [...prev, ...newFiles]) } const removeFile = (id: string) => { - setFiles(files.filter(f => f.id !== id)) + setFiles(files.filter((f) => f.id !== id)) } const handleDrag = useCallback((e: React.DragEvent) => { e.preventDefault() e.stopPropagation() - if (e.type === 'dragenter' || e.type === 'dragover') { - setDragActive(true) - } else if (e.type === 'dragleave') { - setDragActive(false) - } + if (e.type === 'dragenter' || e.type === 'dragover') setDragActive(true) + else if (e.type === 'dragleave') setDragActive(false) }, []) const handleDrop = useCallback((e: React.DragEvent) => { @@ -73,29 +119,25 @@ export default function Upload() { formData.append('files', file) }) - // Update all files to uploading status - setFiles(prevFiles => - prevFiles.map(f => ({ ...f, status: 'uploading' as const })) + setFiles((prev) => + prev.map((f) => ({ ...f, status: 'uploading' })) ) await uploadApi.uploadAudioFiles(formData, (progress) => { setUploadProgress(progress) }) - - // Mark all files as successful - setFiles(prevFiles => - prevFiles.map(f => ({ ...f, status: 'success' as const })) + + setFiles((prev) => + prev.map((f) => ({ ...f, status: 'success' })) ) + } catch (err: any) { + console.error('Upload failed:', err) - } catch (error: any) { - console.error('Upload failed:', error) - - // Mark all files as failed - setFiles(prevFiles => - prevFiles.map(f => ({ - ...f, - status: 'error' as const, - error: error.message || 'Upload failed' + setFiles((prev) => + prev.map((f) => ({ + ...f, + status: 'error', + error: err.message || 'Upload failed', })) ) } finally { @@ -104,8 +146,73 @@ export default function Upload() { } } + // Obsidian handlers + const handleObsidianZipSelect = (fileList: FileList | null) => { + const f = fileList?.[0] + if (!f) return + if (!f.name.toLowerCase().endsWith('.zip')) { + setObsidianError('Please select a .zip file containing your Obsidian vault') + return + } + setObsidianError('') + setObsidianZip(f) + setObsidianUploadProgress(0) + setObsidianJobId(null) + setObsidianStatus(null) + } + + const uploadObsidianZip = async () => { + if (!obsidianZip) return + setObsidianError('') + setObsidianMessage('') + setObsidianUploadProgress(0) + try { + const res = await obsidianApi.uploadZip(obsidianZip, (p) => setObsidianUploadProgress(p)) + setObsidianJobId(res.data.job_id) + setObsidianMessage(`Uploaded. Found ${res.data.total_files} notes. Click Start to ingest.`) + } catch (err: any) { + setObsidianError(err.response?.data?.detail || 'Failed to upload vault zip') + } + } + + const startObsidianIngestion = async () => { + if (!obsidianJobId) return + setObsidianError('') + setObsidianMessage('Starting ingestion...') + try { + await obsidianApi.start(obsidianJobId) + setObsidianPolling(true) + } catch (err: any) { + setObsidianError(err.response?.data?.detail || 'Failed to start ingestion') + } + } + + useEffect(() => { + let interval: number | undefined + if (obsidianPolling && obsidianJobId) { + const poll = async () => { + try { + const res = await obsidianApi.status(obsidianJobId) + setObsidianStatus(res.data) + if (res.data.status === 'completed' || res.data.status === 'failed') { + setObsidianPolling(false) + setObsidianMessage(res.data.status === 'completed' ? '✅ Ingestion completed' : `❌ Failed: ${res.data.error || 'unknown error'}`) + } + } catch (err) { + setObsidianPolling(false) + setObsidianError('Failed to fetch status') + } + } + poll() + interval = window.setInterval(poll, 1500) + } + return () => { + if (interval) window.clearInterval(interval) + } + }, [obsidianPolling, obsidianJobId]) + const clearCompleted = () => { - setFiles(files.filter(f => f.status === 'pending' || f.status === 'uploading')) + setFiles(files.filter((f) => f.status === 'pending' || f.status === 'uploading')) } const formatFileSize = (bytes: number) => { @@ -113,7 +220,7 @@ export default function Upload() { const k = 1024 const sizes = ['Bytes', 'KB', 'MB', 'GB'] const i = Math.floor(Math.log(bytes) / Math.log(k)) - return parseFloat((bytes / Math.pow(k, i)).toFixed(2)) + ' ' + sizes[i] + return `${(bytes / Math.pow(k, i)).toFixed(2)} ${sizes[i]}` } const getStatusIcon = (status: UploadFile['status']) => { @@ -153,6 +260,43 @@ export default function Upload() { + {/* Google Drive Folder Upload */} +
+ + +
+ setGdriveFolderId(e.target.value)} + placeholder="1AbCdEfGhIjKlMnOpQrStUvWxYz123456" + className="flex-1 px-3 py-2 border rounded-lg dark:bg-gray-800 dark:text-gray-100" + /> + + +
+ + {gdriveUploadStatus.type && ( +
+ {gdriveUploadStatus.message} +
+ )} +
+ {/* Drop Zone */}
Supported formats: WAV, MP3, M4A, FLAC

- + handleFileSelect(e.target.files)} className="absolute inset-0 w-full h-full opacity-0 cursor-pointer" /> - + @@ -199,14 +343,14 @@ export default function Upload() {
@@ -237,19 +381,24 @@ export default function Upload() {
- + {uploadFile.status.charAt(0).toUpperCase() + uploadFile.status.slice(1)} - + {uploadFile.status === 'pending' && ( @@ -291,12 +440,106 @@ export default function Upload() {
  • • Audio files will be processed sequentially for transcription and memory extraction
    • -
  • • Processing time varies based on audio length (roughly 3x the audio duration + 60s)
    • -
  • • Large files or multiple files may cause timeout errors - this is normal
    • -
  • • Check the Conversations tab to see processed results
    • +
  • • Processing time varies based on audio length (roughly 3× duration + 60s)
    • +
  • • Large files or multiple files may cause timeout errors
    • +
  • • Check the Conversations tab for processed results
  • • Supported formats: WAV, MP3, M4A, FLAC
+ + {/* Obsidian Vault Import */} + {isAdmin && ( +
+
+
+ +

Obsidian Vault Import

+
+
+ +

+ Upload a .zip of your Obsidian vault, then click Start to ingest notes into Neo4j. Progress will be shown below. +

+ + {/* Zip selector */} +
+ + + + + +
+ + {obsidianZip && ( +
Selected: {obsidianZip.name}
+ )} + + {/* Upload progress */} + {obsidianZip && obsidianUploadProgress > 0 && obsidianUploadProgress < 100 && ( +
+
+ Uploading vault... + {obsidianUploadProgress}% +
+
+
+
+
+ )} + + {/* Ingestion status */} + {obsidianStatus && ( +
+
+
Status: {obsidianStatus.status}
+
Processed: {obsidianStatus.processed}/{obsidianStatus.total} ({obsidianStatus.percent}%)
+
+
+
+
+ {obsidianStatus.last_file && ( +
Last file: {obsidianStatus.last_file}
+ )} + {obsidianStatus.errors?.length > 0 && ( +
+
Errors: {obsidianStatus.errors.length}
+
+ View first 10 errors +
    + {(obsidianStatus.errors.slice(0, 10) as string[]).map((e: string, idx: number) => ( +
  • {e}
    • + ))} +
+
+
+ )} +
+ )} + + {/* Messages */} + {obsidianMessage && ( +
{obsidianMessage}
+ )} + {obsidianError && ( +
{obsidianError}
+ )} +
+ )}
) -} \ No newline at end of file +} diff --git a/backends/advanced/webui/src/services/api.ts b/backends/advanced/webui/src/services/api.ts index 0d988a9d..36e6f5aa 100644 --- a/backends/advanced/webui/src/services/api.ts +++ b/backends/advanced/webui/src/services/api.ts @@ -164,7 +164,7 @@ export const systemApi = { headers: { 'Content-Type': 'text/plain' } }), validateMemoryConfig: (configYaml: string) => - api.post('/api/admin/memory/config/validate', configYaml, { + api.post('/api/admin/memory/config/validate/raw', configYaml, { headers: { 'Content-Type': 'text/plain' } }), reloadMemoryConfig: () => api.post('/api/admin/memory/config/reload'), @@ -204,7 +204,7 @@ export const queueApi = { } export const uploadApi = { - uploadAudioFiles: (files: FormData, onProgress?: (progress: number) => void) => + uploadAudioFiles: (files: FormData, onProgress?: (progress: number) => void) => api.post('/api/audio/upload', files, { headers: { 'Content-Type': 'multipart/form-data' }, timeout: 300000, // 5 minutes @@ -213,10 +213,40 @@ export const uploadApi = { const progress = Math.round((progressEvent.loaded * 100) / progressEvent.total) onProgress(progress) } - } + }, + }), + + uploadFromGDriveFolder: (payload: { gdrive_folder_id: string; device_name?: string; auto_generate_client?: boolean }) => + api.post('/api/audio/upload_audio_from_gdrive', null, { + params: { + gdrive_folder_id: payload.gdrive_folder_id, + device_name: payload.device_name, + auto_generate_client: payload.auto_generate_client, + }, + timeout: 300000, }), } +export const obsidianApi = { + uploadZip: (file: File, onProgress?: (progress: number) => void) => { + const form = new FormData() + form.append('file', file) + return api.post('/api/obsidian/upload_zip', form, { + headers: { 'Content-Type': 'multipart/form-data' }, + onUploadProgress: (e) => { + if (onProgress && e.total) { + onProgress(Math.round((e.loaded * 100) / e.total)) + } + }, + timeout: 300000, + }) + }, + start: (jobId: string) => api.post('/api/obsidian/start', { job_id: jobId }), + status: (jobId: string) => api.get('/api/obsidian/status', { params: { job_id: jobId } }), + cancel: (jobId: string) => api.post('/api/obsidian/cancel', { job_id: jobId }), +} + + export const chatApi = { // Session management createSession: (title?: string) => api.post('/api/chat/sessions', { title }), @@ -238,11 +268,14 @@ export const chatApi = { getHealth: () => api.get('/api/chat/health'), // Streaming chat (returns EventSource for Server-Sent Events) - sendMessage: (message: string, sessionId?: string) => { + sendMessage: (message: string, sessionId?: string, includeObsidianMemory?: boolean) => { const requestBody: any = { message } if (sessionId) { requestBody.session_id = sessionId } + if (includeObsidianMemory) { + requestBody.include_obsidian_memory = includeObsidianMemory + } return fetch(`${BACKEND_URL}/api/chat/send`, { method: 'POST', @@ -268,4 +301,4 @@ export const speakerApi = { // Check speaker service status (admin only) getSpeakerServiceStatus: () => api.get('/api/speaker-service-status'), -} \ No newline at end of file +} diff --git a/backends/simple/README.md b/backends/simple/README.md index 46908810..d9cb2c69 100644 --- a/backends/simple/README.md +++ b/backends/simple/README.md @@ -115,7 +115,7 @@ For full transcription and memory features, use the [Advanced Backend](../advanc ### Logs ```bash # View service logs -docker compose logs -f friend-backend +docker compose logs -f chronicle-backend # Check audio processing tail -f ./audio_chunks/ diff --git a/backends/simple/docker-compose.yml b/backends/simple/docker-compose.yml index 3581d650..8ae18950 100644 --- a/backends/simple/docker-compose.yml +++ b/backends/simple/docker-compose.yml @@ -1,5 +1,5 @@ services: - friend-backend: + chronicle-backend: build: context: . dockerfile: Dockerfile @@ -14,6 +14,6 @@ services: environment: - NGROK_AUTHTOKEN=${NGROK_AUTHTOKEN} - NGROK_DOMAIN=${NGROK_DOMAIN} - command: "http friend-backend:8000 --domain=${NGROK_DOMAIN}" + command: "http chronicle-backend:8000 --domain=${NGROK_DOMAIN}" depends_on: - - friend-backend + - chronicle-backend diff --git a/config.env.template b/config.env.template index b502e626..3312dfae 100644 --- a/config.env.template +++ b/config.env.template @@ -55,20 +55,11 @@ ADMIN_PASSWORD = ****** # LLM CONFIGURATION # ======================================== -# LLM Provider: openai, ollama, or groq -LLM_PROVIDER = openai +# LLM configuration is managed in config.yml (defaults.llm) +# Only API keys need to be set here # OpenAI configuration OPENAI_API_KEY = sk-xxxxx -OPENAI_BASE_URL = https://api.openai.com/v1 -OPENAI_MODEL = gpt-4o-mini - -# Ollama configuration (when LLM_PROVIDER=ollama) -OLLAMA_BASE_URL = http://ollama:11434 -OLLAMA_MODEL = llama3.1:latest - -# Chat-specific settings -CHAT_TEMPERATURE = 0.7 # ======================================== # SPEECH-TO-TEXT CONFIGURATION @@ -96,7 +87,7 @@ MONGODB_URI = mongodb://mongo:$(MONGODB_PORT) MONGODB_K8S_URI = mongodb://mongodb.$(INFRASTRUCTURE_NAMESPACE).svc.cluster.local:27017/friend # Qdrant URLs -QDRANT_BASE_URL = qdrant +# (Connection details managed in config.yml) QDRANT_K8S_URL = qdrant.$(INFRASTRUCTURE_NAMESPACE).svc.cluster.local # Neo4j configuration (optional) @@ -155,7 +146,7 @@ CORS_ORIGINS = http://$(DOMAIN):$(WEBUI_PORT),http://$(DOMAIN):3000,http://local VITE_ALLOWED_HOSTS = localhost 127.0.0.1 $(DOMAIN_PREFIX).$(DOMAIN) $(EXTERNAL_DOMAIN) $(SPEAKER_HOST) # Model configuration -CHAT_LLM_MODEL = $(OPENAI_MODEL) +# (Managed in config.yml) # ======================================== # OPTIONAL SERVICES @@ -173,10 +164,8 @@ LANGFUSE_ENABLE_TELEMETRY = false # Ngrok for external access NGROK_AUTHTOKEN = -# ======================================== -# AUDIO PROCESSING SETTINGS -# ======================================== - +# Audio processing settings +# (Managed in config.yml or hardcoded in constants) NEW_CONVERSATION_TIMEOUT_MINUTES = 1.5 AUDIO_CROPPING_ENABLED = true MIN_SPEECH_SEGMENT_DURATION = 1.0 diff --git a/config/README.md b/config/README.md new file mode 100644 index 00000000..e3a5cf3c --- /dev/null +++ b/config/README.md @@ -0,0 +1,106 @@ +# Chronicle Configuration + +This directory contains Chronicle's centralized configuration files. + +## Files + +- **`config.yml`** - Main configuration file (gitignored, user-specific) + - Contains model registry (LLM, STT, TTS, embeddings, vector store) + - Memory provider settings + - Service endpoints and API keys + +- **`config.yml.template`** - Template for new setups + - Use this to create your `config.yml` + - Contains placeholders with `${ENV_VAR:-default}` patterns + - No secrets included - safe to commit + +## Setup + +### First Time Setup + +```bash +# Option 1: Run the interactive wizard (recommended) +uv run --with-requirements setup-requirements.txt python wizard.py + +# Option 2: Manual setup +cp config/config.yml.template config/config.yml +# Edit config.yml to add your API keys and configure providers +``` + +### Environment Variable Substitution + +The config system supports environment variable substitution using `${VAR:-default}` syntax: + +```yaml +models: + - name: openai-llm + api_key: ${OPENAI_API_KEY:-} # Uses env var or empty string + model_url: ${OPENAI_BASE_URL:-https://api.openai.com/v1} # With fallback +``` + +## Configuration Sections + +### Defaults + +Specifies which models to use by default: + +```yaml +defaults: + llm: openai-llm # Default LLM model + embedding: openai-embed # Default embedding model + stt: stt-deepgram # Default speech-to-text + vector_store: vs-qdrant # Default vector database +``` + +### Models + +Array of model definitions - each model includes: +- `name`: Unique identifier +- `model_type`: llm, embedding, stt, tts, vector_store +- `model_provider`: openai, ollama, deepgram, parakeet, etc. +- `model_name`: Provider-specific model name +- `model_url`: API endpoint +- `api_key`: Authentication (use env vars!) +- `model_params`: Temperature, max_tokens, etc. + +### Memory + +Memory extraction and storage configuration: + +```yaml +memory: + provider: chronicle # chronicle, openmemory_mcp, or mycelia + timeout_seconds: 1200 + extraction: + enabled: true + prompt: "Custom extraction prompt..." +``` + +## Test Configurations + +For testing different provider combinations, see `tests/configs/`: +- These configs are version-controlled +- Use with `CONFIG_FILE` environment variable +- No secrets - only env var placeholders + +Example: +```bash +CONFIG_FILE=tests/configs/parakeet-ollama.yml ./backends/advanced/run-test.sh +``` + +## Hot Reload + +The memory configuration section supports hot reload - changes are picked up without service restart. Model registry changes require service restart. + +## Backups + +The setup wizard automatically backs up `config.yml` before making changes: +- Backups: `config.yml.backup.YYYYMMDD_HHMMSS` +- These are gitignored automatically + +## Documentation + +For detailed configuration guides, see: +- `/Docs/memory-configuration-guide.md` - Memory settings +- `/backends/advanced/Docs/quickstart.md` - Setup guide +- `/CLAUDE.md` - Project overview diff --git a/config/config.yml.template b/config/config.yml.template new file mode 100644 index 00000000..3670a6bb --- /dev/null +++ b/config/config.yml.template @@ -0,0 +1,219 @@ +defaults: + llm: openai-llm + embedding: openai-embed + stt: stt-deepgram + # Transcription provider selection: + # - stt-deepgram: Cloud-based (requires DEEPGRAM_API_KEY in .env) + # - stt-parakeet-batch: Local ASR (requires Parakeet service running) + tts: tts-http + vector_store: vs-qdrant +models: +- name: emberfang-llm + description: Emberfang One LLM + model_type: llm + model_provider: openai + model_name: gpt-oss-20b-f16 + model_url: http://192.168.1.166:8084/v1 + api_key: '1234' + model_params: + temperature: 0.2 + max_tokens: 2000 + model_output: json +- name: emberfang-embed + description: Emberfang embeddings (nomic-embed-text) + model_type: embedding + model_provider: openai + model_name: nomic-embed-text-v1.5 + model_url: http://192.168.1.166:8084/v1 + api_key: '1234' + embedding_dimensions: 768 + model_output: vector +- name: local-llm + description: Local Ollama LLM + model_type: llm + model_provider: ollama + api_family: openai + model_name: llama3.1:latest + model_url: http://localhost:11434/v1 + api_key: ${OPENAI_API_KEY:-ollama} + model_params: + temperature: 0.2 + max_tokens: 2000 + model_output: json +- name: local-embed + description: Local embeddings via Ollama nomic-embed-text + model_type: embedding + model_provider: ollama + api_family: openai + model_name: nomic-embed-text:latest + model_url: http://localhost:11434/v1 + api_key: ${OPENAI_API_KEY:-ollama} + embedding_dimensions: 768 + model_output: vector +- name: openai-llm + description: OpenAI GPT-4o-mini + model_type: llm + model_provider: openai + api_family: openai + model_name: gpt-4o-mini + model_url: https://api.openai.com/v1 + api_key: ${OPENAI_API_KEY:-} + model_params: + temperature: 0.2 + max_tokens: 2000 + model_output: json +- name: openai-embed + description: OpenAI text-embedding-3-small + model_type: embedding + model_provider: openai + api_family: openai + model_name: text-embedding-3-small + model_url: https://api.openai.com/v1 + api_key: ${OPENAI_API_KEY:-} + embedding_dimensions: 1536 + model_output: vector +- name: groq-llm + description: Groq LLM via OpenAI-compatible API + model_type: llm + model_provider: groq + api_family: openai + model_name: llama-3.1-70b-versatile + model_url: https://api.groq.com/openai/v1 + api_key: ${GROQ_API_KEY:-} + model_params: + temperature: 0.2 + max_tokens: 2000 + model_output: json +- name: vs-qdrant + description: Qdrant vector database + model_type: vector_store + model_provider: qdrant + api_family: qdrant + model_url: http://${QDRANT_BASE_URL:-qdrant}:${QDRANT_PORT:-6333} + model_params: + host: ${QDRANT_BASE_URL:-qdrant} + port: ${QDRANT_PORT:-6333} + collection_name: omi_memories +- name: stt-parakeet-batch + description: Parakeet NeMo ASR (batch) + model_type: stt + model_provider: parakeet + api_family: http + model_url: http://${PARAKEET_ASR_URL:-172.17.0.1:8767} + api_key: '' + operations: + stt_transcribe: + method: POST + path: /transcribe + content_type: multipart/form-data + response: + type: json + extract: + text: text + words: words + segments: segments +- name: stt-deepgram + description: Deepgram Nova 3 (batch) + model_type: stt + model_provider: deepgram + api_family: http + model_url: https://api.deepgram.com/v1 + api_key: ${DEEPGRAM_API_KEY:-} + operations: + stt_transcribe: + method: POST + path: /listen + headers: + Authorization: Token ${DEEPGRAM_API_KEY:-} + Content-Type: audio/raw + query: + model: nova-3 + language: multi + smart_format: 'true' + punctuate: 'true' + diarize: 'true' + encoding: linear16 + sample_rate: 16000 + channels: '1' + response: + type: json + extract: + text: results.channels[0].alternatives[0].transcript + words: results.channels[0].alternatives[0].words + segments: results.channels[0].alternatives[0].paragraphs.paragraphs +- name: tts-http + description: Generic JSON TTS endpoint + model_type: tts + model_provider: custom + api_family: http + model_url: http://localhost:9000 + operations: + tts_synthesize: + method: POST + path: /synthesize + headers: + Content-Type: application/json + response: + type: json +- name: stt-parakeet-stream + description: Parakeet streaming transcription over WebSocket + model_type: stt_stream + model_provider: parakeet + api_family: websocket + model_url: ws://localhost:9001/stream + operations: + start: + message: + type: transcribe + config: + vad_enabled: true + vad_silence_ms: 1000 + time_interval_seconds: 30 + return_interim_results: true + min_audio_seconds: 0.5 + chunk_header: + message: + type: audio_chunk + rate: 16000 + width: 2 + channels: 1 + end: + message: + type: stop + expect: + interim_type: interim_result + final_type: final_result + extract: + text: text + words: words + segments: segments +memory: + provider: chronicle + timeout_seconds: 1200 + extraction: + enabled: true + prompt: 'Extract important information from this conversation and return a JSON + object with an array named "facts". Include personal preferences, plans, names, + dates, locations, numbers, and key details. Keep items concise and useful. + + ' + openmemory_mcp: + server_url: http://localhost:8765 + client_name: chronicle + user_id: default + timeout: 30 + mycelia: + api_url: http://localhost:5173 + timeout: 30 + obsidian: + enabled: false + neo4j_host: neo4j-mem0 + timeout: 30 + +speaker_recognition: + # Enable/disable speaker recognition (overrides DISABLE_SPEAKER_RECOGNITION env var) + enabled: true + # Service URL (defaults to SPEAKER_SERVICE_URL env var if not specified) + service_url: null + # Request timeout in seconds + timeout: 60 diff --git a/config_manager.py b/config_manager.py new file mode 100644 index 00000000..6f8a85a6 --- /dev/null +++ b/config_manager.py @@ -0,0 +1,367 @@ +""" +Shared configuration manager for Chronicle. + +This module provides a unified interface for reading and writing configuration +across both config.yml (source of truth) and .env (backward compatibility). + +Key principles: +- config.yml is the source of truth for memory provider and model settings +- .env files are kept in sync for backward compatibility with legacy code +- All config updates should use this module to maintain consistency + +Usage: + # From any service in the project + from config_manager import ConfigManager + + # For backend service + config = ConfigManager(service_path="backends/advanced") + provider = config.get_memory_provider() + config.set_memory_provider("openmemory_mcp") + + # Auto-detects paths from cwd + config = ConfigManager() +""" + +import logging +import os +import shutil +from datetime import datetime +from pathlib import Path +from typing import Any, Dict, Optional + +import yaml + +logger = logging.getLogger(__name__) + + +class ConfigManager: + """Manages Chronicle configuration across config.yml and .env files.""" + + def __init__(self, service_path: Optional[str] = None, repo_root: Optional[Path] = None): + """ + Initialize ConfigManager. + + Args: + service_path: Path to service directory (e.g., "backends/advanced", "extras/speaker-recognition"). + If None, auto-detects from current working directory. + repo_root: Path to repository root. If None, auto-detects by finding config.yml. + """ + # Find repo root + if repo_root is None: + repo_root = self._find_repo_root() + self.repo_root = Path(repo_root) + + # Find service directory + if service_path is None: + service_path = self._detect_service_path() + self.service_path = self.repo_root / service_path if service_path else None + + # Paths + self.config_yml_path = self.repo_root / "config" / "config.yml" + self.env_path = self.service_path / ".env" if self.service_path else None + + logger.debug(f"ConfigManager initialized: repo_root={self.repo_root}, " + f"service_path={self.service_path}, config_yml={self.config_yml_path}") + + def _find_repo_root(self) -> Path: + """Find repository root using __file__ location (config_manager.py is always at repo root).""" + return Path(__file__).parent + + def _detect_service_path(self) -> Optional[str]: + """Auto-detect service path from current working directory.""" + cwd = Path.cwd() + + # Check if we're in a known service directory + known_services = [ + "backends/advanced", + "extras/speaker-recognition", + "extras/openmemory-mcp", + "extras/asr-services", + ] + + for service in known_services: + service_full_path = self.repo_root / service + if cwd == service_full_path or str(cwd).startswith(str(service_full_path)): + return service + + logger.debug("Could not auto-detect service path from cwd") + return None + + def _load_config_yml(self) -> Dict[str, Any]: + """Load config.yml file.""" + if not self.config_yml_path.exists(): + raise RuntimeError( + f"Configuration file not found at {self.config_yml_path}. " + "Please ensure config/config.yml exists in the repository root." + ) + + try: + with open(self.config_yml_path, 'r') as f: + config = yaml.safe_load(f) + if config is None: + raise RuntimeError( + f"Configuration file {self.config_yml_path} is empty or invalid. " + "Please ensure it contains valid YAML configuration." + ) + return config + except yaml.YAMLError as e: + raise RuntimeError( + f"Invalid YAML in configuration file {self.config_yml_path}: {e}" + ) + except Exception as e: + raise RuntimeError( + f"Failed to load configuration file {self.config_yml_path}: {e}" + ) + + def _save_config_yml(self, config: Dict[str, Any]): + """Save config.yml file with backup.""" + try: + # Create backup + if self.config_yml_path.exists(): + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + backup_path = self.config_yml_path.parent / f"config.yml.backup.{timestamp}" + shutil.copy2(self.config_yml_path, backup_path) + logger.info(f"Backed up config.yml to {backup_path.name}") + + # Write updated config + with open(self.config_yml_path, 'w') as f: + yaml.dump(config, f, default_flow_style=False, sort_keys=False) + + logger.info(f"Saved config.yml to {self.config_yml_path}") + + except Exception as e: + logger.error(f"Failed to save config.yml: {e}") + raise + + def _update_env_file(self, key: str, value: str): + """Update a single key in .env file.""" + if self.env_path is None: + logger.debug("No service path set, skipping .env update") + return + + if not self.env_path.exists(): + logger.warning(f".env file not found at {self.env_path}") + return + + try: + # Read current .env + with open(self.env_path, 'r') as f: + lines = f.readlines() + + # Update or add line + key_found = False + updated_lines = [] + + for line in lines: + if line.strip().startswith(f"{key}="): + updated_lines.append(f"{key}={value}\n") + key_found = True + else: + updated_lines.append(line) + + # If key wasn't found, add it + if not key_found: + updated_lines.append(f"\n# Auto-updated by ConfigManager\n{key}={value}\n") + + # Create backup + backup_path = f"{self.env_path}.bak" + shutil.copy2(self.env_path, backup_path) + logger.debug(f"Backed up .env to {backup_path}") + + # Write updated file + with open(self.env_path, 'w') as f: + f.writelines(updated_lines) + + # Update environment variable for current process + os.environ[key] = value + + logger.info(f"Updated {key}={value} in .env file") + + except Exception as e: + logger.error(f"Failed to update .env file: {e}") + raise + + def get_memory_provider(self) -> str: + """ + Get current memory provider from config.yml. + + Returns: + Memory provider name (chronicle, openmemory_mcp, or mycelia) + """ + config = self._load_config_yml() + provider = config.get("memory", {}).get("provider", "chronicle").lower() + + # Map legacy names + if provider in ("friend-lite", "friend_lite"): + provider = "chronicle" + + return provider + + def set_memory_provider(self, provider: str) -> Dict[str, Any]: + """ + Set memory provider in both config.yml and .env. + + This updates: + 1. config.yml: memory.provider field (source of truth) + 2. .env: MEMORY_PROVIDER variable (backward compatibility, if service_path set) + + Args: + provider: Memory provider name (chronicle, openmemory_mcp, or mycelia) + + Returns: + Dict with status and details of the update + + Raises: + ValueError: If provider is invalid + """ + # Validate provider + provider = provider.lower().strip() + valid_providers = ["chronicle", "openmemory_mcp", "mycelia"] + + if provider not in valid_providers: + raise ValueError( + f"Invalid provider '{provider}'. " + f"Valid providers: {', '.join(valid_providers)}" + ) + + # Update config.yml + config = self._load_config_yml() + + if "memory" not in config: + config["memory"] = {} + + config["memory"]["provider"] = provider + self._save_config_yml(config) + + # Update .env for backward compatibility (if we have a service path) + if self.env_path and self.env_path.exists(): + self._update_env_file("MEMORY_PROVIDER", provider) + + return { + "message": ( + f"Memory provider updated to '{provider}' in config.yml" + f"{' and .env' if self.env_path else ''}. " + "Please restart services for changes to take effect." + ), + "provider": provider, + "config_yml_path": str(self.config_yml_path), + "env_path": str(self.env_path) if self.env_path else None, + "requires_restart": True, + "status": "success" + } + + def get_memory_config(self) -> Dict[str, Any]: + """ + Get complete memory configuration from config.yml. + + Returns: + Full memory configuration dict + """ + config = self._load_config_yml() + return config.get("memory", {}) + + def update_memory_config(self, updates: Dict[str, Any]): + """ + Update memory configuration in config.yml. + + Args: + updates: Dict of updates to merge into memory config (deep merge) + """ + config = self._load_config_yml() + + if "memory" not in config: + config["memory"] = {} + + # Deep merge updates recursively + self._deep_merge(config["memory"], updates) + + self._save_config_yml(config) + + # If provider was updated, also update .env + if "provider" in updates and self.env_path: + self._update_env_file("MEMORY_PROVIDER", updates["provider"]) + + def _deep_merge(self, base: dict, updates: dict) -> None: + """ + Recursively merge updates into base dictionary. + + Args: + base: Base dictionary to merge into (modified in-place) + updates: Updates to merge + """ + for key, value in updates.items(): + if key in base and isinstance(base[key], dict) and isinstance(value, dict): + # Recursively merge nested dictionaries + self._deep_merge(base[key], value) + else: + # Direct assignment for non-dict values + base[key] = value + + def get_config_defaults(self) -> Dict[str, Any]: + """ + Get defaults configuration from config.yml. + + Returns: + Defaults configuration dict (llm, embedding, stt, tts, vector_store) + """ + config = self._load_config_yml() + return config.get("defaults", {}) + + def update_config_defaults(self, updates: Dict[str, str]): + """ + Update defaults configuration in config.yml. + + Args: + updates: Dict of updates to merge into defaults config + (e.g., {"llm": "openai-llm", "embedding": "openai-embed"}) + """ + config = self._load_config_yml() + + if "defaults" not in config: + config["defaults"] = {} + + # Update defaults + config["defaults"].update(updates) + + self._save_config_yml(config) + + def get_full_config(self) -> Dict[str, Any]: + """ + Get complete config.yml as dictionary. + + Returns: + Full configuration dict + """ + return self._load_config_yml() + + def save_full_config(self, config: Dict[str, Any]): + """ + Save complete config.yml from dictionary. + + Args: + config: Full configuration dict to save + """ + self._save_config_yml(config) + + +# Global singleton instance +_config_manager: Optional[ConfigManager] = None + + +def get_config_manager(service_path: Optional[str] = None) -> ConfigManager: + """ + Get global ConfigManager singleton instance. + + Args: + service_path: Optional service path for .env updates. + If None, uses cached instance or creates new one. + + Returns: + ConfigManager instance + """ + global _config_manager + + if _config_manager is None or service_path is not None: + _config_manager = ConfigManager(service_path=service_path) + + return _config_manager diff --git a/extras/speaker-recognition/Dockerfile b/extras/speaker-recognition/Dockerfile index d14baf35..0c1ccc81 100644 --- a/extras/speaker-recognition/Dockerfile +++ b/extras/speaker-recognition/Dockerfile @@ -31,6 +31,9 @@ COPY src/simple_speaker_recognition/__init__.py src/simple_speaker_recognition/ RUN uv sync --no-dev --extra ${PYTORCH_CUDA_VERSION} && \ uv cache clean +# Copy the full source code (after dependencies are cached) +COPY src/ src/ + # Create directories RUN mkdir -p /app/audio_chunks /app/debug /app/data /models diff --git a/extras/speaker-recognition/run-test.sh b/extras/speaker-recognition/run-test.sh index 6ac212fa..ac73de91 100755 --- a/extras/speaker-recognition/run-test.sh +++ b/extras/speaker-recognition/run-test.sh @@ -13,12 +13,12 @@ cleanup() { return fi cleanup_called=true - + print_info "Cleaning up on exit..." # Kill any background processes in this process group pkill -P $$ 2>/dev/null || true - # Clean up test containers - docker compose -f docker-compose-test.yml down -v 2>/dev/null || true + # Clean up test containers (use project name for consistency) + COMPOSE_PROJECT_NAME="speaker-recognition-test" docker compose -f docker-compose-test.yml down -v 2>/dev/null || true } # Set up signal traps for proper cleanup (but not EXIT to avoid double cleanup) @@ -124,6 +124,9 @@ uv sync --extra cpu --group test print_info "Environment variables configured for testing" +# Use unique project name to avoid conflicts with development environment +export COMPOSE_PROJECT_NAME="speaker-recognition-test" + # Clean test environment print_info "Cleaning test environment..." # Stop any existing test containers diff --git a/restart.sh b/restart.sh new file mode 100755 index 00000000..019518c4 --- /dev/null +++ b/restart.sh @@ -0,0 +1,2 @@ +#!/bin/bash +uv run --with-requirements setup-requirements.txt python services.py restart --all diff --git a/services.py b/services.py index 716e437e..0ffa014a 100755 --- a/services.py +++ b/services.py @@ -8,12 +8,26 @@ import subprocess from pathlib import Path +import yaml from rich.console import Console from rich.table import Table from dotenv import dotenv_values console = Console() +def load_config_yml(): + """Load config.yml from repository root""" + config_path = Path(__file__).parent / 'config' / 'config.yml' + if not config_path.exists(): + return None + + try: + with open(config_path, 'r') as f: + return yaml.safe_load(f) + except Exception as e: + console.print(f"[yellow]⚠️ Warning: Could not load config/config.yml: {e}[/yellow]") + return None + SERVICES = { 'backend': { 'path': 'backends/advanced', @@ -74,7 +88,30 @@ def run_compose_command(service_name, command, build=False): if caddyfile_path.exists() and caddyfile_path.is_file(): # Enable HTTPS profile to start Caddy service cmd.extend(['--profile', 'https']) - + + # Check if Obsidian/Neo4j is enabled + obsidian_enabled = False + + # Method 1: Check config.yml (preferred) + config_data = load_config_yml() + if config_data: + memory_config = config_data.get('memory', {}) + obsidian_config = memory_config.get('obsidian', {}) + if obsidian_config.get('enabled', False): + obsidian_enabled = True + + # Method 2: Fallback to .env for backward compatibility + if not obsidian_enabled: + env_file = service_path / '.env' + if env_file.exists(): + env_values = dotenv_values(env_file) + if env_values.get('OBSIDIAN_ENABLED', 'false').lower() == 'true': + obsidian_enabled = True + + if obsidian_enabled: + cmd.extend(['--profile', 'obsidian']) + console.print("[blue]ℹ️ Starting with Obsidian/Neo4j support[/blue]") + # Handle speaker-recognition service specially if service_name == 'speaker-recognition' and command in ['up', 'down']: # Read configuration to determine profile diff --git a/skaffold.yaml b/skaffold.yaml index 279566ce..718e61a3 100644 --- a/skaffold.yaml +++ b/skaffold.yaml @@ -184,7 +184,7 @@ profiles: build: artifacts: - - image: friend-backend-test + - image: chronicle-backend-test context: backends/advanced docker: dockerfile: Dockerfile @@ -195,7 +195,7 @@ profiles: deploy: docker: - images: [friend-backend-test, webui-test, mongo-test, qdrant-test, redis-test] + images: [chronicle-backend-test, webui-test, mongo-test, qdrant-test, redis-test] diff --git a/status.py b/status.py index babf6cb7..3b3e61c9 100644 --- a/status.py +++ b/status.py @@ -18,6 +18,7 @@ from rich.panel import Panel from rich.live import Live from rich.layout import Layout +from dotenv import dotenv_values # Import service definitions from services.py from services import SERVICES, check_service_configured @@ -44,11 +45,26 @@ def get_container_status(service_name: str) -> Dict[str, Any]: # Get container status using docker compose ps cmd = ['docker', 'compose', 'ps', '--format', 'json'] - # Handle special profiles for backend (HTTPS) + # Handle special profiles for backend (HTTPS and Obsidian) if service_name == 'backend': + profiles = [] + + # Check for HTTPS profile caddyfile_path = service_path / 'Caddyfile' if caddyfile_path.exists(): - cmd = ['docker', 'compose', '--profile', 'https', 'ps', '--format', 'json'] + profiles.append('https') + + # Check for Obsidian/Neo4j profile + env_file = service_path / '.env' + if env_file.exists(): + env_values = dotenv_values(env_file) + neo4j_host = env_values.get('NEO4J_HOST', '') + if neo4j_host and neo4j_host not in ['', 'your-neo4j-host-here', 'your_neo4j_host_here']: + profiles.append('obsidian') + + # Apply profiles if any are needed + if profiles: + cmd = ['docker', 'compose'] + [item for profile in profiles for item in ['--profile', profile]] + ['ps', '--format', 'json'] # Handle speaker-recognition profiles if service_name == 'speaker-recognition': diff --git a/tests/Makefile b/tests/Makefile index 707743e4..8ba002f5 100644 --- a/tests/Makefile +++ b/tests/Makefile @@ -31,7 +31,7 @@ help: # Creates a persistent fixture conversation that won't be deleted between suites all: @echo "Running all tests..." - CREATE_FIXTURE=true uv run robot --outputdir $(OUTPUTDIR) \ + CREATE_FIXTURE=true uv run --with-requirements test-requirements.txt robot --outputdir $(OUTPUTDIR) \ --name "All Tests" \ --console verbose \ $(TEST_DIR) @@ -39,7 +39,7 @@ all: # Run only endpoint tests endpoints: @echo "Running endpoint tests..." - uv run robot --outputdir $(OUTPUTDIR) \ + uv run --with-requirements test-requirements.txt robot --outputdir $(OUTPUTDIR) \ --name "Endpoint Tests" \ --console verbose \ endpoints @@ -47,7 +47,7 @@ endpoints: # Run only integration tests integration: @echo "Running integration tests..." - CREATE_FIXTURE=true uv run robot --outputdir $(OUTPUTDIR) \ + CREATE_FIXTURE=true uv run --with-requirements test-requirements.txt robot --outputdir $(OUTPUTDIR) \ --name "Integration Tests" \ --console verbose \ integration @@ -55,7 +55,7 @@ integration: # Run only infrastructure tests infra: @echo "Running infrastructure tests..." - uv run robot --outputdir $(OUTPUTDIR) \ + uv run --with-requirements test-requirements.txt robot --outputdir $(OUTPUTDIR) \ --name "Infrastructure Tests" \ --console verbose \ infrastructure diff --git a/tests/TESTING_USER_GUIDE.md b/tests/TESTING_USER_GUIDE.md index d1ebbd9d..5dc6bf6d 100644 --- a/tests/TESTING_USER_GUIDE.md +++ b/tests/TESTING_USER_GUIDE.md @@ -722,7 +722,7 @@ robot --rerunfailed output.xml tests/ CLEANUP_CONTAINERS=false robot tests/endpoints/auth_tests.robot # Inspect backend logs -docker logs advanced-friend-backend-test-1 +docker logs advanced-chronicle-backend-test-1 # Inspect database docker exec -it advanced-mongo-test-1 mongosh test_db diff --git a/tests/configs/README.md b/tests/configs/README.md new file mode 100644 index 00000000..8b1e196f --- /dev/null +++ b/tests/configs/README.md @@ -0,0 +1,132 @@ +# Test Configuration Files + +This directory contains configuration variants for testing different provider combinations. + +## Available Test Configs + +### `deepgram-openai.yml` - Cloud Services +- **STT**: Deepgram Nova 3 +- **LLM**: OpenAI GPT-4o-mini +- **Embedding**: OpenAI text-embedding-3-small +- **Memory**: Chronicle native +- **Use Case**: Cloud-based testing when API credits available +- **Required**: `DEEPGRAM_API_KEY`, `OPENAI_API_KEY` + +### `parakeet-ollama.yml` - Full Local Stack +- **STT**: Parakeet ASR (local) +- **LLM**: Ollama llama3.1:latest +- **Embedding**: Ollama nomic-embed-text +- **Memory**: Chronicle native +- **Use Case**: Offline testing, no API keys needed +- **Required**: Parakeet ASR running on port 8767, Ollama running + +### `full-local.yml` - Alias +Symlink to `parakeet-ollama.yml` for convenience. + +## Usage + +### With run-test.sh + +```bash +# Test with Deepgram + OpenAI (cloud) +CONFIG_FILE=../../tests/configs/deepgram-openai.yml ./backends/advanced/run-test.sh + +# Test with Parakeet + Ollama (local) +CONFIG_FILE=../../tests/configs/parakeet-ollama.yml ./backends/advanced/run-test.sh + +# Using the full-local alias +CONFIG_FILE=../../tests/configs/full-local.yml ./backends/advanced/run-test.sh +``` + +### With Docker Compose + +```bash +# From backends/advanced/ +CONFIG_FILE=../../tests/configs/deepgram-openai.yml docker compose -f docker-compose-test.yml up +``` + +### Matrix Testing + +Test all configurations: + +```bash +for cfg in tests/configs/*.yml; do + echo "Testing with: $cfg" + CONFIG_FILE=$cfg ./backends/advanced/run-test.sh || exit 1 +done +``` + +## Creating New Test Configs + +When creating a new test configuration: + +1. **Name it descriptively**: `{stt}-{llm}.yml` (e.g., `mistral-openai.yml`) +2. **Use environment variables**: Always use `${VAR:-default}` pattern for secrets +3. **Set appropriate defaults**: Update the `defaults:` section to match your provider combo +4. **Include only required models**: Don't include models that aren't used +5. **Document requirements**: Update this README with required environment variables + +### Example Structure + +```yaml +# tests/configs/example-config.yml +defaults: + llm: provider-llm + embedding: provider-embed + stt: stt-provider + vector_store: vs-qdrant + +models: + - name: provider-llm + model_type: llm + model_provider: your_provider + api_key: ${YOUR_API_KEY:-} + # ... model config + + - name: stt-provider + model_type: stt + model_provider: your_stt_provider + api_key: ${YOUR_STT_API_KEY:-} + # ... stt config + +memory: + provider: chronicle + # ... memory config +``` + +## Environment Variables + +Test configs use environment variable substitution to avoid hardcoding secrets: + +- **Pattern**: `${VAR_NAME:-default_value}` +- **Example**: `api_key: ${OPENAI_API_KEY:-}` (empty string if not set) +- **Example**: `model_url: ${PARAKEET_ASR_URL:-http://localhost:8767}` (fallback to default) + +### Required by Config + +**deepgram-openai.yml**: +- `DEEPGRAM_API_KEY` - Deepgram transcription API key +- `OPENAI_API_KEY` - OpenAI LLM and embeddings API key + +**parakeet-ollama.yml**: +- `PARAKEET_ASR_URL` (optional) - Defaults to `http://localhost:8767` +- No API keys needed (all local services) + +## Best Practices + +1. **Never hardcode secrets**: Always use environment variables +2. **Test locally first**: Verify config works before adding to repo +3. **Document dependencies**: Update this README with service requirements +4. **Keep configs minimal**: Only include models actually used in tests +5. **Version control**: Test configs are tracked (no secrets), backups are ignored + +## Adding More Combinations + +As you add support for new providers, create corresponding test configs: + +- `mistral-openai.yml` - Mistral Voxtral STT + OpenAI LLM +- `deepgram-ollama.yml` - Deepgram STT + Local Ollama LLM +- `parakeet-openai.yml` - Local Parakeet STT + OpenAI LLM +- etc. + +Each new config should follow the naming convention and documentation pattern above. diff --git a/tests/configs/deepgram-openai.yml b/tests/configs/deepgram-openai.yml new file mode 100644 index 00000000..46c8ddef --- /dev/null +++ b/tests/configs/deepgram-openai.yml @@ -0,0 +1,89 @@ +# Test Configuration: Deepgram (STT) + OpenAI (LLM) +# Cloud-based services - recommended for CI/testing when API credits available + +defaults: + llm: openai-llm + embedding: openai-embed + stt: stt-deepgram + vector_store: vs-qdrant + +models: + - name: openai-llm + description: OpenAI GPT-4o-mini + model_type: llm + model_provider: openai + api_family: openai + model_name: gpt-4o-mini + model_url: https://api.openai.com/v1 + api_key: ${OPENAI_API_KEY:-} + model_params: + temperature: 0.2 + max_tokens: 2000 + model_output: json + + - name: openai-embed + description: OpenAI text-embedding-3-small + model_type: embedding + model_provider: openai + api_family: openai + model_name: text-embedding-3-small + model_url: https://api.openai.com/v1 + api_key: ${OPENAI_API_KEY:-} + embedding_dimensions: 1536 + model_output: vector + + - name: vs-qdrant + description: Qdrant vector database + model_type: vector_store + model_provider: qdrant + api_family: qdrant + model_url: http://${QDRANT_BASE_URL:-qdrant}:${QDRANT_PORT:-6333} + model_params: + host: ${QDRANT_BASE_URL:-qdrant} + port: ${QDRANT_PORT:-6333} + collection_name: omi_memories + + - name: stt-deepgram + description: Deepgram Nova 3 (batch) + model_type: stt + model_provider: deepgram + api_family: http + model_url: https://api.deepgram.com/v1 + api_key: ${DEEPGRAM_API_KEY:-} + operations: + stt_transcribe: + method: POST + path: /listen + headers: + Authorization: Token ${DEEPGRAM_API_KEY:-} + Content-Type: audio/raw + query: + model: nova-3 + language: multi + smart_format: 'true' + punctuate: 'true' + diarize: 'true' + encoding: linear16 + sample_rate: 16000 + channels: '1' + response: + type: json + extract: + text: results.channels[0].alternatives[0].transcript + words: results.channels[0].alternatives[0].words + segments: results.channels[0].alternatives[0].paragraphs.paragraphs + +memory: + provider: chronicle + timeout_seconds: 1200 + extraction: + enabled: true + prompt: | + Extract important information from this conversation and return a JSON object with an array named "facts". + Include personal preferences, plans, names, dates, locations, numbers, and key details. + Keep items concise and useful. + +speaker_recognition: + # Disable speaker recognition in CI tests (too slow, blocks workers) + enabled: false + timeout: 60 diff --git a/tests/configs/full-local.yml b/tests/configs/full-local.yml new file mode 120000 index 00000000..d2e90934 --- /dev/null +++ b/tests/configs/full-local.yml @@ -0,0 +1 @@ +parakeet-ollama.yml \ No newline at end of file diff --git a/tests/configs/parakeet-ollama.yml b/tests/configs/parakeet-ollama.yml new file mode 100644 index 00000000..a4ef958d --- /dev/null +++ b/tests/configs/parakeet-ollama.yml @@ -0,0 +1,73 @@ +# Test Configuration: Parakeet (STT) + Ollama (LLM) +# Full local stack - no API keys needed, runs entirely offline + +defaults: + llm: local-llm + embedding: local-embed + stt: stt-parakeet-batch + vector_store: vs-qdrant + +models: + - name: local-llm + description: Local Ollama LLM + model_type: llm + model_provider: ollama + api_family: openai + model_name: llama3.1:latest + model_url: http://localhost:11434/v1 + api_key: ${OPENAI_API_KEY:-ollama} + model_params: + temperature: 0.2 + max_tokens: 2000 + model_output: json + + - name: local-embed + description: Local embeddings via Ollama nomic-embed-text + model_type: embedding + model_provider: ollama + api_family: openai + model_name: nomic-embed-text:latest + model_url: http://localhost:11434/v1 + api_key: ${OPENAI_API_KEY:-ollama} + embedding_dimensions: 768 + model_output: vector + + - name: vs-qdrant + description: Qdrant vector database + model_type: vector_store + model_provider: qdrant + api_family: qdrant + model_url: http://${QDRANT_BASE_URL:-qdrant}:${QDRANT_PORT:-6333} + model_params: + host: ${QDRANT_BASE_URL:-qdrant} + port: ${QDRANT_PORT:-6333} + collection_name: omi_memories + + - name: stt-parakeet-batch + description: Parakeet NeMo ASR (batch) - local offline transcription + model_type: stt + model_provider: parakeet + api_family: http + model_url: ${PARAKEET_ASR_URL:-http://localhost:8767} + api_key: '' + operations: + stt_transcribe: + method: POST + path: /transcribe + content_type: multipart/form-data + response: + type: json + extract: + text: text + words: words + segments: segments + +memory: + provider: chronicle + timeout_seconds: 1200 + extraction: + enabled: true + prompt: | + Extract important information from this conversation and return a JSON object with an array named "facts". + Include personal preferences, plans, names, dates, locations, numbers, and key details. + Keep items concise and useful. diff --git a/tests/configs/parakeet-openai.yml b/tests/configs/parakeet-openai.yml new file mode 100644 index 00000000..f3147c33 --- /dev/null +++ b/tests/configs/parakeet-openai.yml @@ -0,0 +1,73 @@ +# Test Configuration: Parakeet (STT) + OpenAI (LLM) +# Hybrid stack - local transcription, cloud LLM + +defaults: + llm: openai-llm + embedding: openai-embed + stt: stt-parakeet-batch + vector_store: vs-qdrant + +models: + - name: openai-llm + description: OpenAI GPT-4o-mini + model_type: llm + model_provider: openai + api_family: openai + model_name: gpt-4o-mini + model_url: https://api.openai.com/v1 + api_key: ${OPENAI_API_KEY:-} + model_params: + temperature: 0.2 + max_tokens: 2000 + model_output: json + + - name: openai-embed + description: OpenAI text-embedding-3-small + model_type: embedding + model_provider: openai + api_family: openai + model_name: text-embedding-3-small + model_url: https://api.openai.com/v1 + api_key: ${OPENAI_API_KEY:-} + embedding_dimensions: 1536 + model_output: vector + + - name: vs-qdrant + description: Qdrant vector database + model_type: vector_store + model_provider: qdrant + api_family: qdrant + model_url: http://${QDRANT_BASE_URL:-qdrant}:${QDRANT_PORT:-6333} + model_params: + host: ${QDRANT_BASE_URL:-qdrant} + port: ${QDRANT_PORT:-6333} + collection_name: omi_memories + + - name: stt-parakeet-batch + description: Parakeet NeMo ASR (batch) - local offline transcription + model_type: stt + model_provider: parakeet + api_family: http + model_url: ${PARAKEET_ASR_URL:-http://localhost:8767} + api_key: '' + operations: + stt_transcribe: + method: POST + path: /transcribe + content_type: multipart/form-data + response: + type: json + extract: + text: text + words: words + segments: segments + +memory: + provider: chronicle + timeout_seconds: 1200 + extraction: + enabled: true + prompt: | + Extract important information from this conversation and return a JSON object with an array named "facts". + Include personal preferences, plans, names, dates, locations, numbers, and key details. + Keep items concise and useful. diff --git a/tests/endpoints/rq_queue_tests.robot b/tests/endpoints/rq_queue_tests.robot index f8b91346..5206b5ff 100644 --- a/tests/endpoints/rq_queue_tests.robot +++ b/tests/endpoints/rq_queue_tests.robot @@ -19,7 +19,7 @@ Suite Teardown Suite Teardown Test Setup Test Cleanup *** Variables *** ${TEST_TIMEOUT} 20s -${COMPOSE_FILE} backends/advanced/docker-compose-test.yml +${COMPOSE_FILE} docker-compose-test.yml *** Keywords *** @@ -28,12 +28,12 @@ Restart Backend Service Log Restarting backend service to test job persistence # Stop backend container - Run Process docker compose -f ${COMPOSE_FILE} stop friend-backend-test - ... cwd=. timeout=30s + Run Process docker compose -f ${COMPOSE_FILE} stop chronicle-backend-test + ... cwd=${BACKEND_DIR} timeout=30s # Start backend container again - Run Process docker compose -f ${COMPOSE_FILE} start friend-backend-test - ... cwd=. timeout=60s + Run Process docker compose -f ${COMPOSE_FILE} start chronicle-backend-test + ... cwd=${BACKEND_DIR} timeout=60s # Wait for backend to be ready again Wait Until Keyword Succeeds ${TEST_TIMEOUT} 5s diff --git a/tests/endpoints/system_admin_tests.robot b/tests/endpoints/system_admin_tests.robot index e524c264..283c1865 100644 --- a/tests/endpoints/system_admin_tests.robot +++ b/tests/endpoints/system_admin_tests.robot @@ -79,7 +79,7 @@ Get Enrolled Speakers Test Dictionary Should Contain Key ${response_data} speakers # If service is available, verify speakers data - Should Be True isinstance($response_data[speakers], list) + Should Be True isinstance($response_data["speakers"], list) Get Speaker Service Status Test [Documentation] Test checking speaker recognition service status (admin only) diff --git a/tests/infrastructure/infra_tests.robot b/tests/infrastructure/infra_tests.robot index 48b1a057..c0d401db 100644 --- a/tests/infrastructure/infra_tests.robot +++ b/tests/infrastructure/infra_tests.robot @@ -44,6 +44,14 @@ Get Worker Count From Health Endpoint ${worker_count}= Set Variable ${redis_service}[worker_count] RETURN ${worker_count} +Verify Minimum Worker Count + [Documentation] Verify that at least the minimum number of workers are registered + [Arguments] ${min_count} + ${worker_count}= Get Worker Count From Health Endpoint + Log To Console Current worker count: ${worker_count} + Should Be True ${worker_count} >= ${min_count} msg=Expected at least ${min_count} workers, got ${worker_count} + RETURN ${worker_count} + Simulate Worker Registration Loss [Documentation] Simulate the scenario where workers lose Redis registration ... This happens when: @@ -176,6 +184,13 @@ Worker Count Validation Test ... - Worker state information is accurate [Tags] health queue + # Wait for workers to register (up to 20s, checking every 2s) + Log To Console \n⏳ Waiting for workers to register (up to 20s)... + ${worker_count}= Wait Until Keyword Succeeds 20s 2s + ... Verify Minimum Worker Count 6 + Log To Console ✅ Workers registered: ${worker_count} + + # Get full health details for validation ${response}= GET On Session api /health Should Be Equal As Integers ${response.status_code} 200 @@ -191,7 +206,7 @@ Worker Count Validation Test Dictionary Should Contain Key ${redis_service} active_workers Dictionary Should Contain Key ${redis_service} idle_workers - # Verify worker count is reasonable (7 workers: 6 RQ + 1 audio stream) + # Get worker state details ${worker_count}= Set Variable ${redis_service}[worker_count] ${active_workers}= Set Variable ${redis_service}[active_workers] ${idle_workers}= Set Variable ${redis_service}[idle_workers] @@ -201,10 +216,11 @@ Worker Count Validation Test Log To Console Active workers: ${active_workers} Log To Console Idle workers: ${idle_workers} - # Verify expected worker count (should be 7: 6 RQ workers + 1 audio stream worker) - # Note: Audio stream worker might not register in RQ, so we expect 6-7 workers - Should Be True ${worker_count} >= 6 msg=Expected at least 6 RQ workers registered - Should Be True ${worker_count} <= 8 msg=Expected no more than 8 workers + # Verify exact worker count + # Expected: 7 RQ workers (6 general workers + 1 audio persistence worker) + # Note: Audio stream workers (Deepgram/Parakeet) are NOT RQ workers - they don't register + # We wait up to 20s for registration, so all workers should be present + Should Be Equal As Integers ${worker_count} 7 msg=Expected exactly 7 RQ workers (6 general + 1 audio persistence) # Verify active + idle = total ${sum}= Evaluate ${active_workers} + ${idle_workers} diff --git a/tests/integration/integration_test.robot b/tests/integration/integration_test.robot index d564a54e..4b08381b 100644 --- a/tests/integration/integration_test.robot +++ b/tests/integration/integration_test.robot @@ -11,6 +11,8 @@ Resource ../setup/teardown_keywords.robot Resource ../resources/session_keywords.robot Resource ../resources/audio_keywords.robot Resource ../resources/conversation_keywords.robot +Resource ../resources/memory_keywords.robot +Resource ../resources/queue_keywords.robot Variables ../setup/test_env.py Variables ../setup/test_data.py Suite Setup Suite Setup @@ -127,6 +129,44 @@ Audio Playback And Segment Timing Test Log All ${segment_count} segments have valid timestamps (0s - ${last_end}s) INFO Log Audio Playback And Segment Timing Test Completed Successfully INFO +End To End Pipeline With Memory Validation Test + [Documentation] Complete E2E test with memory extraction and OpenAI quality validation. + ... Provides comprehensive integration testing of the entire audio processing pipeline. + ... Separate from other tests to avoid breaking existing upload-only tests. + [Tags] e2e memory + [Timeout] 600s + + Log Starting End-to-End Pipeline Test with Memory Validation INFO + + # Phase 1: Upload audio and wait for complete processing + Log Uploading audio file and waiting for full processing INFO + ${conversation} ${memories}= Upload Audio File And Wait For Memory + ... ${TEST_AUDIO_FILE} + ... ${TEST_DEVICE_NAME} + + Set Global Variable ${TEST_CONVERSATION} ${conversation} + + # Phase 2: Verify transcription quality + Log Verifying transcription quality INFO + Verify Transcription Quality ${TEST_CONVERSATION} ${EXPECTED_TRANSCRIPT} + + # Phase 3: Verify memories were extracted + ${memory_count}= Get Length ${memories} + Should Be True ${memory_count} > 0 No memories extracted + Log Extracted ${memory_count} memories INFO + + # Phase 4: Verify memory quality with OpenAI (matches Python test!) + Log Validating memory quality with OpenAI INFO + Verify Memory Quality With OpenAI ${memories} ${EXPECTED_MEMORIES} + + # Phase 5: Verify chat integration + Log Verifying chat integration INFO + Verify Chat Integration api ${TEST_CONVERSATION} + + Log End-to-End Pipeline Test Completed Successfully INFO + Log ✅ Transcript verified INFO + Log ✅ ${memory_count} memories extracted and validated with OpenAI INFO + *** Keywords *** diff --git a/tests/resources/audio_keywords.robot b/tests/resources/audio_keywords.robot index 82c3d782..2d37fcbc 100644 --- a/tests/resources/audio_keywords.robot +++ b/tests/resources/audio_keywords.robot @@ -69,6 +69,50 @@ Upload Audio File RETURN ${conversation} +Upload Audio File And Wait For Memory + [Documentation] Upload audio file and wait for complete processing including memory extraction. + ... This is for E2E testing - use Upload Audio File for upload-only tests. + ... Performs assertions inline to verify successful memory extraction. + [Arguments] ${audio_file_path} ${device_name}=robot-test ${folder}=. ${min_memories}=1 + + # Upload file (uses existing keyword) + ${conversation}= Upload Audio File ${audio_file_path} ${device_name} ${folder} + + # Get conversation ID to find memory job + ${conversation_id}= Set Variable ${conversation}[conversation_id] + Log Conversation ID: ${conversation_id} + + # Find memory job for this conversation + ${memory_jobs}= Get Jobs By Type And Conversation process_memory_job ${conversation_id} + Should Not Be Empty ${memory_jobs} No memory job found for conversation ${conversation_id} + + ${memory_job}= Set Variable ${memory_jobs}[0] + ${memory_job_id}= Set Variable ${memory_job}[job_id] + + Log Found memory job: ${memory_job_id} + + # Wait for memory extraction (returns result dictionary) + ${result}= Wait For Memory Extraction ${memory_job_id} + + # Verify memory extraction succeeded + Should Be True ${result}[success] + ... Memory extraction failed: ${result.get('error_message', 'Unknown error')} + + # Verify job completed successfully + Should Be Equal As Strings ${result}[status] completed + ... Expected job status 'completed', got '${result}[status]' + + # Verify minimum memories were extracted + ${memory_count}= Set Variable ${result}[memory_count] + Should Be True ${memory_count} >= ${min_memories} + ... Expected at least ${min_memories} memories, found ${memory_count} + + ${memories}= Set Variable ${result}[memories] + Log Successfully extracted ${memory_count} memories + + RETURN ${conversation} ${memories} + + Get Cropped Audio Info [Documentation] Get cropped audio information for a conversation [Arguments] ${audio_uuid} diff --git a/tests/resources/memory_keywords.robot b/tests/resources/memory_keywords.robot index 4a02c40e..2ab79d9c 100644 --- a/tests/resources/memory_keywords.robot +++ b/tests/resources/memory_keywords.robot @@ -104,3 +104,189 @@ Verify Memory Extraction Should Be True ${api_memory_count} >= ${min_memories} Insufficient API memories: ${api_memory_count} Log Memory extraction verified: conversation=${conv_memory_count}, api=${api_memory_count} INFO + + +Wait For Memory Extraction + [Documentation] Wait for memory job to complete and fetch extracted memories. + ... Returns a result dictionary with success status, job details, and memories. + ... Does not perform assertions - calling tests should verify the results. + ... + ... Return value structure: + ... { + ... 'success': True/False, + ... 'error_message': 'Error description' (only if success=False), + ... 'status': 'completed'/'failed'/'timeout'/'not_found', + ... 'job': {job object} (if available), + ... 'memories': [list of memories] (if successful), + ... 'memory_count': int (if successful) + ... } + [Arguments] ${memory_job_id} ${timeout}=120 + + Log Waiting for memory job ${memory_job_id} to complete... + + # 1. Check if job exists before waiting + ${job_status}= Get Job Status ${memory_job_id} + IF ${job_status} == ${None} + ${result}= Create Dictionary + ... success=${False} + ... error_message=Memory job ${memory_job_id} not found in queue + ... status=not_found + RETURN ${result} + END + + # 2. Check if job already failed + ${current_status}= Set Variable ${job_status}[status] + IF '${current_status}' == 'failed' + ${error_info}= Evaluate $job_status.get('exc_info', 'Unknown error') + ${result}= Create Dictionary + ... success=${False} + ... error_message=Memory job already failed: ${error_info} + ... status=failed + ... job=${job_status} + RETURN ${result} + END + + # 3. Wait for job completion with status monitoring + ${start_time}= Get Time epoch + ${end_time}= Evaluate ${start_time} + ${timeout} + ${final_job}= Set Variable ${job_status} + ${final_status}= Set Variable ${current_status} + + WHILE True + # Get current job status + ${job}= Get Job Status ${memory_job_id} + + # Handle job not found (e.g., expired from queue) + IF ${job} == ${None} + ${result}= Create Dictionary + ... success=${False} + ... error_message=Memory job ${memory_job_id} disappeared from queue during wait + ... status=not_found + ... job=${final_job} + RETURN ${result} + END + + ${status}= Set Variable ${job}[status] + ${final_job}= Set Variable ${job} + ${final_status}= Set Variable ${status} + + # Success case - job completed + IF '${status}' == 'completed' or '${status}' == 'finished' + Log Memory job completed successfully + BREAK + END + + # Failure case - job failed + IF '${status}' == 'failed' + ${error_info}= Evaluate $job.get('exc_info', 'Unknown error') + ${result}= Create Dictionary + ... success=${False} + ... error_message=Memory job failed during processing: ${error_info} + ... status=failed + ... job=${job} + RETURN ${result} + END + + # Timeout check + ${current_time}= Get Time epoch + IF ${current_time} >= ${end_time} + ${result}= Create Dictionary + ... success=${False} + ... error_message=Memory job did not complete within ${timeout}s (last status: ${status}) + ... status=timeout + ... job=${job} + RETURN ${result} + END + + # Log progress every iteration + Log Memory job status: ${status} (waiting...) DEBUG + + # Wait before next check + Sleep 5s + END + + # 4. Fetch memories from API + TRY + ${response}= GET On Session api /api/memories expected_status=200 + ${memories_data}= Set Variable ${response.json()} + ${memories}= Set Variable ${memories_data}[memories] + ${memory_count}= Get Length ${memories} + + # Return success result + ${result}= Create Dictionary + ... success=${True} + ... status=completed + ... job=${final_job} + ... memories=${memories} + ... memory_count=${memory_count} + + Log Successfully extracted ${memory_count} memories + RETURN ${result} + EXCEPT AS ${error} + # Return error if API fetch fails + ${result}= Create Dictionary + ... success=${False} + ... error_message=Failed to fetch memories from API: ${error} + ... status=api_error + ... job=${final_job} + RETURN ${result} + END + + +Check Memory Similarity With OpenAI + [Documentation] Use OpenAI to check if extracted memories match expected memories + [Arguments] ${actual_memories} ${expected_memories} ${openai_api_key} + + # Extract just the memory text from actual memories + ${actual_memory_texts}= Evaluate [mem.get('memory', '') for mem in $actual_memories] + + # Build OpenAI prompt (same as Python test) + ${prompt}= Catenate SEPARATOR=\n + ... Compare these two lists of memories to determine if they represent content from the same audio source. + ... + ... EXPECTED MEMORIES: + ... ${expected_memories} + ... + ... EXTRACTED MEMORIES: + ... ${actual_memory_texts} + ... + ... Respond in JSON format with: + ... {"similar": true/false, "reason": "brief explanation"} + + # Call OpenAI API + ${headers}= Create Dictionary Authorization=Bearer ${openai_api_key} Content-Type=application/json + ${payload}= Create Dictionary + ... model=gpt-4o-mini + ... messages=${{ [{"role": "user", "content": """${prompt}"""}] }} + ... response_format=${{ {"type": "json_object"} }} + + ${response}= POST https://api.openai.com/v1/chat/completions + ... headers=${headers} + ... json=${payload} + ... expected_status=200 + + ${result_json}= Set Variable ${response.json()} + ${content}= Set Variable ${result_json}[choices][0][message][content] + ${similarity_result}= Evaluate json.loads("""${content}""") json + + Log Memory similarity: ${similarity_result}[similar] INFO + Log Reason: ${similarity_result}[reason] INFO + + RETURN ${similarity_result} + + +Verify Memory Quality With OpenAI + [Documentation] Verify extracted memories match expected memories using OpenAI + [Arguments] ${actual_memories} ${expected_memories} + + # Get OpenAI API key from environment + ${openai_key}= Get Environment Variable OPENAI_API_KEY + + # Check similarity + ${result}= Check Memory Similarity With OpenAI ${actual_memories} ${expected_memories} ${openai_key} + + # Assert memories are similar + Should Be True ${result}[similar] == ${True} + ... Memory similarity check failed: ${result}[reason] + + Log ✅ Memory quality validated INFO diff --git a/tests/resources/queue_keywords.robot b/tests/resources/queue_keywords.robot index 32f8b7fa..3d709661 100644 --- a/tests/resources/queue_keywords.robot +++ b/tests/resources/queue_keywords.robot @@ -59,6 +59,7 @@ Get Job Status Check job status [Documentation] Check the status of a specific job by ID + ... Fails immediately if job is in 'failed' state when expecting 'completed' [Arguments] ${job_id} ${expected_status} ${job}= Get Job status ${job_id} @@ -69,6 +70,12 @@ Check job status ${actual_status}= Set Variable ${job}[status] Log Job ${job_id} status: ${actual_status} (expected: ${expected_status}) + # Fail fast if job is in failed state when we're expecting completed + IF '${actual_status}' == 'failed' and '${expected_status}' == 'completed' + ${error_msg}= Evaluate $job.get('exc_info') or $job.get('error', 'Unknown error') + Fail Job ${job_id} failed: ${error_msg} + END + Should Be Equal As Strings ${actual_status} ${expected_status} Job status is '${actual_status}', expected '${expected_status}' RETURN ${job} diff --git a/tests/run-custom.sh b/tests/run-custom.sh new file mode 100755 index 00000000..c1ce1317 --- /dev/null +++ b/tests/run-custom.sh @@ -0,0 +1,20 @@ +#!/bin/bash +# Quick wrapper for running Robot tests with custom configs +# Usage: ./run-custom.sh [parakeet-url] +# +# Examples: +# ./run-custom.sh parakeet-openai http://host.docker.internal:8767 +# ./run-custom.sh deepgram-openai +# ./run-custom.sh parakeet-ollama http://host.docker.internal:8767 + +set -e + +CONFIG_NAME="${1:-parakeet-openai}" +PARAKEET_URL="${2:-http://host.docker.internal:8767}" + +echo "Running Robot tests with config: ${CONFIG_NAME}" +echo "Parakeet ASR URL: ${PARAKEET_URL}" + +CONFIG_FILE="../tests/configs/${CONFIG_NAME}.yml" \ + PARAKEET_ASR_URL="${PARAKEET_URL}" \ + ./run-robot-tests.sh diff --git a/tests/run-robot-tests.sh b/tests/run-robot-tests.sh index d56adab7..b5af8682 100755 --- a/tests/run-robot-tests.sh +++ b/tests/run-robot-tests.sh @@ -35,6 +35,10 @@ if [ ! -f "Makefile" ] || [ ! -d "endpoints" ]; then exit 1 fi +# Set absolute paths for consistent directory references +TESTS_DIR="$(pwd)" +BACKEND_DIR="$(cd ../backends/advanced && pwd)" + print_info "Robot Framework Test Runner" print_info "============================" @@ -42,6 +46,16 @@ print_info "============================" CLEANUP_CONTAINERS="${CLEANUP_CONTAINERS:-true}" OUTPUTDIR="${OUTPUTDIR:-results}" +# Set default CONFIG_FILE if not provided +# Use test config by default (disables speaker recognition for CI performance) +# Override: CONFIG_FILE=../config/config.yml ./run-robot-tests.sh +export CONFIG_FILE="${CONFIG_FILE:-configs/deepgram-openai.yml}" + +# Convert CONFIG_FILE to absolute path (Docker Compose resolves relative paths from compose file location) +if [[ ! "$CONFIG_FILE" = /* ]]; then + CONFIG_FILE="$(cd "$(dirname "$CONFIG_FILE")" && pwd)/$(basename "$CONFIG_FILE")" +fi + # Load environment variables (CI or local) if [ -f "setup/.env.test" ] && [ -z "$DEEPGRAM_API_KEY" ]; then print_info "Loading environment variables from setup/.env.test..." @@ -69,6 +83,7 @@ fi print_info "DEEPGRAM_API_KEY length: ${#DEEPGRAM_API_KEY}" print_info "OPENAI_API_KEY length: ${#OPENAI_API_KEY}" +print_info "Using config file: $CONFIG_FILE" # Create test environment file if it doesn't exist if [ ! -f "setup/.env.test" ]; then @@ -96,38 +111,42 @@ EOF fi # Navigate to backend directory for docker compose -cd ../backends/advanced +cd "$BACKEND_DIR" print_info "Starting test infrastructure..." +# Use unique project name to avoid conflicts with development environment +export COMPOSE_PROJECT_NAME="advanced-backend-test" + # Ensure required config files exist -if [ ! -f "memory_config.yaml" ] && [ -f "memory_config.yaml.template" ]; then - print_info "Creating memory_config.yaml from template..." - cp memory_config.yaml.template memory_config.yaml -fi +# memory_config.yaml no longer used; memory settings live in config.yml # Clean up any existing test containers and volumes for fresh start print_info "Cleaning up any existing test environment..." -docker compose -f docker-compose-ci.yml down -v 2>/dev/null || true +docker compose -f docker-compose-test.yml down -v 2>/dev/null || true -# Force remove any stuck containers with test names +# Force remove any stuck containers with test names (uses COMPOSE_PROJECT_NAME) print_info "Removing any stuck test containers..." -docker rm -f advanced-mongo-test-1 advanced-redis-test-1 advanced-qdrant-test-1 advanced-friend-backend-test-1 advanced-workers-test-1 advanced-webui-test-1 2>/dev/null || true +# Dynamically construct container names from docker-compose services +TEST_SERVICES=(mongo-test redis-test qdrant-test chronicle-backend-test workers-test webui-test speaker-service-test) +for service in "${TEST_SERVICES[@]}"; do + docker rm -f "${COMPOSE_PROJECT_NAME}-${service}-1" 2>/dev/null || true +done # Start infrastructure services (MongoDB, Redis, Qdrant) print_info "Starting MongoDB, Redis, and Qdrant (fresh containers)..." -docker compose -f docker-compose-ci.yml up -d --quiet-pull mongo-test redis-test qdrant-test +docker compose -f docker-compose-test.yml up -d --quiet-pull mongo-test redis-test qdrant-test # Wait for MongoDB print_info "Waiting for MongoDB (up to 60s)..." for i in {1..30}; do - if docker compose -f docker-compose-ci.yml exec -T mongo-test mongosh --eval "db.adminCommand({ping: 1})" > /dev/null 2>&1; then + if docker compose -f docker-compose-test.yml exec -T mongo-test mongosh --eval "db.adminCommand({ping: 1})" > /dev/null 2>&1; then print_success "MongoDB is ready" break fi if [ $i -eq 30 ]; then print_error "MongoDB failed to start" - docker compose -f docker-compose-ci.yml logs mongo-test + docker compose -f docker-compose-test.yml logs mongo-test exit 1 fi sleep 2 @@ -142,7 +161,7 @@ for i in {1..30}; do fi if [ $i -eq 30 ]; then print_error "Qdrant failed to start" - docker compose -f docker-compose-ci.yml logs qdrant-test + docker compose -f docker-compose-test.yml logs qdrant-test exit 1 fi sleep 2 @@ -150,10 +169,10 @@ done # Build and start backend print_info "Building backend..." -docker compose -f docker-compose-ci.yml build friend-backend-test +docker compose -f docker-compose-test.yml build chronicle-backend-test print_info "Starting backend..." -docker compose -f docker-compose-ci.yml up -d friend-backend-test +docker compose -f docker-compose-test.yml up -d chronicle-backend-test # Wait for backend print_info "Waiting for backend (up to 120s)..." @@ -164,7 +183,7 @@ for i in {1..40}; do fi if [ $i -eq 40 ]; then print_error "Backend failed to start" - docker compose -f docker-compose-ci.yml logs friend-backend-test + docker compose -f docker-compose-test.yml logs chronicle-backend-test exit 1 fi sleep 3 @@ -172,18 +191,18 @@ done # Start workers print_info "Starting RQ workers..." -docker compose -f docker-compose-ci.yml up -d workers-test +docker compose -f docker-compose-test.yml up -d workers-test # Wait for workers container print_info "Waiting for workers container (up to 30s)..." for i in {1..15}; do - if docker compose -f docker-compose-ci.yml ps workers-test | grep -q "Up"; then + if docker compose -f docker-compose-test.yml ps workers-test | grep -q "Up"; then print_success "Workers container is running" break fi if [ $i -eq 15 ]; then print_error "Workers container failed to start" - docker compose -f docker-compose-ci.yml logs workers-test + docker compose -f docker-compose-test.yml logs workers-test exit 1 fi sleep 2 @@ -192,7 +211,7 @@ done # Verify workers are registered print_info "Waiting for workers to register with Redis (up to 60s)..." for i in {1..30}; do - WORKER_COUNT=$(docker compose -f docker-compose-ci.yml exec -T workers-test uv run python -c 'from rq import Worker; from redis import Redis; import os; r = Redis.from_url(os.getenv("REDIS_URL", "redis://redis-test:6379/0")); print(len(Worker.all(connection=r)))' 2>/dev/null || echo "0") + WORKER_COUNT=$(docker compose -f docker-compose-test.yml exec -T workers-test uv run python -c 'from rq import Worker; from redis import Redis; import os; r = Redis.from_url(os.getenv("REDIS_URL", "redis://redis-test:6379/0")); print(len(Worker.all(connection=r)))' 2>/dev/null || echo "0") if [ "$WORKER_COUNT" -ge 6 ]; then print_success "Found $WORKER_COUNT workers registered" @@ -201,7 +220,7 @@ for i in {1..30}; do if [ $i -eq 30 ]; then print_error "Workers failed to register after 60s" - docker compose -f docker-compose-ci.yml logs --tail=50 workers-test + docker compose -f docker-compose-test.yml logs --tail=50 workers-test exit 1 fi @@ -211,16 +230,10 @@ done print_success "All services ready!" # Return to tests directory -cd ../../tests - -# Install Robot Framework dependencies if not in CI -if [ -z "$CI" ]; then - print_info "Installing Robot Framework dependencies..." - uv venv --quiet --python 3.12 || true # May already exist - uv pip install --quiet robotframework robotframework-requests python-dotenv websockets -fi +cd "$TESTS_DIR" # Run Robot Framework tests via Makefile +# Dependencies are handled automatically by 'uv run' in Makefile print_info "Running Robot Framework tests..." print_info "Output directory: $OUTPUTDIR" @@ -234,13 +247,13 @@ fi # Show service logs if tests failed if [ $TEST_EXIT_CODE -ne 0 ]; then print_info "Showing service logs..." - cd ../backends/advanced + cd "$BACKEND_DIR" echo "=== Backend Logs (last 50 lines) ===" - docker compose -f docker-compose-ci.yml logs --tail=50 friend-backend-test + docker compose -f docker-compose-test.yml logs --tail=50 chronicle-backend-test echo "" echo "=== Worker Logs (last 50 lines) ===" - docker compose -f docker-compose-ci.yml logs --tail=50 workers-test - cd ../../tests + docker compose -f docker-compose-test.yml logs --tail=50 workers-test + cd "$TESTS_DIR" fi # Display test results summary @@ -282,16 +295,63 @@ if stats is not None: PYTHON_SCRIPT fi +# Capture container logs before cleanup (always, for debugging) +print_info "Capturing container logs for debugging..." +LOG_DIR="${TESTS_DIR}/${OUTPUTDIR}/container-logs" +mkdir -p "$LOG_DIR" + +cd "$BACKEND_DIR" + +# Capture container status +print_info "Capturing container status..." +docker compose -f docker-compose-test.yml ps > "$LOG_DIR/container-status.txt" 2>&1 || true + +# Capture worker registration status +print_info "Capturing worker registration status..." +docker compose -f docker-compose-test.yml exec -T workers-test uv run python -c ' +from rq import Worker +from redis import Redis +import os + +redis_url = os.getenv("REDIS_URL", "redis://redis-test:6379/0") +r = Redis.from_url(redis_url) +workers = Worker.all(connection=r) + +print(f"Total workers: {len(workers)}") +print(f"\nWorker details:") +for i, worker in enumerate(workers, 1): + print(f" {i}. {worker.name}") + print(f" State: {worker.state}") + print(f" Queues: {[q.name for q in worker.queues]}") + print(f" Current job: {worker.get_current_job()}") + print() +' > "$LOG_DIR/worker-status.txt" 2>&1 || echo "Failed to capture worker status" > "$LOG_DIR/worker-status.txt" + +# Capture logs from all services +print_info "Capturing service logs..." +SERVICES=(chronicle-backend-test workers-test mongo-test redis-test qdrant-test speaker-service-test) +for service in "${SERVICES[@]}"; do + docker compose -f docker-compose-test.yml logs --tail=200 "$service" > "$LOG_DIR/${service}.log" 2>&1 || true +done + +# Capture container resource usage +print_info "Capturing container resource usage..." +docker stats --no-stream --format "table {{.Name}}\t{{.CPUPerc}}\t{{.MemUsage}}\t{{.MemPerc}}\t{{.NetIO}}\t{{.BlockIO}}" > "$LOG_DIR/container-stats.txt" 2>&1 || true + +print_success "Container logs saved to: $LOG_DIR" + +cd "$TESTS_DIR" + # Cleanup test containers if [ "$CLEANUP_CONTAINERS" = "true" ]; then print_info "Cleaning up test containers..." - cd ../backends/advanced - docker compose -f docker-compose-ci.yml down -v - cd ../../tests + cd "$BACKEND_DIR" + docker compose -f docker-compose-test.yml down -v + cd "$TESTS_DIR" print_success "Cleanup complete" else print_warning "Skipping container cleanup (CLEANUP_CONTAINERS=false)" - print_info "To cleanup manually: cd backends/advanced && docker compose -f docker-compose-ci.yml down -v" + print_info "To cleanup manually: cd $BACKEND_DIR && docker compose -f docker-compose-test.yml down -v" fi if [ $TEST_EXIT_CODE -eq 0 ]; then diff --git a/tests/setup/README.md b/tests/setup/README.md index b5ea71c8..3e9ba561 100644 --- a/tests/setup/README.md +++ b/tests/setup/README.md @@ -213,7 +213,7 @@ REBUILD=true robot tests/ CLEANUP_CONTAINERS=false robot tests/endpoints/failing_test.robot # Inspect logs -docker logs advanced-friend-backend-test-1 +docker logs advanced-chronicle-backend-test-1 docker logs advanced-mongo-test-1 # Inspect database diff --git a/tests/setup/setup_keywords.robot b/tests/setup/setup_keywords.robot index 3fe7bd17..656a082d 100644 --- a/tests/setup/setup_keywords.robot +++ b/tests/setup/setup_keywords.robot @@ -85,7 +85,7 @@ Prod Mode Setup Log To Console Tearing down existing containers and volumes... Stop Docker Services remove_volumes=${True} - Run Process rm -rf data/test_mongo_data data/test_qdrant_data data/test_audio_chunks cwd=backends/advanced shell=True + Run Process rm -rf data/test_mongo_data data/test_qdrant_data data/test_audio_chunks cwd=${BACKEND_DIR} shell=True Log To Console Building and starting fresh containers... Start Docker Services build=${True} @@ -95,7 +95,7 @@ Prod Mode Setup Start Docker Services [Documentation] Start Docker services using docker-compose ... Checks if services are already running to avoid redundant starts - [Arguments] ${compose_file}=docker-compose-test.yml ${working_dir}=backends/advanced ${build}=${False} + [Arguments] ${compose_file}=docker-compose-test.yml ${working_dir}=${BACKEND_DIR} ${build}=${False} ${is_up}= Run Keyword And Return Status Check Services Ready ${API_URL} @@ -120,7 +120,7 @@ Start Docker Services Stop Docker Services [Documentation] Stop Docker services using docker-compose - [Arguments] ${compose_file}=docker-compose-test.yml ${working_dir}=backends/advanced ${remove_volumes}=${False} + [Arguments] ${compose_file}=docker-compose-test.yml ${working_dir}=${BACKEND_DIR} ${remove_volumes}=${False} IF ${remove_volumes} Run Process docker compose -f ${compose_file} down -v cwd=${working_dir} shell=True @@ -130,7 +130,7 @@ Stop Docker Services Rebuild Docker Services [Documentation] Rebuild and restart Docker services - [Arguments] ${compose_file}=docker-compose-test.yml ${working_dir}=backends/advanced + [Arguments] ${compose_file}=docker-compose-test.yml ${working_dir}=${BACKEND_DIR} Log To Console Rebuilding containers with latest code... Run Process docker compose -f ${compose_file} up -d --build cwd=${working_dir} shell=True @@ -155,7 +155,7 @@ Start Speaker Recognition Service END Log Starting speaker-recognition-service - Run Process docker compose -f extras/speaker-recognition/docker-compose-test.yml up -d --build shell=True + Run Process docker compose -f docker-compose-test.yml up -d --build cwd=${SPEAKER_RECOGNITION_DIR} shell=True Log Waiting for speaker recognition service to start... Wait Until Keyword Succeeds 60s 5s Check Services Ready ${SPEAKER_RECOGNITION_URL} @@ -166,9 +166,9 @@ Stop Speaker Recognition Service [Arguments] ${remove_volumes}=${False} IF ${remove_volumes} - Run Process docker compose -f extras/speaker-recognition/docker-compose-test.yml down -v shell=True + Run Process docker compose -f docker-compose-test.yml down -v cwd=${SPEAKER_RECOGNITION_DIR} shell=True ELSE - Run Process docker compose -f extras/speaker-recognition/docker-compose-test.yml down shell=True + Run Process docker compose -f docker-compose-test.yml down cwd=${SPEAKER_RECOGNITION_DIR} shell=True END Check Environment Variables diff --git a/tests/setup/teardown_keywords.robot b/tests/setup/teardown_keywords.robot index 4553ad0a..cd4b2b5a 100644 --- a/tests/setup/teardown_keywords.robot +++ b/tests/setup/teardown_keywords.robot @@ -38,7 +38,7 @@ Dev Mode Teardown Log To Console \n=== Dev Mode Teardown (Default) === Log To Console ✓ Keeping containers running for next test run Log To Console Tip: Use 'TEST_MODE=prod' for full cleanup or run manually: - Log To Console docker compose -f backends/advanced/docker-compose-ci.yml down -v + Log To Console docker compose -f ${BACKEND_DIR}/docker-compose-ci.yml down -v # Only delete HTTP sessions Delete All Sessions @@ -52,9 +52,9 @@ Prod Mode Teardown Stop Docker Services remove_volumes=${True} # Clean up any remaining volumes - Run Process rm -rf backends/advanced/data/test_mongo_data shell=True - Run Process rm -rf ${EXECDIR}/backends/advanced/data/test_qdrant_data shell=True - Run Process rm -rf ${EXECDIR}/backends/advanced/data/test_audio_chunks shell=True + Run Process rm -rf ${BACKEND_DIR}/data/test_mongo_data shell=True + Run Process rm -rf ${BACKEND_DIR}/data/test_qdrant_data shell=True + Run Process rm -rf ${BACKEND_DIR}/data/test_audio_chunks shell=True # Delete all HTTP sessions Delete All Sessions diff --git a/tests/setup/test_data.py b/tests/setup/test_data.py index 787f0399..6d73b265 100644 --- a/tests/setup/test_data.py +++ b/tests/setup/test_data.py @@ -36,6 +36,20 @@ # Expected content for transcript quality verification EXPECTED_TRANSCRIPT = "glass blowing" +# Expected memories for DIY Glass Blowing audio (from Python integration test) +# Source: backends/advanced/tests/assets/expected_memories.json +EXPECTED_MEMORIES = [ + "Nick assists significantly in the glass blowing process", + "Excitement and nervousness expressed during the process", + "Furnace contains about 400 pounds of liquid glass", + "Choice of color for the flower is light blue", + "Caitlin is mentioned as a participant", + "Class involves making a trumpet flower", + "Gravity is used as a tool in glass blowing", + "Nick did most of the turning during the demonstration", + "The video is sponsored by Squarespace." +] + # Expected segment timestamps for DIY Glass Blowing audio (4-minute version, 500 chunks) # These are the cropped audio timestamps after silence removal # Updated 2025-01-22 based on actual test output with streaming websocket processing diff --git a/tests/setup/test_env.py b/tests/setup/test_env.py index 929e83e2..94956a14 100644 --- a/tests/setup/test_env.py +++ b/tests/setup/test_env.py @@ -1,30 +1,30 @@ # Test Environment Configuration import os from pathlib import Path +from dotenv import load_dotenv -# Load .env file from backends/advanced directory if it exists -# This allows tests to work when run from VSCode or command line -def load_env_file(): - """Load environment variables from .env file if it exists.""" - # Look for .env in backends/advanced directory - env_file = Path(__file__).parent.parent.parent / "backends" / "advanced" / ".env" - if env_file.exists(): - with open(env_file) as f: - for line in f: - line = line.strip() - if line and not line.startswith('#') and '=' in line: - key, value = line.split('=', 1) - # Only set if not already in environment (CI takes precedence) - if key not in os.environ: - os.environ[key] = value - -# Load .env file (CI environment variables take precedence) -load_env_file() - -# Load .env from backends/advanced directory to get COMPOSE_PROJECT_NAME -backend_env_path = Path(__file__).resolve().parents[2] / "backends" / "advanced" / ".env" -if backend_env_path.exists(): - load_dotenv(backend_env_path, override=False) +# Load environment files with correct precedence: +# 1. Environment variables (highest priority - from shell, CI, etc.) +# 2. .env.test (test-specific configuration) +# 3. .env (default configuration) + +# Find repository root (tests/setup/test_env.py -> go up 2 levels) +REPO_ROOT = Path(__file__).parent.parent.parent +backend_dir = REPO_ROOT / "backends" / "advanced" + +# Export absolute paths for Robot Framework keywords +BACKEND_DIR = str(backend_dir.absolute()) +REPO_ROOT_DIR = str(REPO_ROOT.absolute()) +SPEAKER_RECOGNITION_DIR = str((REPO_ROOT / "extras" / "speaker-recognition").absolute()) + +# Load in reverse order of precedence (since override=False won't overwrite existing vars) +# Load .env.test first (will set test-specific values) +load_dotenv(backend_dir / ".env.test", override=False) + +# Load .env second (will only fill in missing values, won't override .env.test or existing env vars) +load_dotenv(backend_dir / ".env", override=False) + +# Final precedence: environment variables > .env.test > .env # API Configuration API_URL = 'http://localhost:8001' # Use BACKEND_URL from test.env diff --git a/tests/setup/test_manager_keywords.robot b/tests/setup/test_manager_keywords.robot index 65506551..8927994a 100644 --- a/tests/setup/test_manager_keywords.robot +++ b/tests/setup/test_manager_keywords.robot @@ -62,8 +62,8 @@ Clear Test Databases Log To Console Qdrant collections cleared # Clear audio files (except fixtures subfolder) - Run Process bash -c find ${EXECDIR}/backends/advanced/data/test_audio_chunks -maxdepth 1 -name "*.wav" -delete || true shell=True - Run Process bash -c rm -rf ${EXECDIR}/backends/advanced/data/test_debug_dir/* || true shell=True + Run Process bash -c find ${BACKEND_DIR}/data/test_audio_chunks -maxdepth 1 -name "*.wav" -delete || true shell=True + Run Process bash -c rm -rf ${BACKEND_DIR}/data/test_debug_dir/* || true shell=True Log To Console Audio files cleared (fixtures/ subfolder preserved) # Clear container audio files (except fixtures subfolder) @@ -90,8 +90,8 @@ Clear All Test Data Run Process curl -s -X DELETE http://localhost:6337/collections/conversations shell=True # Clear all audio files - Run Process bash -c rm -rf ${EXECDIR}/backends/advanced/data/test_audio_chunks/* || true shell=True - Run Process bash -c rm -rf ${EXECDIR}/backends/advanced/data/test_debug_dir/* || true shell=True + Run Process bash -c rm -rf ${BACKEND_DIR}/data/test_audio_chunks/* || true shell=True + Run Process bash -c rm -rf ${BACKEND_DIR}/data/test_debug_dir/* || true shell=True # Clear all Redis data Run Process docker exec ${REDIS_CONTAINER} redis-cli FLUSHALL shell=True diff --git a/requirements.txt b/tests/test-requirements.txt similarity index 89% rename from requirements.txt rename to tests/test-requirements.txt index 48b8ad96..4efaf39b 100644 --- a/requirements.txt +++ b/tests/test-requirements.txt @@ -3,4 +3,5 @@ robotframework-tidy robotframework-requests robotframework-browser python-dotenv +websockets \ No newline at end of file diff --git a/tests/test_assets/obsidian_dataview_example_vault.zip b/tests/test_assets/obsidian_dataview_example_vault.zip new file mode 100644 index 00000000..8fc6f695 Binary files /dev/null and b/tests/test_assets/obsidian_dataview_example_vault.zip differ diff --git a/wizard.py b/wizard.py index c153cb0f..a2e2b2f7 100755 --- a/wizard.py +++ b/wizard.py @@ -4,10 +4,12 @@ Handles service selection and delegation only - no configuration duplication """ +import shutil import subprocess import sys from datetime import datetime from pathlib import Path +import yaml from dotenv import get_key from rich import print as rprint @@ -150,7 +152,8 @@ def cleanup_unselected_services(selected_services): env_file.rename(backup_file) console.print(f"🧹 [dim]Backed up {service_name} configuration to {backup_file.name} (service not selected)[/dim]") -def run_service_setup(service_name, selected_services, https_enabled=False, server_ip=None): +def run_service_setup(service_name, selected_services, https_enabled=False, server_ip=None, + obsidian_enabled=False, neo4j_password=None): """Execute individual service setup script""" if service_name == 'advanced': service = SERVICES['backend'][service_name] @@ -165,7 +168,11 @@ def run_service_setup(service_name, selected_services, https_enabled=False, serv # Add HTTPS configuration if https_enabled and server_ip: cmd.extend(['--enable-https', '--server-ip', server_ip]) - + + # Add Obsidian configuration + if obsidian_enabled and neo4j_password: + cmd.extend(['--enable-obsidian', '--neo4j-password', neo4j_password]) + else: service = SERVICES['extras'][service_name] cmd = service['cmd'].copy() @@ -308,10 +315,29 @@ def setup_git_hooks(): except Exception as e: console.print(f"⚠️ [yellow]Could not setup git hooks: {e} (optional)[/yellow]") +def setup_config_file(): + """Setup config/config.yml from template if it doesn't exist""" + config_file = Path("config/config.yml") + config_template = Path("config/config.yml.template") + + if not config_file.exists(): + if config_template.exists(): + # Ensure config/ directory exists + config_file.parent.mkdir(parents=True, exist_ok=True) + shutil.copy(config_template, config_file) + console.print("✅ [green]Created config/config.yml from template[/green]") + else: + console.print("⚠️ [yellow]config/config.yml.template not found, skipping config setup[/yellow]") + else: + console.print("ℹ️ [blue]config/config.yml already exists, keeping existing configuration[/blue]") + def main(): """Main orchestration logic""" console.print("🎉 [bold green]Welcome to Chronicle![/bold green]\n") + # Setup config file from template + setup_config_file() + # Setup git hooks first setup_git_hooks() @@ -336,30 +362,78 @@ def main(): if needs_https: console.print("\n🔒 [bold cyan]HTTPS Configuration[/bold cyan]") console.print("HTTPS enables microphone access in browsers and secure connections") - + try: https_enabled = Confirm.ask("Enable HTTPS for selected services?", default=False) except EOFError: console.print("Using default: No") https_enabled = False - + if https_enabled: console.print("\n[blue][INFO][/blue] For distributed deployments, use your Tailscale IP") console.print("[blue][INFO][/blue] For local-only access, use 'localhost'") console.print("Examples: localhost, 100.64.1.2, your-domain.com") - + + # Check for existing SERVER_IP + backend_env_path = 'backends/advanced/.env' + existing_ip = read_env_value(backend_env_path, 'SERVER_IP') + + if existing_ip and existing_ip not in ['localhost', 'your-server-ip-here']: + # Show existing IP with option to reuse + prompt_text = f"Server IP/Domain for SSL certificates ({existing_ip}) [press Enter to reuse, or enter new]" + default_value = existing_ip + else: + prompt_text = "Server IP/Domain for SSL certificates [localhost]" + default_value = "localhost" + while True: try: - server_ip = console.input("Server IP/Domain for SSL certificates [localhost]: ").strip() + server_ip = console.input(f"{prompt_text}: ").strip() if not server_ip: - server_ip = "localhost" + server_ip = default_value break except EOFError: - server_ip = "localhost" + server_ip = default_value break - + console.print(f"[green]✅[/green] HTTPS configured for: {server_ip}") - + + # Obsidian/Neo4j Integration + obsidian_enabled = False + neo4j_password = None + + # Check if advanced backend is selected + if 'advanced' in selected_services: + console.print("\n🗂️ [bold cyan]Obsidian/Neo4j Integration[/bold cyan]") + console.print("Enable graph-based knowledge management for Obsidian vault notes") + console.print() + + try: + obsidian_enabled = Confirm.ask("Enable Obsidian/Neo4j integration?", default=False) + except EOFError: + console.print("Using default: No") + obsidian_enabled = False + + if obsidian_enabled: + console.print("[blue][INFO][/blue] Neo4j will be configured for graph-based memory storage") + console.print() + + # Prompt for Neo4j password + while True: + try: + neo4j_password = console.input("Neo4j password (min 8 chars) [default: neo4jpassword]: ").strip() + if not neo4j_password: + neo4j_password = "neo4jpassword" + if len(neo4j_password) >= 8: + break + console.print("[yellow][WARNING][/yellow] Password must be at least 8 characters") + except EOFError: + neo4j_password = "neo4jpassword" + console.print(f"Using default password") + break + + console.print("[green]✅[/green] Obsidian/Neo4j integration will be configured") + # Pure Delegation - Run Each Service Setup console.print(f"\n📋 [bold]Setting up {len(selected_services)} services...[/bold]") @@ -370,21 +444,48 @@ def main(): failed_services = [] for service in selected_services: - if run_service_setup(service, selected_services, https_enabled, server_ip): + if run_service_setup(service, selected_services, https_enabled, server_ip, + obsidian_enabled, neo4j_password): success_count += 1 else: failed_services.append(service) - + + # Check for Obsidian/Neo4j configuration (read from config.yml) + obsidian_enabled = False + if 'advanced' in selected_services and 'advanced' not in failed_services: + config_yml_path = Path('config/config.yml') + if config_yml_path.exists(): + try: + with open(config_yml_path, 'r') as f: + config_data = yaml.safe_load(f) + obsidian_config = config_data.get('memory', {}).get('obsidian', {}) + obsidian_enabled = obsidian_config.get('enabled', False) + except Exception as e: + console.print(f"[yellow]Warning: Could not read config.yml: {e}[/yellow]") + # Final Summary console.print(f"\n🎊 [bold green]Setup Complete![/bold green]") console.print(f"✅ {success_count}/{len(selected_services)} services configured successfully") - + if failed_services: console.print(f"❌ Failed services: {', '.join(failed_services)}") + + # Inform about Obsidian/Neo4j if configured + if obsidian_enabled: + console.print(f"\n📚 [bold cyan]Obsidian Integration Detected[/bold cyan]") + console.print(" Neo4j will be automatically started with the 'obsidian' profile") + console.print(" when you start the backend service.") # Next Steps console.print("\n📖 [bold]Next Steps:[/bold]") + # Configuration info + console.print("") + console.print("📝 [bold cyan]Configuration Files Updated:[/bold cyan]") + console.print(" • [green].env files[/green] - API keys and service URLs") + console.print(" • [green]config.yml[/green] - Model definitions and memory provider settings") + console.print("") + # Development Environment Setup console.print("1. Setup development environment (git hooks, testing):") console.print(" [cyan]make setup-dev[/cyan]")