Update configuration management and enhance file structure, add test-matrix#237
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- 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.
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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 📝 WalkthroughWalkthroughThe PR centralizes configuration under Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Wizard/Init
participant ConfigManager
participant FS as FileSystem
participant Env as .env
participant Services
Note left of User: interactive setup / test runner
User->>Wizard/Init: start setup or run-test
Wizard/Init->>ConfigManager: get_config_manager()
ConfigManager->>FS: load config/config.yml (or template)
alt config missing
ConfigManager->>FS: write config/config.yml from template
ConfigManager->>FS: create backups on save
end
Wizard/Init->>ConfigManager: update defaults / memory / stt
ConfigManager->>FS: save config/config.yml (with backup)
ConfigManager->>Env: update .env variables (MEMORY_PROVIDER etc.)
ConfigManager->>Services: (optional) provide provider info for startup
Services->>ConfigManager: query defaults (e.g., DEFAULT_STT) at runtime
Services->>Env: start/skip Deepgram or Parakeet based on DEFAULT_STT
Note right of Services: tests run (Robot) using CONFIG_FILE env
Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes Possibly related PRs
Suggested reviewers
Poem
Pre-merge checks and finishing touches❌ Failed checks (1 inconclusive)
✅ Passed checks (2 passed)
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Actionable comments posted: 5
🧹 Nitpick comments (5)
.gitignore (1)
14-15: Backup patterns show minor redundancy (optional refactor).The pattern
config/*.backup*on line 15 is strictly broader thanconfig/*.backup.*on line 14, making the latter redundant. Consider simplifying to justconfig/*.backup*unless you specifically need to distinguish between backups with and without dot-separated extensions.backends/advanced/start-workers.sh (1)
54-63: Consider improving error handling and observability.The current implementation suppresses all errors when reading the configuration (
2>/dev/null), which could hide important failures such as missing config files, syntax errors, or import failures. Additionally, an emptyDEFAULT_STTis logged but not flagged as potentially problematic.💡 Suggested improvement
Consider capturing error output separately and logging it, or at least warning when
DEFAULT_STTis empty:# Determine which STT provider to use from config.yml echo "📋 Checking config.yml for default STT provider..." -DEFAULT_STT=$(uv run python -c " +DEFAULT_STT=$(uv run python -c " from advanced_omi_backend.model_registry import get_models_registry registry = get_models_registry() if registry and registry.defaults: print(registry.defaults.get('stt', '')) -" 2>/dev/null || echo "") +" 2>&1 || echo "") -echo "📋 Configured STT provider: ${DEFAULT_STT:-none}" +if [ -z "$DEFAULT_STT" ]; then + echo "⚠️ No default STT provider configured" +else + echo "📋 Configured STT provider: $DEFAULT_STT" +fibackends/advanced/init.py (1)
729-729: Remove unnecessary f-string prefix.The f-string has no placeholders, so the
fprefix is redundant.🔎 Proposed fix
- self.console.print(f" • ../../config/config.yml - Model and memory provider configuration") + self.console.print(" • ../../config/config.yml - Model and memory provider configuration")As per static analysis hint from Ruff.
tests/resources/memory_keywords.robot (1)
187-226: Consider moving memory similarity check to test layer.
Check Memory Similarity With OpenAIis a verification/comparison keyword. While it doesn't contain explicit assertions, it implements verification logic that the coding guidelines recommend keeping in the test layer for clarity and adherence to the Arrange-Act-Assert pattern.Consider whether this keyword should be refactored to be called directly from tests rather than being a reusable keyword, especially since it's tightly coupled to test validation logic.
tests/integration/integration_test.robot (1)
15-15: Remove unused import.The
queue_keywords.robotresource is imported but no keywords from it are used in this test file.🔎 Proposed fix
Resource ../resources/memory_keywords.robot -Resource ../resources/queue_keywords.robot Variables ../setup/test_env.py
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📒 Files selected for processing (28)
.gitignoreDocs/getting-started.mdbackends/advanced/Docs/README.mdbackends/advanced/Docs/contribution.mdbackends/advanced/Docs/memories.mdbackends/advanced/Docs/memory-configuration-guide.mdbackends/advanced/Docs/quickstart.mdbackends/advanced/SETUP_SCRIPTS.mdbackends/advanced/docker-compose-test.ymlbackends/advanced/docker-compose.ymlbackends/advanced/init.pybackends/advanced/run-test.shbackends/advanced/start-workers.shconfig/README.mdconfig/config.yml.templateextras/speaker-recognition/run-test.shservices.pytests/configs/README.mdtests/configs/deepgram-openai.ymltests/configs/full-local.ymltests/configs/parakeet-ollama.ymltests/configs/parakeet-openai.ymltests/integration/integration_test.robottests/resources/audio_keywords.robottests/resources/memory_keywords.robottests/run-robot-tests.shtests/setup/test_data.pywizard.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:
tests/setup/test_data.pywizard.pyservices.pybackends/advanced/init.py
**/*.robot
📄 CodeRabbit inference engine (CLAUDE.md)
**/*.robot: Only use the 11 approved tags from @tests/tags.md in Robot Framework tests - custom tags are not permitted
Use tab-separated tags in Robot Framework tests (e.g.,[Tags] infra audio-streaming), never space-separated
Write verifications directly in Robot Framework tests inline, not abstracted to keywords
Follow the Arrange-Act-Assert pattern in Robot Framework tests with inline verifications
Use descriptive Robot Framework test and keyword names that explain business purpose, not technical implementation
Files:
tests/resources/audio_keywords.robottests/resources/memory_keywords.robottests/integration/integration_test.robot
🧠 Learnings (4)
📚 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:
tests/setup/test_data.pywizard.pyservices.pybackends/advanced/init.py
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Applies to **/*.robot : Use descriptive Robot Framework test and keyword names that explain business purpose, not technical implementation
Applied to files:
tests/run-robot-tests.shtests/resources/memory_keywords.robottests/integration/integration_test.robot
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Before writing Robot Framework test code, scan relevant resource files for existing keywords - never write code that duplicates existing keywords
Applied to files:
tests/resources/memory_keywords.robottests/integration/integration_test.robot
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Applies to **/*.robot : Write verifications directly in Robot Framework tests inline, not abstracted to keywords
Applied to files:
tests/integration/integration_test.robot
🧬 Code graph analysis (2)
tests/run-robot-tests.sh (3)
backends/advanced/run-test.sh (1)
print_info(16-18)extras/speaker-recognition/run-test.sh (1)
print_info(34-36)backends/advanced/setup-https.sh (1)
print_info(15-17)
extras/speaker-recognition/run-test.sh (3)
backends/advanced/run-test.sh (1)
print_info(16-18)tests/run-robot-tests.sh (1)
print_info(16-18)run-test.sh (1)
print_info(17-19)
🪛 LanguageTool
backends/advanced/Docs/README.md
[style] ~91-~91: You have already used this phrasing in nearby sentences. Consider replacing it to add variety to your writing.
Context: ...yml` - Configuration overview ### "I want to work on memory extraction" 1. [memori...
(REP_WANT_TO_VB)
🪛 Ruff (0.14.10)
wizard.py
331-331: String contains ambiguous ℹ (INFORMATION SOURCE). Did you mean i (LATIN SMALL LETTER I)?
(RUF001)
services.py
27-27: Do not catch blind exception: Exception
(BLE001)
backends/advanced/init.py
729-729: f-string without any placeholders
Remove extraneous f prefix
(F541)
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)
- GitHub Check: robot-tests
🔇 Additional comments (31)
.gitignore (2)
9-15: Configuration directory restructuring is correctly implemented.The changes properly migrate configuration file handling from root-level to the dedicated
config/subdirectory, following established gitignore conventions (similar to.envandmemory_config.yamlpatterns elsewhere in the file). The negation pattern!config/config.yml.templateensures the template file is tracked.
7-7: Old root-level configuration patterns have been successfully removed.The file contains no instances of the old root-level
config.ymlor!config.yml.templatepatterns. All configuration entries now use the subdirectory-level patterns (config/config.ymland!config/config.yml.templateon lines 10-11), with no conflicting entries elsewhere in the file.backends/advanced/start-workers.sh (1)
54-61: The config file path handling and deployment context are already properly addressed in the codebase:
Path resolution is explicit:
_find_config_path()searches CONFIG_FILE environment variable, current directory,/app/config.yml(Docker container path), and walks up from the module directory.Error handling is graceful:
load_models_config()returnsNoneif the config file doesn't exist (line 302-303), and the script checksif registry and registry.defaults:before accessing it, so missing config fails safely without crashing.Docker mounting is correct: Both
docker-compose.ymlanddocker-compose-test.ymlexplicitly mount../../config/config.yml:/app/config.yml, mapping the host config to the container's expected path at/app/config.yml.Script behavior is correct: When config is missing,
DEFAULT_STTbecomes empty, provider-specific workers are skipped, and the script continues without error.No changes needed—the implementation already handles path resolution and deployment context correctly.
Likely an incorrect or invalid review comment.
backends/advanced/SETUP_SCRIPTS.md (1)
9-9: LGTM!The documentation update correctly reflects the new configuration path
config/config.yml.tests/configs/full-local.yml (1)
1-1: Verify the YAML format.This file contains a single string without list syntax. If this is intended to be a list of test configuration files, it should use YAML list syntax:
-parakeet-ollama.yml +- parakeet-ollama.ymlIf this file is meant to contain only a single string value for a specific purpose, the current format is correct.
Can you clarify the intended format and usage of this file?
services.py (1)
18-29: LGTM!The configuration path update is correctly implemented. The function now loads from
config/config.ymland handles errors appropriately by logging a warning and returningNone, which allows the system to continue with fallback behavior.The static analysis hint about catching blind
Exceptionis acceptable here since any error during configuration loading should be caught and logged, allowing the service to continue with defaults.backends/advanced/Docs/quickstart.md (1)
343-343: LGTM!All configuration path references have been correctly updated from
config.ymltoconfig/config.ymlthroughout the documentation.Also applies to: 542-545, 614-614, 728-728
backends/advanced/Docs/memories.md (1)
13-13: LGTM!Configuration path references correctly updated to
config/config.yml.Also applies to: 183-183
backends/advanced/Docs/memory-configuration-guide.md (1)
9-12: LGTM!Configuration path references correctly updated to
config/config.ymlin the Quick Start section and Next Steps.Also applies to: 130-130
tests/setup/test_data.py (1)
39-51: LGTM!The new
EXPECTED_MEMORIESconstant is well-documented and provides clear test expectations for the DIY Glass Blowing audio integration test.backends/advanced/docker-compose-test.yml (1)
17-17: LGTM!The configuration mount path has been updated to use an environment variable with a sensible default. The change:
- Provides flexibility to override the config file location via
CONFIG_FILEenvironment variable- Maintains the default path
../../config/config.ymlwhich correctly resolves to the repository root- Preserves read-only mount semantics
- Is consistently applied to both
chronicle-backend-testandworkers-testservicesAlso applies to: 132-132
config/README.md (1)
1-106: LGTM! Well-structured configuration documentation.The README clearly documents the new config directory structure, setup procedures, environment variable substitution, and configuration sections. The examples are accurate and helpful for users.
backends/advanced/init.py (1)
31-31: LGTM! Configuration path updated correctly.The path reference has been updated to reflect the new
config/config.ymllocation, consistent with the PR's configuration restructuring.Docs/getting-started.md (1)
345-345: LGTM! Documentation references updated correctly.All configuration file path references have been consistently updated to
config/config.ymlthroughout the documentation.Also applies to: 547-547, 616-616, 730-730
backends/advanced/Docs/README.md (1)
16-16: LGTM! Documentation paths updated consistently.All configuration file references have been updated to reflect the new
config/config.ymlpath structure.Also applies to: 73-73, 89-89, 93-93, 133-133, 151-151, 165-165, 178-178, 185-185, 191-191
backends/advanced/Docs/contribution.md (1)
4-4: LGTM! Configuration path references updated.The documentation correctly references the new
config/config.ymlpath.Also applies to: 9-9
tests/configs/parakeet-openai.yml (1)
1-73: LGTM! Well-structured test configuration.This test configuration correctly sets up a hybrid stack with local Parakeet STT and cloud-based OpenAI LLM. The configuration properly uses environment variable substitution, avoids hardcoded secrets, and defines appropriate model parameters.
extras/speaker-recognition/run-test.sh (1)
16-21: LGTM! Proper test environment isolation.The explicit
COMPOSE_PROJECT_NAMEexport and its use in the cleanup function ensures test containers are isolated from development environments, preventing conflicts. This aligns with the broader pattern of test isolation across the project.Also applies to: 127-128
tests/configs/deepgram-openai.yml (1)
1-84: LGTM - Well-structured test configuration.The configuration properly uses environment variable substitution (
${VAR:-default}) for secrets, includes comprehensive provider settings, and follows consistent YAML structure. The memory extraction prompt and timeout settings are appropriate for testing.tests/configs/parakeet-ollama.yml (1)
1-73: LGTM - Consistent local test configuration.The configuration properly supports fully local testing with sensible defaults (localhost URLs, no API keys required). The structure is consistent with
deepgram-openai.ymland follows the same patterns for environment variable substitution.backends/advanced/docker-compose.yml (1)
15-15: LGTM - Configuration path updated consistently.Both the
chronicle-backendandworkersservices now correctly reference the nested configuration path../../config/config.yml, aligning with the repository-wide configuration restructuring described in the PR objectives.Also applies to: 68-68
tests/run-robot-tests.sh (2)
45-53: LGTM - Proper config file handling with path normalization.The script correctly:
- Sets a default
CONFIG_FILEpointing to the new nested path (../config/config.yml)- Converts relative paths to absolute paths for Docker Compose compatibility
- Exports the variable for use by Docker Compose
- Logs the resolved config path for debugging
Also applies to: 82-82
114-116: LGTM - Test isolation via unique project name.Setting
COMPOSE_PROJECT_NAME="advanced-backend-test"properly isolates test containers from the development environment, and the cleanup logic has been updated to match the new container naming convention.Also applies to: 126-126
tests/resources/audio_keywords.robot (2)
72-96: Orchestration keyword is well-structured.
Upload Audio File And Wait For Memoryappropriately orchestrates multiple actions (upload, find job, wait) and is suitable for end-to-end test flows. The keyword follows good composition patterns by reusing existing keywords.Minor note: Line 86 contains a
Should Not Be Emptyassertion. While orchestration keywords can include basic sanity checks, consider whether this assertion should be in the test layer for strictest adherence to inline verification guidelines. However, this is acceptable as-is for fail-fast behavior in composite actions.
85-85: TheGet Jobs By Type And Conversationkeyword is properly defined inqueue_keywords.robotand is correctly used here. Keyword definition found at queue_keywords.robot:204-222 with matching arguments.tests/configs/README.md (1)
1-132: LGTM - Comprehensive test configuration documentation.The README provides clear guidance on:
- Available test configurations and their use cases
- Usage patterns with different test runners
- Best practices for creating new configurations
- Environment variable handling patterns
The documentation will help maintainers understand and extend the test configuration matrix.
backends/advanced/run-test.sh (2)
50-50: LGTM - Consistent config file override handling.The script properly:
- Captures command-line
CONFIG_FILEoverrides before loading.envfiles- Restores the override after environment loading to ensure CLI takes precedence
- Sets a sensible default (
../../config/config.yml) when not provided- Logs the override for debugging
This pattern is consistent with other environment variable overrides in the script.
Also applies to: 94-102
175-176: LGTM - Test container isolation.Setting
COMPOSE_PROJECT_NAME="advanced-backend-test"before bringing down containers ensures test containers are properly isolated from development containers, matching the pattern intests/run-robot-tests.sh.tests/integration/integration_test.robot (3)
153-156: Excellent inline verification pattern.This phase demonstrates the correct approach by writing verifications directly in the test rather than abstracting them to keywords. This makes the test logic clear and easy to follow.
Based on coding guidelines requiring inline verifications.
136-136: No issues found. Both "e2e" and "memory" are in the approved tag list from tests/tags.md, and the tags are correctly tab-separated.
158-160: Move memory quality verifications inline to the test.The
Verify Memory Quality With OpenAIkeyword abstracts verifications into a resource file, violating the coding guideline that verification steps must be written directly in test files. This keyword is used only once inintegration_test.robotand does not meet the exception criteria (which requires complex multi-step verification reused across multiple test suites). Move the assertion logic (Should Be True ${result}[similar] == ${True}...) directly into this test at line 160, keeping only the setup/action (Check Memory Similarity With OpenAI) in the resource file.⛔ Skipped due to learnings
Learnt from: CR Repo: chronicler-ai/chronicle PR: 0 File: CLAUDE.md:0-0 Timestamp: 2025-12-20T01:11:51.495Z Learning: Applies to **/*.robot : Write verifications directly in Robot Framework tests inline, not abstracted to keywordsLearnt from: CR Repo: chronicler-ai/chronicle PR: 0 File: CLAUDE.md:0-0 Timestamp: 2025-12-20T01:11:51.495Z Learning: Applies to **/*.robot : Follow the Arrange-Act-Assert pattern in Robot Framework tests with inline verificationsLearnt from: CR Repo: chronicler-ai/chronicle PR: 0 File: CLAUDE.md:0-0 Timestamp: 2025-12-20T01:11:51.495Z Learning: Applies to **/*.robot : Use descriptive Robot Framework test and keyword names that explain business purpose, not technical implementation
- Introduced a new `test-requirements.txt` file to manage testing dependencies. - Removed redundant import of `shutil` in `wizard.py` to improve code clarity.
- 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.
- 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.
- 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.
- 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.
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⚠️ Outside diff range comments (1)
tests/setup/test_env.py (1)
22-24: Fix misleading comment or update implementation.The comment on line 23 claims "Use BACKEND_URL from test.env" but
API_URLis hardcoded. Either update the code to read from the environment or correct the comment.Proposed fix options
Option 1: Read from environment (recommended for test flexibility)
-API_URL = 'http://localhost:8001' # Use BACKEND_URL from test.env -API_BASE = 'http://localhost:8001/api' +API_URL = os.getenv('BACKEND_URL', 'http://localhost:8001') +API_BASE = f'{API_URL}/api'Option 2: Update comment to match current behavior
-API_URL = 'http://localhost:8001' # Use BACKEND_URL from test.env +API_URL = 'http://localhost:8001' # Hardcoded for test environment
♻️ Duplicate comments (1)
tests/resources/memory_keywords.robot (1)
278-292: Remove verification keyword - move assertions to tests.This is the same issue flagged in the previous review.
Verify Memory Quality With OpenAIcontains aShould Be Trueassertion (line 289), violating the coding guidelines that state: "Write verifications directly in Robot Framework tests inline, not abstracted to keywords."The file's own documentation (line 14) confirms: "Keywords that should NOT be in this file: Verification/assertion keywords (belong in tests)".
Remove this keyword and move the verification logic directly into test cases as inline assertions following the Arrange-Act-Assert pattern.
Based on learnings, coding guidelines.
🔎 Proposed refactor
Remove from memory_keywords.robot:
-Verify Memory Quality With OpenAI - [Documentation] Verify extracted memories match expected memories using OpenAI - [Arguments] ${actual_memories} ${expected_memories} - - # Get OpenAI API key from environment - ${openai_key}= Get Environment Variable OPENAI_API_KEY - - # Check similarity - ${result}= Check Memory Similarity With OpenAI ${actual_memories} ${expected_memories} ${openai_key} - - # Assert memories are similar - Should Be True ${result}[similar] == ${True} - ... Memory similarity check failed: ${result}[reason] - - Log ✅ Memory quality validated INFOAdd inline to your test:
# Arrange ${openai_key}= Get Environment Variable OPENAI_API_KEY ${expected_memories}= Set Variable ${TEST_EXPECTED_MEMORIES} # Act ${result}= Check Memory Similarity With OpenAI ${actual_memories} ${expected_memories} ${openai_key} # Assert Should Be True ${result}[similar] == ${True} ... Memory similarity check failed: ${result}[reason] Log ✅ Memory quality validated INFO
🧹 Nitpick comments (8)
tests/setup/test_env.py (2)
4-20: Environment loading implementation looks good.The dotenv-based loading with correct precedence is well-implemented. The use of
override=Falseensures the proper priority: environment variables > .env.test > .env.Optional: Add validation for missing .env files
If you want to ensure .env files are present during development (while keeping flexibility for CI), consider:
# Load .env.test first (will set test-specific values) -load_dotenv(backend_dir / ".env.test", override=False) +env_test_loaded = load_dotenv(backend_dir / ".env.test", override=False) +if not env_test_loaded: + print(f"Warning: {backend_dir / '.env.test'} not found") # Load .env second (will only fill in missing values, won't override .env.test or existing env vars) -load_dotenv(backend_dir / ".env", override=False) +env_loaded = load_dotenv(backend_dir / ".env", override=False) +if not env_loaded: + print(f"Warning: {backend_dir / '.env'} not found")This aids debugging when developers expect .env files but they're missing.
13-13: Consider clarifying "reverse order" phrasing.The comment is technically accurate but "reverse order of precedence" might confuse readers. Consider rephrasing for clarity:
-# Load in reverse order of precedence (since override=False won't overwrite existing vars) +# Load from lowest to highest priority (override=False won't overwrite existing vars)tests/run-custom.sh (1)
1-20: Consider adding validation for robustness.The script works correctly for its purpose. However, you could optionally add validation to provide better error messages:
🔎 Optional validation improvements
set -e CONFIG_NAME="${1:-parakeet-openai}" PARAKEET_URL="${2:-http://host.docker.internal:8767}" + +CONFIG_FILE="../tests/configs/${CONFIG_NAME}.yml" + +# Validate config file exists +if [[ ! -f "$CONFIG_FILE" ]]; then + echo "Error: Config file not found: $CONFIG_FILE" + exit 1 +fi + +# Validate run-robot-tests.sh exists +if [[ ! -f "./run-robot-tests.sh" ]]; then + echo "Error: run-robot-tests.sh not found in current directory" + exit 1 +fi echo "Running Robot tests with config: ${CONFIG_NAME}" echo "Parakeet ASR URL: ${PARAKEET_URL}" -CONFIG_FILE="../tests/configs/${CONFIG_NAME}.yml" \ +CONFIG_FILE="$CONFIG_FILE" \ PARAKEET_ASR_URL="${PARAKEET_URL}" \ ./run-robot-tests.shbackends/advanced/src/advanced_omi_backend/controllers/websocket_controller.py (1)
305-320: LGTM! Config-driven provider resolution with proper validation.The registry-based approach correctly:
- Validates registry availability
- Checks for configured STT defaults
- Validates provider type against allowed values
- Logs the selected provider and model
The clear error messages aid debugging when configuration is missing or invalid.
Note: Ruff flagged the inline exception messages (TRY003), suggesting custom exception classes. However, for configuration validation errors, inline messages are perfectly appropriate and more readable than creating dedicated exception types.
config_manager.py (2)
106-111: Improve exception handling withlogging.exception()and exception chaining.Per project conventions, use
logging.exception()to capture full stack traces and chain exceptions when re-raising.🔎 Proposed fix
try: with open(self.config_yml_path, 'r') as f: return yaml.safe_load(f) or {} except Exception as e: - logger.error(f"Failed to load config.yml: {e}") + logger.exception(f"Failed to load config.yml: {e}") return {}Similarly for
_save_config_yml(lines 129-131):except Exception as e: - logger.error(f"Failed to save config.yml: {e}") - raise + logger.exception(f"Failed to save config.yml: {e}") + raise RuntimeError(f"Failed to save config.yml: {e}") from eAnd
_update_env_file(lines 177-179):except Exception as e: - logger.error(f"Failed to update .env file: {e}") - raise + logger.exception(f"Failed to update .env file: {e}") + raise RuntimeError(f"Failed to update .env file: {e}") from eBased on learnings: "prefer logging.exception() inside except blocks to automatically log the full stack trace. When re-raising exceptions, always chain with 'raise ... from e'."
358-363: Singleton behavior may be surprising whenservice_pathis provided.Calling
get_config_manager(service_path="some/path")always creates a new instance, replacing the cached one. This could lead to unexpected behavior if multiple callers provide different service paths. Consider documenting this behavior more explicitly or using a cache keyed by service_path.tests/integration/integration_test.robot (1)
132-168: Well-structured E2E test with comprehensive validation.The test follows Robot Framework guidelines with descriptive naming, tab-separated tags, and inline verifications. Good coverage of the complete pipeline including memory extraction and OpenAI validation.
One note: using
Set Global Variable(line 147) may cause issues if tests run in parallel. Consider using test-scoped variables instead if parallelization is planned.backends/advanced/init.py (1)
700-700: Remove unnecessary f-string prefix.Line 700 uses an f-string without any placeholders. Remove the
fprefix as flagged by static analysis.🔎 Proposed fix
- self.console.print(f" • ../../config/config.yml - Model and memory provider configuration") + self.console.print(" • ../../config/config.yml - Model and memory provider configuration")
📜 Review details
Configuration used: Organization UI
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (23)
.github/workflows/README.mdCLAUDE.mdDocs/getting-started.mdbackends/advanced/.env.templatebackends/advanced/Docs/quickstart.mdbackends/advanced/README.mdbackends/advanced/docker-compose.ymlbackends/advanced/init.pybackends/advanced/run-test.shbackends/advanced/src/advanced_omi_backend/controllers/websocket_controller.pybackends/advanced/src/advanced_omi_backend/routers/modules/health_routes.pybackends/advanced/start-workers.shbackends/advanced/tests/test_integration.pyconfig/config.yml.templateconfig_manager.pytest-requirements.txttests/integration/integration_test.robottests/resources/audio_keywords.robottests/resources/memory_keywords.robottests/resources/queue_keywords.robottests/run-custom.shtests/setup/test_env.pywizard.py
💤 Files with no reviewable changes (1)
- backends/advanced/tests/test_integration.py
✅ Files skipped from review due to trivial changes (1)
- backends/advanced/README.md
🚧 Files skipped from review as they are similar to previous changes (4)
- Docs/getting-started.md
- backends/advanced/Docs/quickstart.md
- backends/advanced/start-workers.sh
- backends/advanced/docker-compose.yml
🧰 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:
backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.pywizard.pybackends/advanced/src/advanced_omi_backend/controllers/websocket_controller.pyconfig_manager.pybackends/advanced/init.pytests/setup/test_env.py
**/*.robot
📄 CodeRabbit inference engine (CLAUDE.md)
**/*.robot: Only use the 11 approved tags from @tests/tags.md in Robot Framework tests - custom tags are not permitted
Use tab-separated tags in Robot Framework tests (e.g.,[Tags] infra audio-streaming), never space-separated
Write verifications directly in Robot Framework tests inline, not abstracted to keywords
Follow the Arrange-Act-Assert pattern in Robot Framework tests with inline verifications
Use descriptive Robot Framework test and keyword names that explain business purpose, not technical implementation
Files:
tests/resources/audio_keywords.robottests/resources/memory_keywords.robottests/integration/integration_test.robottests/resources/queue_keywords.robot
🧠 Learnings (7)
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Applies to **/*.robot : Use descriptive Robot Framework test and keyword names that explain business purpose, not technical implementation
Applied to files:
.github/workflows/README.mdtests/resources/memory_keywords.robottests/integration/integration_test.robotCLAUDE.mdtests/resources/queue_keywords.robot
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Applies to **/*.robot : Write verifications directly in Robot Framework tests inline, not abstracted to keywords
Applied to files:
.github/workflows/README.mdtests/resources/memory_keywords.robottests/integration/integration_test.robot
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Before writing any Robot Framework test, read [tests/TESTING_GUIDELINES.md](tests/TESTING_GUIDELINES.md) for comprehensive testing patterns and standards
Applied to files:
.github/workflows/README.mdtests/resources/memory_keywords.robotCLAUDE.md
📚 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:
backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.pywizard.pybackends/advanced/src/advanced_omi_backend/controllers/websocket_controller.pyconfig_manager.pybackends/advanced/init.pytests/setup/test_env.py
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Applies to **/*.py : ALL imports must be at the top of the file after the docstring - never import modules in the middle of functions or files
Applied to files:
wizard.py
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Before writing Robot Framework test code, scan relevant resource files for existing keywords - never write code that duplicates existing keywords
Applied to files:
tests/resources/memory_keywords.robottests/integration/integration_test.robot
📚 Learning: 2025-12-20T01:11:51.495Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-20T01:11:51.495Z
Learning: Applies to **/*.robot : Follow the Arrange-Act-Assert pattern in Robot Framework tests with inline verifications
Applied to files:
tests/resources/memory_keywords.robot
🧬 Code graph analysis (2)
backends/advanced/src/advanced_omi_backend/controllers/websocket_controller.py (1)
backends/advanced/src/advanced_omi_backend/model_registry.py (2)
get_models_registry(338-353)get_default(196-218)
backends/advanced/init.py (1)
config_manager.py (4)
ConfigManager(37-341)get_full_config(325-332)update_config_defaults(307-323)update_memory_config(260-279)
🪛 Ruff (0.14.10)
wizard.py
331-331: String contains ambiguous ℹ (INFORMATION SOURCE). Did you mean i (LATIN SMALL LETTER I)?
(RUF001)
backends/advanced/src/advanced_omi_backend/controllers/websocket_controller.py
310-310: Avoid specifying long messages outside the exception class
(TRY003)
314-314: Avoid specifying long messages outside the exception class
(TRY003)
318-318: Avoid specifying long messages outside the exception class
(TRY003)
config_manager.py
109-109: Do not catch blind exception: Exception
(BLE001)
110-110: Use logging.exception instead of logging.error
Replace with exception
(TRY400)
130-130: Use logging.exception instead of logging.error
Replace with exception
(TRY400)
178-178: Use logging.exception instead of logging.error
Replace with exception
(TRY400)
219-222: Avoid specifying long messages outside the exception class
(TRY003)
backends/advanced/init.py
700-700: f-string without any placeholders
Remove extraneous f prefix
(F541)
🔇 Additional comments (20)
config/config.yml.template (2)
5-7: LGTM! Clear provider documentation.The added comments effectively document the available transcription providers and their requirements, improving template usability.
102-102: LGTM! Environment-driven configuration.The environment variable substitution with fallback default enhances deployment flexibility while maintaining backward compatibility.
backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py (1)
112-115: LGTM! Registry-based provider resolution.The shift from environment variable to registry-based lookup aligns with the centralized configuration approach. The conditional check properly handles cases where the registry or default STT model is unavailable.
CLAUDE.md (2)
119-119: LGTM! Test framework migration documentation.The updated commands correctly reflect the shift from pytest to Robot Framework, with appropriate CLI options for test execution.
Also applies to: 123-123
393-393: LGTM! Consistent test reference update.The reference update aligns with the repository-wide migration to Robot Framework-based integration testing.
.github/workflows/README.md (1)
89-90: Documentation correctly updated for Robot Framework migration.The command and path reference align with the new integration test structure.
tests/resources/queue_keywords.robot (1)
73-77: Good addition for fail-fast behavior.Early termination with descriptive error message improves test debugging. The inline verification follows Robot Framework testing guidelines.
backends/advanced/.env.template (1)
48-55: Template correctly simplified to reference centralized config.The removal of inline provider options and redirection to
config.ymlaligns with the centralized configuration management approach.tests/integration/integration_test.robot (1)
14-15: Resource imports correctly added for memory and queue keywords.The imports enable the new end-to-end memory validation test.
wizard.py (2)
7-7: Import correctly moved to top of file.This addresses the previous review feedback about inline imports.
317-331: Config path correctly updated toconfig/config.yml.The changes properly handle the new config directory structure with directory creation and updated messaging.
Note: This implementation uses
config/config.ymlbutconfig_manager.pystill referencesconfig.ymlat the repo root. Ensure these are aligned.tests/resources/audio_keywords.robot (1)
72-114: Well-implemented keyword with inline assertions.The keyword follows Robot Framework guidelines:
- Descriptive name explaining business purpose
- Reuses existing
Upload Audio Filekeyword (avoiding duplication)- Inline verifications for all assertions
- Clear documentation distinguishing from upload-only tests
tests/resources/memory_keywords.robot (2)
109-234: Excellent refactoring - keyword now properly separates action from verification!The
Wait For Memory Extractionkeyword has been correctly refactored to address the previous review feedback. It now:
- Returns a structured result dictionary instead of performing assertions
- Allows tests to verify success/failure conditions inline
- Documents clearly that "calling tests should verify the results"
- Uses IF blocks to return error states rather than calling
Should*orFailkeywordsThis follows the Arrange-Act-Assert pattern and coding guidelines.
Based on learnings, coding guidelines.
236-276: LGTM - well-designed action keyword.
Check Memory Similarity With OpenAIis a properly designed action keyword that:
- Performs the OpenAI API call
- Returns the similarity result for test-layer verification
- Contains no assertions
backends/advanced/run-test.sh (4)
49-100: LGTM - CONFIG_FILE handling is well-structured.The CONFIG_FILE override support and default configuration are implemented correctly:
- Preserves command-line overrides with proper precedence
- Sets sensible default to
../../config/config.yml- Provides clear informational messages
101-141: Well-implemented STT provider configuration from config.yml.The refactored provider handling correctly:
- Reads STT provider from the model registry in config.yml (source of truth)
- Falls back to
TRANSCRIPTION_PROVIDERenvironment variable for backward compatibility with appropriate warning- Updates all provider validation logic to use
STT_PROVIDER- Handles Parakeet case with proper URL configuration
The Python code for reading from the registry is sound and the error handling is appropriate.
183-184: Good practice - unique project name prevents conflicts.Setting
COMPOSE_PROJECT_NAME="advanced-backend-test"ensures test containers don't conflict with development environment containers.
208-215: Robot Framework integration properly configured.The test invocation correctly:
- Sets
TEST_MODE=devto keep containers running for Robot Framework- Uses appropriate 15-minute timeout for comprehensive tests
- Specifies proper output directory and log level
backends/advanced/init.py (2)
178-293: ConfigManager integration follows excellent pattern.The refactored
setup_transcriptionandsetup_llmmethods correctly:
- Use
config_manager.update_config_defaults()to update config.yml- Call
get_full_config()to reload in-memory config after updates- Keep config.yml as the source of truth with synchronized .env updates
- Provide clear user feedback about configuration changes
This centralized approach eliminates duplicate config handling logic and maintains consistency.
294-356: Memory provider configuration properly uses ConfigManager.The
setup_memorymethod correctly usesupdate_memory_config()with deep merge for nested configuration updates, and reloads the in-memory config to stay synchronized. The pattern is consistent with other setup methods.
- 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.
- 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.
🎉 Robot Framework Test ResultsStatus: ✅ All tests passed!
📊 View ReportsGitHub Pages (Live Reports): Download Artifacts:
|
|
| Metric | Count |
|---|---|
| ✅ Passed | 91 |
| ❌ Failed | 1 |
| 📊 Total | 92 |
📊 View Reports
GitHub Pages (Live Reports):
Download Artifacts:
- robot-test-reports-html - HTML reports
- robot-test-results-xml - XML output
|
failing test is openai being too picky about what qualifies good memory extraction. thats okay I think, unrelated to this PR |
|
Also see how its fickle lol |
|
| Metric | Count |
|---|---|
| ✅ Passed | 91 |
| ❌ Failed | 1 |
| 📊 Total | 92 |
📊 View Reports
GitHub Pages (Live Reports):
Download Artifacts:
- robot-test-reports-html - HTML reports
- robot-test-results-xml - XML output
- 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.
|
| Metric | Count |
|---|---|
| ✅ Passed | 91 |
| ❌ Failed | 1 |
| 📊 Total | 92 |
📊 View Reports
GitHub Pages (Live Reports):
Download Artifacts:
- robot-test-reports-html - HTML reports
- robot-test-results-xml - XML output
- 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.
🎉 Robot Framework Test ResultsStatus: ✅ All tests passed!
📊 View ReportsGitHub Pages (Live Reports): Download Artifacts:
|
* 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.
* 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>
* 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>
* 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…
* 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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