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Important Review skippedAuto reviews are disabled on this repository. Please check the settings in the CodeRabbit UI or the You can disable this status message by setting the 📝 WalkthroughWalkthroughThis pull request introduces a complete Obsidian vault ingestion system spanning frontend and backend. It adds a React Native component for vault ingestion, FastAPI endpoints for upload/status tracking, Neo4j integration for graph-based storage, RQ background job processing, chat memory integration, and necessary configuration and utility modules across the stack. Changes
Sequence Diagram(s)sequenceDiagram
actor User
participant FE as Frontend<br/>(Upload UI)
participant API as FastAPI<br/>(Obsidian Routes)
participant Redis
participant RQ as Job Queue<br/>(RQ)
participant ObsService as Obsidian Service
participant Neo4j
User->>FE: Select & upload vault.zip
FE->>API: POST /obsidian/upload_zip
API->>API: Validate & extract ZIP
API->>Redis: Store pending state<br/>(24h expiry)
API-->>FE: Return job_id & vault_path
User->>FE: Click "Start Ingestion"
FE->>API: POST /obsidian/start
API->>Redis: Fetch pending state
API->>RQ: Enqueue ingest_obsidian_vault_job
API-->>FE: Return RQ job_id
loop User Polls Status
FE->>API: GET /obsidian/status?job_id=...
API->>RQ: Check job status
alt Job found in RQ
API->>API: Extract meta (progress, total)
API-->>FE: Return status & progress
else Fallback to Redis
API->>Redis: Get pending state
API-->>FE: Return pending state
end
end
rect rgb(220, 240, 255)
note over RQ,Neo4j: Background Job Processing
RQ->>ObsService: Process each .md file
loop For each Markdown file
ObsService->>ObsService: Parse, chunk, embed
ObsService->>Neo4j: Create Note & Chunk nodes
ObsService->>Neo4j: Create relationships
ObsService->>RQ: Update job meta (progress)
end
ObsService-->>RQ: Job complete with summary
end
sequenceDiagram
actor User
participant ChatUI as Chat UI
participant API as FastAPI<br/>(Chat Routes)
participant ChatSvc as Chat Service
participant ObsidianSvc as Obsidian Service
participant LLM as LLM Provider
User->>ChatUI: Type message<br/>(check "Include Obsidian Memory")
ChatUI->>API: POST /chat/stream<br/>include_obsidian_memory=true
API->>ChatSvc: generate_response_stream(...<br/>include_obsidian_memory=true)
rect rgb(220, 240, 255)
note over ChatSvc,ObsidianSvc: Context Formatting with Obsidian
ChatSvc->>ChatSvc: get_relevant_memories(query)
ChatSvc->>ChatSvc: format_conversation_context(...<br/>include_obsidian_memory=true)
alt include_obsidian_memory is true
ChatSvc->>ObsidianSvc: search_obsidian(query)
ObsidianSvc->>ObsidianSvc: Generate embeddings
ObsidianSvc-->>ChatSvc: Obsidian search results<br/>(source, tags, links)
ChatSvc->>ChatSvc: Merge Obsidian context<br/>with memory context
end
end
ChatSvc->>LLM: generate(...context)
LLM-->>ChatSvc: Streamed response
ChatSvc-->>API: Stream response chunks
API-->>ChatUI: Display response
Estimated code review effort🎯 4 (Complex) | ⏱️ ~60 minutes Possibly related PRs
Suggested reviewers
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Actionable comments posted: 6
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⚠️ Outside diff range comments (1)
status.py (1)
71-71: Remove redundant import inside function.
dotenv_valuesis already imported at the module level (line 21). This local import is redundant and violates the coding guideline that all imports must be at the top of the file.🔎 Proposed fix
# Handle speaker-recognition profiles if service_name == 'speaker-recognition': - from dotenv import dotenv_values env_file = service_path / '.env'As per coding guidelines, ALL imports must be at the top of the file after the docstring.
🧹 Nitpick comments (21)
backends/advanced/webui/src/components/MemorySettings.tsx (1)
224-224: Consider clearing the error state when configuration is modified.When
!!erroris true, both Validate and Save buttons are disabled. However, if the user edits the YAML after an error occurred, they cannot validate/save until they reload. Consider clearing the error whenconfigYamlchanges.🔎 Suggested enhancement
<textarea value={configYaml} - onChange={(e) => setConfigYaml(e.target.value)} + onChange={(e) => { + setConfigYaml(e.target.value) + if (error) setError('') + }} placeholder="Loading configuration..."Also applies to: 242-242
backends/advanced/src/advanced_omi_backend/utils/file_utils.py (1)
66-81: Uselogging.exception()in except blocks to capture stack traces.Based on learnings,
logging.exception()should be used inside except blocks to automatically log the full stack trace, improving debuggability.🔎 Suggested fix
except zipfile.BadZipFile as e: error_msg = f"Invalid zip file: {zip_path} - {e}" - logger.error(error_msg) + logger.exception(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) + logger.exception(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) + logger.exception(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) + logger.exception(error_msg) raise ZipExtractionError(error_msg) from ebackends/advanced/webui/src/pages/Upload.tsx (2)
32-39: Consider defining an interface forobsidianStatusinstead of usingany.Using
anyloses type safety. Based on the API response structure used in lines 509-530, define a proper type.🔎 Suggested type definition
interface ObsidianIngestionStatus { status: 'pending' | 'processing' | 'completed' | 'failed' processed: number total: number percent: number last_file?: string errors?: string[] error?: string } // Then replace: const [obsidianStatus, setObsidianStatus] = useState<ObsidianIngestionStatus | null>(null)
479-485: Consider adding a Cancel button for in-progress ingestion.The
obsidianApi.cancel(jobId)endpoint exists (perapi.tslines 229-246) but isn't exposed in the UI. Users may want to cancel a long-running ingestion.backends/advanced/src/advanced_omi_backend/chat_service.py (1)
336-345: Uselogging.exception()and bareraisefor proper error handling.Based on learnings, use
logging.exception()to automatically capture stack traces. Also, use bareraiseinstead ofraise eto preserve the original traceback.🔎 Suggested fix
except ObsidianSearchError as exc: - logger.error( + logger.exception( "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 + logger.exception(f"Failed to get Obsidian context: {e}") + raisebackends/advanced/src/advanced_omi_backend/services/neo4j_client.py (1)
15-18: Consider thread safety for lazy driver initialization.If multiple threads call
get_driver()simultaneously on first access, multiple drivers could be created. For single-threaded async usage this is fine, but if used in threaded contexts, consider adding a lock.🔎 Thread-safe alternative (if needed)
import threading class Neo4jClient: def __init__(self, uri: str, user: str, password: str): self.uri = uri self.auth = (user, password) self._driver: Optional[Driver] = None self._lock = threading.Lock() def get_driver(self) -> Driver: if not self._driver: with self._lock: if not self._driver: # Double-check pattern self._driver = GraphDatabase.driver(self.uri, auth=self.auth) return self._driverwizard.py (1)
400-410: Remove unnecessary f-string prefixes.Lines 400 and 408 use f-strings without any placeholders. These should be regular strings for clarity and to avoid confusion.
As per coding guidelines:
🔎 Proposed fix
- console.print(f"\n🎊 [bold green]Setup Complete![/bold green]") + console.print("\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("\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.")backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py (1)
283-285: Uselogging.exception()and chain the exception for better debuggability.Per project conventions, prefer
logging.exception()in except blocks to capture the full stack trace automatically. Also chain the exception withraise ... from eto preserve context.🔎 Proposed fix
except Exception as e: - memory_logger.error(f"OpenAI embedding generation failed: {e}") - raise + memory_logger.exception(f"OpenAI embedding generation failed: {e}") + raise RuntimeError(f"OpenAI embedding generation failed: {e}") from eBased on learnings, in Python code (chronicle project), prefer
logging.exception()inside except blocks to automatically log the full stack trace, and chain withraise ... from eto preserve context.app/app/components/ObsidianIngest.tsx (1)
1-3: Remove leading empty line and unused import.Line 1 has an unnecessary empty line, and
ActivityIndicatoris imported but never used in the component's render output.🔎 Proposed fix
- import React, { useState } from 'react'; -import { View, Text, TextInput, TouchableOpacity, StyleSheet, Alert, ActivityIndicator } from 'react-native'; +import { View, Text, TextInput, TouchableOpacity, StyleSheet, Alert } from 'react-native';Alternatively, if you want to show a spinner while loading, use the
ActivityIndicator:<TouchableOpacity style={[styles.button, loading ? styles.buttonDisabled : null]} onPress={handleIngest} disabled={loading} > + {loading && <ActivityIndicator color="white" style={{ marginRight: 8 }} />} <Text style={styles.buttonText}> {loading ? 'Starting Ingestion...' : 'Ingest to Neo4j'} </Text> </TouchableOpacity>backends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.py (3)
17-25: Rename unused loop variable.In
count_markdown_files, therootvariable is not used within the loop body. Rename to_rootto indicate intentional non-use.🔎 Proposed fix
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): + 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
46-51: Remove redundant exception object fromlogging.exception()call.When using
logging.exception(), the exception info is automatically included. Passingexcexplicitly is redundant.🔎 Proposed fix
except Exception as exc: - logger.exception("Database setup failed for job %s: %s", job.id, exc) + logger.exception("Database setup failed for job %s", job.id) job.meta["status"] = "failed" job.meta["error"] = f"Database setup failed: {exc}" job.save_meta() raise
93-97: Uselogging.exception()for full stack trace in error handling.Per project conventions, use
logging.exception()instead oflogging.error()inside except blocks to automatically capture the full stack trace.🔎 Proposed fix
except Exception as exc: - logger.error("Processing %s failed: %s", filename, exc) + logger.exception("Processing %s failed", filename) errors.append(f"{filename}: {exc}") job.meta["errors"] = errors job.save_meta()Based on learnings, prefer
logging.exception()inside except blocks to automatically log the full stack trace.backends/advanced/src/advanced_omi_backend/services/obsidian_service.py (4)
108-114: Redundant validation afterget_model_configwhich already raises.The
get_model_configutility (per the relevant code snippets) already raisesValueErrorif the config is not found. These additional checks are redundant and will never trigger.🔎 Proposed fix
# 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")
283-293: Fix logging and addstrict=Truetozip()for safety.
logging.exception()already includes the exception - no need to append{e}zip()withoutstrict=Truecan silently drop items if list lengths mismatch🔎 Proposed fix
except Exception as e: - logger.exception(f"Embedding generation failed for {note_data['path']}: {e}") + logger.exception(f"Embedding generation failed for {note_data['path']}") return [] chunk_payloads: List[ChunkPayload] = [] - for orig_text, vector in zip(original_chunks, vectors): + for orig_text, vector in zip(original_chunks, vectors, strict=True):
406-451: Uselogging.exception()in except blocks for full stack traces.Per project conventions, prefer
logging.exception()inside except blocks to automatically log the full stack trace. The exception chaining withfrom exc/from eis correct.🔎 Proposed fix
except Exception as exc: - logger.error("Obsidian search embedding failed: %s", exc) + logger.exception("Obsidian search embedding failed") raise ObsidianSearchError("embedding", str(exc)) from excexcept Exception as e: - logger.error(f"Obsidian search failed: {e}") + logger.exception("Obsidian search failed") raise ObsidianSearchError("database", str(e)) from eBased on learnings, prefer
logging.exception()inside except blocks.
381-384: Minor: Use!sconversion flag instead ofstr().🔎 Proposed fix
except Exception as e: logger.exception(f"Processing {file} failed") - errors.append(f"{file}: {str(e)}") + errors.append(f"{file}: {e!s}")backends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.py (3)
46-48: Uselogging.exception()and chain the exception.Per project conventions, use
logging.exception()for automatic stack traces and chain exceptions when re-raising.🔎 Proposed fix
except Exception as e: - logger.error(f"Ingestion failed: {e}") - raise HTTPException(status_code=500, detail=str(e)) + logger.exception("Ingestion failed") + raise HTTPException(status_code=500, detail=str(e)) from eBased on learnings, prefer
logging.exception()and exception chaining.
78-93: Improve exception handling with proper chaining and logging.Multiple exception handlers need
logging.exception()and exception chaining per project conventions.🔎 Proposed fix
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}") + logger.exception(f"Error writing zip file {zip_path}") + raise HTTPException(status_code=500, detail=f"Failed to save uploaded zip: {e}") from 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}") + logger.exception("Invalid zip file") + raise HTTPException(status_code=400, detail=f"Invalid zip file: {e}") from 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}") + logger.exception("Error extracting zip file") + raise HTTPException(status_code=500, detail=f"Failed to extract zip file: {e}") from eBased on learnings, prefer
logging.exception()and exception chaining.
151-166: Add exception chaining when raising HTTPException.🔎 Proposed fix
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}") + logger.exception(f"Failed to start job {job_id}") + raise HTTPException(status_code=500, detail=f"Failed to start job: {e}") from 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") + raise HTTPException(status_code=404, detail="Job not found") from NoneBased on learnings, chain exceptions. Use
from NoneforNoSuchJobErrorsince the 404 response intentionally suppresses the original context.backends/advanced/src/advanced_omi_backend/services/memory/config.py (2)
101-102: Use explicitOptionaltype annotation.PEP 484 prohibits implicit
Optional. UseOptional[str]orstr | Noneexplicitly.🔎 Proposed fix
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: Optional[str] = None, timeout: int = 30, **kwargs ) -> Dict[str, Any]:
311-315: Use bareraiseto preserve the original traceback.Using
raise eresets the traceback to this line. Bareraisepreserves the full original traceback.🔎 Proposed fix
except Exception as e: memory_logger.exception( f"Failed to get embedding dimensions from registry for model '{embedding_model}'" ) - raise e + raise
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⛔ Files ignored due to path filters (2)
backends/advanced/uv.lockis excluded by!**/*.locktests/test_assets/obsidian_dataview_example_vault.zipis excluded by!**/*.zip
📒 Files selected for processing (29)
app/app/components/ObsidianIngest.tsxapp/app/index.tsxbackends/advanced/docker-compose.ymlbackends/advanced/pyproject.tomlbackends/advanced/src/advanced_omi_backend/chat_service.pybackends/advanced/src/advanced_omi_backend/controllers/system_controller.pybackends/advanced/src/advanced_omi_backend/llm_client.pybackends/advanced/src/advanced_omi_backend/routers/api_router.pybackends/advanced/src/advanced_omi_backend/routers/modules/__init__.pybackends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.pybackends/advanced/src/advanced_omi_backend/routers/modules/health_routes.pybackends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.pybackends/advanced/src/advanced_omi_backend/routers/modules/system_routes.pybackends/advanced/src/advanced_omi_backend/services/memory/config.pybackends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.pybackends/advanced/src/advanced_omi_backend/services/neo4j_client.pybackends/advanced/src/advanced_omi_backend/services/obsidian_service.pybackends/advanced/src/advanced_omi_backend/utils/config_utils.pybackends/advanced/src/advanced_omi_backend/utils/file_utils.pybackends/advanced/src/advanced_omi_backend/utils/model_utils.pybackends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.pybackends/advanced/tests/test_obsidian_service.pybackends/advanced/webui/src/components/MemorySettings.tsxbackends/advanced/webui/src/pages/Chat.tsxbackends/advanced/webui/src/pages/Upload.tsxbackends/advanced/webui/src/services/api.tsservices.pystatus.pywizard.py
💤 Files with no reviewable changes (1)
- backends/advanced/src/advanced_omi_backend/controllers/system_controller.py
🧰 Additional context used
📓 Path-based instructions (2)
**/*.py
📄 CodeRabbit inference engine (CLAUDE.md)
**/*.py: Use Black formatter with 100-character line length for Python code
Use isort for Python import organization
ALL imports must be at the top of the file after the docstring - never import modules in the middle of functions or files
Group imports in Python files: standard library, third-party, then local imports
Use lazy imports sparingly and only when absolutely necessary for circular import issues in Python
Always raise errors in Python, never silently ignore - use explicit error handling with proper exceptions rather than silent failures
Avoid defensivehasattr()checks in Python - research and understand input/response or class structure instead
Files:
services.pybackends/advanced/src/advanced_omi_backend/utils/file_utils.pybackends/advanced/src/advanced_omi_backend/routers/modules/__init__.pybackends/advanced/src/advanced_omi_backend/utils/config_utils.pybackends/advanced/src/advanced_omi_backend/utils/model_utils.pybackends/advanced/src/advanced_omi_backend/routers/api_router.pybackends/advanced/src/advanced_omi_backend/services/obsidian_service.pybackends/advanced/src/advanced_omi_backend/llm_client.pybackends/advanced/src/advanced_omi_backend/chat_service.pybackends/advanced/tests/test_obsidian_service.pybackends/advanced/src/advanced_omi_backend/routers/modules/health_routes.pybackends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.pybackends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.pybackends/advanced/src/advanced_omi_backend/services/memory/config.pybackends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.pybackends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.pystatus.pybackends/advanced/src/advanced_omi_backend/routers/modules/system_routes.pywizard.pybackends/advanced/src/advanced_omi_backend/services/neo4j_client.py
app/**/*.{ts,tsx}
📄 CodeRabbit inference engine (CLAUDE.md)
Use TypeScript following standard React Native conventions for mobile app development
Files:
app/app/index.tsxapp/app/components/ObsidianIngest.tsx
🧠 Learnings (1)
📚 Learning: 2025-12-08T23:52:34.959Z
Learnt from: AnkushMalaker
Repo: chronicler-ai/chronicle PR: 178
File: backends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py:218-223
Timestamp: 2025-12-08T23:52:34.959Z
Learning: In Python code (chronicle project), prefer logging.exception() inside except blocks to automatically log the full stack trace. When re-raising exceptions, always chain with 'raise ... from e' to preserve the original context; use 'raise ... from None' only if you explicitly want to suppress the context. This improves debuggability across Python files.
Applied to files:
services.pybackends/advanced/src/advanced_omi_backend/utils/file_utils.pybackends/advanced/src/advanced_omi_backend/routers/modules/__init__.pybackends/advanced/src/advanced_omi_backend/utils/config_utils.pybackends/advanced/src/advanced_omi_backend/utils/model_utils.pybackends/advanced/src/advanced_omi_backend/routers/api_router.pybackends/advanced/src/advanced_omi_backend/services/obsidian_service.pybackends/advanced/src/advanced_omi_backend/llm_client.pybackends/advanced/src/advanced_omi_backend/chat_service.pybackends/advanced/tests/test_obsidian_service.pybackends/advanced/src/advanced_omi_backend/routers/modules/health_routes.pybackends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.pybackends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.pybackends/advanced/src/advanced_omi_backend/services/memory/config.pybackends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.pybackends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.pystatus.pybackends/advanced/src/advanced_omi_backend/routers/modules/system_routes.pywizard.pybackends/advanced/src/advanced_omi_backend/services/neo4j_client.py
🧬 Code graph analysis (11)
app/app/index.tsx (1)
app/app/components/ObsidianIngest.tsx (1)
ObsidianIngest(10-91)
backends/advanced/src/advanced_omi_backend/services/obsidian_service.py (5)
backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py (2)
generate_openai_embeddings(75-91)chunk_text_with_spacy(102-155)backends/advanced/src/advanced_omi_backend/services/memory/config.py (1)
load_config_yml(67-83)backends/advanced/src/advanced_omi_backend/utils/model_utils.py (1)
get_model_config(11-45)backends/advanced/src/advanced_omi_backend/utils/config_utils.py (1)
resolve_value(7-20)backends/advanced/src/advanced_omi_backend/services/neo4j_client.py (5)
Neo4jClient(7-32)close(26-29)reset(31-32)session(20-24)session(42-43)
backends/advanced/src/advanced_omi_backend/llm_client.py (3)
backends/advanced/src/advanced_omi_backend/services/memory/config.py (1)
load_config_yml(67-83)backends/advanced/init.py (1)
load_config_yml(129-143)backends/advanced/src/advanced_omi_backend/utils/config_utils.py (1)
resolve_value(7-20)
backends/advanced/webui/src/pages/Chat.tsx (1)
backends/advanced/webui/src/services/api.ts (1)
chatApi(250-289)
backends/advanced/src/advanced_omi_backend/chat_service.py (4)
backends/advanced/src/advanced_omi_backend/services/memory/base.py (1)
MemoryEntry(26-63)backends/advanced/src/advanced_omi_backend/services/obsidian_service.py (3)
get_obsidian_service(460-469)ObsidianSearchError(56-61)search_obsidian(387-453)backends/advanced/src/advanced_omi_backend/models/user.py (1)
user_id(71-73)backends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.py (1)
get_session_messages(240-281)
backends/advanced/tests/test_obsidian_service.py (1)
backends/advanced/src/advanced_omi_backend/services/obsidian_service.py (5)
ObsidianSearchError(56-61)search_obsidian(387-453)setup_database(165-184)chunking_and_embedding(246-294)ingest_note_and_chunks(296-345)
backends/advanced/webui/src/components/MemorySettings.tsx (1)
backends/advanced/webui/src/contexts/AuthContext.tsx (1)
useAuth(115-121)
backends/advanced/webui/src/pages/Upload.tsx (1)
backends/advanced/webui/src/services/api.ts (1)
obsidianApi(230-247)
backends/advanced/src/advanced_omi_backend/services/memory/config.py (4)
backends/advanced/src/advanced_omi_backend/model_registry.py (1)
get_models_registry(338-353)backends/advanced/src/advanced_omi_backend/utils/config_utils.py (1)
resolve_value(7-20)backends/advanced/src/advanced_omi_backend/models/conversation.py (1)
MemoryProvider(29-34)backends/advanced/init.py (1)
load_config_yml(129-143)
backends/advanced/src/advanced_omi_backend/routers/modules/system_routes.py (1)
backends/advanced/src/advanced_omi_backend/controllers/system_controller.py (2)
get_memory_config_raw(257-277)update_memory_config_raw(280-315)
backends/advanced/src/advanced_omi_backend/services/neo4j_client.py (1)
backends/advanced/src/advanced_omi_backend/services/obsidian_service.py (1)
close(157-159)
🪛 Ruff (0.14.10)
backends/advanced/src/advanced_omi_backend/utils/file_utils.py
65-65: Consider moving this statement to an else block
(TRY300)
68-68: Use logging.exception instead of logging.error
Replace with exception
(TRY400)
72-72: Use logging.exception instead of logging.error
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(TRY400)
76-76: Use logging.exception instead of logging.error
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(TRY400)
80-80: Use logging.exception instead of logging.error
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(TRY400)
backends/advanced/src/advanced_omi_backend/utils/model_utils.py
39-39: Avoid specifying long messages outside the exception class
(TRY003)
45-45: Avoid specifying long messages outside the exception class
(TRY003)
backends/advanced/src/advanced_omi_backend/services/obsidian_service.py
110-110: Avoid specifying long messages outside the exception class
(TRY003)
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(TRY003)
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284-284: Redundant exception object included in logging.exception call
(TRY401)
288-288: zip() without an explicit strict= parameter
Add explicit value for parameter strict=
(B905)
318-318: Probable use of insecure hash functions in hashlib: md5
(S324)
363-363: Avoid specifying long messages outside the exception class
(TRY003)
383-383: Use explicit conversion flag
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(RUF010)
407-407: Use logging.exception instead of logging.error
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(TRY400)
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(TRY400)
backends/advanced/src/advanced_omi_backend/chat_service.py
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(TRY400)
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(TRY400)
345-345: Use raise without specifying exception name
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(TRY201)
backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py
97-97: Undefined name _load_root_config
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105-105: Undefined name _resolve_value
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(TRY201)
backends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.py
34-34: Unused function argument: current_user
(ARG001)
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(B008)
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(TRY300)
46-46: Do not catch blind exception: Exception
(BLE001)
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(TRY400)
48-48: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
53-53: Do not perform function call File in argument defaults; instead, perform the call within the function, or read the default from a module-level singleton variable
(B008)
54-54: Unused function argument: current_user
(ARG001)
54-54: Do not perform function call Depends in argument defaults; instead, perform the call within the function, or read the default from a module-level singleton variable
(B008)
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Replace with exception
(TRY400)
83-83: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
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(B008)
150-150: Consider moving this statement to an else block
(TRY300)
152-152: Redundant exception object included in logging.exception call
(TRY401)
153-153: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
166-166: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
170-170: Unused function argument: current_user
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(B008)
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(B904)
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(B904)
backends/advanced/src/advanced_omi_backend/services/memory/config.py
83-83: Avoid specifying long messages outside the exception class
(TRY003)
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Convert to T | None
(RUF013)
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(TRY201)
backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py
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(TRY400)
backends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.py
20-20: Loop control variable root not used within loop body
Rename unused root to _root
(B007)
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status.py
60-60: Local variable dotenv_values referenced before assignment
(F823)
backends/advanced/src/advanced_omi_backend/routers/modules/system_routes.py
88-88: Unused function argument: current_user
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(B008)
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(ARG001)
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wizard.py
400-400: f-string without any placeholders
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(F541)
408-408: f-string without any placeholders
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(F541)
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🔇 Additional comments (37)
backends/advanced/pyproject.toml (2)
13-13: LGTM! New dependencies for Obsidian/Neo4j integration.The
neo4j>=5.0.0,<6.0.0andhttpx>=0.28.0,<1.0.0dependencies are properly version-constrained and align with the new Obsidian ingestion and Neo4j graph storage features.Also applies to: 21-21
59-59: PR #3250 async fix is merged into main. The commit "Improve async handling in AsyncMemory class for better performance (#3250)" (dated 2025-08-12) is present in the main branch, along with subsequent AsyncMemory improvements. Theasync-client-unbound-var-fixbranch no longer exists, confirming the fix has been integrated. The dependency change is safe.backends/advanced/webui/src/components/MemorySettings.tsx (2)
134-136: LGTM! Correct placement of admin check after hooks.The early return is properly placed after all hook calls (
useState,useEffect,useAuth), which complies with React's Rules of Hooks.
34-42: Good improvement: Granular error handling for different HTTP status codes.Distinguishing between 401 (unauthorized), 404/405 (missing endpoints), and other errors provides clearer feedback to administrators.
backends/advanced/webui/src/pages/Upload.tsx (1)
190-212: LGTM! Polling logic with proper cleanup.The useEffect correctly clears the interval on unmount or when dependencies change. The polling stops appropriately when status is 'completed' or 'failed'.
backends/advanced/src/advanced_omi_backend/routers/modules/system_routes.py (1)
86-90: LGTM! Updated docstrings clarify config.yml usage.The docstring updates accurately reflect that configuration is managed via
config.yml.backends/advanced/src/advanced_omi_backend/chat_service.py (2)
287-287: LGTM! Return type updated toList[MemoryEntry]with correct attribute access.The change from
List[Dict]toList[MemoryEntry]is correctly reflected in attribute access patterns (.id,.contentinstead of.get()).Also applies to: 310-310, 319-319
324-335: Obsidian integration correctly retrieves and formats context.The integration properly handles the search result structure and formats entries into the context with appropriate logging.
backends/advanced/src/advanced_omi_backend/services/neo4j_client.py (2)
7-33: LGTM! Clean lazy initialization pattern for Neo4j driver.The driver is created on first use and properly closed/reset. The
close()method handles the None case correctly.
45-53: Note:run()eagerly consumes results, which may not suit all use cases.The comment at lines 48-49 correctly documents this limitation. For queries returning large result sets, callers should use
session()directly. This is a good design with clear documentation.app/app/index.tsx (1)
31-31: LGTM! Clean integration of Obsidian ingestion UI.The import and conditional rendering of the ObsidianIngest component follows the existing patterns in the file. Properly gated by authentication status and receives the necessary props (backendUrl and jwtToken) for API communication.
Also applies to: 542-548
backends/advanced/src/advanced_omi_backend/routers/api_router.py (1)
18-18: LGTM! Obsidian router properly integrated.The obsidian_router import and registration follow the established pattern for other routers in this module. Import is correctly placed at the top with other router imports, and the include_router call maintains consistency with the existing structure.
Also applies to: 38-38
backends/advanced/webui/src/pages/Chat.tsx (2)
47-47: LGTM! State initialization follows React conventions.The boolean state for controlling Obsidian memory inclusion is properly initialized with a sensible default (false).
519-531: LGTM! Clean checkbox implementation for Obsidian memory.The checkbox UI properly binds to the state variable and provides clear labeling for users. The implementation follows React patterns and integrates well with the existing input area layout.
services.py (1)
77-86: LGTM! Obsidian profile activation logic is sound.The conditional profile activation for Neo4j/Obsidian integration follows the same pattern as the HTTPS profile handling. The placeholder detection correctly handles both hyphen and underscore variants.
backends/advanced/src/advanced_omi_backend/routers/modules/__init__.py (1)
23-23: LGTM! Module exports properly updated.The obsidian_router import and all export follow the established pattern and maintain alphabetical ordering with other router modules.
Also applies to: 36-36
wizard.py (1)
390-397: LGTM! Obsidian configuration detection logic is sound.The code properly detects Neo4j/Obsidian configuration by checking the .env file and validating that NEO4J_HOST is set to a non-placeholder value. The logic correctly gates on successful advanced backend setup.
backends/advanced/src/advanced_omi_backend/utils/config_utils.py (1)
1-20: LGTM! Clean and well-designed utility function.The
resolve_valuefunction correctly implements environment variable resolution with default value support. The logic handles edge cases appropriately (e.g., multiple:-occurrences viasplit(":-", 1)), and the implementation follows Python best practices with proper type hints and documentation.backends/advanced/src/advanced_omi_backend/llm_client.py (2)
59-62: LGTM! Config-driven initialization aligns with new architecture.The removal of environment variable fallbacks in favor of explicit parameter passing aligns with the registry/config.yml-based configuration approach. The comment clearly documents this design decision, and the subsequent validation (line 63) ensures all required parameters are provided.
12-15: Remove unused imports on lines 14-15.The imports
_load_root_configand_resolve_valueare not used anywhere in the file. Remove them per coding guidelines.backends/advanced/src/advanced_omi_backend/utils/model_utils.py (1)
1-46: LGTM!Clean utility function with proper error handling. The descriptive error messages (flagged by TRY003) are appropriate here for debugging configuration issues—creating custom exception classes would be over-engineering for this simple use case.
backends/advanced/src/advanced_omi_backend/routers/modules/chat_routes.py (2)
33-34: LGTM!Clean addition of the optional
include_obsidian_memoryfield with a sensible default ofFalse, ensuring backward compatibility.
310-315: LGTM!The new parameter is correctly propagated to the chat service's streaming response generator.
backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py (1)
75-91: LGTM!Well-structured async helper function that centralizes embedding generation with Langfuse tracing support. This enables reuse across the codebase (e.g., ObsidianService).
status.py (1)
48-67: LGTM!Good logic for detecting Obsidian profile eligibility by checking for a valid NEO4J_HOST value (excluding placeholder strings). The multi-profile support allows combining
httpsandobsidianprofiles correctly.backends/advanced/tests/test_obsidian_service.py (3)
1-57: LGTM!Well-structured test setup with comprehensive mocking of external dependencies (config, embeddings, Neo4j, environment). The use of
addCleanupensures proper teardown.
58-105: LGTM!Thorough test of the search flow—verifies embedding generation, Cypher query execution with correct parameters, and result formatting including tags and links.
166-189: LGTM!Good coverage of error paths. Tests correctly verify that
ObsidianSearchErroris raised with appropriate stage values ('embedding' vs 'database') for different failure scenarios.backends/advanced/docker-compose.yml (1)
178-199: LGTM on Neo4j service configuration.Good setup with:
- APOC plugins enabled with proper security allowlists
- Reasonable memory limits (512m–2G heap)
- Data persistence via volumes
- Conditional startup via
obsidianprofileapp/app/components/ObsidianIngest.tsx (1)
17-59: LGTM!Clean implementation with proper validation, URL normalization for WebSocket URLs, authentication handling, and appropriate user feedback via Alerts. The loading state management is correct.
backends/advanced/src/advanced_omi_backend/workers/obsidian_jobs.py (2)
28-42: LGTM on job structure and meta tracking.Good implementation with proper job meta initialization and persistence. The
job_idandredis_clientparameters are likely required by the@async_jobdecorator contract, so the unused argument warnings are false positives.
74-80: Good cancellation support.Nice pattern for checking job cancellation status mid-processing, allowing graceful termination of long-running vault ingestion jobs.
backends/advanced/webui/src/services/api.ts (2)
230-247: LGTM! Clean API implementation following existing patterns.The
obsidianApiobject correctly mirrors the file upload pattern fromuploadApi, with appropriate timeout (5 minutes) for large vault uploads and proper progress tracking. The endpoint structure aligns with the backend routes.
271-278: LGTM! Optional parameter handling is correct.The
includeObsidianMemoryparameter is properly handled as optional, only adding it to the request body when truthy.backends/advanced/src/advanced_omi_backend/services/obsidian_service.py (1)
317-318: MD5 usage is acceptable here for non-security chunk ID generation.The static analysis flags MD5 as insecure, but this is a false positive - MD5 is being used for deterministic chunk identification (path + index), not for cryptographic security. This pattern is appropriate for content-addressable storage keys.
backends/advanced/src/advanced_omi_backend/services/memory/config.py (2)
67-83: LGTM! Clean config loading with proper fallback paths.The function correctly handles multiple config locations (Docker container, relative paths, current directory) and provides a helpful error message listing all searched paths when not found.
115-147: LGTM! Well-structured configuration factory functions.Both
create_openai_configandcreate_qdrant_configfollow good patterns with clear defaults and appropriate use of keyword-only arguments.
backends/advanced/docker-compose.yml
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| neo4j-mem0: | ||
| condition: service_started |
Contributor
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🧩 Analysis chain
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#!/bin/bash
# First, check the file exists and read the relevant sections
if [ -f "backends/advanced/docker-compose.yml" ]; then
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sed -n '35,50p' backends/advanced/docker-compose.yml | cat -n
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fiRepository: chronicler-ai/chronicle
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🌐 Web query:
Docker Compose profiles with depends_on - how does it handle dependencies on profiled services
💡 Result:
Short answer
- Docker Compose only includes services whose profiles are active (services without profiles are always included). If a service depends_on another service that's excluded by profiles, the model is invalid and Compose may error. [1][2]
- If you explicitly target a profiled service on the command line, Compose auto-enables that service's profile (so its own depends_on entries that are included will be started). Compose does NOT automatically enable profiles required by its dependencies — those dependencies must be either unprofiled, share the same profile, or have their profile enabled explicitly. [1][2]
Practical rules
- Keep core deps unprofiled, or
- Put dependent services and their dependencies in the same profile, or
- Enable needed profiles via --profile or COMPOSE_PROFILES when you run up. [1][2]
Sources
[1] Docker Docs — Using profiles with Compose.
[2] Docker Compose file reference — profiles (Compose reference).
Unconditional dependency on profiled service will cause startup failure.
The chronicle-backend service depends unconditionally on neo4j-mem0, but neo4j-mem0 is only started when the obsidian profile is active. Docker Compose does not automatically enable profiles required by a service's dependencies, so running docker compose up without --profile obsidian will fail because the dependency is not satisfied.
Options to fix:
- Add
profiles: [obsidian]tochronicle-backendso both services share the same profile, or - Remove
neo4j-mem0from the profiles list to make it always available, or - Require users to explicitly enable the profile via
--profile obsidianorCOMPOSE_PROFILES=obsidian.
🤖 Prompt for AI Agents
In backends/advanced/docker-compose.yml around lines 41-42, chronicle-backend
currently lists neo4j-mem0 as a dependency but neo4j-mem0 is only started under
the obsidian profile, causing startup failures when the profile is not enabled;
fix by making the dependency available under the same profile—add profiles:
[obsidian] to the chronicle-backend service so both services share the obsidian
profile (alternatively, remove neo4j-mem0 from profiles to make it always
available or update docs to require running with --profile
obsidian/COMPOSE_PROFILES=obsidian).
Collaborator
Author
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@coderabbitai Require users to explicitly enable the profile via --profile obsidian or COMPOSE_PROFILES=obsidian.
yeah third one is what I want. So? how do i make it work with the ./wizard.sh and init flows?
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@AnkushMalaker Good news - the infrastructure is already in place! Your scripts already auto-detect and enable the obsidian profile. Here's how it works:
Current Workflow (Already Implemented ✅)
-
User runs wizard/init:
./wizard.sh
-
User configures NEO4J settings in
.env:NEO4J_HOST=neo4j-mem0 NEO4J_USER=neo4j NEO4J_PASSWORD=your_password
-
services.pyauto-detects and enables profile:- When starting backend, it checks if
NEO4J_HOSTis set and not a placeholder - Automatically adds
--profile obsidianto the docker compose command - Both
chronicle-backendandneo4j-mem0start together
- When starting backend, it checks if
-
wizard.pyshows confirmation:- Detects Obsidian config after setup
- Prints: "📚 Obsidian Integration Detected"
The One Issue: Direct Docker Compose Usage
The only problem is if someone runs docker compose up directly (bypassing your scripts), they'll hit the error because of the unconditional depends_on.
Solution: Make neo4j-mem0 Dependency Conditional
Update the depends_on section in docker-compose.yml:
depends_on:
qdrant:
condition: service_started
mongo:
condition: service_healthy
redis:
condition: service_healthy
# Remove neo4j-mem0 from here - it's optional and controlled by profileThen add a note in your documentation or startup scripts that neo4j-mem0 will only start when:
- NEO4J_HOST is configured in
.env - The obsidian profile is enabled (automatically by
services.py)
Alternative: Keep Current Setup + Documentation
If you want to keep the unconditional dependency, just document that users must use your scripts:
# ✅ Correct way (uses services.py which handles profiles)
./wizard.sh
# or
python services.py start backend
# ❌ Don't do this (will fail if profile not enabled)
docker compose upVerification
Your system already works! Test it:
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#!/bin/bash
# Show that services.py already handles the profile
echo "=== services.py obsidian profile handling ==="
rg -n "Enable obsidian profile" backends/advanced/services.py -C 3
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cat backends/advanced/.env.template | rg "NEO4J" -A 1 -B 1
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echo "=== Find services.py location ==="
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rg -n "Enable obsidian profile" services.py -C 3
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rg -n "obsidian" services.py -C 5 -i
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Perfect! Now I can see the complete picture. Your system already works correctly! 🎉
Summary: How It Already Works### The Workflow That's Already Implemented:
-
User runs wizard:
./wizard.sh # or ./init.sh -
User configures NEO4J in
.env:- During setup or manually edit
backends/advanced/.env - Sets
NEO4J_HOST=neo4j-mem0
- During setup or manually edit
-
services.pyauto-enables obsidian profile:- Lines 78-86 detect
NEO4J_HOSTis set - Automatically add
--profile obsidianto docker compose command - Both
chronicle-backendANDneo4j-mem0start together ✅
- Lines 78-86 detect
-
wizard.pyconfirms to user:- Lines 406-410 show: "📚 Obsidian Integration Detected"
- Tells user Neo4j will start automatically
The Problem & Solution
Problem: The unconditional depends_on: neo4j-mem0 in docker-compose.yml will cause failures if someone runs docker compose up directly (bypassing your services.py script).
Recommended Solution: Remove neo4j-mem0 from the unconditional depends_on list:
# In backends/advanced/docker-compose.yml
depends_on:
qdrant:
condition: service_started
mongo:
condition: service_healthy
redis:
condition: service_healthy
# neo4j-mem0: <-- REMOVE THIS
# condition: service_startedWhy This Works:
-
Through scripts (recommended path):
- User runs
./wizard.sh→ configures.env→services.pyautomatically adds--profile obsidian - Both services start together because the profile pulls in neo4j-mem0
- User runs
-
Direct docker compose (edge case):
- If someone runs
docker compose updirectly WITHOUT the profile:- chronicle-backend starts normally
- neo4j-mem0 doesn't start (because profile not enabled)
- No error! Backend just runs without Obsidian features
- If someone runs
-
With NEO4J configured:
- User runs
python services.py start backend - Script detects NEO4J_HOST → adds
--profile obsidian - Both services start correctly
- User runs
Documentation Update
Add this to your docs or README:
## Obsidian Integration
The Obsidian/Neo4j integration is **automatically enabled** when you:
1. Set `NEO4J_HOST` in `backends/advanced/.env`
2. Start services via the wizard or `python services.py start backend`
**✅ Recommended (handles profiles automatically):**
```bash
./wizard.sh # Initial setup
python services.py start backend # Start backend
# Or use shortcuts
./services.sh start advanced # If you have service shortcuts# If you must use docker compose directly:
cd backends/advanced
docker compose --profile obsidian up -d
# Or set environment variable:
COMPOSE_PROFILES=obsidian docker compose up -dThe wizard and services scripts automatically detect your Obsidian configuration and enable the profile for you.
## Summary
**You don't need to change anything in your scripts!** Your wizard.sh and init flows already handle this correctly via `services.py`.
The only change needed is:
1. **Remove** the unconditional `depends_on: neo4j-mem0` from docker-compose.yml (it's redundant since the profile handles the relationship)
2. **Document** that users should use your scripts (not raw docker compose)
Your infrastructure is solid! 🚀
<!-- This is an auto-generated reply by CodeRabbit -->
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| # Load model config once for display fields | ||
| try: | ||
| _cfg = _load_root_config() or {} | ||
| _defaults = _cfg.get("defaults", {}) or {} | ||
| _models = _cfg.get("models", []) or [] | ||
| _llm_name = _defaults.get("llm") | ||
| _stt_name = _defaults.get("stt") | ||
| _llm_def = next((m for m in _models if m.get("name") == _llm_name), None) | ||
| _llm_provider = (_llm_def.get("model_provider") if _llm_def else None) or "openai" | ||
| _llm_model = str(_resolve_value(_llm_def.get("model_name", ""))) if _llm_def else None | ||
| _llm_base_url = str(_resolve_value(_llm_def.get("model_url", ""))) if _llm_def else None | ||
| except Exception as e: | ||
| _llm_provider, _llm_model, _llm_base_url, _stt_name = "openai", None, None, None | ||
| raise e |
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Critical: Undefined functions _load_root_config and _resolve_value will cause runtime NameError.
These functions are called but never defined or imported. The /health endpoint will fail with NameError when accessed.
Additionally, the exception handling is inconsistent: it sets fallback values but then immediately re-raises the exception, so the fallback values are never used.
🔎 Suggested fix options
Option 1: Import the missing functions if they exist elsewhere:
+from advanced_omi_backend.services.memory.config import _load_root_config, _resolve_valueOption 2: If fallback behavior is intended, remove the re-raise:
except Exception as e:
_llm_provider, _llm_model, _llm_base_url, _stt_name = "openai", None, None, None
- raise e
+ logger.warning(f"Failed to load model config, using defaults: {e}")Committable suggestion skipped: line range outside the PR's diff.
🧰 Tools
🪛 Ruff (0.14.10)
97-97: Undefined name _load_root_config
(F821)
104-104: Undefined name _resolve_value
(F821)
105-105: Undefined name _resolve_value
(F821)
108-108: Use raise without specifying exception name
Remove exception name
(TRY201)
🤖 Prompt for AI Agents
In backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py
around lines 95 to 108, the code calls _load_root_config and _resolve_value but
those functions are not defined or imported (causing NameError at runtime) and
the except block sets fallback values then re-raises the exception (making
fallbacks useless); fix by importing or defining _load_root_config and
_resolve_value at the top of the module (or replace calls with the correct
functions from their source), and if fallbacks are intended remove the raise in
the except block so the fallback values are used (or alternatively keep the
raise but remove the fallback assignments) to make behavior consistent.
Comment on lines
+221
to
+223
| except: | ||
| raise HTTPException(status_code=500, detail="Failed to get job status") | ||
| raise HTTPException(status_code=404, detail="Job not found") |
Contributor
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Replace bare except with specific exception type.
Bare except catches all exceptions including KeyboardInterrupt and SystemExit, making debugging difficult. Catch the specific exception you expect.
🔎 Proposed fix
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")
+ except json.JSONDecodeError as e:
+ raise HTTPException(status_code=500, detail="Failed to get job status") from e
+ raise HTTPException(status_code=404, detail="Job not found") from None🧰 Tools
🪛 Ruff (0.14.10)
221-221: Do not use bare except
(E722)
222-222: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
223-223: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
🤖 Prompt for AI Agents
In backends/advanced/src/advanced_omi_backend/routers/modules/obsidian_routes.py
around lines 221 to 223, the code uses a bare except which should be replaced
with a specific exception handler; identify the exception(s) that can be raised
by the job lookup (e.g., KeyError, LookupError, or the client-specific
exception), catch those explicitly (e.g., except KeyError as e or except
ClientError as e), and propagate a 500 HTTPException including the captured
exception message for diagnostics; avoid catching
BaseException/SystemExit/KeyboardInterrupt and ensure any unexpected exceptions
bubble up or are logged separately.
backends/advanced/src/advanced_omi_backend/routers/modules/system_routes.py
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|
|
||
| // Send message and handle streaming response | ||
| const response = await chatApi.sendMessage(messageText, sessionId) | ||
| const response = await chatApi.sendMessage(messageText, sessionId, includeObsidian) |
Contributor
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🧩 Analysis chain
🏁 Script executed:
# First, let's check the sendMessage function definition and calls
rg -n -A 3 'sendMessage.*includeObsidian' --type=tsRepository: chronicler-ai/chronicle
Length of output: 832
🏁 Script executed:
# Also check the Chat.tsx file around line 203
cat -n backends/advanced/webui/src/pages/Chat.tsx | sed -n '200,210p'Repository: chronicler-ai/chronicle
Length of output: 527
🏁 Script executed:
# Check the API definition in api.ts around lines 249-288
cat -n backends/advanced/webui/src/services/api.ts | sed -n '245,290p'Repository: chronicler-ai/chronicle
Length of output: 2134
🏁 Script executed:
# Search for the definition of includeObsidian in Chat.tsx
rg -n 'includeObsidian' backends/advanced/webui/src/pages/Chat.tsxRepository: chronicler-ai/chronicle
Length of output: 457
Align variable name with API parameter for code clarity.
The variable includeObsidian passed at Chat.tsx:203 does not match the API parameter name includeObsidianMemory defined in api.ts:271. While positional arguments work at runtime, rename the variable to includeObsidianMemory to maintain naming consistency and avoid confusion about what "Obsidian" refers to in this context.
🤖 Prompt for AI Agents
In backends/advanced/webui/src/pages/Chat.tsx around line 203, the call passes
includeObsidian to chatApi.sendMessage while the API parameter is named
includeObsidianMemory; rename the local variable (and its declarations/usages)
from includeObsidian to includeObsidianMemory so the argument name matches the
API parameter for clarity, update any references (state, props, handlers) in
this file to the new name, and ensure imports/exports or prop types are updated
accordingly to avoid type/compile errors.
|
| Metric | Count |
|---|---|
| ✅ Passed | 82 |
| ❌ Failed | 9 |
| 📊 Total | 91 |
📊 View Reports
GitHub Pages (Live Reports):
Download Artifacts:
- robot-test-reports-html - HTML reports
- robot-test-results-xml - XML output
- Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation. - Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input. - Adjusted the API call in the frontend to point to the new validation endpoint.
- Updated the health check function to load model configuration from the models registry instead of the root config. - Improved error handling by logging warnings when model configuration loading fails.
|
| Metric | Count |
|---|---|
| ✅ Passed | 83 |
| ❌ Failed | 8 |
| 📊 Total | 91 |
📊 View Reports
GitHub Pages (Live Reports):
Download Artifacts:
- robot-test-reports-html - HTML reports
- robot-test-results-xml - XML output
🎉 Robot Framework Test ResultsStatus: ✅ All tests passed!
📊 View ReportsGitHub Pages (Live Reports): Download Artifacts:
|
Collaborator
Author
|
Merging with commits from #222 |
Merged
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added a commit
that referenced
this pull request
Jan 3, 2026
* audio upload extension with gdrive credentials * FIX: API parameters * UPDATE: tmp files cleanup n code refactored as per review * REFACTOR: minor refactor as per review * REFACTOR: minor update as per review * UPDATE: gdrive sync logic * REFACTOR: code update as per gdrive and update credential client * REFACTOR: validation updated - as per review from CR * UPDATE: code has been refactore for UUID for diffrent audio upload sources * REFACTOR: updated code as per review * Update documentation and configuration to reflect the transition from 'friend-backend' to 'chronicle-backend' across various files, including setup instructions, Docker configurations, and service logs. * Update test script to use docker-compose-test.yml for all test-related operations * Added standard MIT license * Fix/cleanup model (#219) * refactor memory * add config * docstring * more cleanup * code quality * code quality * unused return * DOTTED GET * Refactor Docker and CI configurations - Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process. - Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services. - Added new dependencies for Google API clients in `uv.lock` to support upcoming features. * Update configuration files for model providers and Docker setup - Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram. - Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving. - Updated memory configuration endpoint to accept plain text for YAML input. * Update transcription job handling to format speaker IDs - Changed variable name from `speaker_name` to `speaker_id` for clarity. - Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling. * Remove loading of backend .env file in test environment setup - Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests. * Enhance configuration management and setup wizard - Updated README to reflect the new setup wizard process. - Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers. - Improved user feedback during configuration updates, including success messages for configuration file updates. - Enabled backup of existing `config.yml` before saving changes. * Enhance HTTPS configuration in setup wizard - Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates. - Improved user prompts for server IP/domain input during HTTPS setup. - Updated default behavior to use existing IP or localhost based on user input. - Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access. * Add source parameter to audio file writing in websocket controller - Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * fix/broken-tests (#230) * refactor memory * add config * docstring * more cleanup * code quality * code quality * unused return * DOTTED GET * Refactor Docker and CI configurations - Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process. - Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services. - Added new dependencies for Google API clients in `uv.lock` to support upcoming features. * Update configuration files for model providers and Docker setup - Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram. - Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving. - Updated memory configuration endpoint to accept plain text for YAML input. * Update transcription job handling to format speaker IDs - Changed variable name from `speaker_name` to `speaker_id` for clarity. - Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling. * Remove loading of backend .env file in test environment setup - Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests. * Enhance configuration management and setup wizard - Updated README to reflect the new setup wizard process. - Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers. - Improved user feedback during configuration updates, including success messages for configuration file updates. - Enabled backup of existing `config.yml` before saving changes. * Enhance HTTPS configuration in setup wizard - Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates. - Improved user prompts for server IP/domain input during HTTPS setup. - Updated default behavior to use existing IP or localhost based on user input. - Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access. * Add source parameter to audio file writing in websocket controller - Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking. * Refactor error handling in system controller and update memory config routes - Replaced ValueError with HTTPException for better error handling in `save_diarization_settings` and `validate_memory_config` functions. - Introduced a new Pydantic model, `MemoryConfigRequest`, for validating memory configuration requests in the system routes. - Updated the `validate_memory_config` endpoint to accept the new request model, improving input handling and validation. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * Feat/add obsidian 3 (#233) * obsidian support * neo4j comment * cleanup code * unused line * unused line * Fix MemoryEntry object usage in chat service * comment * feat(obsidian): add obsidian memory search integration to chat * unit test * use rq * neo4j service * typefix * test fix * cleanup * cleanup * version changes * profile * remove unused imports * Refactor memory configuration validation endpoints - Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation. - Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input. - Adjusted the API call in the frontend to point to the new validation endpoint. * Refactor health check model configuration loading - Updated the health check function to load model configuration from the models registry instead of the root config. - Improved error handling by logging warnings when model configuration loading fails. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * Update .gitignore to exclude all files in app/ios and app/android directories (#238) * fix: Copy full source code in speaker-recognition Dockerfile (#243) Adds COPY src/ src/ step after dependency installation to ensure all source files are available in the Docker image. This improves build caching while ensuring complete source code is present. * Enhance configuration management and add new setup scripts (#235) * Enhance configuration management and add new setup scripts - Updated .gitignore to include config.yml and its template. - Added config.yml.template for default configuration settings. - Introduced restart.sh script for service management. - Enhanced services.py to load config.yml and check for Obsidian/Neo4j integration. - Updated wizard.py to prompt for Obsidian/Neo4j configuration during setup and create config.yml from template if it doesn't exist. * Refactor transcription providers and enhance configuration management - Updated Docker Compose files to include the new Neo4j service configuration. - Added support for Obsidian/Neo4j integration in the setup process. - Refactored transcription providers to utilize a registry-driven approach for Deepgram and Parakeet. - Enhanced error handling and logging in transcription processes. - Improved environment variable management in test scripts to prioritize command-line overrides. - Removed deprecated Parakeet provider implementation and streamlined audio stream workers. * Update configuration management and enhance file structure, add test-matrix (#237) * Update configuration management and enhance file structure - Refactored configuration file paths to use a dedicated `config/` directory, including updates to `config.yml` and its template. - Modified service scripts to load the new configuration path for `config.yml`. - Enhanced `.gitignore` to include the new configuration files and templates. - Updated documentation to reflect changes in configuration file locations and usage. - Improved setup scripts to ensure proper creation and management of configuration files. - Added new test configurations for various provider combinations to streamline testing processes. * Add test requirements and clean up imports in wizard.py - Introduced a new `test-requirements.txt` file to manage testing dependencies. - Removed redundant import of `shutil` in `wizard.py` to improve code clarity. * Add ConfigManager for unified configuration management - Introduced a new `config_manager.py` module to handle reading and writing configurations from `config.yml` and `.env` files, ensuring backward compatibility. - Refactored `ChronicleSetup` in `backends/advanced/init.py` to utilize `ConfigManager` for loading and updating configurations, simplifying the setup process. - Removed redundant methods for loading and saving `config.yml` directly in `ChronicleSetup`, as these are now managed by `ConfigManager`. - Enhanced user feedback during configuration updates, including success messages for changes made to configuration files. * Refactor transcription provider configuration and enhance setup process - Updated `.env.template` to clarify speech-to-text configuration and removed deprecated options for Mistral. - Modified `docker-compose.yml` to streamline environment variable management by removing unused Mistral keys. - Enhanced `ChronicleSetup` in `init.py` to provide clearer user feedback and updated the transcription provider selection process to rely on `config.yml`. - Improved error handling in the websocket controller to determine the transcription provider from the model registry instead of environment variables. - Updated health check routes to reflect the new method of retrieving the transcription provider from `config.yml`. - Adjusted `config.yml.template` to include comments on transcription provider options for better user guidance. * Enhance ConfigManager with deep merge functionality - Updated the `update_memory_config` method to perform a deep merge of updates into the memory configuration, ensuring nested dictionaries are merged correctly. - Added a new `_deep_merge` method to handle recursive merging of dictionaries, improving configuration management capabilities. * Refactor run-test.sh and enhance memory extraction tests - Removed deprecated environment variable handling for TRANSCRIPTION_PROVIDER in `run-test.sh`, streamlining the configuration process. - Introduced a new `run-custom.sh` script for executing Robot tests with custom configurations, improving test flexibility. - Enhanced memory extraction tests in `audio_keywords.robot` and `memory_keywords.robot` to include detailed assertions and result handling. - Updated `queue_keywords.robot` to fail fast if a job is in a 'failed' state when expecting 'completed', improving error handling. - Refactored `test_env.py` to load environment variables with correct precedence, ensuring better configuration management. * unify tests to robot test, add some more clean up * Update health check configuration in docker-compose-test.yml (#241) - Increased the number of retries from 5 to 10 for improved resilience during service readiness checks. - Extended the start period from 30s to 60s to allow more time for services to initialize before health checks commence. * Add step to create test configuration file in robot-tests.yml - Introduced a new step in the GitHub Actions workflow to copy the test configuration file from tests/configs/deepgram-openai.yml to a new config/config.yml. - Added logging to confirm the creation of the test config file, improving visibility during the test setup process. * remove cache step since not required * coderabbit comments * Refactor ConfigManager error handling for configuration file loading - Updated the ConfigManager to raise RuntimeError exceptions when the configuration file is not found or is invalid, improving error visibility and user guidance. - Removed fallback behavior that previously returned the current directory, ensuring users are explicitly informed about missing or invalid configuration files. * Refactor _find_repo_root method in ConfigManager - Updated the _find_repo_root method to locate the repository root using the __file__ location instead of searching for config/config.yml, simplifying the logic and improving reliability. - Removed the previous error handling that raised a RuntimeError if the configuration file was not found, as the new approach assumes config_manager.py is always at the repo root. * Enhance speaker recognition service integration and error handling (#245) * Enhance speaker recognition service integration and error handling - Updated `docker-compose-test.yml` to enable speaker recognition in the test environment and added a new `speaker-service-test` service for testing purposes. - Refactored `run-test.sh` to improve the execution of Robot Framework tests from the repository root. - Enhanced error handling in `speaker_recognition_client.py` to return detailed error messages for connection issues. - Improved error logging in `speaker_jobs.py` to handle and report errors from the speaker recognition service more effectively. - Updated `Dockerfile` to copy the full source code after dependencies are cached, ensuring all necessary files are included in the image. * Remove integration tests workflow and enhance robot tests with HF_TOKEN verification - Deleted the `integration-tests.yml` workflow file to streamline CI processes. - Updated `robot-tests.yml` to include verification for the new `HF_TOKEN` secret, ensuring all required secrets are checked before running tests. * Fix key access in system admin tests to use string indexing for speakers data * Refactor Robot Framework tests and enhance error handling in memory services - Removed the creation of the test environment file from the GitHub Actions workflow to streamline setup. - Updated the Robot Framework tests to utilize a unified test script for improved consistency. - Enhanced error messages in the MemoryService class to provide more context on connection failures for LLM and vector store providers. - Added critical checks for API key presence in the OpenAIProvider class to ensure valid credentials are provided before proceeding. - Adjusted various test setup scripts to use a centralized BACKEND_DIR variable for better maintainability and clarity. * Refactor test container cleanup in run-robot-tests.sh - Updated the script to dynamically construct container names from docker-compose services, improving maintainability and reducing hardcoded values. - Enhanced the cleanup process for stuck test containers by utilizing the COMPOSE_PROJECT_NAME variable. * Enhance run-robot-tests.sh for improved logging and cleanup - Set absolute paths for consistent directory references to simplify navigation. - Capture container logs, status, and resource usage for better debugging. - Refactor cleanup process to utilize dynamic backend directory references, improving maintainability. - Ensure proper navigation back to the tests directory after operations. * Add speaker recognition configuration and update test script defaults - Introduced speaker recognition settings in config.yml.template, allowing for easy enable/disable and service URL configuration. - Updated run-robot-tests.sh to use a test-specific configuration file that disables speaker recognition for improved CI performance. - Modified deepgram-openai.yml to disable speaker recognition during CI tests to enhance execution speed. * Refactor speaker recognition configuration management - Updated docker-compose-test.yml to clarify speaker recognition settings, now controlled via config.yml for improved CI performance. - Enhanced model_registry.py to include a dedicated speaker_recognition field for better configuration handling. - Modified speaker_recognition_client.py to load configuration from config.yml, allowing for dynamic enabling/disabling of the speaker recognition service based on the configuration. * Add minimum worker count verification to infrastructure tests - Introduced a new keyword to verify that the minimum number of workers are registered, enhancing the robustness of health checks. - Updated the worker count validation test to include a wait mechanism for worker registration, improving test reliability. - Clarified comments regarding expected worker counts to reflect the distinction between RQ and audio stream workers. * Update configuration management and enhance model handling - Added OBSIDIAN_ENABLED configuration to ChronicleSetup for improved feature toggling. - Introduced speaker_recognition configuration handling in model_registry.py to streamline model loading. - Refactored imports in deepgram.py to improve clarity and reduce redundancy. * Refactor configuration management in wizard and ChronicleSetup (#246) * Refactor configuration management in wizard and ChronicleSetup - Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling. - Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth. - Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers. * Fix string formatting for error message in ChronicleSetup --------- Co-authored-by: 01PrathamS <pratham21btai35@karnavatiuniversity.edu.in> Co-authored-by: Stu Alexandere <thestumonkey@gmail.com> Co-authored-by: Stuart Alexander <stu@theawesome.co.uk> Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
AnkushMalaker
added a commit
that referenced
this pull request
Jan 6, 2026
* audio upload extension with gdrive credentials * FIX: API parameters * UPDATE: tmp files cleanup n code refactored as per review * REFACTOR: minor refactor as per review * REFACTOR: minor update as per review * UPDATE: gdrive sync logic * REFACTOR: code update as per gdrive and update credential client * REFACTOR: validation updated - as per review from CR * UPDATE: code has been refactore for UUID for diffrent audio upload sources * REFACTOR: updated code as per review * Update documentation and configuration to reflect the transition from 'friend-backend' to 'chronicle-backend' across various files, including setup instructions, Docker configurations, and service logs. * Update test script to use docker-compose-test.yml for all test-related operations * Added standard MIT license * Fix/cleanup model (#219) * refactor memory * add config * docstring * more cleanup * code quality * code quality * unused return * DOTTED GET * Refactor Docker and CI configurations - Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process. - Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services. - Added new dependencies for Google API clients in `uv.lock` to support upcoming features. * Update configuration files for model providers and Docker setup - Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram. - Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving. - Updated memory configuration endpoint to accept plain text for YAML input. * Update transcription job handling to format speaker IDs - Changed variable name from `speaker_name` to `speaker_id` for clarity. - Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling. * Remove loading of backend .env file in test environment setup - Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests. * Enhance configuration management and setup wizard - Updated README to reflect the new setup wizard process. - Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers. - Improved user feedback during configuration updates, including success messages for configuration file updates. - Enabled backup of existing `config.yml` before saving changes. * Enhance HTTPS configuration in setup wizard - Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates. - Improved user prompts for server IP/domain input during HTTPS setup. - Updated default behavior to use existing IP or localhost based on user input. - Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access. * Add source parameter to audio file writing in websocket controller - Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * fix/broken-tests (#230) * refactor memory * add config * docstring * more cleanup * code quality * code quality * unused return * DOTTED GET * Refactor Docker and CI configurations - Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process. - Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services. - Added new dependencies for Google API clients in `uv.lock` to support upcoming features. * Update configuration files for model providers and Docker setup - Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram. - Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving. - Updated memory configuration endpoint to accept plain text for YAML input. * Update transcription job handling to format speaker IDs - Changed variable name from `speaker_name` to `speaker_id` for clarity. - Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling. * Remove loading of backend .env file in test environment setup - Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests. * Enhance configuration management and setup wizard - Updated README to reflect the new setup wizard process. - Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers. - Improved user feedback during configuration updates, including success messages for configuration file updates. - Enabled backup of existing `config.yml` before saving changes. * Enhance HTTPS configuration in setup wizard - Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates. - Improved user prompts for server IP/domain input during HTTPS setup. - Updated default behavior to use existing IP or localhost based on user input. - Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access. * Add source parameter to audio file writing in websocket controller - Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking. * Refactor error handling in system controller and update memory config routes - Replaced ValueError with HTTPException for better error handling in `save_diarization_settings` and `validate_memory_config` functions. - Introduced a new Pydantic model, `MemoryConfigRequest`, for validating memory configuration requests in the system routes. - Updated the `validate_memory_config` endpoint to accept the new request model, improving input handling and validation. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * Feat/add obsidian 3 (#233) * obsidian support * neo4j comment * cleanup code * unused line * unused line * Fix MemoryEntry object usage in chat service * comment * feat(obsidian): add obsidian memory search integration to chat * unit test * use rq * neo4j service * typefix * test fix * cleanup * cleanup * version changes * profile * remove unused imports * Refactor memory configuration validation endpoints - Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation. - Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input. - Adjusted the API call in the frontend to point to the new validation endpoint. * Refactor health check model configuration loading - Updated the health check function to load model configuration from the models registry instead of the root config. - Improved error handling by logging warnings when model configuration loading fails. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * Update .gitignore to exclude all files in app/ios and app/android directories (#238) * fix: Copy full source code in speaker-recognition Dockerfile (#243) Adds COPY src/ src/ step after dependency installation to ensure all source files are available in the Docker image. This improves build caching while ensuring complete source code is present. * Enhance configuration management and add new setup scripts (#235) * Enhance configuration management and add new setup scripts - Updated .gitignore to include config.yml and its template. - Added config.yml.template for default configuration settings. - Introduced restart.sh script for service management. - Enhanced services.py to load config.yml and check for Obsidian/Neo4j integration. - Updated wizard.py to prompt for Obsidian/Neo4j configuration during setup and create config.yml from template if it doesn't exist. * Refactor transcription providers and enhance configuration management - Updated Docker Compose files to include the new Neo4j service configuration. - Added support for Obsidian/Neo4j integration in the setup process. - Refactored transcription providers to utilize a registry-driven approach for Deepgram and Parakeet. - Enhanced error handling and logging in transcription processes. - Improved environment variable management in test scripts to prioritize command-line overrides. - Removed deprecated Parakeet provider implementation and streamlined audio stream workers. * Update configuration management and enhance file structure, add test-matrix (#237) * Update configuration management and enhance file structure - Refactored configuration file paths to use a dedicated `config/` directory, including updates to `config.yml` and its template. - Modified service scripts to load the new configuration path for `config.yml`. - Enhanced `.gitignore` to include the new configuration files and templates. - Updated documentation to reflect changes in configuration file locations and usage. - Improved setup scripts to ensure proper creation and management of configuration files. - Added new test configurations for various provider combinations to streamline testing processes. * Add test requirements and clean up imports in wizard.py - Introduced a new `test-requirements.txt` file to manage testing dependencies. - Removed redundant import of `shutil` in `wizard.py` to improve code clarity. * Add ConfigManager for unified configuration management - Introduced a new `config_manager.py` module to handle reading and writing configurations from `config.yml` and `.env` files, ensuring backward compatibility. - Refactored `ChronicleSetup` in `backends/advanced/init.py` to utilize `ConfigManager` for loading and updating configurations, simplifying the setup process. - Removed redundant methods for loading and saving `config.yml` directly in `ChronicleSetup`, as these are now managed by `ConfigManager`. - Enhanced user feedback during configuration updates, including success messages for changes made to configuration files. * Refactor transcription provider configuration and enhance setup process - Updated `.env.template` to clarify speech-to-text configuration and removed deprecated options for Mistral. - Modified `docker-compose.yml` to streamline environment variable management by removing unused Mistral keys. - Enhanced `ChronicleSetup` in `init.py` to provide clearer user feedback and updated the transcription provider selection process to rely on `config.yml`. - Improved error handling in the websocket controller to determine the transcription provider from the model registry instead of environment variables. - Updated health check routes to reflect the new method of retrieving the transcription provider from `config.yml`. - Adjusted `config.yml.template` to include comments on transcription provider options for better user guidance. * Enhance ConfigManager with deep merge functionality - Updated the `update_memory_config` method to perform a deep merge of updates into the memory configuration, ensuring nested dictionaries are merged correctly. - Added a new `_deep_merge` method to handle recursive merging of dictionaries, improving configuration management capabilities. * Refactor run-test.sh and enhance memory extraction tests - Removed deprecated environment variable handling for TRANSCRIPTION_PROVIDER in `run-test.sh`, streamlining the configuration process. - Introduced a new `run-custom.sh` script for executing Robot tests with custom configurations, improving test flexibility. - Enhanced memory extraction tests in `audio_keywords.robot` and `memory_keywords.robot` to include detailed assertions and result handling. - Updated `queue_keywords.robot` to fail fast if a job is in a 'failed' state when expecting 'completed', improving error handling. - Refactored `test_env.py` to load environment variables with correct precedence, ensuring better configuration management. * unify tests to robot test, add some more clean up * Update health check configuration in docker-compose-test.yml (#241) - Increased the number of retries from 5 to 10 for improved resilience during service readiness checks. - Extended the start period from 30s to 60s to allow more time for services to initialize before health checks commence. * Add step to create test configuration file in robot-tests.yml - Introduced a new step in the GitHub Actions workflow to copy the test configuration file from tests/configs/deepgram-openai.yml to a new config/config.yml. - Added logging to confirm the creation of the test config file, improving visibility during the test setup process. * remove cache step since not required * coderabbit comments * Refactor ConfigManager error handling for configuration file loading - Updated the ConfigManager to raise RuntimeError exceptions when the configuration file is not found or is invalid, improving error visibility and user guidance. - Removed fallback behavior that previously returned the current directory, ensuring users are explicitly informed about missing or invalid configuration files. * Refactor _find_repo_root method in ConfigManager - Updated the _find_repo_root method to locate the repository root using the __file__ location instead of searching for config/config.yml, simplifying the logic and improving reliability. - Removed the previous error handling that raised a RuntimeError if the configuration file was not found, as the new approach assumes config_manager.py is always at the repo root. * Enhance speaker recognition service integration and error handling (#245) * Enhance speaker recognition service integration and error handling - Updated `docker-compose-test.yml` to enable speaker recognition in the test environment and added a new `speaker-service-test` service for testing purposes. - Refactored `run-test.sh` to improve the execution of Robot Framework tests from the repository root. - Enhanced error handling in `speaker_recognition_client.py` to return detailed error messages for connection issues. - Improved error logging in `speaker_jobs.py` to handle and report errors from the speaker recognition service more effectively. - Updated `Dockerfile` to copy the full source code after dependencies are cached, ensuring all necessary files are included in the image. * Remove integration tests workflow and enhance robot tests with HF_TOKEN verification - Deleted the `integration-tests.yml` workflow file to streamline CI processes. - Updated `robot-tests.yml` to include verification for the new `HF_TOKEN` secret, ensuring all required secrets are checked before running tests. * Fix key access in system admin tests to use string indexing for speakers data * Refactor Robot Framework tests and enhance error handling in memory services - Removed the creation of the test environment file from the GitHub Actions workflow to streamline setup. - Updated the Robot Framework tests to utilize a unified test script for improved consistency. - Enhanced error messages in the MemoryService class to provide more context on connection failures for LLM and vector store providers. - Added critical checks for API key presence in the OpenAIProvider class to ensure valid credentials are provided before proceeding. - Adjusted various test setup scripts to use a centralized BACKEND_DIR variable for better maintainability and clarity. * Refactor test container cleanup in run-robot-tests.sh - Updated the script to dynamically construct container names from docker-compose services, improving maintainability and reducing hardcoded values. - Enhanced the cleanup process for stuck test containers by utilizing the COMPOSE_PROJECT_NAME variable. * Enhance run-robot-tests.sh for improved logging and cleanup - Set absolute paths for consistent directory references to simplify navigation. - Capture container logs, status, and resource usage for better debugging. - Refactor cleanup process to utilize dynamic backend directory references, improving maintainability. - Ensure proper navigation back to the tests directory after operations. * Add speaker recognition configuration and update test script defaults - Introduced speaker recognition settings in config.yml.template, allowing for easy enable/disable and service URL configuration. - Updated run-robot-tests.sh to use a test-specific configuration file that disables speaker recognition for improved CI performance. - Modified deepgram-openai.yml to disable speaker recognition during CI tests to enhance execution speed. * Refactor speaker recognition configuration management - Updated docker-compose-test.yml to clarify speaker recognition settings, now controlled via config.yml for improved CI performance. - Enhanced model_registry.py to include a dedicated speaker_recognition field for better configuration handling. - Modified speaker_recognition_client.py to load configuration from config.yml, allowing for dynamic enabling/disabling of the speaker recognition service based on the configuration. * Add minimum worker count verification to infrastructure tests - Introduced a new keyword to verify that the minimum number of workers are registered, enhancing the robustness of health checks. - Updated the worker count validation test to include a wait mechanism for worker registration, improving test reliability. - Clarified comments regarding expected worker counts to reflect the distinction between RQ and audio stream workers. * Update configuration management and enhance model handling - Added OBSIDIAN_ENABLED configuration to ChronicleSetup for improved feature toggling. - Introduced speaker_recognition configuration handling in model_registry.py to streamline model loading. - Refactored imports in deepgram.py to improve clarity and reduce redundancy. * Refactor configuration management in wizard and ChronicleSetup (#246) * Refactor configuration management in wizard and ChronicleSetup - Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling. - Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth. - Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers. * Fix string formatting for error message in ChronicleSetup * added JWT issuers for audience auth for service interop and shared us… (#250) * added JWT issuers for audience auth for service interop and shared user accounts * amended default value in line wioth code --------- Co-authored-by: 01PrathamS <pratham21btai35@karnavatiuniversity.edu.in> Co-authored-by: Stu Alexandere <thestumonkey@gmail.com> Co-authored-by: Stuart Alexander <stu@theawesome.co.uk> Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
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* audio upload extension with gdrive credentials
* FIX: API parameters
* UPDATE: tmp files cleanup n code refactored as per review
* REFACTOR: minor refactor as per review
* REFACTOR: minor update as per review
* UPDATE: gdrive sync logic
* REFACTOR: code update as per gdrive and update credential client
* REFACTOR: validation updated - as per review from CR
* UPDATE: code has been refactore for UUID for diffrent audio upload sources
* REFACTOR: updated code as per review
* Update documentation and configuration to reflect the transition from 'friend-backend' to 'chronicle-backend' across various files, including setup instructions, Docker configurations, and service logs.
* Update test script to use docker-compose-test.yml for all test-related operations
* Added standard MIT license
* Fix/cleanup model (#219)
* refactor memory
* add config
* docstring
* more cleanup
* code quality
* code quality
* unused return
* DOTTED GET
* Refactor Docker and CI configurations
- Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process.
- Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services.
- Added new dependencies for Google API clients in `uv.lock` to support upcoming features.
* Update configuration files for model providers and Docker setup
- Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram.
- Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving.
- Updated memory configuration endpoint to accept plain text for YAML input.
* Update transcription job handling to format speaker IDs
- Changed variable name from `speaker_name` to `speaker_id` for clarity.
- Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling.
* Remove loading of backend .env file in test environment setup
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
* Enhance configuration management and setup wizard
- Updated README to reflect the new setup wizard process.
- Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers.
- Improved user feedback during configuration updates, including success messages for configuration file updates.
- Enabled backup of existing `config.yml` before saving changes.
* Enhance HTTPS configuration in setup wizard
- Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates.
- Improved user prompts for server IP/domain input during HTTPS setup.
- Updated default behavior to use existing IP or localhost based on user input.
- Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access.
* Add source parameter to audio file writing in websocket controller
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* fix/broken-tests (#230)
* refactor memory
* add config
* docstring
* more cleanup
* code quality
* code quality
* unused return
* DOTTED GET
* Refactor Docker and CI configurations
- Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process.
- Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services.
- Added new dependencies for Google API clients in `uv.lock` to support upcoming features.
* Update configuration files for model providers and Docker setup
- Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram.
- Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving.
- Updated memory configuration endpoint to accept plain text for YAML input.
* Update transcription job handling to format speaker IDs
- Changed variable name from `speaker_name` to `speaker_id` for clarity.
- Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling.
* Remove loading of backend .env file in test environment setup
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
* Enhance configuration management and setup wizard
- Updated README to reflect the new setup wizard process.
- Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers.
- Improved user feedback during configuration updates, including success messages for configuration file updates.
- Enabled backup of existing `config.yml` before saving changes.
* Enhance HTTPS configuration in setup wizard
- Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates.
- Improved user prompts for server IP/domain input during HTTPS setup.
- Updated default behavior to use existing IP or localhost based on user input.
- Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access.
* Add source parameter to audio file writing in websocket controller
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
* Refactor error handling in system controller and update memory config routes
- Replaced ValueError with HTTPException for better error handling in `save_diarization_settings` and `validate_memory_config` functions.
- Introduced a new Pydantic model, `MemoryConfigRequest`, for validating memory configuration requests in the system routes.
- Updated the `validate_memory_config` endpoint to accept the new request model, improving input handling and validation.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* Feat/add obsidian 3 (#233)
* obsidian support
* neo4j comment
* cleanup code
* unused line
* unused line
* Fix MemoryEntry object usage in chat service
* comment
* feat(obsidian): add obsidian memory search integration to chat
* unit test
* use rq
* neo4j service
* typefix
* test fix
* cleanup
* cleanup
* version changes
* profile
* remove unused imports
* Refactor memory configuration validation endpoints
- Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation.
- Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input.
- Adjusted the API call in the frontend to point to the new validation endpoint.
* Refactor health check model configuration loading
- Updated the health check function to load model configuration from the models registry instead of the root config.
- Improved error handling by logging warnings when model configuration loading fails.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* Update .gitignore to exclude all files in app/ios and app/android directories (#238)
* fix: Copy full source code in speaker-recognition Dockerfile (#243)
Adds COPY src/ src/ step after dependency installation to ensure
all source files are available in the Docker image. This improves
build caching while ensuring complete source code is present.
* Enhance configuration management and add new setup scripts (#235)
* Enhance configuration management and add new setup scripts
- Updated .gitignore to include config.yml and its template.
- Added config.yml.template for default configuration settings.
- Introduced restart.sh script for service management.
- Enhanced services.py to load config.yml and check for Obsidian/Neo4j integration.
- Updated wizard.py to prompt for Obsidian/Neo4j configuration during setup and create config.yml from template if it doesn't exist.
* Refactor transcription providers and enhance configuration management
- Updated Docker Compose files to include the new Neo4j service configuration.
- Added support for Obsidian/Neo4j integration in the setup process.
- Refactored transcription providers to utilize a registry-driven approach for Deepgram and Parakeet.
- Enhanced error handling and logging in transcription processes.
- Improved environment variable management in test scripts to prioritize command-line overrides.
- Removed deprecated Parakeet provider implementation and streamlined audio stream workers.
* Update configuration management and enhance file structure, add test-matrix (#237)
* Update configuration management and enhance file structure
- Refactored configuration file paths to use a dedicated `config/` directory, including updates to `config.yml` and its template.
- Modified service scripts to load the new configuration path for `config.yml`.
- Enhanced `.gitignore` to include the new configuration files and templates.
- Updated documentation to reflect changes in configuration file locations and usage.
- Improved setup scripts to ensure proper creation and management of configuration files.
- Added new test configurations for various provider combinations to streamline testing processes.
* Add test requirements and clean up imports in wizard.py
- Introduced a new `test-requirements.txt` file to manage testing dependencies.
- Removed redundant import of `shutil` in `wizard.py` to improve code clarity.
* Add ConfigManager for unified configuration management
- Introduced a new `config_manager.py` module to handle reading and writing configurations from `config.yml` and `.env` files, ensuring backward compatibility.
- Refactored `ChronicleSetup` in `backends/advanced/init.py` to utilize `ConfigManager` for loading and updating configurations, simplifying the setup process.
- Removed redundant methods for loading and saving `config.yml` directly in `ChronicleSetup`, as these are now managed by `ConfigManager`.
- Enhanced user feedback during configuration updates, including success messages for changes made to configuration files.
* Refactor transcription provider configuration and enhance setup process
- Updated `.env.template` to clarify speech-to-text configuration and removed deprecated options for Mistral.
- Modified `docker-compose.yml` to streamline environment variable management by removing unused Mistral keys.
- Enhanced `ChronicleSetup` in `init.py` to provide clearer user feedback and updated the transcription provider selection process to rely on `config.yml`.
- Improved error handling in the websocket controller to determine the transcription provider from the model registry instead of environment variables.
- Updated health check routes to reflect the new method of retrieving the transcription provider from `config.yml`.
- Adjusted `config.yml.template` to include comments on transcription provider options for better user guidance.
* Enhance ConfigManager with deep merge functionality
- Updated the `update_memory_config` method to perform a deep merge of updates into the memory configuration, ensuring nested dictionaries are merged correctly.
- Added a new `_deep_merge` method to handle recursive merging of dictionaries, improving configuration management capabilities.
* Refactor run-test.sh and enhance memory extraction tests
- Removed deprecated environment variable handling for TRANSCRIPTION_PROVIDER in `run-test.sh`, streamlining the configuration process.
- Introduced a new `run-custom.sh` script for executing Robot tests with custom configurations, improving test flexibility.
- Enhanced memory extraction tests in `audio_keywords.robot` and `memory_keywords.robot` to include detailed assertions and result handling.
- Updated `queue_keywords.robot` to fail fast if a job is in a 'failed' state when expecting 'completed', improving error handling.
- Refactored `test_env.py` to load environment variables with correct precedence, ensuring better configuration management.
* unify tests to robot test, add some more clean up
* Update health check configuration in docker-compose-test.yml (#241)
- Increased the number of retries from 5 to 10 for improved resilience during service readiness checks.
- Extended the start period from 30s to 60s to allow more time for services to initialize before health checks commence.
* Add step to create test configuration file in robot-tests.yml
- Introduced a new step in the GitHub Actions workflow to copy the test configuration file from tests/configs/deepgram-openai.yml to a new config/config.yml.
- Added logging to confirm the creation of the test config file, improving visibility during the test setup process.
* remove cache step since not required
* coderabbit comments
* Refactor ConfigManager error handling for configuration file loading
- Updated the ConfigManager to raise RuntimeError exceptions when the configuration file is not found or is invalid, improving error visibility and user guidance.
- Removed fallback behavior that previously returned the current directory, ensuring users are explicitly informed about missing or invalid configuration files.
* Refactor _find_repo_root method in ConfigManager
- Updated the _find_repo_root method to locate the repository root using the __file__ location instead of searching for config/config.yml, simplifying the logic and improving reliability.
- Removed the previous error handling that raised a RuntimeError if the configuration file was not found, as the new approach assumes config_manager.py is always at the repo root.
* Enhance speaker recognition service integration and error handling (#245)
* Enhance speaker recognition service integration and error handling
- Updated `docker-compose-test.yml` to enable speaker recognition in the test environment and added a new `speaker-service-test` service for testing purposes.
- Refactored `run-test.sh` to improve the execution of Robot Framework tests from the repository root.
- Enhanced error handling in `speaker_recognition_client.py` to return detailed error messages for connection issues.
- Improved error logging in `speaker_jobs.py` to handle and report errors from the speaker recognition service more effectively.
- Updated `Dockerfile` to copy the full source code after dependencies are cached, ensuring all necessary files are included in the image.
* Remove integration tests workflow and enhance robot tests with HF_TOKEN verification
- Deleted the `integration-tests.yml` workflow file to streamline CI processes.
- Updated `robot-tests.yml` to include verification for the new `HF_TOKEN` secret, ensuring all required secrets are checked before running tests.
* Fix key access in system admin tests to use string indexing for speakers data
* Refactor Robot Framework tests and enhance error handling in memory services
- Removed the creation of the test environment file from the GitHub Actions workflow to streamline setup.
- Updated the Robot Framework tests to utilize a unified test script for improved consistency.
- Enhanced error messages in the MemoryService class to provide more context on connection failures for LLM and vector store providers.
- Added critical checks for API key presence in the OpenAIProvider class to ensure valid credentials are provided before proceeding.
- Adjusted various test setup scripts to use a centralized BACKEND_DIR variable for better maintainability and clarity.
* Refactor test container cleanup in run-robot-tests.sh
- Updated the script to dynamically construct container names from docker-compose services, improving maintainability and reducing hardcoded values.
- Enhanced the cleanup process for stuck test containers by utilizing the COMPOSE_PROJECT_NAME variable.
* Enhance run-robot-tests.sh for improved logging and cleanup
- Set absolute paths for consistent directory references to simplify navigation.
- Capture container logs, status, and resource usage for better debugging.
- Refactor cleanup process to utilize dynamic backend directory references, improving maintainability.
- Ensure proper navigation back to the tests directory after operations.
* Add speaker recognition configuration and update test script defaults
- Introduced speaker recognition settings in config.yml.template, allowing for easy enable/disable and service URL configuration.
- Updated run-robot-tests.sh to use a test-specific configuration file that disables speaker recognition for improved CI performance.
- Modified deepgram-openai.yml to disable speaker recognition during CI tests to enhance execution speed.
* Refactor speaker recognition configuration management
- Updated docker-compose-test.yml to clarify speaker recognition settings, now controlled via config.yml for improved CI performance.
- Enhanced model_registry.py to include a dedicated speaker_recognition field for better configuration handling.
- Modified speaker_recognition_client.py to load configuration from config.yml, allowing for dynamic enabling/disabling of the speaker recognition service based on the configuration.
* Add minimum worker count verification to infrastructure tests
- Introduced a new keyword to verify that the minimum number of workers are registered, enhancing the robustness of health checks.
- Updated the worker count validation test to include a wait mechanism for worker registration, improving test reliability.
- Clarified comments regarding expected worker counts to reflect the distinction between RQ and audio stream workers.
* Update configuration management and enhance model handling
- Added OBSIDIAN_ENABLED configuration to ChronicleSetup for improved feature toggling.
- Introduced speaker_recognition configuration handling in model_registry.py to streamline model loading.
- Refactored imports in deepgram.py to improve clarity and reduce redundancy.
* Refactor configuration management in wizard and ChronicleSetup (#246)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* added JWT issuers for audience auth for service interop and shared us… (#250)
* added JWT issuers for audience auth for service interop and shared user accounts
* amended default value in line wioth code
* Feat/edit chat system prompt (#247)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* Enhance chat configuration management and UI integration
- Updated `services.py` to allow service restart with an option to recreate containers, addressing WSL2 bind mount issues.
- Added new chat configuration management functions in `system_controller.py` for loading, saving, and validating chat prompts.
- Introduced `ChatSettings` component in the web UI for admin users to manage chat configurations easily.
- Updated API service methods in `api.ts` to support chat configuration endpoints.
- Integrated chat settings into the system management page for better accessibility.
* Refactor backend shutdown process and enhance chat service configuration logging
- Updated `start.sh` to improve shutdown handling by explicitly killing the backend process if running.
- Modified `chat_service.py` to enhance logging for loading chat system prompts, providing clearer feedback on configuration usage.
- Added a new `chat` field in `model_registry.py` for better chat service configuration management.
- Updated vector store query parameters in `vector_stores.py` for improved clarity and functionality.
- Enhanced the chat component in the web UI to conditionally auto-scroll based on message sending status.
* Return JSONResponse instead of raw result
* Refactor headers creation in system admin tests
* Make config.yml writable for admin updates
* Docs consolidation (#257)
* Enhance setup documentation and convenience scripts
- Updated the interactive setup wizard instructions to recommend using the convenience script `./wizard.sh` for easier configuration.
- Added detailed instructions for uploading and processing existing audio files via the API, including example commands for single and multiple file uploads.
- Introduced a new section on HAVPE relay configuration for ESP32 audio streaming, providing environment variable setup and command examples.
- Clarified the distributed deployment setup, including GPU and backend separation instructions, and added benefits of using Tailscale for networking.
- Removed outdated `getting-started.md` and `SETUP_SCRIPTS.md` files to streamline documentation and avoid redundancy.
* Update setup instructions and enhance service management scripts
- Replaced direct command instructions with convenience scripts (`./wizard.sh` and `./start.sh`) for easier setup and service management.
- Added detailed usage of convenience scripts for checking service status, restarting, and stopping services.
- Clarified the distinction between convenience scripts and direct command usage for improved user guidance.
* Update speaker recognition models and documentation
- Changed the speaker diarization model from `pyannote/speaker-diarization-3.1` to `pyannote/speaker-diarization-community-1` across multiple files for consistency.
- Updated README files to reflect the new model and its usage instructions, ensuring users have the correct links and information for setup.
- Enhanced clarity in configuration settings related to speaker recognition.
* Docs consolidation (#258)
* Enhance setup documentation and convenience scripts
- Updated the interactive setup wizard instructions to recommend using the convenience script `./wizard.sh` for easier configuration.
- Added detailed instructions for uploading and processing existing audio files via the API, including example commands for single and multiple file uploads.
- Introduced a new section on HAVPE relay configuration for ESP32 audio streaming, providing environment variable setup and command examples.
- Clarified the distributed deployment setup, including GPU and backend separation instructions, and added benefits of using Tailscale for networking.
- Removed outdated `getting-started.md` and `SETUP_SCRIPTS.md` files to streamline documentation and avoid redundancy.
* Update setup instructions and enhance service management scripts
- Replaced direct command instructions with convenience scripts (`./wizard.sh` and `./start.sh`) for easier setup and service management.
- Added detailed usage of convenience scripts for checking service status, restarting, and stopping services.
- Clarified the distinction between convenience scripts and direct command usage for improved user guidance.
* Update speaker recognition models and documentation
- Changed the speaker diarization model from `pyannote/speaker-diarization-3.1` to `pyannote/speaker-diarization-community-1` across multiple files for consistency.
- Updated README files to reflect the new model and its usage instructions, ensuring users have the correct links and information for setup.
- Enhanced clarity in configuration settings related to speaker recognition.
* Enhance transcription provider selection and update HTTPS documentation
- Added a new function in `wizard.py` to prompt users for their preferred transcription provider, allowing options for Deepgram, Parakeet ASR, or none.
- Updated the service setup logic to automatically include ASR services if Parakeet is selected.
- Introduced a new documentation file on SSL certificates and HTTPS setup, detailing the importance of HTTPS for secure connections and microphone access.
- Removed outdated HTTPS setup documentation from `backends/advanced/Docs/HTTPS_SETUP.md` to streamline resources.
* Remove HTTPS setup scripts and related configurations
- Deleted `init-https.sh`, `setup-https.sh`, and `nginx.conf.template` as part of the transition to a new HTTPS setup process.
- Updated `README.md` to reflect the new automatic HTTPS configuration via the setup wizard.
- Adjusted `init.py` to remove references to the deleted HTTPS scripts and ensure proper handling of Caddyfile generation for SSL.
- Streamlined documentation to clarify the new approach for HTTPS setup and configuration management.
* Update quickstart.md (#268)
* v0.2 (#279)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* Enhance chat configuration management and UI integration
- Updated `services.py` to allow service restart with an option to recreate containers, addressing WSL2 bind mount issues.
- Added new chat configuration management functions in `system_controller.py` for loading, saving, and validating chat prompts.
- Introduced `ChatSettings` component in the web UI for admin users to manage chat configurations easily.
- Updated API service methods in `api.ts` to support chat configuration endpoints.
- Integrated chat settings into the system management page for better accessibility.
* Refactor backend shutdown process and enhance chat service configuration logging
- Updated `start.sh` to improve shutdown handling by explicitly killing the backend process if running.
- Modified `chat_service.py` to enhance logging for loading chat system prompts, providing clearer feedback on configuration usage.
- Added a new `chat` field in `model_registry.py` for better chat service configuration management.
- Updated vector store query parameters in `vector_stores.py` for improved clarity and functionality.
- Enhanced the chat component in the web UI to conditionally auto-scroll based on message sending status.
* Implement plugin system for enhanced functionality and configuration management
- Introduced a new plugin architecture to allow for extensibility in the Chronicle application.
- Added Home Assistant plugin for controlling devices via natural language commands triggered by wake words.
- Implemented plugin configuration management endpoints in the API for loading, saving, and validating plugin settings.
- Enhanced the web UI with a dedicated Plugins page for managing plugin configurations.
- Updated Docker Compose files to include Tailscale integration for remote service access.
- Refactored existing services to support plugin interactions during conversation and memory processing.
- Improved error handling and logging for plugin initialization and execution processes.
* Enhance configuration management and plugin system integration
- Updated .gitignore to include plugins.yml for security reasons.
- Modified start.sh to allow passing additional arguments during service startup.
- Refactored wizard.py to support new HF_TOKEN configuration prompts and improved handling of wake words in plugin settings.
- Introduced a new setup_hf_token_if_needed function to streamline Hugging Face token management.
- Enhanced the GitHub Actions workflow to create plugins.yml from a template, ensuring proper configuration setup.
- Added detailed comments and documentation in the plugins.yml.template for better user guidance on Home Assistant integration.
* Implement Redis integration for client-user mapping and enhance wake word processing
- Added asynchronous Redis support in ClientManager for tracking client-user relationships.
- Introduced `initialize_redis_for_client_manager` to set up Redis for cross-container mapping.
- Updated `create_client_state` to use asynchronous tracking for client-user relationships.
- Enhanced wake word processing in PluginRouter with normalization and command extraction.
- Refactored DeepgramStreamingConsumer to utilize async Redis lookups for user ID retrieval.
- Set TTL on Redis streams during client state cleanup for better resource management.
* Refactor Deepgram worker management and enhance text normalization
- Disabled the batch Deepgram worker in favor of the streaming worker to prevent race conditions.
- Updated text normalization in wake word processing to replace punctuation with spaces, preserving word boundaries.
- Enhanced regex pattern for wake word matching to allow optional punctuation and whitespace after the last part.
- Improved logging in DeepgramStreamingConsumer for better visibility of message processing and error handling.
* Add original prompt retrieval and restoration in chat configuration test
- Implemented retrieval of the original chat prompt before saving a custom prompt to ensure test isolation.
- Added restoration of the original prompt after the test to prevent interference with subsequent tests.
- Enhanced the test documentation for clarity on the purpose of these changes.
* Refactor test execution and enhance documentation for integration tests
- Simplified test execution commands in CLAUDE.md and quickstart.md for better usability.
- Added instructions for running tests from the project root and clarified the process for executing the complete Robot Framework test suite.
- Introduced a new Docker service for the Deepgram streaming worker in docker-compose-test.yml to improve testing capabilities.
- Updated system_admin_tests.robot to use a defined default prompt for restoration, enhancing test reliability and clarity.
* Enhance test environment cleanup and improve Deepgram worker management
- Updated `run-test.sh` and `run-robot-tests.sh` to improve cleanup processes, including handling permission issues with Docker.
- Introduced a new function `mark_session_complete` in `session_controller.py` to ensure atomic updates for session completion status.
- Refactored WebSocket and conversation job handling to utilize the new session completion function, enhancing reliability.
- Updated `start-workers.sh` to enable the batch Deepgram worker alongside the streaming worker for improved transcription capabilities.
- Enhanced test scripts to verify the status of Deepgram workers and ensure proper cleanup of test containers.
* Refactor worker management and introduce orchestrator for improved process handling
- Replaced the bash-based `start-workers.sh` script with a Python-based worker orchestrator for better process management and health monitoring.
- Updated `docker-compose.yml` to configure the new orchestrator and adjust worker definitions, including the addition of audio persistence and stream workers.
- Enhanced the Dockerfile to remove the old startup script and ensure the orchestrator is executable.
- Introduced new modules for orchestrator configuration, health monitoring, process management, and worker registry to streamline worker lifecycle management.
- Improved environment variable handling for worker configuration and health checks.
* oops
* oops2
* Remove legacy test runner script and update worker orchestration
- Deleted the `run-test.sh` script, which was used for local test execution.
- Updated Docker configurations to replace the `start-workers.sh` script with `worker_orchestrator.py` for improved worker management.
- Enhanced health monitoring and process management in the orchestrator to ensure better reliability and logging.
- Adjusted deployment configurations to reflect the new orchestrator setup.
* Add bulk restart mechanism for RQ worker registration loss
- Introduced a new method `_handle_registration_loss` to manage RQ worker registration loss, replicating the behavior of the previous bash script.
- Implemented a cooldown period to prevent frequent restarts during network issues.
- Added logging for bulk restart actions and their outcomes to enhance monitoring and debugging capabilities.
- Created a `_restart_all_rq_workers` method to facilitate the bulk restart of RQ workers, ensuring they re-register with Redis upon startup.
* Enhance plugin architecture with event-driven system and test integration
- Introduced a new Test Event Plugin to log all plugin events to an SQLite database for integration testing.
- Updated the plugin system to utilize event subscriptions instead of access levels, allowing for more flexible event handling.
- Refactored the PluginRouter to dispatch events based on subscriptions, improving the event-driven architecture.
- Enhanced Docker configurations to support development and testing environments with appropriate dependencies.
- Added comprehensive integration tests to verify the functionality of the event dispatch system and plugin interactions.
- Updated documentation and test configurations to reflect the new event-based plugin structure.
* Enhance Docker configurations and startup script for test mode
- Updated `docker-compose-test.yml` to include a test command for services, enabling a dedicated test mode.
- Modified `start.sh` to support a `--test` flag, allowing the FastAPI backend to run with test-specific configurations.
- Adjusted worker commands to utilize the `--group test` option in test mode for improved orchestration and management.
* Refactor test scripts for improved reliability and clarity
- Updated `run-robot-tests.sh` to enhance the verification of the Deepgram batch worker process, ensuring non-numeric characters are removed from the check.
- Modified `plugin_tests.robot` to use a more explicit method for checking the length of subscriptions and added a skip condition for unavailable audio files.
- Adjusted `plugin_event_tests.robot` to load the test audio file from a variable, improving test data management.
- Refactored `plugin_keywords.robot` to utilize clearer length checks for subscriptions and event parts, enhancing readability and maintainability.
* remove mistral deadcode; notebooks untouched
* Refactor audio streaming endpoints and improve documentation
- Updated WebSocket endpoints to use a unified format with codec parameters (`/ws?codec=pcm` and `/ws?codec=opus`) for audio streaming, replacing the previous `/ws_pcm` and `/ws_omi` endpoints.
- Enhanced documentation to reflect the new endpoint structure and clarify audio processing capabilities.
- Removed deprecated audio cropping functionality and related configurations to streamline the audio processing workflow.
- Updated various components and scripts to align with the new endpoint structure, ensuring consistent usage across the application.
* Enhance testing infrastructure and API routes for plugin events
- Updated `docker-compose-test.yml` to introduce low speech detection thresholds for testing, improving the accuracy of speech detection during tests.
- Added new test-only API routes in `test_routes.py` for clearing and retrieving plugin events, ensuring a clean state between tests.
- Refactored existing test scripts to utilize the new API endpoints for event management, enhancing test reliability and clarity.
- Improved logging and error handling in various components to facilitate debugging during test execution.
- Adjusted environment variable handling in test setup scripts to streamline configuration and improve flexibility.
* Add audio pipeline architecture documentation and improve audio persistence worker configuration
- Introduced a comprehensive documentation file detailing the audio pipeline architecture, covering data flow, processing stages, and key components.
- Enhanced the audio persistence worker setup by implementing multiple concurrent workers to improve audio processing efficiency.
- Adjusted sleep intervals in the audio streaming persistence job for better responsiveness and event loop yielding.
- Updated test script to run the full suite of integration tests from the specified directory, ensuring thorough testing coverage.
* Add test container setup and teardown scripts
- Introduced `setup-test-containers.sh` for streamlined startup of test containers, including health checks and environment variable loading.
- Added `teardown-test-containers.sh` for simplified container shutdown, with options to remove volumes.
- Enhanced user feedback with color-coded messages for better visibility during test setup and teardown processes.
* Update worker count validation and websocket disconnect tests
- Adjusted worker count expectations in the Worker Count Validation Test to reflect an increase from 7 to 9 workers, accounting for additional audio persistence workers.
- Enhanced the WebSocket Disconnect Conversation End Reason Test by adding steps to maintain audio streaming during disconnection, ensuring accurate simulation of network dropout scenarios.
- Improved comments for clarity and added critical notes regarding inactivity timeout handling.
* Refactor audio storage to MongoDB chunks and enhance cleanup settings management
- Replaced the legacy AudioFile model with AudioChunkDocument for storing audio data in MongoDB, optimizing storage and retrieval.
- Introduced CleanupSettings dataclass for managing soft-deletion configurations, including auto-cleanup and retention days.
- Added admin API routes for retrieving and saving cleanup settings, ensuring better control over data retention policies.
- Updated audio processing workflows to utilize MongoDB chunks, removing dependencies on disk-based audio files.
- Enhanced tests to validate the new audio chunk storage and cleanup functionalities, ensuring robust integration with existing systems.
* Refactor audio processing to utilize MongoDB chunks and enhance job handling
- Removed audio file path parameters from various functions, transitioning to audio data retrieval from MongoDB chunks.
- Updated the `start_post_conversation_jobs` function to reflect changes in audio handling, ensuring jobs reconstruct audio from database chunks.
- Enhanced the `transcribe_full_audio_job` and `recognise_speakers_job` to process audio directly from memory, eliminating the need for temporary files.
- Improved error handling and logging for audio data retrieval, ensuring better feedback during processing.
- Added a new utility function for converting PCM data to WAV format in memory, streamlining audio format handling.
* Refactor speaker recognition client to use in-memory audio data
- Updated methods to accept audio data as bytes instead of file paths, enhancing performance by eliminating disk I/O.
- Improved logging to reflect in-memory audio processing, providing better insights during speaker identification and diarization.
- Streamlined audio data handling in the `diarize_identify_match` and `diarize_and_identify` methods, ensuring consistency across the client.
- Removed temporary file handling, simplifying the audio processing workflow and reducing potential file system errors.
* Add mock providers and update testing workflows for API-independent execution
- Introduced `MockLLMProvider` and `MockTranscriptionProvider` to facilitate testing without external API dependencies, allowing for consistent and controlled test environments.
- Created `run-no-api-tests.sh` script to execute tests that do not require API keys, ensuring separation of API-dependent and independent tests.
- Updated Robot Framework test configurations to utilize mock services, enhancing test reliability and reducing external dependencies.
- Modified existing test workflows to include new configurations and ensure proper handling of results for tests excluding API keys.
- Added `mock-services.yml` configuration to disable external API services while maintaining core functionality for testing purposes.
- Enhanced documentation to reflect the new tagging system for tests requiring API keys, improving clarity on test execution requirements.
* Enhance testing documentation and workflows for API key separation
- Updated CLAUDE.md to clarify test execution modes, emphasizing the separation of tests requiring API keys from those that do not.
- Expanded the testing guidelines in TESTING_GUIDELINES.md to detail the organization of tests based on API dependencies, including tagging conventions and execution paths.
- Improved mock-services.yml to include dummy configurations for LLM and embedding services, ensuring tests can run without actual API calls.
- Added comprehensive documentation on GitHub workflows for different test scenarios, enhancing clarity for contributors and maintainers.
* Update test configurations and documentation for API key management
- Modified `plugins.yml.template` to implement event subscriptions for the Home Assistant plugin, enhancing its event-driven capabilities.
- Revised `README.md` to clarify test execution processes, emphasizing the distinction between tests requiring API keys and those that do not.
- Updated `mock-services.yml` to streamline mock configurations, ensuring compatibility with the new testing workflows.
- Added `requires-api-keys` tags to relevant test cases across various test files, improving organization and clarity regarding API dependencies.
- Enhanced documentation for test scripts and configurations, providing clearer guidance for contributors on executing tests based on API key requirements.
* Add optional service profile to Docker Compose test configuration
* Refactor audio processing and job handling for transcription workflows
- Updated `upload_and_process_audio_files` and `start_post_conversation_jobs` to enqueue transcription jobs separately for file uploads, ensuring accurate processing order.
- Enhanced logging to provide clearer insights into job enqueuing and processing stages.
- Removed batch transcription from the post-conversation job chain for streaming audio, utilizing the streaming transcript directly.
- Introduced word-level timestamps in the `Conversation` model to improve transcript detail and accuracy.
- Updated tests to reflect changes in job handling and ensure proper verification of post-conversation processing.
* Remove unnecessary network aliases from speaker service in Docker Compose configuration
* Add network aliases for speaker service in Docker Compose configuration
* Refactor Conversation model to use string for provider field
- Updated the `Conversation` model to replace the `TranscriptProvider` enum with a string type for the `provider` field, allowing for greater flexibility in provider names.
- Adjusted related job functions to accommodate this change, simplifying provider handling in the transcription workflow.
* Enhance configuration and model handling for waveform data
- Updated Docker Compose files to mount the entire config directory, allowing for better management of configuration files.
- Introduced a new `WaveformData` model to store pre-computed waveform visualization data, improving UI performance by enabling waveform display without real-time decoding.
- Enhanced the `app_factory` and `job` models to include the new `WaveformData` model, ensuring proper initialization and data handling.
- Implemented waveform generation logic in a new worker module, allowing for on-demand waveform creation from audio chunks.
- Added API endpoints for retrieving and generating waveform data, improving the overall audio processing capabilities.
- Updated tests to cover new functionality and ensure robustness in waveform data handling.
* Add SDK testing scripts for authentication, conversation retrieval, and audio upload
- Introduced three new test scripts: `sdk_test_auth.py`, `sdk_test_conversations.py`, and `sdk_test_upload.py`.
- Each script tests different functionalities of the SDK, including authentication, conversation retrieval, and audio file uploads.
- The scripts utilize the `ChronicleClient` to perform operations and print results for verification.
- Enhanced testing capabilities for the SDK, ensuring robust validation of core features.
* Enhance audio processing and conversation handling for large files
- Added configuration options for speaker recognition chunking in `.env.template`, allowing for better management of large audio files.
- Updated `get_conversations` function to include an `include_deleted` parameter for filtering conversations based on their deletion status.
- Enhanced `finalize_session` method in `AudioStreamProducer` to send an end marker to Redis, ensuring proper session closure.
- Introduced `reconstruct_audio_segments` function to yield audio segments with overlap for efficient processing of lengthy conversations.
- Implemented merging of overlapping speaker segments to improve accuracy in speaker recognition.
- Added integration tests for WebSocket streaming transcription to validate the end_marker functionality and overall transcription flow.
* archive
* Implement annotation system and enhance audio processing capabilities
- Introduced a new annotation model to support user edits and AI-powered suggestions for memories and transcripts.
- Added annotation routes for CRUD operations, enabling the creation and management of annotations via the API.
- Enhanced the audio processing workflow to support fetching audio segments from the backend, improving speaker recognition accuracy.
- Updated the speaker recognition client to handle conversation-based audio fetching, allowing for better management of large audio files.
- Implemented a cron job for generating AI suggestions on potential errors in transcripts and memories, improving user experience and content accuracy.
- Enhanced the web UI to support inline editing of transcript segments and memory content, providing a more interactive user experience.
- Updated configuration files to support new features and improve overall system flexibility.
* Implement OmegaConf-based configuration management for backend settings
- Introduced a new configuration loader using OmegaConf for unified management of backend settings.
- Updated existing configuration functions to leverage the new loader, enhancing flexibility and maintainability.
- Added support for environment variable interpolation in configuration files.
- Refactored various components to retrieve settings from the new configuration system, improving consistency across the application.
- Updated requirements to include OmegaConf as a dependency.
- Enhanced documentation and comments for clarity on configuration management.
* Refactor .env.template and remove unused diarization configuration
- Updated the .env.template to clarify its purpose for secret values and streamline setup instructions.
- Removed the deprecated diarization_config.json.template file, as it is no longer needed.
- Added new environment variables for Langfuse and Tailscale integration to enhance observability and remote service access.
* Implement legacy environment variable syntax support in configuration loader
- Added custom OmegaConf resolvers to handle legacy ${VAR:-default} syntax for backward compatibility.
- Introduced a preprocessing function to convert legacy syntax in YAML files to OmegaConf-compatible format.
- Updated the load_config function to utilize the new preprocessing for loading defaults and user configurations.
- Enhanced documentation for clarity on the new legacy syntax handling.
* Add plugins configuration path retrieval and refactor usage
- Introduced a new function `get_plugins_yml_path` to centralize the retrieval of the plugins.yml file path.
- Updated `system_controller.py` and `plugin_service.py` to use the new function for improved maintainability and consistency in accessing the plugins configuration.
- Enhanced code clarity by removing hardcoded paths and utilizing the centralized configuration method.
* Unify plugin terminology and fix memory job dependencies
Plugin terminology: subscriptions→events, trigger→condition
Memory jobs: no longer blocked by disabled speaker recognition
* Update Docker Compose configuration and enhance system routes
- Updated Docker Compose files to mount the entire config directory, consolidating configuration management.
- Refactored the `save_diarization_settings` function to improve clarity and maintainability by renaming it to `save_diarization_settings_controller`.
- Enhanced the System component in the web UI to include configuration diagnostics, providing better visibility into system health and issues.
* circular import
* Refactor testing infrastructure and enhance container management
- Updated the testing documentation to reflect a new Makefile-based approach for running tests and managing containers.
- Introduced new scripts for container management, including starting, stopping, restarting, and cleaning containers while preserving logs.
- Added a cleanup script to handle data ownership and permissions correctly.
- Implemented a logging system that saves container logs automatically before cleanup.
- Enhanced the README with detailed instructions for running tests and managing the test environment.
* Add Email Summarizer Plugin and SMTP Email Service
- Introduced the Email Summarizer Plugin that automatically sends email summaries upon conversation completion.
- Implemented SMTP Email Service for sending emails, supporting HTML and plain text formats with TLS/SSL encryption.
- Added configuration options for SMTP settings in the .env.template and plugins.yml.template.
- Created comprehensive documentation for plugin development and usage, including a new plugin generation script.
- Enhanced testing coverage for the Email Summarizer Plugin and SMTP Email Service to ensure reliability and functionality.
* Refactor plugin management and introduce Email Summarizer setup
- Removed the static PLUGINS dictionary and replaced it with a dynamic discovery mechanism for plugins.
- Implemented a new setup process for plugins, allowing for configuration via individual setup scripts.
- Added the Email Summarizer plugin with a dedicated setup script for SMTP configuration.
- Enhanced the main setup flow to support community plugins and their configuration.
- Cleaned up unused functions related to plugin configuration and streamlined the overall plugin setup process.
* Enhance plugin configuration and documentation
- Updated the .env.template to include new configuration options for the Home Assistant and Email Summarizer plugins, including server URLs, tokens, and additional settings.
- Refactored Docker Compose files to correctly mount plugin configuration paths.
- Introduced comprehensive documentation for plugin configuration architecture, detailing the separation of concerns for orchestration, settings, and secrets.
- Added individual configuration files for the Home Assistant and Email Summarizer plugins, ensuring proper management of non-secret settings and environment variable references.
- Improved the plugin loading process to merge configurations from multiple sources, enhancing flexibility and maintainability.
* Refactor plugin setup process to allow interactive user input
- Updated the plugin setup script to run interactively, enabling plugins to prompt for user input during configuration.
- Removed output capturing to facilitate real-time interaction and improved error messaging to include exit codes for better debugging.
* Add shared setup utilities for interactive configuration
- Introduced `setup_utils.py` containing functions for reading environment variables, prompting user input, and masking sensitive values.
- Refactored existing code in `wizard.py` and `init.py` to utilize these shared utilities, improving code reuse and maintainability.
- Updated documentation to include usage examples for the new utilities in plugin setup scripts, enhancing developer experience and clarity.
* Enhance plugin security architecture and configuration management
- Introduced a three-file separation for plugin configuration to improve security:
- `backends/advanced/.env` for secrets (gitignored)
- `config/plugins.yml` for orchestration with environment variable references
- `plugins/{plugin_id}/config.yml` for non-secret defaults
- Updated documentation to emphasize the importance of using `${ENV_VAR}` syntax for sensitive data and provided examples of correct usage.
- Enhanced the Email Summarizer plugin setup process to automatically update `config/plugins.yml` with environment variable references, ensuring secrets are not hardcoded.
- Added new fields to the User model for notification email management and improved error logging in user-related functions.
- Refactored audio chunk utilities to use a consistent method for fetching conversation metadata.
* Refactor backend components for improved functionality and stability
- Added a new parameter `transcript_version_id` to the `open_conversation_job` function to support streaming transcript versioning.
- Enhanced error handling in `check_enrolled_speakers_job` and `recognise_speakers_job` to allow conversations to proceed even when the speaker service is unavailable, improving resilience.
- Updated `send_to_adv.py` to support dynamic WebSocket and HTTP protocols based on environment settings, enhancing configuration flexibility.
- Introduced a background task in `send_to_adv.py` to handle incoming messages from the backend, ensuring connection stability and logging interim results.
* Refactor plugin setup timing to enhance configuration flow
* Refactor save_diarization_settings_controller to improve validation and error handling
- Updated the controller to filter out invalid settings instead of raising an error for each unknown key, allowing for more flexible input.
- Added a check to reject requests with no valid settings provided, enhancing robustness.
- Adjusted logging to reflect the filtered settings being saved.
* Refactor audio processing and conversation management for improved deduplication and tracking
* Refactor audio and email handling for improved functionality and security
- Updated `mask_value` function to handle whitespace more effectively.
- Enhanced `create_plugin` to remove existing directories when using the `--force` option.
- Changed logging level from error to debug for existing admin user checks.
- Improved client ID generation logging for clarity.
- Removed unused fields from conversation creation.
- Added HTML escaping in email templates to prevent XSS attacks.
- Updated audio file download function to include user ID for better tracking.
- Adjusted WebSocket connection settings to respect SSL verification based on environment variables.
* Refactor audio upload functionality to remove unused parameters
- Removed `auto_generate_client` and `folder` parameters from audio upload functions to streamline the API.
- Updated related function calls and documentation to reflect these changes, enhancing clarity and reducing complexity.
* Refactor Email Summarizer plugin configuration for improved clarity and security
- Removed outdated migration instructions from `plugin-configuration.md` to streamline documentation.
- Enhanced `README.md` to clearly outline the three-file separation for plugin configuration, emphasizing the roles of `.env`, `config.yml`, and `plugins.yml`.
- Updated `setup.py` to reflect changes in orchestration settings, ensuring only relevant configurations are included in `config/plugins.yml`.
- Improved security messaging to highlight the importance of not committing secrets to version control.
* Update API key configuration in config.yml.template to use environment variable syntax for improved flexibility and security. This change standardizes the way API keys are referenced across different models and services. (#273)
Co-authored-by: roshan.john <roshanjohn1460@gmail.com>
* Refactor Redis job queue cleanup process for improved success tracking
- Replaced total job count with separate counters for successful and failed jobs during Redis queue cleanup.
- Enhanced logging to provide detailed feedback on the number of jobs cleared and any failures encountered.
- Improved error handling to ensure job counts are accurately reflected even when exceptions occur.
* fix tests
* Update CI workflows to use 'docker compose' for log retrieval and added container status check
- Replaced 'docker logs' commands with 'docker compose -f docker-compose-test.yml logs' for consistency across workflows.
- Added a check for running containers before saving logs to enhance debugging capabilities.
* test fixes
* FIX StreamingTranscriptionConsumer to support cumulative audio timestamp adjustments
- Added `audio_offset_seconds` to track cumulative audio duration for accurate timestamp adjustments across transcription sessions.
- Updated `store_final_result` method to adjust word and segment timestamps based on cumulative audio offset.
- Improved logging to reflect changes in audio offset after storing results.
- Modified Makefile and documentation to clarify test execution options, including new tags for slow and SDK tests, enhancing test organization and execution clarity.
* Enhance test container setup and improve error messages in integration tests
- Set `COMPOSE_PROJECT_NAME` for test containers to ensure consistent naming.
- Consolidated error messages in the `websocket_transcription_e2e_test.robot` file for clarity, improving readability and debugging.
* Improve WebSocket closing logic and enhance integration test teardown
- Added timeout handling for WebSocket closure in `AudioStreamClient` to prevent hanging and ensure clean disconnection.
- Updated integration tests to log the total chunks sent when closing audio streams, improving clarity on resource management during test teardown.
* Refactor job status handling to align with RQ standards
- Updated job status checks across various modules to use "started" and "finished" instead of "processing" and "completed" for consistency with RQ's naming conventions.
- Adjusted related logging and response messages to reflect the new status terminology.
- Simplified Docker Compose project name handling in test scripts to avoid conflicts and improve clarity in test environment setup.
* Update test configurations and improve audio inactivity handling
- Increased `SPEECH_INACTIVITY_THRESHOLD_SECONDS` to 20 seconds in `docker-compose-test.yml` for better audio duration handling during tests.
- Refactored session handling in `session_controller.py` to clarify client ID usage.
- Updated `conversation_utils.py` to track speech activity using audio timestamps, enhancing accuracy in inactivity detection.
- Simplified test scripts by removing unnecessary `COMPOSE_PROJECT_NAME` references, aligning with the new project naming convention.
- Adjusted integration tests to reflect changes in inactivity timeout and ensure proper handling of audio timestamps.
* Refactor audio processing and enhance error handling
- Updated `worker_orchestrator.py` to use `logger.exception` for improved error logging.
- Changed default MongoDB database name from "friend-lite" to "chronicle" in multiple files for consistency.
- Added a new method `close_stream_without_stop` in `audio_stream_client.py` to handle abrupt WebSocket disconnections.
- Enhanced audio validation in `audio_utils.py` to support automatic resampling of audio data if sample rates do not match.
- Improved logging in various modules to provide clearer insights during audio processing and event dispatching.
* Enhance Docker command handling and configuration management
- Updated `run_compose_command` to support separate build commands for services, including profile management for backend and speaker-recognition services.
- Improved error handling and output streaming during Docker command execution.
- Added `ensure_docker_network` function to verify and create the required Docker network before starting services.
- Refactored configuration files to utilize `oc.env` for environment variable management, ensuring better compatibility and flexibility across different environments.
* Enhance configuration loading to support custom config file paths
- Added support for the CONFIG_FILE environment variable to allow specifying custom configuration files for testing.
- Implemented logic to handle both absolute paths and relative filenames for the configuration file, improving flexibility in configuration management.
* Update test scripts to use TEST_CONFIG_FILE for configuration management
- Replaced CONFIG_FILE with TEST_CONFIG_FILE in both run-no-api-tests.sh and run-robot-tests.sh to standardize configuration file usage.
- Updated paths to point to mock and deepgram-openai configuration files inside the container, improving clarity and consistency in test setups.
* Refactor audio upload response handling and improve error reporting
- Updated `upload_and_process_audio_files` to return appropriate HTTP status codes based on upload results: 400 for all failures, 207 for partial successes, and 200 for complete success.
- Enhanced error messages in the audio upload tests to provide clearer feedback on upload failures, including specific error details for better debugging.
- Adjusted test scripts to ensure consistent handling of conversation IDs in job metadata, improving validation checks for job creation.
* Refactor audio processing and job handling to improve transcription management
- Updated `upload_and_process_audio_files` to check for transcription provider availability before enqueueing jobs, enhancing error handling and logging.
- Modified `start_post_conversation_jobs` to conditionally enqueue memory extraction jobs based on configuration, improving flexibility in job management.
- Enhanced event dispatch job dependencies to only include jobs that were actually enqueued, ensuring accurate job tracking.
- Added `is_transcription_available` function to check transcription provider status, improving modularity and clarity in the transcription workflow.
* Enhance integration tests for plugin events and improve error handling
- Updated integration tests to filter plugin events by conversation ID, ensuring accurate event tracking and reducing noise from fixture events.
- Improved error messages in event verification to include conversation ID context, enhancing clarity during test failures.
- Refactored audio upload handling to check for transcription job creation, allowing for more robust conversation polling and error reporting.
- Added new keyword to verify conversation end reasons, improving test coverage for conversation state validation.
* Enhance speaker recognition testing and audio processing
- Added mock speaker recognition client to facilitate testing without resource-intensive dependencies.
- Updated Docker Compose configurations to include mock speaker client for test environments.
- Refactored audio segment reconstruction to ensure precise clipping based on time boundaries.
- Improved error handling in transcription jobs and speaker recognition workflows to enhance robustness.
- Adjusted integration tests to utilize real-time pacing for audio chunk streaming, improving test accuracy.
* Refactor audio chunk retrieval and enhance logging in audio processing
- Introduced logging for audio chunk requests to improve traceability.
- Replaced manual audio chunk processing with a dedicated `reconstruct_audio_segment` function for better clarity and efficiency.
- Improved error handling during audio reconstruction to provide more informative responses in case of failures.
- Cleaned up imports and removed redundant code related to audio chunk calculations.
* Refactor mock speaker recognition client and improve testing structure
- Replaced direct import of mock client with a structured import from the new testing module.
- Introduced a dedicated `mock_speaker_client.py` to provide a mock implementation for speaker recognition, facilitating testing without heavy dependencies.
- Added an `__init__.py` file in the testing directory to organize testing utilities and mocks.
* Enhance conversation model to include word-level timestamps and improve transcript handling
- Added a new `words` field to the `Conversation` model for storing word-level timestamps.
- Updated methods to handle word data during transcript version creation, ensuring compatibility with speaker recognition.
- Refactored conversation job processing to utilize the new word structure, improving data integrity and access.
- Enhanced speaker recognition job to read words from the new standardized location, ensuring backward compatibility with legacy data.
* Implement speaker reprocessing feature and enhance timeout calculation
- Added a new endpoint to reprocess speaker identification for existing transcripts, creating a new version with re-identified speakers.
- Introduced a method to calculate proportional t…
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* audio upload extension with gdrive credentials
* FIX: API parameters
* UPDATE: tmp files cleanup n code refactored as per review
* REFACTOR: minor refactor as per review
* REFACTOR: minor update as per review
* UPDATE: gdrive sync logic
* REFACTOR: code update as per gdrive and update credential client
* REFACTOR: validation updated - as per review from CR
* UPDATE: code has been refactore for UUID for diffrent audio upload sources
* REFACTOR: updated code as per review
* Update documentation and configuration to reflect the transition from 'friend-backend' to 'chronicle-backend' across various files, including setup instructions, Docker configurations, and service logs.
* Update test script to use docker-compose-test.yml for all test-related operations
* Added standard MIT license
* Fix/cleanup model (#219)
* refactor memory
* add config
* docstring
* more cleanup
* code quality
* code quality
* unused return
* DOTTED GET
* Refactor Docker and CI configurations
- Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process.
- Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services.
- Added new dependencies for Google API clients in `uv.lock` to support upcoming features.
* Update configuration files for model providers and Docker setup
- Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram.
- Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving.
- Updated memory configuration endpoint to accept plain text for YAML input.
* Update transcription job handling to format speaker IDs
- Changed variable name from `speaker_name` to `speaker_id` for clarity.
- Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling.
* Remove loading of backend .env file in test environment setup
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
* Enhance configuration management and setup wizard
- Updated README to reflect the new setup wizard process.
- Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers.
- Improved user feedback during configuration updates, including success messages for configuration file updates.
- Enabled backup of existing `config.yml` before saving changes.
* Enhance HTTPS configuration in setup wizard
- Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates.
- Improved user prompts for server IP/domain input during HTTPS setup.
- Updated default behavior to use existing IP or localhost based on user input.
- Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access.
* Add source parameter to audio file writing in websocket controller
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* fix/broken-tests (#230)
* refactor memory
* add config
* docstring
* more cleanup
* code quality
* code quality
* unused return
* DOTTED GET
* Refactor Docker and CI configurations
- Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process.
- Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services.
- Added new dependencies for Google API clients in `uv.lock` to support upcoming features.
* Update configuration files for model providers and Docker setup
- Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram.
- Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving.
- Updated memory configuration endpoint to accept plain text for YAML input.
* Update transcription job handling to format speaker IDs
- Changed variable name from `speaker_name` to `speaker_id` for clarity.
- Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling.
* Remove loading of backend .env file in test environment setup
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
* Enhance configuration management and setup wizard
- Updated README to reflect the new setup wizard process.
- Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers.
- Improved user feedback during configuration updates, including success messages for configuration file updates.
- Enabled backup of existing `config.yml` before saving changes.
* Enhance HTTPS configuration in setup wizard
- Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates.
- Improved user prompts for server IP/domain input during HTTPS setup.
- Updated default behavior to use existing IP or localhost based on user input.
- Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access.
* Add source parameter to audio file writing in websocket controller
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
* Refactor error handling in system controller and update memory config routes
- Replaced ValueError with HTTPException for better error handling in `save_diarization_settings` and `validate_memory_config` functions.
- Introduced a new Pydantic model, `MemoryConfigRequest`, for validating memory configuration requests in the system routes.
- Updated the `validate_memory_config` endpoint to accept the new request model, improving input handling and validation.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* Feat/add obsidian 3 (#233)
* obsidian support
* neo4j comment
* cleanup code
* unused line
* unused line
* Fix MemoryEntry object usage in chat service
* comment
* feat(obsidian): add obsidian memory search integration to chat
* unit test
* use rq
* neo4j service
* typefix
* test fix
* cleanup
* cleanup
* version changes
* profile
* remove unused imports
* Refactor memory configuration validation endpoints
- Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation.
- Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input.
- Adjusted the API call in the frontend to point to the new validation endpoint.
* Refactor health check model configuration loading
- Updated the health check function to load model configuration from the models registry instead of the root config.
- Improved error handling by logging warnings when model configuration loading fails.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* Update .gitignore to exclude all files in app/ios and app/android directories (#238)
* fix: Copy full source code in speaker-recognition Dockerfile (#243)
Adds COPY src/ src/ step after dependency installation to ensure
all source files are available in the Docker image. This improves
build caching while ensuring complete source code is present.
* Enhance configuration management and add new setup scripts (#235)
* Enhance configuration management and add new setup scripts
- Updated .gitignore to include config.yml and its template.
- Added config.yml.template for default configuration settings.
- Introduced restart.sh script for service management.
- Enhanced services.py to load config.yml and check for Obsidian/Neo4j integration.
- Updated wizard.py to prompt for Obsidian/Neo4j configuration during setup and create config.yml from template if it doesn't exist.
* Refactor transcription providers and enhance configuration management
- Updated Docker Compose files to include the new Neo4j service configuration.
- Added support for Obsidian/Neo4j integration in the setup process.
- Refactored transcription providers to utilize a registry-driven approach for Deepgram and Parakeet.
- Enhanced error handling and logging in transcription processes.
- Improved environment variable management in test scripts to prioritize command-line overrides.
- Removed deprecated Parakeet provider implementation and streamlined audio stream workers.
* Update configuration management and enhance file structure, add test-matrix (#237)
* Update configuration management and enhance file structure
- Refactored configuration file paths to use a dedicated `config/` directory, including updates to `config.yml` and its template.
- Modified service scripts to load the new configuration path for `config.yml`.
- Enhanced `.gitignore` to include the new configuration files and templates.
- Updated documentation to reflect changes in configuration file locations and usage.
- Improved setup scripts to ensure proper creation and management of configuration files.
- Added new test configurations for various provider combinations to streamline testing processes.
* Add test requirements and clean up imports in wizard.py
- Introduced a new `test-requirements.txt` file to manage testing dependencies.
- Removed redundant import of `shutil` in `wizard.py` to improve code clarity.
* Add ConfigManager for unified configuration management
- Introduced a new `config_manager.py` module to handle reading and writing configurations from `config.yml` and `.env` files, ensuring backward compatibility.
- Refactored `ChronicleSetup` in `backends/advanced/init.py` to utilize `ConfigManager` for loading and updating configurations, simplifying the setup process.
- Removed redundant methods for loading and saving `config.yml` directly in `ChronicleSetup`, as these are now managed by `ConfigManager`.
- Enhanced user feedback during configuration updates, including success messages for changes made to configuration files.
* Refactor transcription provider configuration and enhance setup process
- Updated `.env.template` to clarify speech-to-text configuration and removed deprecated options for Mistral.
- Modified `docker-compose.yml` to streamline environment variable management by removing unused Mistral keys.
- Enhanced `ChronicleSetup` in `init.py` to provide clearer user feedback and updated the transcription provider selection process to rely on `config.yml`.
- Improved error handling in the websocket controller to determine the transcription provider from the model registry instead of environment variables.
- Updated health check routes to reflect the new method of retrieving the transcription provider from `config.yml`.
- Adjusted `config.yml.template` to include comments on transcription provider options for better user guidance.
* Enhance ConfigManager with deep merge functionality
- Updated the `update_memory_config` method to perform a deep merge of updates into the memory configuration, ensuring nested dictionaries are merged correctly.
- Added a new `_deep_merge` method to handle recursive merging of dictionaries, improving configuration management capabilities.
* Refactor run-test.sh and enhance memory extraction tests
- Removed deprecated environment variable handling for TRANSCRIPTION_PROVIDER in `run-test.sh`, streamlining the configuration process.
- Introduced a new `run-custom.sh` script for executing Robot tests with custom configurations, improving test flexibility.
- Enhanced memory extraction tests in `audio_keywords.robot` and `memory_keywords.robot` to include detailed assertions and result handling.
- Updated `queue_keywords.robot` to fail fast if a job is in a 'failed' state when expecting 'completed', improving error handling.
- Refactored `test_env.py` to load environment variables with correct precedence, ensuring better configuration management.
* unify tests to robot test, add some more clean up
* Update health check configuration in docker-compose-test.yml (#241)
- Increased the number of retries from 5 to 10 for improved resilience during service readiness checks.
- Extended the start period from 30s to 60s to allow more time for services to initialize before health checks commence.
* Add step to create test configuration file in robot-tests.yml
- Introduced a new step in the GitHub Actions workflow to copy the test configuration file from tests/configs/deepgram-openai.yml to a new config/config.yml.
- Added logging to confirm the creation of the test config file, improving visibility during the test setup process.
* remove cache step since not required
* coderabbit comments
* Refactor ConfigManager error handling for configuration file loading
- Updated the ConfigManager to raise RuntimeError exceptions when the configuration file is not found or is invalid, improving error visibility and user guidance.
- Removed fallback behavior that previously returned the current directory, ensuring users are explicitly informed about missing or invalid configuration files.
* Refactor _find_repo_root method in ConfigManager
- Updated the _find_repo_root method to locate the repository root using the __file__ location instead of searching for config/config.yml, simplifying the logic and improving reliability.
- Removed the previous error handling that raised a RuntimeError if the configuration file was not found, as the new approach assumes config_manager.py is always at the repo root.
* Enhance speaker recognition service integration and error handling (#245)
* Enhance speaker recognition service integration and error handling
- Updated `docker-compose-test.yml` to enable speaker recognition in the test environment and added a new `speaker-service-test` service for testing purposes.
- Refactored `run-test.sh` to improve the execution of Robot Framework tests from the repository root.
- Enhanced error handling in `speaker_recognition_client.py` to return detailed error messages for connection issues.
- Improved error logging in `speaker_jobs.py` to handle and report errors from the speaker recognition service more effectively.
- Updated `Dockerfile` to copy the full source code after dependencies are cached, ensuring all necessary files are included in the image.
* Remove integration tests workflow and enhance robot tests with HF_TOKEN verification
- Deleted the `integration-tests.yml` workflow file to streamline CI processes.
- Updated `robot-tests.yml` to include verification for the new `HF_TOKEN` secret, ensuring all required secrets are checked before running tests.
* Fix key access in system admin tests to use string indexing for speakers data
* Refactor Robot Framework tests and enhance error handling in memory services
- Removed the creation of the test environment file from the GitHub Actions workflow to streamline setup.
- Updated the Robot Framework tests to utilize a unified test script for improved consistency.
- Enhanced error messages in the MemoryService class to provide more context on connection failures for LLM and vector store providers.
- Added critical checks for API key presence in the OpenAIProvider class to ensure valid credentials are provided before proceeding.
- Adjusted various test setup scripts to use a centralized BACKEND_DIR variable for better maintainability and clarity.
* Refactor test container cleanup in run-robot-tests.sh
- Updated the script to dynamically construct container names from docker-compose services, improving maintainability and reducing hardcoded values.
- Enhanced the cleanup process for stuck test containers by utilizing the COMPOSE_PROJECT_NAME variable.
* Enhance run-robot-tests.sh for improved logging and cleanup
- Set absolute paths for consistent directory references to simplify navigation.
- Capture container logs, status, and resource usage for better debugging.
- Refactor cleanup process to utilize dynamic backend directory references, improving maintainability.
- Ensure proper navigation back to the tests directory after operations.
* Add speaker recognition configuration and update test script defaults
- Introduced speaker recognition settings in config.yml.template, allowing for easy enable/disable and service URL configuration.
- Updated run-robot-tests.sh to use a test-specific configuration file that disables speaker recognition for improved CI performance.
- Modified deepgram-openai.yml to disable speaker recognition during CI tests to enhance execution speed.
* Refactor speaker recognition configuration management
- Updated docker-compose-test.yml to clarify speaker recognition settings, now controlled via config.yml for improved CI performance.
- Enhanced model_registry.py to include a dedicated speaker_recognition field for better configuration handling.
- Modified speaker_recognition_client.py to load configuration from config.yml, allowing for dynamic enabling/disabling of the speaker recognition service based on the configuration.
* Add minimum worker count verification to infrastructure tests
- Introduced a new keyword to verify that the minimum number of workers are registered, enhancing the robustness of health checks.
- Updated the worker count validation test to include a wait mechanism for worker registration, improving test reliability.
- Clarified comments regarding expected worker counts to reflect the distinction between RQ and audio stream workers.
* Update configuration management and enhance model handling
- Added OBSIDIAN_ENABLED configuration to ChronicleSetup for improved feature toggling.
- Introduced speaker_recognition configuration handling in model_registry.py to streamline model loading.
- Refactored imports in deepgram.py to improve clarity and reduce redundancy.
* Refactor configuration management in wizard and ChronicleSetup (#246)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* added JWT issuers for audience auth for service interop and shared us… (#250)
* added JWT issuers for audience auth for service interop and shared user accounts
* amended default value in line wioth code
* Feat/edit chat system prompt (#247)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* Enhance chat configuration management and UI integration
- Updated `services.py` to allow service restart with an option to recreate containers, addressing WSL2 bind mount issues.
- Added new chat configuration management functions in `system_controller.py` for loading, saving, and validating chat prompts.
- Introduced `ChatSettings` component in the web UI for admin users to manage chat configurations easily.
- Updated API service methods in `api.ts` to support chat configuration endpoints.
- Integrated chat settings into the system management page for better accessibility.
* Refactor backend shutdown process and enhance chat service configuration logging
- Updated `start.sh` to improve shutdown handling by explicitly killing the backend process if running.
- Modified `chat_service.py` to enhance logging for loading chat system prompts, providing clearer feedback on configuration usage.
- Added a new `chat` field in `model_registry.py` for better chat service configuration management.
- Updated vector store query parameters in `vector_stores.py` for improved clarity and functionality.
- Enhanced the chat component in the web UI to conditionally auto-scroll based on message sending status.
* Return JSONResponse instead of raw result
* Refactor headers creation in system admin tests
* Make config.yml writable for admin updates
* Docs consolidation (#257)
* Enhance setup documentation and convenience scripts
- Updated the interactive setup wizard instructions to recommend using the convenience script `./wizard.sh` for easier configuration.
- Added detailed instructions for uploading and processing existing audio files via the API, including example commands for single and multiple file uploads.
- Introduced a new section on HAVPE relay configuration for ESP32 audio streaming, providing environment variable setup and command examples.
- Clarified the distributed deployment setup, including GPU and backend separation instructions, and added benefits of using Tailscale for networking.
- Removed outdated `getting-started.md` and `SETUP_SCRIPTS.md` files to streamline documentation and avoid redundancy.
* Update setup instructions and enhance service management scripts
- Replaced direct command instructions with convenience scripts (`./wizard.sh` and `./start.sh`) for easier setup and service management.
- Added detailed usage of convenience scripts for checking service status, restarting, and stopping services.
- Clarified the distinction between convenience scripts and direct command usage for improved user guidance.
* Update speaker recognition models and documentation
- Changed the speaker diarization model from `pyannote/speaker-diarization-3.1` to `pyannote/speaker-diarization-community-1` across multiple files for consistency.
- Updated README files to reflect the new model and its usage instructions, ensuring users have the correct links and information for setup.
- Enhanced clarity in configuration settings related to speaker recognition.
* Docs consolidation (#258)
* Enhance setup documentation and convenience scripts
- Updated the interactive setup wizard instructions to recommend using the convenience script `./wizard.sh` for easier configuration.
- Added detailed instructions for uploading and processing existing audio files via the API, including example commands for single and multiple file uploads.
- Introduced a new section on HAVPE relay configuration for ESP32 audio streaming, providing environment variable setup and command examples.
- Clarified the distributed deployment setup, including GPU and backend separation instructions, and added benefits of using Tailscale for networking.
- Removed outdated `getting-started.md` and `SETUP_SCRIPTS.md` files to streamline documentation and avoid redundancy.
* Update setup instructions and enhance service management scripts
- Replaced direct command instructions with convenience scripts (`./wizard.sh` and `./start.sh`) for easier setup and service management.
- Added detailed usage of convenience scripts for checking service status, restarting, and stopping services.
- Clarified the distinction between convenience scripts and direct command usage for improved user guidance.
* Update speaker recognition models and documentation
- Changed the speaker diarization model from `pyannote/speaker-diarization-3.1` to `pyannote/speaker-diarization-community-1` across multiple files for consistency.
- Updated README files to reflect the new model and its usage instructions, ensuring users have the correct links and information for setup.
- Enhanced clarity in configuration settings related to speaker recognition.
* Enhance transcription provider selection and update HTTPS documentation
- Added a new function in `wizard.py` to prompt users for their preferred transcription provider, allowing options for Deepgram, Parakeet ASR, or none.
- Updated the service setup logic to automatically include ASR services if Parakeet is selected.
- Introduced a new documentation file on SSL certificates and HTTPS setup, detailing the importance of HTTPS for secure connections and microphone access.
- Removed outdated HTTPS setup documentation from `backends/advanced/Docs/HTTPS_SETUP.md` to streamline resources.
* Remove HTTPS setup scripts and related configurations
- Deleted `init-https.sh`, `setup-https.sh`, and `nginx.conf.template` as part of the transition to a new HTTPS setup process.
- Updated `README.md` to reflect the new automatic HTTPS configuration via the setup wizard.
- Adjusted `init.py` to remove references to the deleted HTTPS scripts and ensure proper handling of Caddyfile generation for SSL.
- Streamlined documentation to clarify the new approach for HTTPS setup and configuration management.
* Update quickstart.md (#268)
* v0.2 (#279)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* Enhance chat configuration management and UI integration
- Updated `services.py` to allow service restart with an option to recreate containers, addressing WSL2 bind mount issues.
- Added new chat configuration management functions in `system_controller.py` for loading, saving, and validating chat prompts.
- Introduced `ChatSettings` component in the web UI for admin users to manage chat configurations easily.
- Updated API service methods in `api.ts` to support chat configuration endpoints.
- Integrated chat settings into the system management page for better accessibility.
* Refactor backend shutdown process and enhance chat service configuration logging
- Updated `start.sh` to improve shutdown handling by explicitly killing the backend process if running.
- Modified `chat_service.py` to enhance logging for loading chat system prompts, providing clearer feedback on configuration usage.
- Added a new `chat` field in `model_registry.py` for better chat service configuration management.
- Updated vector store query parameters in `vector_stores.py` for improved clarity and functionality.
- Enhanced the chat component in the web UI to conditionally auto-scroll based on message sending status.
* Implement plugin system for enhanced functionality and configuration management
- Introduced a new plugin architecture to allow for extensibility in the Chronicle application.
- Added Home Assistant plugin for controlling devices via natural language commands triggered by wake words.
- Implemented plugin configuration management endpoints in the API for loading, saving, and validating plugin settings.
- Enhanced the web UI with a dedicated Plugins page for managing plugin configurations.
- Updated Docker Compose files to include Tailscale integration for remote service access.
- Refactored existing services to support plugin interactions during conversation and memory processing.
- Improved error handling and logging for plugin initialization and execution processes.
* Enhance configuration management and plugin system integration
- Updated .gitignore to include plugins.yml for security reasons.
- Modified start.sh to allow passing additional arguments during service startup.
- Refactored wizard.py to support new HF_TOKEN configuration prompts and improved handling of wake words in plugin settings.
- Introduced a new setup_hf_token_if_needed function to streamline Hugging Face token management.
- Enhanced the GitHub Actions workflow to create plugins.yml from a template, ensuring proper configuration setup.
- Added detailed comments and documentation in the plugins.yml.template for better user guidance on Home Assistant integration.
* Implement Redis integration for client-user mapping and enhance wake word processing
- Added asynchronous Redis support in ClientManager for tracking client-user relationships.
- Introduced `initialize_redis_for_client_manager` to set up Redis for cross-container mapping.
- Updated `create_client_state` to use asynchronous tracking for client-user relationships.
- Enhanced wake word processing in PluginRouter with normalization and command extraction.
- Refactored DeepgramStreamingConsumer to utilize async Redis lookups for user ID retrieval.
- Set TTL on Redis streams during client state cleanup for better resource management.
* Refactor Deepgram worker management and enhance text normalization
- Disabled the batch Deepgram worker in favor of the streaming worker to prevent race conditions.
- Updated text normalization in wake word processing to replace punctuation with spaces, preserving word boundaries.
- Enhanced regex pattern for wake word matching to allow optional punctuation and whitespace after the last part.
- Improved logging in DeepgramStreamingConsumer for better visibility of message processing and error handling.
* Add original prompt retrieval and restoration in chat configuration test
- Implemented retrieval of the original chat prompt before saving a custom prompt to ensure test isolation.
- Added restoration of the original prompt after the test to prevent interference with subsequent tests.
- Enhanced the test documentation for clarity on the purpose of these changes.
* Refactor test execution and enhance documentation for integration tests
- Simplified test execution commands in CLAUDE.md and quickstart.md for better usability.
- Added instructions for running tests from the project root and clarified the process for executing the complete Robot Framework test suite.
- Introduced a new Docker service for the Deepgram streaming worker in docker-compose-test.yml to improve testing capabilities.
- Updated system_admin_tests.robot to use a defined default prompt for restoration, enhancing test reliability and clarity.
* Enhance test environment cleanup and improve Deepgram worker management
- Updated `run-test.sh` and `run-robot-tests.sh` to improve cleanup processes, including handling permission issues with Docker.
- Introduced a new function `mark_session_complete` in `session_controller.py` to ensure atomic updates for session completion status.
- Refactored WebSocket and conversation job handling to utilize the new session completion function, enhancing reliability.
- Updated `start-workers.sh` to enable the batch Deepgram worker alongside the streaming worker for improved transcription capabilities.
- Enhanced test scripts to verify the status of Deepgram workers and ensure proper cleanup of test containers.
* Refactor worker management and introduce orchestrator for improved process handling
- Replaced the bash-based `start-workers.sh` script with a Python-based worker orchestrator for better process management and health monitoring.
- Updated `docker-compose.yml` to configure the new orchestrator and adjust worker definitions, including the addition of audio persistence and stream workers.
- Enhanced the Dockerfile to remove the old startup script and ensure the orchestrator is executable.
- Introduced new modules for orchestrator configuration, health monitoring, process management, and worker registry to streamline worker lifecycle management.
- Improved environment variable handling for worker configuration and health checks.
* oops
* oops2
* Remove legacy test runner script and update worker orchestration
- Deleted the `run-test.sh` script, which was used for local test execution.
- Updated Docker configurations to replace the `start-workers.sh` script with `worker_orchestrator.py` for improved worker management.
- Enhanced health monitoring and process management in the orchestrator to ensure better reliability and logging.
- Adjusted deployment configurations to reflect the new orchestrator setup.
* Add bulk restart mechanism for RQ worker registration loss
- Introduced a new method `_handle_registration_loss` to manage RQ worker registration loss, replicating the behavior of the previous bash script.
- Implemented a cooldown period to prevent frequent restarts during network issues.
- Added logging for bulk restart actions and their outcomes to enhance monitoring and debugging capabilities.
- Created a `_restart_all_rq_workers` method to facilitate the bulk restart of RQ workers, ensuring they re-register with Redis upon startup.
* Enhance plugin architecture with event-driven system and test integration
- Introduced a new Test Event Plugin to log all plugin events to an SQLite database for integration testing.
- Updated the plugin system to utilize event subscriptions instead of access levels, allowing for more flexible event handling.
- Refactored the PluginRouter to dispatch events based on subscriptions, improving the event-driven architecture.
- Enhanced Docker configurations to support development and testing environments with appropriate dependencies.
- Added comprehensive integration tests to verify the functionality of the event dispatch system and plugin interactions.
- Updated documentation and test configurations to reflect the new event-based plugin structure.
* Enhance Docker configurations and startup script for test mode
- Updated `docker-compose-test.yml` to include a test command for services, enabling a dedicated test mode.
- Modified `start.sh` to support a `--test` flag, allowing the FastAPI backend to run with test-specific configurations.
- Adjusted worker commands to utilize the `--group test` option in test mode for improved orchestration and management.
* Refactor test scripts for improved reliability and clarity
- Updated `run-robot-tests.sh` to enhance the verification of the Deepgram batch worker process, ensuring non-numeric characters are removed from the check.
- Modified `plugin_tests.robot` to use a more explicit method for checking the length of subscriptions and added a skip condition for unavailable audio files.
- Adjusted `plugin_event_tests.robot` to load the test audio file from a variable, improving test data management.
- Refactored `plugin_keywords.robot` to utilize clearer length checks for subscriptions and event parts, enhancing readability and maintainability.
* remove mistral deadcode; notebooks untouched
* Refactor audio streaming endpoints and improve documentation
- Updated WebSocket endpoints to use a unified format with codec parameters (`/ws?codec=pcm` and `/ws?codec=opus`) for audio streaming, replacing the previous `/ws_pcm` and `/ws_omi` endpoints.
- Enhanced documentation to reflect the new endpoint structure and clarify audio processing capabilities.
- Removed deprecated audio cropping functionality and related configurations to streamline the audio processing workflow.
- Updated various components and scripts to align with the new endpoint structure, ensuring consistent usage across the application.
* Enhance testing infrastructure and API routes for plugin events
- Updated `docker-compose-test.yml` to introduce low speech detection thresholds for testing, improving the accuracy of speech detection during tests.
- Added new test-only API routes in `test_routes.py` for clearing and retrieving plugin events, ensuring a clean state between tests.
- Refactored existing test scripts to utilize the new API endpoints for event management, enhancing test reliability and clarity.
- Improved logging and error handling in various components to facilitate debugging during test execution.
- Adjusted environment variable handling in test setup scripts to streamline configuration and improve flexibility.
* Add audio pipeline architecture documentation and improve audio persistence worker configuration
- Introduced a comprehensive documentation file detailing the audio pipeline architecture, covering data flow, processing stages, and key components.
- Enhanced the audio persistence worker setup by implementing multiple concurrent workers to improve audio processing efficiency.
- Adjusted sleep intervals in the audio streaming persistence job for better responsiveness and event loop yielding.
- Updated test script to run the full suite of integration tests from the specified directory, ensuring thorough testing coverage.
* Add test container setup and teardown scripts
- Introduced `setup-test-containers.sh` for streamlined startup of test containers, including health checks and environment variable loading.
- Added `teardown-test-containers.sh` for simplified container shutdown, with options to remove volumes.
- Enhanced user feedback with color-coded messages for better visibility during test setup and teardown processes.
* Update worker count validation and websocket disconnect tests
- Adjusted worker count expectations in the Worker Count Validation Test to reflect an increase from 7 to 9 workers, accounting for additional audio persistence workers.
- Enhanced the WebSocket Disconnect Conversation End Reason Test by adding steps to maintain audio streaming during disconnection, ensuring accurate simulation of network dropout scenarios.
- Improved comments for clarity and added critical notes regarding inactivity timeout handling.
* Refactor audio storage to MongoDB chunks and enhance cleanup settings management
- Replaced the legacy AudioFile model with AudioChunkDocument for storing audio data in MongoDB, optimizing storage and retrieval.
- Introduced CleanupSettings dataclass for managing soft-deletion configurations, including auto-cleanup and retention days.
- Added admin API routes for retrieving and saving cleanup settings, ensuring better control over data retention policies.
- Updated audio processing workflows to utilize MongoDB chunks, removing dependencies on disk-based audio files.
- Enhanced tests to validate the new audio chunk storage and cleanup functionalities, ensuring robust integration with existing systems.
* Refactor audio processing to utilize MongoDB chunks and enhance job handling
- Removed audio file path parameters from various functions, transitioning to audio data retrieval from MongoDB chunks.
- Updated the `start_post_conversation_jobs` function to reflect changes in audio handling, ensuring jobs reconstruct audio from database chunks.
- Enhanced the `transcribe_full_audio_job` and `recognise_speakers_job` to process audio directly from memory, eliminating the need for temporary files.
- Improved error handling and logging for audio data retrieval, ensuring better feedback during processing.
- Added a new utility function for converting PCM data to WAV format in memory, streamlining audio format handling.
* Refactor speaker recognition client to use in-memory audio data
- Updated methods to accept audio data as bytes instead of file paths, enhancing performance by eliminating disk I/O.
- Improved logging to reflect in-memory audio processing, providing better insights during speaker identification and diarization.
- Streamlined audio data handling in the `diarize_identify_match` and `diarize_and_identify` methods, ensuring consistency across the client.
- Removed temporary file handling, simplifying the audio processing workflow and reducing potential file system errors.
* Add mock providers and update testing workflows for API-independent execution
- Introduced `MockLLMProvider` and `MockTranscriptionProvider` to facilitate testing without external API dependencies, allowing for consistent and controlled test environments.
- Created `run-no-api-tests.sh` script to execute tests that do not require API keys, ensuring separation of API-dependent and independent tests.
- Updated Robot Framework test configurations to utilize mock services, enhancing test reliability and reducing external dependencies.
- Modified existing test workflows to include new configurations and ensure proper handling of results for tests excluding API keys.
- Added `mock-services.yml` configuration to disable external API services while maintaining core functionality for testing purposes.
- Enhanced documentation to reflect the new tagging system for tests requiring API keys, improving clarity on test execution requirements.
* Enhance testing documentation and workflows for API key separation
- Updated CLAUDE.md to clarify test execution modes, emphasizing the separation of tests requiring API keys from those that do not.
- Expanded the testing guidelines in TESTING_GUIDELINES.md to detail the organization of tests based on API dependencies, including tagging conventions and execution paths.
- Improved mock-services.yml to include dummy configurations for LLM and embedding services, ensuring tests can run without actual API calls.
- Added comprehensive documentation on GitHub workflows for different test scenarios, enhancing clarity for contributors and maintainers.
* Update test configurations and documentation for API key management
- Modified `plugins.yml.template` to implement event subscriptions for the Home Assistant plugin, enhancing its event-driven capabilities.
- Revised `README.md` to clarify test execution processes, emphasizing the distinction between tests requiring API keys and those that do not.
- Updated `mock-services.yml` to streamline mock configurations, ensuring compatibility with the new testing workflows.
- Added `requires-api-keys` tags to relevant test cases across various test files, improving organization and clarity regarding API dependencies.
- Enhanced documentation for test scripts and configurations, providing clearer guidance for contributors on executing tests based on API key requirements.
* Add optional service profile to Docker Compose test configuration
* Refactor audio processing and job handling for transcription workflows
- Updated `upload_and_process_audio_files` and `start_post_conversation_jobs` to enqueue transcription jobs separately for file uploads, ensuring accurate processing order.
- Enhanced logging to provide clearer insights into job enqueuing and processing stages.
- Removed batch transcription from the post-conversation job chain for streaming audio, utilizing the streaming transcript directly.
- Introduced word-level timestamps in the `Conversation` model to improve transcript detail and accuracy.
- Updated tests to reflect changes in job handling and ensure proper verification of post-conversation processing.
* Remove unnecessary network aliases from speaker service in Docker Compose configuration
* Add network aliases for speaker service in Docker Compose configuration
* Refactor Conversation model to use string for provider field
- Updated the `Conversation` model to replace the `TranscriptProvider` enum with a string type for the `provider` field, allowing for greater flexibility in provider names.
- Adjusted related job functions to accommodate this change, simplifying provider handling in the transcription workflow.
* Enhance configuration and model handling for waveform data
- Updated Docker Compose files to mount the entire config directory, allowing for better management of configuration files.
- Introduced a new `WaveformData` model to store pre-computed waveform visualization data, improving UI performance by enabling waveform display without real-time decoding.
- Enhanced the `app_factory` and `job` models to include the new `WaveformData` model, ensuring proper initialization and data handling.
- Implemented waveform generation logic in a new worker module, allowing for on-demand waveform creation from audio chunks.
- Added API endpoints for retrieving and generating waveform data, improving the overall audio processing capabilities.
- Updated tests to cover new functionality and ensure robustness in waveform data handling.
* Add SDK testing scripts for authentication, conversation retrieval, and audio upload
- Introduced three new test scripts: `sdk_test_auth.py`, `sdk_test_conversations.py`, and `sdk_test_upload.py`.
- Each script tests different functionalities of the SDK, including authentication, conversation retrieval, and audio file uploads.
- The scripts utilize the `ChronicleClient` to perform operations and print results for verification.
- Enhanced testing capabilities for the SDK, ensuring robust validation of core features.
* Enhance audio processing and conversation handling for large files
- Added configuration options for speaker recognition chunking in `.env.template`, allowing for better management of large audio files.
- Updated `get_conversations` function to include an `include_deleted` parameter for filtering conversations based on their deletion status.
- Enhanced `finalize_session` method in `AudioStreamProducer` to send an end marker to Redis, ensuring proper session closure.
- Introduced `reconstruct_audio_segments` function to yield audio segments with overlap for efficient processing of lengthy conversations.
- Implemented merging of overlapping speaker segments to improve accuracy in speaker recognition.
- Added integration tests for WebSocket streaming transcription to validate the end_marker functionality and overall transcription flow.
* archive
* Implement annotation system and enhance audio processing capabilities
- Introduced a new annotation model to support user edits and AI-powered suggestions for memories and transcripts.
- Added annotation routes for CRUD operations, enabling the creation and management of annotations via the API.
- Enhanced the audio processing workflow to support fetching audio segments from the backend, improving speaker recognition accuracy.
- Updated the speaker recognition client to handle conversation-based audio fetching, allowing for better management of large audio files.
- Implemented a cron job for generating AI suggestions on potential errors in transcripts and memories, improving user experience and content accuracy.
- Enhanced the web UI to support inline editing of transcript segments and memory content, providing a more interactive user experience.
- Updated configuration files to support new features and improve overall system flexibility.
* Implement OmegaConf-based configuration management for backend settings
- Introduced a new configuration loader using OmegaConf for unified management of backend settings.
- Updated existing configuration functions to leverage the new loader, enhancing flexibility and maintainability.
- Added support for environment variable interpolation in configuration files.
- Refactored various components to retrieve settings from the new configuration system, improving consistency across the application.
- Updated requirements to include OmegaConf as a dependency.
- Enhanced documentation and comments for clarity on configuration management.
* Refactor .env.template and remove unused diarization configuration
- Updated the .env.template to clarify its purpose for secret values and streamline setup instructions.
- Removed the deprecated diarization_config.json.template file, as it is no longer needed.
- Added new environment variables for Langfuse and Tailscale integration to enhance observability and remote service access.
* Implement legacy environment variable syntax support in configuration loader
- Added custom OmegaConf resolvers to handle legacy ${VAR:-default} syntax for backward compatibility.
- Introduced a preprocessing function to convert legacy syntax in YAML files to OmegaConf-compatible format.
- Updated the load_config function to utilize the new preprocessing for loading defaults and user configurations.
- Enhanced documentation for clarity on the new legacy syntax handling.
* Add plugins configuration path retrieval and refactor usage
- Introduced a new function `get_plugins_yml_path` to centralize the retrieval of the plugins.yml file path.
- Updated `system_controller.py` and `plugin_service.py` to use the new function for improved maintainability and consistency in accessing the plugins configuration.
- Enhanced code clarity by removing hardcoded paths and utilizing the centralized configuration method.
* Unify plugin terminology and fix memory job dependencies
Plugin terminology: subscriptions→events, trigger→condition
Memory jobs: no longer blocked by disabled speaker recognition
* Update Docker Compose configuration and enhance system routes
- Updated Docker Compose files to mount the entire config directory, consolidating configuration management.
- Refactored the `save_diarization_settings` function to improve clarity and maintainability by renaming it to `save_diarization_settings_controller`.
- Enhanced the System component in the web UI to include configuration diagnostics, providing better visibility into system health and issues.
* circular import
* Refactor testing infrastructure and enhance container management
- Updated the testing documentation to reflect a new Makefile-based approach for running tests and managing containers.
- Introduced new scripts for container management, including starting, stopping, restarting, and cleaning containers while preserving logs.
- Added a cleanup script to handle data ownership and permissions correctly.
- Implemented a logging system that saves container logs automatically before cleanup.
- Enhanced the README with detailed instructions for running tests and managing the test environment.
* Add Email Summarizer Plugin and SMTP Email Service
- Introduced the Email Summarizer Plugin that automatically sends email summaries upon conversation completion.
- Implemented SMTP Email Service for sending emails, supporting HTML and plain text formats with TLS/SSL encryption.
- Added configuration options for SMTP settings in the .env.template and plugins.yml.template.
- Created comprehensive documentation for plugin development and usage, including a new plugin generation script.
- Enhanced testing coverage for the Email Summarizer Plugin and SMTP Email Service to ensure reliability and functionality.
* Refactor plugin management and introduce Email Summarizer setup
- Removed the static PLUGINS dictionary and replaced it with a dynamic discovery mechanism for plugins.
- Implemented a new setup process for plugins, allowing for configuration via individual setup scripts.
- Added the Email Summarizer plugin with a dedicated setup script for SMTP configuration.
- Enhanced the main setup flow to support community plugins and their configuration.
- Cleaned up unused functions related to plugin configuration and streamlined the overall plugin setup process.
* Enhance plugin configuration and documentation
- Updated the .env.template to include new configuration options for the Home Assistant and Email Summarizer plugins, including server URLs, tokens, and additional settings.
- Refactored Docker Compose files to correctly mount plugin configuration paths.
- Introduced comprehensive documentation for plugin configuration architecture, detailing the separation of concerns for orchestration, settings, and secrets.
- Added individual configuration files for the Home Assistant and Email Summarizer plugins, ensuring proper management of non-secret settings and environment variable references.
- Improved the plugin loading process to merge configurations from multiple sources, enhancing flexibility and maintainability.
* Refactor plugin setup process to allow interactive user input
- Updated the plugin setup script to run interactively, enabling plugins to prompt for user input during configuration.
- Removed output capturing to facilitate real-time interaction and improved error messaging to include exit codes for better debugging.
* Add shared setup utilities for interactive configuration
- Introduced `setup_utils.py` containing functions for reading environment variables, prompting user input, and masking sensitive values.
- Refactored existing code in `wizard.py` and `init.py` to utilize these shared utilities, improving code reuse and maintainability.
- Updated documentation to include usage examples for the new utilities in plugin setup scripts, enhancing developer experience and clarity.
* Enhance plugin security architecture and configuration management
- Introduced a three-file separation for plugin configuration to improve security:
- `backends/advanced/.env` for secrets (gitignored)
- `config/plugins.yml` for orchestration with environment variable references
- `plugins/{plugin_id}/config.yml` for non-secret defaults
- Updated documentation to emphasize the importance of using `${ENV_VAR}` syntax for sensitive data and provided examples of correct usage.
- Enhanced the Email Summarizer plugin setup process to automatically update `config/plugins.yml` with environment variable references, ensuring secrets are not hardcoded.
- Added new fields to the User model for notification email management and improved error logging in user-related functions.
- Refactored audio chunk utilities to use a consistent method for fetching conversation metadata.
* Refactor backend components for improved functionality and stability
- Added a new parameter `transcript_version_id` to the `open_conversation_job` function to support streaming transcript versioning.
- Enhanced error handling in `check_enrolled_speakers_job` and `recognise_speakers_job` to allow conversations to proceed even when the speaker service is unavailable, improving resilience.
- Updated `send_to_adv.py` to support dynamic WebSocket and HTTP protocols based on environment settings, enhancing configuration flexibility.
- Introduced a background task in `send_to_adv.py` to handle incoming messages from the backend, ensuring connection stability and logging interim results.
* Refactor plugin setup timing to enhance configuration flow
* Refactor save_diarization_settings_controller to improve validation and error handling
- Updated the controller to filter out invalid settings instead of raising an error for each unknown key, allowing for more flexible input.
- Added a check to reject requests with no valid settings provided, enhancing robustness.
- Adjusted logging to reflect the filtered settings being saved.
* Refactor audio processing and conversation management for improved deduplication and tracking
* Refactor audio and email handling for improved functionality and security
- Updated `mask_value` function to handle whitespace more effectively.
- Enhanced `create_plugin` to remove existing directories when using the `--force` option.
- Changed logging level from error to debug for existing admin user checks.
- Improved client ID generation logging for clarity.
- Removed unused fields from conversation creation.
- Added HTML escaping in email templates to prevent XSS attacks.
- Updated audio file download function to include user ID for better tracking.
- Adjusted WebSocket connection settings to respect SSL verification based on environment variables.
* Refactor audio upload functionality to remove unused parameters
- Removed `auto_generate_client` and `folder` parameters from audio upload functions to streamline the API.
- Updated related function calls and documentation to reflect these changes, enhancing clarity and reducing complexity.
* Refactor Email Summarizer plugin configuration for improved clarity and security
- Removed outdated migration instructions from `plugin-configuration.md` to streamline documentation.
- Enhanced `README.md` to clearly outline the three-file separation for plugin configuration, emphasizing the roles of `.env`, `config.yml`, and `plugins.yml`.
- Updated `setup.py` to reflect changes in orchestration settings, ensuring only relevant configurations are included in `config/plugins.yml`.
- Improved security messaging to highlight the importance of not committing secrets to version control.
* Update API key configuration in config.yml.template to use environment variable syntax for improved flexibility and security. This change standardizes the way API keys are referenced across different models and services. (#273)
Co-authored-by: roshan.john <roshanjohn1460@gmail.com>
* Refactor Redis job queue cleanup process for improved success tracking
- Replaced total job count with separate counters for successful and failed jobs during Redis queue cleanup.
- Enhanced logging to provide detailed feedback on the number of jobs cleared and any failures encountered.
- Improved error handling to ensure job counts are accurately reflected even when exceptions occur.
* fix tests
* Update CI workflows to use 'docker compose' for log retrieval and added container status check
- Replaced 'docker logs' commands with 'docker compose -f docker-compose-test.yml logs' for consistency across workflows.
- Added a check for running containers before saving logs to enhance debugging capabilities.
* test fixes
* FIX StreamingTranscriptionConsumer to support cumulative audio timestamp adjustments
- Added `audio_offset_seconds` to track cumulative audio duration for accurate timestamp adjustments across transcription sessions.
- Updated `store_final_result` method to adjust word and segment timestamps based on cumulative audio offset.
- Improved logging to reflect changes in audio offset after storing results.
- Modified Makefile and documentation to clarify test execution options, including new tags for slow and SDK tests, enhancing test organization and execution clarity.
* Enhance test container setup and improve error messages in integration tests
- Set `COMPOSE_PROJECT_NAME` for test containers to ensure consistent naming.
- Consolidated error messages in the `websocket_transcription_e2e_test.robot` file for clarity, improving readability and debugging.
* Improve WebSocket closing logic and enhance integration test teardown
- Added timeout handling for WebSocket closure in `AudioStreamClient` to prevent hanging and ensure clean disconnection.
- Updated integration tests to log the total chunks sent when closing audio streams, improving clarity on resource management during test teardown.
* Refactor job status handling to align with RQ standards
- Updated job status checks across various modules to use "started" and "finished" instead of "processing" and "completed" for consistency with RQ's naming conventions.
- Adjusted related logging and response messages to reflect the new status terminology.
- Simplified Docker Compose project name handling in test scripts to avoid conflicts and improve clarity in test environment setup.
* Update test configurations and improve audio inactivity handling
- Increased `SPEECH_INACTIVITY_THRESHOLD_SECONDS` to 20 seconds in `docker-compose-test.yml` for better audio duration handling during tests.
- Refactored session handling in `session_controller.py` to clarify client ID usage.
- Updated `conversation_utils.py` to track speech activity using audio timestamps, enhancing accuracy in inactivity detection.
- Simplified test scripts by removing unnecessary `COMPOSE_PROJECT_NAME` references, aligning with the new project naming convention.
- Adjusted integration tests to reflect changes in inactivity timeout and ensure proper handling of audio timestamps.
* Refactor audio processing and enhance error handling
- Updated `worker_orchestrator.py` to use `logger.exception` for improved error logging.
- Changed default MongoDB database name from "friend-lite" to "chronicle" in multiple files for consistency.
- Added a new method `close_stream_without_stop` in `audio_stream_client.py` to handle abrupt WebSocket disconnections.
- Enhanced audio validation in `audio_utils.py` to support automatic resampling of audio data if sample rates do not match.
- Improved logging in various modules to provide clearer insights during audio processing and event dispatching.
* Enhance Docker command handling and configuration management
- Updated `run_compose_command` to support separate build commands for services, including profile management for backend and speaker-recognition services.
- Improved error handling and output streaming during Docker command execution.
- Added `ensure_docker_network` function to verify and create the required Docker network before starting services.
- Refactored configuration files to utilize `oc.env` for environment variable management, ensuring better compatibility and flexibility across different environments.
* Enhance configuration loading to support custom config file paths
- Added support for the CONFIG_FILE environment variable to allow specifying custom configuration files for testing.
- Implemented logic to handle both absolute paths and relative filenames for the configuration file, improving flexibility in configuration management.
* Update test scripts to use TEST_CONFIG_FILE for configuration management
- Replaced CONFIG_FILE with TEST_CONFIG_FILE in both run-no-api-tests.sh and run-robot-tests.sh to standardize configuration file usage.
- Updated paths to point to mock and deepgram-openai configuration files inside the container, improving clarity and consistency in test setups.
* Refactor audio upload response handling and improve error reporting
- Updated `upload_and_process_audio_files` to return appropriate HTTP status codes based on upload results: 400 for all failures, 207 for partial successes, and 200 for complete success.
- Enhanced error messages in the audio upload tests to provide clearer feedback on upload failures, including specific error details for better debugging.
- Adjusted test scripts to ensure consistent handling of conversation IDs in job metadata, improving validation checks for job creation.
* Refactor audio processing and job handling to improve transcription management
- Updated `upload_and_process_audio_files` to check for transcription provider availability before enqueueing jobs, enhancing error handling and logging.
- Modified `start_post_conversation_jobs` to conditionally enqueue memory extraction jobs based on configuration, improving flexibility in job management.
- Enhanced event dispatch job dependencies to only include jobs that were actually enqueued, ensuring accurate job tracking.
- Added `is_transcription_available` function to check transcription provider status, improving modularity and clarity in the transcription workflow.
* Enhance integration tests for plugin events and improve error handling
- Updated integration tests to filter plugin events by conversation ID, ensuring accurate event tracking and reducing noise from fixture events.
- Improved error messages in event verification to include conversation ID context, enhancing clarity during test failures.
- Refactored audio upload handling to check for transcription job creation, allowing for more robust conversation polling and error reporting.
- Added new keyword to verify conversation end reasons, improving test coverage for conversation state validation.
* Enhance speaker recognition testing and audio processing
- Added mock speaker recognition client to facilitate testing without resource-intensive dependencies.
- Updated Docker Compose configurations to include mock speaker client for test environments.
- Refactored audio segment reconstruction to ensure precise clipping based on time boundaries.
- Improved error handling in transcription jobs and speaker recognition workflows to enhance robustness.
- Adjusted integration tests to utilize real-time pacing for audio chunk streaming, improving test accuracy.
* Refactor audio chunk retrieval and enhance logging in audio processing
- Introduced logging for audio chunk requests to improve traceability.
- Replaced manual audio chunk processing with a dedicated `reconstruct_audio_segment` function for better clarity and efficiency.
- Improved error handling during audio reconstruction to provide more informative responses in case of failures.
- Cleaned up imports and removed redundant code related to audio chunk calculations.
* Refactor mock speaker recognition client and improve testing structure
- Replaced direct import of mock client with a structured import from the new testing module.
- Introduced a dedicated `mock_speaker_client.py` to provide a mock implementation for speaker recognition, facilitating testing without heavy dependencies.
- Added an `__init__.py` file in the testing directory to organize testing utilities and mocks.
* Enhance conversation model to include word-level timestamps and improve transcript handling
- Added a new `words` field to the `Conversation` model for storing word-level timestamps.
- Updated methods to handle word data during transcript version creation, ensuring compatibility with speaker recognition.
- Refactored conversation job processing to utilize the new word structure, improving data integrity and access.
- Enhanced speaker recognition job to read words from the new standardized location, ensuring backward compatibility with legacy data.
* Implement speaker reprocessing feature and enhance timeout calculation
- Added a new endpoint to reprocess speaker identification for existing transcripts, creating a new version with re-identified speakers.
- Introduced a method…
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