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Caution Review failedThe pull request is closed. WalkthroughConsolidates runtime configuration into a repository-wide config.yml and a Pydantic-backed model registry; removes legacy memory_config.yaml/template and loader; and rewires LLM, embedding, memory, transcription, controllers, init scripts, containers, docs, and tests to use the registry. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
participant App as Application Startup
participant Reg as Model Registry
participant File as config.yml
participant LLM as LLM Client Factory
participant Mem as Memory Service
participant STT as Transcription Service
App->>Reg: load_models_config()
Reg->>File: locate & read YAML
File-->>Reg: parsed AppModels (defaults, models, memory)
Reg->>Reg: validate, expand env, cache
App->>LLM: create_client()
LLM->>Reg: get_default LLM
Reg-->>LLM: ModelDef (api_key, base_url, model_name, params)
LLM->>LLM: construct provider client
LLM-->>App: client ready
App->>Mem: init memory service
Mem->>Reg: get memory & embedding defs
Reg-->>Mem: memory config, embedding/model defs
Mem->>Mem: configure embedding dims, vector-store client
Mem-->>App: memory service ready
App->>STT: get_transcription_provider(mode)
STT->>Reg: get default STT/STT_STREAM model
Reg-->>STT: STT model config (HTTP/WS endpoints, headers, extractors)
STT->>STT: create registry-backed provider (HTTP or WS)
STT-->>App: transcription provider ready
Estimated code review effort🎯 4 (Complex) | ⏱️ ~60 minutes Areas needing extra attention:
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⚠️ Outside diff range comments (2)
backends/advanced/tests/test_integration.py (1)
76-84: Mount config.yml in test containers for LLM configuration access.The backend requires config.yml to be present and readable when LLM features (memory extraction, transcription) are used. Currently, config.yml is not included in the Docker image or mounted in docker-compose-test.yml, causing tests with OPENAI_API_KEY set to fail with "config.yml not found or invalid" RuntimeError.
Add config.yml to the backend Docker image (.dockerignore) and mount it in docker-compose-test.yml volumes to ensure tests have access to LLM configuration.
config.env.template (1)
167-172: Resolve configuration source inconsistency.The comment states "Managed in config.yml or hardcoded in constants," but then immediately defines
NEW_CONVERSATION_TIMEOUT_MINUTESandCROPPING_CONTEXT_PADDINGas environment variables. This creates confusion about the authoritative source for these settings.Options:
- If these should be in
config.yml, remove them from this template and update the comment- If these should remain as environment variables, remove or revise the comment to accurately reflect their purpose
- Document clearly when each approach (config.yml vs env var) is used
🧹 Nitpick comments (17)
backends/advanced/Dockerfile.k8s (1)
36-37: Stale comment after removal of COPY instruction.The comment "Copy memory config (created by init.sh from template)" now refers to a removed instruction. Consider removing or updating this comment to avoid confusion.
Suggested fix
-# Copy memory config (created by init.sh from template) - +# Note: Memory configuration now handled via centralized config.ymlOr simply remove both lines entirely.
backends/advanced/src/advanced_omi_backend/controllers/system_controller.py (1)
41-42: Consider using bareraiseinstead ofraise e.Throughout this file, after
logging.exception(), you re-raise withraise e. A bareraisepreserves the original traceback more cleanly and is the idiomatic pattern in Python.This applies to multiple locations in the file (lines 42, 75, 126, 139, 175, 208, 251, 277, 315, 332, 343, 367, 391, 454).
Example fix
except Exception as e: audio_logger.exception("Error fetching metrics") - raise e + raiseconfig.yml (2)
10-20: Consider using environment variables for IP addresses and API keys.The hardcoded IP address
192.168.1.166and API key"1234"reduce portability. Consider:
- Using
${EMBERFANG_URL:-http://192.168.1.166:8084/v1}for the URL- Using
${EMBERFANG_API_KEY:-1234}for the API key- Adding documentation that these are example values
This applies to other model definitions with hardcoded IPs as well (lines 22-30).
109-128: The Docker gateway IP may not be portable across environments.Line 115 uses
http://172.17.0.1:8767, which is Docker's default bridge gateway. Consider usinghttp://host.docker.internal:8767for better compatibility across Docker Desktop and other environments, or make it configurable via environment variable.README.md (1)
7-7: Minor: Bare URL flagged by linter.The bare URL
http://localhost:5173is flagged by markdownlint. You can wrap it in angle brackets (<http://localhost:5173>) or make it a proper markdown link to satisfy the linter, though this is purely cosmetic.config.env.template (1)
58-59: Clarify comment about API keys.The comment states "Only API keys need to be set here," but the template still includes other configuration variables like
TRANSCRIPTION_PROVIDER,MISTRAL_MODEL, authentication settings, and database URLs. Consider revising to: "LLM configuration is managed in config.yml (defaults.llm). API keys and provider selection are set here."backends/advanced/src/advanced_omi_backend/llm_client.py (1)
150-166: Improve error message to distinguish between missing registry and missing LLM definition.When
registryisNone(config.yml not found), the error message "No default LLM defined in config.yml" is misleading—the issue is that the config file itself is missing or invalid.🔎 Proposed fix
if registry: llm_def = registry.get_default("llm") if llm_def: logger.info(f"Creating LLM client from registry: {llm_def.name} ({llm_def.model_provider})") params = llm_def.model_params or {} return OpenAILLMClient( api_key=llm_def.api_key, base_url=llm_def.model_url, model=llm_def.model_name, temperature=params.get("temperature", 0.1), ) + raise ValueError("No default LLM defined in config.yml") - raise ValueError("No default LLM defined in config.yml") + raise ValueError("config.yml not found or invalid - cannot create LLM client")backends/advanced/src/advanced_omi_backend/services/memory/config.py (2)
266-268: Redundantlocals()check.
llm_defis always defined at this point because line 224 raises if it's missing. The'llm_def' in locals()check is unnecessary and adds confusion.🔎 Suggested fix
memory_logger.info( - f"🔧 Memory config: Provider=Chronicle, LLM={llm_def.model_provider if 'llm_def' in locals() else 'unknown'}, VectorStore={vector_store_provider_enum}, Extraction={extraction_enabled}" + f"🔧 Memory config: Provider=Chronicle, LLM={llm_def.model_provider}, VectorStore={vector_store_provider_enum}, Extraction={extraction_enabled}" )
299-303: Use bareraiseinstead ofraise e.When re-raising the same exception after logging, use bare
raiseto preserve the original traceback. Based on learnings, this improves debuggability.🔎 Suggested fix
except Exception as e: memory_logger.exception( f"Failed to get embedding dimensions from registry for model '{embedding_model}'" ) - raise e + raisebackends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py (3)
246-263: Consider caching registry lookups or extracting to a helper.The pattern of fetching
get_models_registry()andreg.get_default("llm")is duplicated in both_extract_memories_via_llm(lines 247-254) and_extract_temporal_entity_via_llm(lines 302-309). Consider extracting this to a helper method or caching thellm_defin__init__to reduce code duplication and improve performance.🔎 Suggested helper method
def _get_llm_client_and_def(self): """Get LLM client and definition from registry. Returns: Tuple of (client, llm_def) or (None, None) if unavailable """ reg = get_models_registry() if not reg: memory_logger.warning("No registry available for LLM") return None, None llm_def = reg.get_default("llm") if not llm_def: memory_logger.warning("No default LLM in config.yml") return None, None client = _get_openai_client( api_key=llm_def.api_key or "", base_url=llm_def.model_url, is_async=True ) return client, llm_def
279-282: Uselogging.exception()for JSON parse errors.Per project learnings, prefer
logging.exception()inside except blocks to automatically log the full stack trace for better debuggability.🔎 Suggested fix
except json.JSONDecodeError as e: - memory_logger.error(f"Failed to parse LLM response as JSON: {e}") - memory_logger.error(f"LLM response was: {content[:300]}") + memory_logger.exception(f"Failed to parse LLM response as JSON, content: {content[:300]}") return []
354-360: Uselogging.exception()for validation errors.Consistent with the previous comment, use
logging.exception()here for automatic stack trace logging.🔎 Suggested fix
except json.JSONDecodeError as e: - memory_logger.error(f"❌ Failed to parse temporal extraction JSON: {e}") - memory_logger.error(f"Content (first 300 chars): {content[:300]}") + memory_logger.exception(f"❌ Failed to parse temporal extraction JSON, content: {content[:300]}") return None except Exception as e: - memory_logger.error(f"Failed to validate temporal entity: {e}") - memory_logger.error(f"Data: {content[:300] if content else 'None'}") + memory_logger.exception(f"Failed to validate temporal entity, data: {content[:300] if content else 'None'}") return Nonebackends/advanced/src/advanced_omi_backend/model_registry.py (1)
265-271: Silent exception handling hides debugging information.The
try-except-passpattern here silences any errors when walking up parent directories. Consider logging at debug level to aid troubleshooting config discovery issues.🔎 Suggested fix
# Also walk up from current file's parents defensively try: for parent in Path(__file__).resolve().parents: c = parent / "config.yml" if c.exists(): return c - except Exception: - pass + except Exception as e: + logging.debug(f"Error walking parent directories for config.yml: {e}")backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py (1)
172-176: Silent exception handling in WebSocket operations.While the "best effort" approach is reasonable for non-critical operations, consider logging at debug level to aid troubleshooting connection issues.
🔎 Suggested fix
# Wait for confirmation; non-fatal if not provided try: await asyncio.wait_for(ws.recv(), timeout=2.0) - except Exception: - pass + except Exception as e: + logger.debug(f"WebSocket confirmation not received: {e}") self._streams[client_id] = {"ws": ws, "sample_rate": sample_rate, "final": None, "interim": []}backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py (3)
153-157: Type annotation claims non-None butget_defaultcan returnNone.Line 153 annotates
self.llm_def: ModelDefbutregistry.get_default("llm")returnsOptional[ModelDef]. While line 156-157 raises ifNone, the type annotation is misleading for static analysis tools. Consider using the validated value directly.🔎 Suggested fix
# Resolve default models - self.llm_def: ModelDef = registry.get_default("llm") # type: ignore - self.embed_def: ModelDef | None = registry.get_default("embedding") - - if not self.llm_def: + llm_def = registry.get_default("llm") + if not llm_def: raise RuntimeError("No default LLM defined in config.yml") + self.llm_def: ModelDef = llm_def + self.embed_def: ModelDef | None = registry.get_default("embedding")
267-284: Redundant nested exception handling and uselogging.exception().The inner try-except (lines 274-280) catches the same exceptions that the outer try-except (lines 282-284) would catch. Additionally, per project learnings, use
logging.exception()instead oflogging.error()for automatic stack traces.🔎 Suggested fix
async def test_connection(self) -> bool: """Test OpenAI connection. Returns: True if connection successful, False otherwise """ try: - try: - client = _get_openai_client(api_key=self.api_key, base_url=self.base_url, is_async=True) - await client.models.list() - return True - except Exception as e: - memory_logger.error(f"OpenAI connection test failed: {e}") - return False - + client = _get_openai_client(api_key=self.api_key, base_url=self.base_url, is_async=True) + await client.models.list() + return True except Exception as e: - memory_logger.error(f"OpenAI connection test failed: {e}") + memory_logger.exception("OpenAI connection test failed") return False
146-171: Unusedconfigparameter kept for interface compatibility.The
configparameter is now unused since configuration comes from the registry. This is acceptable for backward compatibility. Consider adding a brief comment or using_prefix to signal intent.🔎 Suggested documentation
- def __init__(self, config: Dict[str, Any]): + def __init__(self, config: Dict[str, Any]): # config unused; kept for interface compatibility # Ignore provider-specific envs; use registry as single source of truth
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📒 Files selected for processing (35)
Docs/getting-started.md(4 hunks)README.md(1 hunks)backends/advanced/Dockerfile(1 hunks)backends/advanced/Dockerfile.k8s(1 hunks)backends/advanced/Docs/README.md(7 hunks)backends/advanced/Docs/contribution.md(2 hunks)backends/advanced/Docs/memories.md(3 hunks)backends/advanced/Docs/memory-configuration-guide.md(2 hunks)backends/advanced/Docs/quickstart.md(4 hunks)backends/advanced/SETUP_SCRIPTS.md(2 hunks)backends/advanced/docker-compose-test.yml(2 hunks)backends/advanced/docker-compose.yml(3 hunks)backends/advanced/init-https.sh(2 hunks)backends/advanced/init.py(4 hunks)backends/advanced/memory_config.yaml.template(0 hunks)backends/advanced/run-test.sh(2 hunks)backends/advanced/setup-https.sh(3 hunks)backends/advanced/src/advanced_omi_backend/app_config.py(4 hunks)backends/advanced/src/advanced_omi_backend/chat_service.py(2 hunks)backends/advanced/src/advanced_omi_backend/controllers/system_controller.py(14 hunks)backends/advanced/src/advanced_omi_backend/llm_client.py(3 hunks)backends/advanced/src/advanced_omi_backend/memory_config_loader.py(0 hunks)backends/advanced/src/advanced_omi_backend/model_registry.py(1 hunks)backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py(5 hunks)backends/advanced/src/advanced_omi_backend/services/memory/config.py(5 hunks)backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py(8 hunks)backends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py(4 hunks)backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py(1 hunks)backends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py(1 hunks)backends/advanced/src/advanced_omi_backend/workers/transcription_jobs.py(1 hunks)backends/advanced/start-workers.sh(0 hunks)backends/advanced/tests/test_integration.py(3 hunks)config.env.template(4 hunks)config.yml(1 hunks)tests/run-robot-tests.sh(1 hunks)
💤 Files with no reviewable changes (3)
- backends/advanced/start-workers.sh
- backends/advanced/src/advanced_omi_backend/memory_config_loader.py
- backends/advanced/memory_config.yaml.template
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📓 Path-based instructions (5)
**/*.py
📄 CodeRabbit inference engine (CLAUDE.md)
**/*.py: Use Black formatter with 100-character line length for Python code
Use isort for import sorting in Python code
ALL imports must be at the top of the file after the docstring. NEVER import modules in the middle of functions or files. Use lazy imports sparingly and only when absolutely necessary for circular import issues.
Group imports in order: standard library, third-party, local imports
Always raise errors, never silently ignore. Use explicit error handling with proper exceptions rather than silent failures.
Do not add defensivehasattr()checks. Research and understand input/response or class structure instead.
Useuv run pythonoruv run python3instead of directpythonorpython3commands for Python execution
Files:
backends/advanced/tests/test_integration.pybackends/advanced/init.pybackends/advanced/src/advanced_omi_backend/llm_client.pybackends/advanced/src/advanced_omi_backend/chat_service.pybackends/advanced/src/advanced_omi_backend/model_registry.pybackends/advanced/src/advanced_omi_backend/controllers/system_controller.pybackends/advanced/src/advanced_omi_backend/services/transcription/__init__.pybackends/advanced/src/advanced_omi_backend/workers/conversation_jobs.pybackends/advanced/src/advanced_omi_backend/routers/modules/health_routes.pybackends/advanced/src/advanced_omi_backend/services/memory/config.pybackends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.pybackends/advanced/src/advanced_omi_backend/workers/transcription_jobs.pybackends/advanced/src/advanced_omi_backend/app_config.pybackends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py
**/docker-compose*.{yml,yaml}
📄 CodeRabbit inference engine (CLAUDE.md)
Check if src/ is volume mounted. If not, run
docker compose buildso that code changes are reflected. Do not simply rundocker compose restartas it will not rebuild the image.
Files:
backends/advanced/docker-compose.ymlbackends/advanced/docker-compose-test.yml
**/{auth,permission,security,model,database,db}*.py
📄 CodeRabbit inference engine (CLAUDE.md)
Scope all data by user_id with efficient permission checking for data isolation
Files:
backends/advanced/src/advanced_omi_backend/model_registry.py
**/{conversation,audio,memory,processing}*.py
📄 CodeRabbit inference engine (CLAUDE.md)
Only create conversations when speech is detected, eliminating noise-only sessions. Store all audio sessions in
audio_chunkscollection, conversations only inconversationscollection when speech is detected.
Files:
backends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py
**/Dockerfile
📄 CodeRabbit inference engine (CLAUDE.md)
Use
docker compose buildwithout--no-cacheby default for faster builds. Only use--no-cachewhen explicitly needed (e.g., if cached layers are causing issues or when troubleshooting build problems).
Files:
backends/advanced/Dockerfile
🧠 Learnings (5)
📚 Learning: 2025-12-16T14:24:28.301Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-16T14:24:28.301Z
Learning: Applies to **/{memory,provider}*.py : Implement pluggable memory providers supporting both Chronicle native (individual facts) and OpenMemory MCP delegation
Applied to files:
backends/advanced/Docs/README.mdbackends/advanced/src/advanced_omi_backend/services/memory/config.py
📚 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/tests/test_integration.pybackends/advanced/init.pybackends/advanced/src/advanced_omi_backend/llm_client.pybackends/advanced/src/advanced_omi_backend/chat_service.pybackends/advanced/src/advanced_omi_backend/model_registry.pybackends/advanced/src/advanced_omi_backend/controllers/system_controller.pybackends/advanced/src/advanced_omi_backend/services/transcription/__init__.pybackends/advanced/src/advanced_omi_backend/workers/conversation_jobs.pybackends/advanced/src/advanced_omi_backend/routers/modules/health_routes.pybackends/advanced/src/advanced_omi_backend/services/memory/config.pybackends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.pybackends/advanced/src/advanced_omi_backend/workers/transcription_jobs.pybackends/advanced/src/advanced_omi_backend/app_config.pybackends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py
📚 Learning: 2025-12-16T14:24:28.301Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-16T14:24:28.301Z
Learning: Applies to **/*.robot : When writing or modifying Robot Framework tests, follow the testing guidelines in [tests/TESTING_GUIDELINES.md](tests/TESTING_GUIDELINES.md) and approved tags in [tests/tags.md](tests/tags.md). Only use the 11 approved tags, tab-separated.
Applied to files:
tests/run-robot-tests.sh
📚 Learning: 2025-12-16T14:24:28.301Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-16T14:24:28.301Z
Learning: Applies to **/{conversation,audio,memory,processing}*.py : Only create conversations when speech is detected, eliminating noise-only sessions. Store all audio sessions in `audio_chunks` collection, conversations only in `conversations` collection when speech is detected.
Applied to files:
config.env.templatebackends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py
📚 Learning: 2025-12-16T14:24:28.301Z
Learnt from: CR
Repo: chronicler-ai/chronicle PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-16T14:24:28.301Z
Learning: Applies to **/{job,queue,pipeline,processor}*.py : Use a Job-based tracking system for all audio processing (WebSocket and file uploads) with stage events (audio → transcription → memory) and completion status
Applied to files:
backends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py
🧬 Code graph analysis (10)
backends/advanced/run-test.sh (4)
backends/advanced/setup-https.sh (1)
print_success(19-21)tests/run-robot-tests.sh (1)
print_success(20-22)run-test.sh (1)
print_success(21-23)extras/speaker-recognition/run-test.sh (1)
print_success(38-40)
backends/advanced/src/advanced_omi_backend/llm_client.py (1)
backends/advanced/src/advanced_omi_backend/model_registry.py (2)
get_models_registry(338-353)get_default(196-218)
backends/advanced/src/advanced_omi_backend/controllers/system_controller.py (1)
backends/advanced/src/advanced_omi_backend/model_registry.py (2)
_find_config_path(244-278)load_models_config(281-335)
backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py (1)
backends/advanced/src/advanced_omi_backend/model_registry.py (2)
get_models_registry(338-353)get_default(196-218)
backends/advanced/src/advanced_omi_backend/services/memory/config.py (3)
backends/advanced/src/advanced_omi_backend/model_registry.py (2)
get_models_registry(338-353)get_default(196-218)backends/advanced/src/advanced_omi_backend/models/user.py (1)
user_id(71-73)backends/advanced/src/advanced_omi_backend/models/conversation.py (1)
MemoryProvider(29-34)
backends/advanced/setup-https.sh (3)
backends/advanced/run-test.sh (2)
print_info(16-18)print_success(20-22)tests/run-robot-tests.sh (2)
print_info(16-18)print_success(20-22)run-test.sh (2)
print_info(17-19)print_success(21-23)
backends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py (2)
backends/advanced/src/advanced_omi_backend/model_registry.py (2)
get_models_registry(338-353)get_default(196-218)backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py (1)
_get_openai_client(48-72)
backends/advanced/src/advanced_omi_backend/workers/transcription_jobs.py (4)
backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py (2)
name(68-69)name(153-154)backends/advanced/src/advanced_omi_backend/services/transcription/base.py (1)
name(65-67)backends/advanced/src/advanced_omi_backend/services/transcription/parakeet.py (2)
name(35-36)name(106-107)backends/advanced/src/advanced_omi_backend/services/transcription/deepgram.py (2)
name(31-32)name(226-227)
backends/advanced/src/advanced_omi_backend/app_config.py (2)
backends/advanced/src/advanced_omi_backend/model_registry.py (1)
get_models_registry(338-353)backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py (1)
get_transcription_provider(243-266)
backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py (1)
backends/advanced/src/advanced_omi_backend/model_registry.py (3)
get_models_registry(338-353)ModelDef(90-158)get_default(196-218)
🪛 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)
🪛 markdownlint-cli2 (0.18.1)
backends/advanced/Docs/README.md
74-74: Emphasis used instead of a heading
(MD036, no-emphasis-as-heading)
README.md
7-7: Bare URL used
(MD034, no-bare-urls)
🪛 Ruff (0.14.8)
backends/advanced/src/advanced_omi_backend/llm_client.py
61-61: Avoid specifying long messages outside the exception class
(TRY003)
166-166: Avoid specifying long messages outside the exception class
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backends/advanced/src/advanced_omi_backend/model_registry.py
270-271: try-except-pass detected, consider logging the exception
(S110)
270-270: Do not catch blind exception: Exception
(BLE001)
backends/advanced/src/advanced_omi_backend/controllers/system_controller.py
42-42: Use raise without specifying exception name
Remove exception name
(TRY201)
75-75: Use raise without specifying exception name
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(TRY201)
89-89: Abstract raise to an inner function
(TRY301)
89-89: Avoid specifying long messages outside the exception class
(TRY003)
94-94: Abstract raise to an inner function
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94-94: Avoid specifying long messages outside the exception class
(TRY003)
97-97: Abstract raise to an inner function
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97-97: Avoid specifying long messages outside the exception class
(TRY003)
100-100: Abstract raise to an inner function
(TRY301)
100-100: Avoid specifying long messages outside the exception class
(TRY003)
126-126: Use raise without specifying exception name
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(TRY201)
139-139: Use raise without specifying exception name
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(TRY201)
148-148: Prefer TypeError exception for invalid type
(TRY004)
148-148: Abstract raise to an inner function
(TRY301)
148-148: Avoid specifying long messages outside the exception class
(TRY003)
153-153: Abstract raise to an inner function
(TRY301)
153-153: Avoid specifying long messages outside the exception class
(TRY003)
175-175: Use raise without specifying exception name
Remove exception name
(TRY201)
208-208: Use raise without specifying exception name
Remove exception name
(TRY201)
251-251: Use raise without specifying exception name
Remove exception name
(TRY201)
262-262: Abstract raise to an inner function
(TRY301)
262-262: Avoid specifying long messages outside the exception class
(TRY003)
277-277: Use raise without specifying exception name
Remove exception name
(TRY201)
287-287: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
287-287: Avoid specifying long messages outside the exception class
(TRY003)
287-287: Use explicit conversion flag
Replace with conversion flag
(RUF010)
291-291: Abstract raise to an inner function
(TRY301)
291-291: Avoid specifying long messages outside the exception class
(TRY003)
315-315: Use raise without specifying exception name
Remove exception name
(TRY201)
324-324: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
324-324: Avoid specifying long messages outside the exception class
(TRY003)
324-324: Use explicit conversion flag
Replace with conversion flag
(RUF010)
326-326: Prefer TypeError exception for invalid type
(TRY004)
326-326: Abstract raise to an inner function
(TRY301)
326-326: Avoid specifying long messages outside the exception class
(TRY003)
329-329: Consider moving this statement to an else block
(TRY300)
332-332: Use raise without specifying exception name
Remove exception name
(TRY201)
343-343: Use raise without specifying exception name
Remove exception name
(TRY201)
367-367: Use raise without specifying exception name
Remove exception name
(TRY201)
391-391: Use raise without specifying exception name
Remove exception name
(TRY201)
402-402: Abstract raise to an inner function
(TRY301)
402-402: Avoid specifying long messages outside the exception class
(TRY003)
408-408: Abstract raise to an inner function
(TRY301)
408-408: Avoid specifying long messages outside the exception class
(TRY003)
454-454: Use raise without specifying exception name
Remove exception name
(TRY201)
backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py
41-41: Do not catch blind exception: Exception
(BLE001)
60-60: Avoid specifying long messages outside the exception class
(TRY003)
63-63: Avoid specifying long messages outside the exception class
(TRY003)
144-144: Avoid specifying long messages outside the exception class
(TRY003)
147-147: Avoid specifying long messages outside the exception class
(TRY003)
174-175: try-except-pass detected, consider logging the exception
(S110)
174-174: Do not catch blind exception: Exception
(BLE001)
225-226: try-except-pass detected, consider logging the exception
(S110)
225-225: Do not catch blind exception: Exception
(BLE001)
229-230: try-except-pass detected, consider logging the exception
(S110)
229-229: Do not catch blind exception: Exception
(BLE001)
243-243: Unused function argument: provider_name
(ARG001)
backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py
235-235: Do not catch blind exception: Exception
(BLE001)
237-237: Use explicit conversion flag
Replace with conversion flag
(RUF010)
backends/advanced/src/advanced_omi_backend/services/memory/config.py
220-220: Avoid specifying long messages outside the exception class
(TRY003)
224-224: Avoid specifying long messages outside the exception class
(TRY003)
245-245: Avoid specifying long messages outside the exception class
(TRY003)
303-303: Use raise without specifying exception name
Remove exception name
(TRY201)
backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py
146-146: Unused method argument: config
(ARG002)
150-150: Avoid specifying long messages outside the exception class
(TRY003)
157-157: Avoid specifying long messages outside the exception class
(TRY003)
277-277: Consider moving this statement to an else block
(TRY300)
278-278: Do not catch blind exception: Exception
(BLE001)
279-279: Use logging.exception instead of logging.error
Replace with exception
(TRY400)
🔇 Additional comments (41)
backends/advanced/src/advanced_omi_backend/workers/transcription_jobs.py (1)
352-352: Verify semantic change:modelfield now stores provider name instead of model identifier.Previously, this used
getattr(provider, "model", "unknown")to capture the specific model variant. Now it usesprovider.name, which returns the provider type (e.g., "deepgram", "parakeet").This means:
- Line 351:
provider= "deepgram" (fromprovider_normalized)- Line 352:
model= "deepgram" (fromprovider.name)Both fields now contain the same value. If tracking specific model variants (e.g., "nova-2", "whisper-large") was intentional, this change loses that capability.
backends/advanced/Docs/contribution.md (1)
4-9: LGTM!Documentation correctly updated to reference the new centralized
config.ymlconfiguration structure with appropriate section paths.backends/advanced/Docs/README.md (1)
73-79: LGTM!Documentation correctly updated to reflect the new configuration system:
config.ymlas the central configuration file andmodel_registry.pyas the configuration loading module.backends/advanced/src/advanced_omi_backend/workers/conversation_jobs.py (1)
430-432: Verify removal of final speech validation safeguard.This change removes the final validation check against aggregated speech data before post-processing. The comment explains this is to avoid "false negatives from aggregated results lacking proper word-level data."
While the initial speech detection in
stream_speech_detection_jobvalidates speech to create the conversation, this was a secondary safeguard. Consider whether edge cases exist where:
- Initial detection passed but subsequent audio had no meaningful content
- Aggregated results differ significantly from streaming validation
If the aggregated validation was producing false negatives due to data structure issues, fixing the root cause in
analyze_speech()or the aggregator might be preferable to removing the check entirely.backends/advanced/src/advanced_omi_backend/controllers/system_controller.py (1)
257-312: LGTM on YAML configuration handling.The migration to YAML-based configuration management is well-implemented:
- Uses centralized
_find_config_path()for consistent config discovery- Creates backup before modifications (line 295)
- Properly reloads the registry after updates (line 305)
- Validates YAML syntax before applying changes
config.yml (1)
160-209: Placeholder endpoints are appropriately documented.The TTS and streaming STT configurations use placeholder URLs with clear comments. This is good practice for a configuration template.
backends/advanced/init.py (1)
204-250: Good guidance for config.yml migration.The updated messages clearly direct users to configure LLMs in config.yml while still collecting API keys through the interactive setup. This provides a smooth migration path.
backends/advanced/Dockerfile (1)
38-40: Dockerfile correctly updated for config migration.The change from
memory_config.yaml*todiarization_config.json*aligns with the broader migration to centralized config.yml. This ensures the container only includes necessary configuration files.backends/advanced/SETUP_SCRIPTS.md (1)
9-9: Documentation accurately reflects new configuration approach.The updated script overview clearly indicates that memory is now configured in config.yml, helping users understand the new configuration model.
tests/run-robot-tests.sh (1)
104-104: Test script properly updated for config migration.The comment clearly documents that memory_config.yaml is deprecated and tests now use config.yml. This prevents confusion for developers running tests.
backends/advanced/tests/test_integration.py (1)
485-485: Configuration migration properly documented in tests.The comment clearly indicates the migration from memory_config.yaml to config.yml, which helps maintainers understand the change.
backends/advanced/docker-compose.yml (1)
15-15: Config.yml mount enables centralized configuration.The read-only mount of config.yml provides both containers access to centralized model and memory configuration. The
:roflag is good security practice.Also applies to: 68-68
backends/advanced/Docs/memories.md (2)
13-13: LGTM! Documentation accurately reflects centralized configuration.The update from
memory_config.yamltoconfig.yml(memory section) andsrc/model_registry.pycorrectly documents the new configuration architecture.
183-183: LGTM! Consistent documentation update.The reference to
config.yml(memory block) is consistent with the earlier changes in this file and the PR's migration objective.backends/advanced/run-test.sh (1)
111-111: LGTM! Clear deprecation notice.The deprecation comment correctly informs users that memory configuration has moved from
memory_config.yamltoconfig.yml.backends/advanced/src/advanced_omi_backend/chat_service.py (2)
30-32: LGTM! Constants added for better configurability.The addition of
MAX_MEMORY_CONTEXTandMAX_CONVERSATION_HISTORYmodule-level constants improves code maintainability by centralizing these configuration values.
382-384: Temperature configuration properly moved to config.yml.The
temperatureparameter has been successfully removed from thegenerate()call at lines 382-384. Verification confirms:
- Temperature configuration is centralized in config.yml under each model's
model_params(0.2 for all LLM models)- The LLM client correctly reads temperature from config during initialization (llm_client.py line 163:
temperature=params.get("temperature", 0.1))- Default temperature behavior is acceptable—0.1 in code with 0.2 override from config
backends/advanced/init-https.sh (1)
74-74: LGTM! Clear migration messaging.The updated message correctly informs users that memory configuration is now managed in
config.yml(memory section) instead ofmemory_config.yaml.backends/advanced/setup-https.sh (2)
137-137: LGTM! Clear configuration guidance.The updated message correctly informs users that memory settings are now managed in
config.yml(memory section), consistent with the migration objective.
278-278: LGTM! Consistent summary message.The setup summary correctly reflects that memory configuration is ready via
config.yml, maintaining consistency with the earlier message in the script.backends/advanced/Docs/memory-configuration-guide.md (2)
9-22: LGTM! Clear migration guidance with proper examples.The updated quick start correctly guides users to edit the
memorysection ofconfig.ymlinstead of copyingmemory_config.yaml.template. The extended YAML example clearly shows the mem0-specific configuration options.
130-132: LGTM! Next steps updated consistently.The next steps correctly reference
config.yml(memory.extraction) instead of the deprecatedmemory_config.yaml, maintaining documentation consistency.backends/advanced/docker-compose-test.yml (1)
26-27: Provider configuration is correctly handled throughconfig.yml. The removed environment variables (OPENAI_BASE_URL, LLM_PROVIDER, OPENAI_MODEL) were not used by the application code. The model registry loads config.yml at runtime, resolves API keys from environment variables (${OPENAI_API_KEY},${GROQ_API_KEY}), and instantiates clients from registry definitions. Both OPENAI_API_KEY and GROQ_API_KEY remain present in the docker-compose file. Thesrc/volume mount is correctly configured, and the migration to centralized config.yml is fully implemented and working as intended.Likely an incorrect or invalid review comment.
Docs/getting-started.md (3)
345-345: LGTM!Documentation correctly updated to reference the centralized
config.yml(memory section) instead of the legacymemory_config.yaml.
544-549: LGTM!Configuration file location documentation is correctly updated to point to the repository root
config.ymlwith proper override guidance viaCONFIG_FILEenvironment variable.
730-731: LGTM!Next steps section correctly references editing the
memorysection inconfig.ymlfor memory extraction customization.backends/advanced/Docs/quickstart.md (3)
343-343: LGTM!Configuration reference correctly updated to point to
config.ymlfor both memory and model settings.
542-547: LGTM!Centralized configuration documentation is consistent with the broader PR changes, correctly pointing to
config.ymlin the repo root.
728-729: LGTM!Next steps correctly updated to reference the
memorysection inconfig.yml.backends/advanced/src/advanced_omi_backend/llm_client.py (2)
14-15: LGTM!Import correctly placed at the top of the file following the coding guidelines.
59-61: LGTM!Enhanced validation messaging provides clear diagnostic information about which configuration fields are missing, improving debuggability.
backends/advanced/src/advanced_omi_backend/app_config.py (3)
18-18: LGTM!Import correctly placed at the top of the file following the coding guidelines.
55-62: LGTM!Registry-based transcription provider initialization with appropriate logging for both configured and unconfigured states.
67-70: Review comment is incorrect; no fix needed.The code is safe against the claimed issue. The
memoryfield is guaranteed to always be a dict (never None) due to: (1) Pydantic'sdefault_factory=dictat the field definition (line 180), and (2) the safeguardmemory_settings = raw.get("memory", {}) or {}(line 315) ensuring memory is never None before being passed toAppModels(line 330). The conditional_mem = _reg.memory if _reg else {}already handles the None case for_regitself, making the proposed additional check unnecessary.Likely an incorrect or invalid review comment.
backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py (4)
23-23: LGTM!Import correctly placed at the top of the file following the coding guidelines.
120-122: LGTM!Conditional access pattern
(_llm_def.model_provider if _llm_def else None)safely handles the case when no default LLM is defined.
224-241: LGTM!Provider field consistently derived from registry across success and error branches for LLM health checks.
42-52: The code is correct as written and does not require changes.The
model_paramsfield in theModelDefclass is defined withField(default_factory=dict), which guarantees thatmodel_paramswill always be a dictionary instance, neverNone. With Pydantic'sdefault_factoryargument, a callable is called to generate a default value, and Pydantic internally creates a deep copy of default values when instantiating model instances.When
_vs_defexists, accessing_vs_def.model_params.get("host")is safe because themodel_paramsattribute is guaranteed to be a dictionary (either provided explicitly or created by the default factory). The existing conditional checkif _vs_def else "qdrant"is sufficient. The proposed fix of addingand _vs_def.model_paramswould actually introduce a bug—an empty dictionary is falsy in Python, so the code would incorrectly return the default value even when a valid (but empty)model_paramsdict exists.backends/advanced/src/advanced_omi_backend/model_registry.py (1)
90-158: Well-structured Pydantic model with sensible defaults.The
ModelDefclass provides good validation with appropriate defaults for embedding dimensions. The use offield_validatorandmodel_validatoris correct for Pydantic v2.backends/advanced/src/advanced_omi_backend/services/transcription/__init__.py (1)
54-69: Clean registry-based initialization pattern.The
RegistryBatchTranscriptionProviderproperly validates registry availability and raises clear errors when configuration is missing. Good fail-fast behavior.backends/advanced/src/advanced_omi_backend/services/memory/providers/llm_providers.py (1)
258-261: Good separation of embedding credentials.Using separate
embedding_api_keyandembedding_base_urlallows flexibility when embedding and LLM services have different endpoints or credentials. This is a clean design improvement.
Comment on lines
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| networks: | ||
| default: | ||
| name: chronicle-network | ||
| external: true |
Contributor
There was a problem hiding this comment.
🧩 Analysis chain
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Add docker network create chronicle-network to setup documentation.
The external: true flag on line 227 requires the chronicle-network to be pre-created before running docker compose up. This is not currently documented. Add the following command to the README or setup scripts:
docker network create chronicle-networkAlternatively, add this step to the automated setup flow in the main setup script.
🤖 Prompt for AI Agents
In backends/advanced/docker-compose.yml around lines 224 to 227 the compose file
declares an external network "chronicle-network" but the README/setup does not
instruct users to create it beforehand; update the project setup documentation
or main setup script to run "docker network create chronicle-network" (or
equivalent idempotent check/create logic) before users run docker compose up, or
add that command into the automated setup flow so the external network exists
prior to bringing up the stack.
Comment on lines
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| new_mem = yaml.safe_load(config_yaml) or {} | ||
| except yaml.YAMLError as e: | ||
| return JSONResponse( | ||
| status_code=400, content={"error": f"Invalid YAML syntax: {str(e)}"} | ||
| ) | ||
|
|
||
| config_loader = get_config_loader() | ||
| config_path = config_loader.config_path | ||
|
|
||
| # Create backup | ||
| backup_path = f"{config_path}.bak" | ||
| if os.path.exists(config_path): | ||
| shutil.copy2(config_path, backup_path) | ||
| logger.info(f"Created backup at {backup_path}") | ||
|
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||
| # Write new configuration | ||
| with open(config_path, 'w') as file: | ||
| file.write(config_yaml) | ||
|
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||
| # Hot reload configuration | ||
| reload_success = config_loader.reload_config() | ||
|
|
||
| if reload_success: | ||
| logger.info("Memory configuration updated and reloaded successfully") | ||
| return { | ||
| "message": "Memory configuration updated and reloaded successfully", | ||
| "config_path": config_path, | ||
| "backup_created": os.path.exists(backup_path), | ||
| "status": "success" | ||
| } | ||
| else: | ||
| return JSONResponse( | ||
| status_code=500, content={"error": "Configuration saved but reload failed"} | ||
| ) | ||
|
|
||
| raise ValueError(f"Invalid YAML syntax: {str(e)}") | ||
|
|
Contributor
There was a problem hiding this comment.
Chain exceptions to preserve original context.
When catching an exception and raising a new one, use raise ... from e to preserve the exception chain. This improves debuggability by showing the original cause. Based on learnings for this project.
Suggested fix
try:
new_mem = yaml.safe_load(config_yaml) or {}
except yaml.YAMLError as e:
- raise ValueError(f"Invalid YAML syntax: {str(e)}")
+ raise ValueError(f"Invalid YAML syntax: {e}") from e🧰 Tools
🪛 Ruff (0.14.8)
287-287: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
287-287: Avoid specifying long messages outside the exception class
(TRY003)
287-287: Use explicit conversion flag
Replace with conversion flag
(RUF010)
🤖 Prompt for AI Agents
In backends/advanced/src/advanced_omi_backend/controllers/system_controller.py
around lines 285 to 288, the except block re-raises a ValueError without
chaining the original yaml.YAMLError; change the raise to chain the original
exception using "raise ValueError(f'Invalid YAML syntax: {str(e)}') from e" so
the original exception context is preserved for debugging.
Comment on lines
+322
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+324
| parsed = yaml.safe_load(config_yaml) | ||
| except yaml.YAMLError as e: | ||
| return JSONResponse( | ||
| status_code=400, content={"error": f"Invalid YAML syntax: {str(e)}"} | ||
| ) | ||
|
|
||
| # Create a temporary config loader to validate structure | ||
| try: | ||
| # Create a temporary file for validation | ||
| import tempfile | ||
| with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as tmp_file: | ||
| tmp_file.write(config_yaml) | ||
| tmp_path = tmp_file.name | ||
|
|
||
| # Try to load with MemoryConfigLoader to validate structure | ||
| temp_loader = MemoryConfigLoader(tmp_path) | ||
| temp_loader.validate_config() | ||
|
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| # Clean up temp file | ||
| os.unlink(tmp_path) | ||
|
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| return { | ||
| "message": "Configuration is valid", | ||
| "status": "success" | ||
| } | ||
|
|
||
| except ValueError as e: | ||
| return JSONResponse( | ||
| status_code=400, content={"error": f"Configuration validation failed: {str(e)}"} | ||
| ) | ||
|
|
||
| raise ValueError(f"Invalid YAML syntax: {str(e)}") |
Contributor
There was a problem hiding this comment.
Chain exceptions to preserve original context.
Same issue as above - use raise ... from e when wrapping exceptions.
Suggested fix
try:
parsed = yaml.safe_load(config_yaml)
except yaml.YAMLError as e:
- raise ValueError(f"Invalid YAML syntax: {str(e)}")
+ raise ValueError(f"Invalid YAML syntax: {e}") from e🧰 Tools
🪛 Ruff (0.14.8)
324-324: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
324-324: Avoid specifying long messages outside the exception class
(TRY003)
324-324: Use explicit conversion flag
Replace with conversion flag
(RUF010)
🤖 Prompt for AI Agents
In backends/advanced/src/advanced_omi_backend/controllers/system_controller.py
around lines 322 to 324, the ValueError raised when catching yaml.YAMLError
should chain the original exception to preserve context; change the raise to use
"raise ValueError(f'Invalid YAML syntax: {str(e)}') from e" so the original
traceback is retained when the new exception is propagated.
Comment on lines
+130
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+132
| # Memory provider (registry-based) | ||
| mem_settings = REGISTRY.memory if REGISTRY else {} | ||
| memory_provider = (mem_settings.get("provider") or "chronicle").lower() |
Contributor
There was a problem hiding this comment.
Same potential AttributeError as in app_config.py.
If REGISTRY exists but REGISTRY.memory is None, calling .get("provider") will fail.
🔎 Proposed fix
# Memory provider (registry-based)
- mem_settings = REGISTRY.memory if REGISTRY else {}
+ mem_settings = (REGISTRY.memory if REGISTRY and REGISTRY.memory else {})
memory_provider = (mem_settings.get("provider") or "chronicle").lower()🤖 Prompt for AI Agents
In backends/advanced/src/advanced_omi_backend/routers/modules/health_routes.py
around lines 130 to 132, REGISTRY.memory may be None which causes an
AttributeError when calling .get; change mem_settings assignment to use a
fallback dict (e.g., mem_settings = REGISTRY.memory or {}) so mem_settings is
always a mapping before calling mem_settings.get("provider"), then keep
memory_provider = (mem_settings.get("provider") or "chronicle").lower().
Comment on lines
+243
to
+266
| def get_transcription_provider(provider_name: Optional[str] = None, mode: Optional[str] = None) -> Optional[BaseTranscriptionProvider]: | ||
| """Return a registry-driven transcription provider. | ||
|
|
||
| - mode="batch": HTTP-based STT (default) | ||
| - mode="streaming": WebSocket-based STT | ||
|
|
||
| Note: The models registry returns None when config.yml is missing or invalid. | ||
| We avoid broad exception handling here and simply return None when the | ||
| required defaults are not configured. | ||
| """ | ||
| registry = get_models_registry() | ||
| if not registry: | ||
| return None | ||
|
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||
| selected_mode = (mode or "batch").lower() | ||
| if selected_mode == "streaming": | ||
| if not registry.get_default("stt_stream"): | ||
| return None | ||
| else: | ||
| return RegistryStreamingTranscriptionProvider() | ||
|
|
||
| # batch mode | ||
| if not registry.get_default("stt"): | ||
| return None | ||
| return RegistryBatchTranscriptionProvider() |
Contributor
There was a problem hiding this comment.
Unused provider_name parameter is a potential breaking change.
The provider_name parameter is accepted but ignored. If existing callers pass a specific provider name expecting it to be used, this will silently break their expectations. Consider either:
- Removing the parameter (breaking change, but explicit)
- Using it to select a specific model from the registry
- Logging a deprecation warning
🔎 Suggested fix - Option 2: Use provider_name if specified
def get_transcription_provider(provider_name: Optional[str] = None, mode: Optional[str] = None) -> Optional[BaseTranscriptionProvider]:
"""Return a registry-driven transcription provider.
- mode="batch": HTTP-based STT (default)
- mode="streaming": WebSocket-based STT
Note: The models registry returns None when config.yml is missing or invalid.
We avoid broad exception handling here and simply return None when the
required defaults are not configured.
"""
registry = get_models_registry()
if not registry:
return None
+ # Log if provider_name is specified but ignored (deprecated behavior)
+ if provider_name:
+ logger.warning(f"provider_name '{provider_name}' is ignored; using registry defaults")
+
selected_mode = (mode or "batch").lower()Committable suggestion skipped: line range outside the PR's diff.
🧰 Tools
🪛 Ruff (0.14.8)
243-243: Unused function argument: provider_name
(ARG001)
- 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.
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backends/advanced/Docs/quickstart.md (1)
263-276: UpdateDocs/getting-started.mdto use correct API endpoint.Lines 265 and 271 reference the non-existent endpoint
/api/process-audio-files. The actual implemented endpoint is/api/audio/upload(as correctly documented inbackends/advanced/Docs/quickstart.md). Change both occurrences to/api/audio/uploadfor consistency with the codebase.
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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...
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74-74: Emphasis used instead of a heading
(MD036, no-emphasis-as-heading)
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Docs/getting-started.md (2)
344-346: ✅ Configuration reference clarity.Line 345 correctly updates the configuration reference from memory_config.yaml to config.yml with proper section guidance (memory section). Documentation is clear and actionable.
544-550: Configuration source updated correctly.The centralized configuration approach is clearly documented with proper path guidance (repo root, CONFIG_FILE override, hot-reload behavior, fallback). Transition from memory_config.yaml to config.yml is complete in this section.
backends/advanced/Docs/quickstart.md (1)
342-344: ✅ Configuration documentation updated consistently.Memory system configuration reference correctly updated from memory_config.yaml to config.yml. Consistent with broader documentation changes.
backends/advanced/Docs/README.md (2)
16-16: ✅ config.yml references are consistent and properly pathed.All references to
config.ymlcorrectly identify it as repository root configuration file. Relative paths (../config.yml) and file tree documentation (line 133) are consistent throughout.Also applies to: 89-89, 133-133, 151-151
78-78: Module name verification complete: memory_config_loader.py → model_registry.py is accurate.The
model_registry.pymodule exists atsrc/advanced_omi_backend/model_registry.pyand correctly serves as the configuration loading module, replacing the formermemory_config_loader.py. It loads configuration fromconfig.ymlusing Pydantic for robust validation and environment variable resolution. Documentation references at lines 78, 131, and 150 in README.md are correct.
Comment on lines
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| ### 6. **Configuration File** → `../config.yml` | ||
| **Central configuration for all extraction** | ||
| - Memory extraction settings and prompts | ||
| - Quality control and debug settings | ||
| - **Code References**: | ||
| - `src/advanced_omi_backend/memory_config_loader.py` (config loading) | ||
| - `src/advanced_omi_backend/model_registry.py` (config loading) | ||
| - `src/advanced_omi_backend/memory/memory_service.py` (config usage) |
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Use proper heading syntax instead of emphasis.
Line 73 uses emphasis (bold) instead of a proper Markdown heading (line 72 is a ### heading, but line 73 should not be emphasized text pointing to a heading). Apply proper heading hierarchy.
Static analysis concern: markdownlint MD036 flags this pattern. Consider:
### Configuration File
Central configuration in `../config.yml` at repository root.🧰 Tools
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74-74: Emphasis used instead of a heading
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🤖 Prompt for AI Agents
In backends/advanced/Docs/README.md around lines 73 to 79, the heading uses
emphasis markup inside the heading (e.g. "### 6. **Configuration File** →
`../config.yml`"); replace the emphasized text with a proper markdown heading
and clean heading hierarchy (e.g. "### Configuration File — ../config.yml" or
"### Configuration File" with the file path inline or on the next line), remove
the bold formatting, and ensure the following descriptive line is plain
paragraph text; this will satisfy markdownlint MD036 and keep the heading level
consistent.
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- 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 configuration files for model providers and Docker setup
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- 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.
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
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|
Oh hell yeah test report is available now @0xrushi The thing is, the bug caused the test to time out. The bug was a dict/access error |
AnkushMalaker
commented
Dec 22, 2025
README.md
Outdated
| ## Quick Start → [Get Started](quickstart.md) | ||
|
|
||
| Clone, run setup wizard, start services, access at http://localhost:5173 | ||
| Clone, customize config.yml, start services, access at http://localhost:5173 |
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So this PR looks good to me but I don't like the first thing we recommend is config a yaml file. I make working on a quick PR that should make this one config.yml compatible with the 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.
- 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.
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
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backends/advanced/src/advanced_omi_backend/controllers/websocket_controller.py (1)
719-728: Move imports to top of file to comply with coding guidelines.The change adding
source="websocket"is correct—verified thatwrite_audio_fileaccepts this parameter. However, the_process_batch_audio_completefunction violates the import organization guideline: imports fromadvanced_omi_backend.utils.audio_utils(line 705) andadvanced_omi_backend.models.conversation(line 706) must be at the top of the file after the module docstring, not inside the function. The same applies to the import at line 752 fromadvanced_omi_backend.controllers.queue_controller. These should be moved to the top-level imports section since they are not required for circular import resolution (other imports likeprocess_audio_chunkfromaudio_utilsare already at the top).
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**/*.py
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**/*.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
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🧠 Learnings (1)
📚 Learning: 2025-12-08T23:52:34.959Z
Learnt from: AnkushMalaker
Repo: chronicler-ai/chronicle PR: 178
File: backends/advanced/src/advanced_omi_backend/services/memory/providers/mycelia.py:218-223
Timestamp: 2025-12-08T23:52:34.959Z
Learning: In Python code (chronicle project), prefer logging.exception() inside except blocks to automatically log the full stack trace. When re-raising exceptions, always chain with 'raise ... from e' to preserve the original context; use 'raise ... from None' only if you explicitly want to suppress the context. This improves debuggability across Python files.
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…e-wizard Enhance configuration management and setup wizard
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This was referenced Dec 23, 2025
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* audio upload extension with gdrive credentials * FIX: API parameters * UPDATE: tmp files cleanup n code refactored as per review * REFACTOR: minor refactor as per review * REFACTOR: minor update as per review * UPDATE: gdrive sync logic * REFACTOR: code update as per gdrive and update credential client * REFACTOR: validation updated - as per review from CR * UPDATE: code has been refactore for UUID for diffrent audio upload sources * REFACTOR: updated code as per review * Update documentation and configuration to reflect the transition from 'friend-backend' to 'chronicle-backend' across various files, including setup instructions, Docker configurations, and service logs. * Update test script to use docker-compose-test.yml for all test-related operations * Added standard MIT license * Fix/cleanup model (#219) * refactor memory * add config * docstring * more cleanup * code quality * code quality * unused return * DOTTED GET * Refactor Docker and CI configurations - Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process. - Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services. - Added new dependencies for Google API clients in `uv.lock` to support upcoming features. * Update configuration files for model providers and Docker setup - Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram. - Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving. - Updated memory configuration endpoint to accept plain text for YAML input. * Update transcription job handling to format speaker IDs - Changed variable name from `speaker_name` to `speaker_id` for clarity. - Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling. * Remove loading of backend .env file in test environment setup - Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests. * Enhance configuration management and setup wizard - Updated README to reflect the new setup wizard process. - Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers. - Improved user feedback during configuration updates, including success messages for configuration file updates. - Enabled backup of existing `config.yml` before saving changes. * Enhance HTTPS configuration in setup wizard - Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates. - Improved user prompts for server IP/domain input during HTTPS setup. - Updated default behavior to use existing IP or localhost based on user input. - Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access. * Add source parameter to audio file writing in websocket controller - Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * fix/broken-tests (#230) * refactor memory * add config * docstring * more cleanup * code quality * code quality * unused return * DOTTED GET * Refactor Docker and CI configurations - Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process. - Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services. - Added new dependencies for Google API clients in `uv.lock` to support upcoming features. * Update configuration files for model providers and Docker setup - Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram. - Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving. - Updated memory configuration endpoint to accept plain text for YAML input. * Update transcription job handling to format speaker IDs - Changed variable name from `speaker_name` to `speaker_id` for clarity. - Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling. * Remove loading of backend .env file in test environment setup - Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests. * Enhance configuration management and setup wizard - Updated README to reflect the new setup wizard process. - Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers. - Improved user feedback during configuration updates, including success messages for configuration file updates. - Enabled backup of existing `config.yml` before saving changes. * Enhance HTTPS configuration in setup wizard - Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates. - Improved user prompts for server IP/domain input during HTTPS setup. - Updated default behavior to use existing IP or localhost based on user input. - Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access. * Add source parameter to audio file writing in websocket controller - Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking. * Refactor error handling in system controller and update memory config routes - Replaced ValueError with HTTPException for better error handling in `save_diarization_settings` and `validate_memory_config` functions. - Introduced a new Pydantic model, `MemoryConfigRequest`, for validating memory configuration requests in the system routes. - Updated the `validate_memory_config` endpoint to accept the new request model, improving input handling and validation. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * Feat/add obsidian 3 (#233) * obsidian support * neo4j comment * cleanup code * unused line * unused line * Fix MemoryEntry object usage in chat service * comment * feat(obsidian): add obsidian memory search integration to chat * unit test * use rq * neo4j service * typefix * test fix * cleanup * cleanup * version changes * profile * remove unused imports * Refactor memory configuration validation endpoints - Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation. - Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input. - Adjusted the API call in the frontend to point to the new validation endpoint. * Refactor health check model configuration loading - Updated the health check function to load model configuration from the models registry instead of the root config. - Improved error handling by logging warnings when model configuration loading fails. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * Update .gitignore to exclude all files in app/ios and app/android directories (#238) * fix: Copy full source code in speaker-recognition Dockerfile (#243) Adds COPY src/ src/ step after dependency installation to ensure all source files are available in the Docker image. This improves build caching while ensuring complete source code is present. * Enhance configuration management and add new setup scripts (#235) * Enhance configuration management and add new setup scripts - Updated .gitignore to include config.yml and its template. - Added config.yml.template for default configuration settings. - Introduced restart.sh script for service management. - Enhanced services.py to load config.yml and check for Obsidian/Neo4j integration. - Updated wizard.py to prompt for Obsidian/Neo4j configuration during setup and create config.yml from template if it doesn't exist. * Refactor transcription providers and enhance configuration management - Updated Docker Compose files to include the new Neo4j service configuration. - Added support for Obsidian/Neo4j integration in the setup process. - Refactored transcription providers to utilize a registry-driven approach for Deepgram and Parakeet. - Enhanced error handling and logging in transcription processes. - Improved environment variable management in test scripts to prioritize command-line overrides. - Removed deprecated Parakeet provider implementation and streamlined audio stream workers. * Update configuration management and enhance file structure, add test-matrix (#237) * Update configuration management and enhance file structure - Refactored configuration file paths to use a dedicated `config/` directory, including updates to `config.yml` and its template. - Modified service scripts to load the new configuration path for `config.yml`. - Enhanced `.gitignore` to include the new configuration files and templates. - Updated documentation to reflect changes in configuration file locations and usage. - Improved setup scripts to ensure proper creation and management of configuration files. - Added new test configurations for various provider combinations to streamline testing processes. * Add test requirements and clean up imports in wizard.py - Introduced a new `test-requirements.txt` file to manage testing dependencies. - Removed redundant import of `shutil` in `wizard.py` to improve code clarity. * Add ConfigManager for unified configuration management - Introduced a new `config_manager.py` module to handle reading and writing configurations from `config.yml` and `.env` files, ensuring backward compatibility. - Refactored `ChronicleSetup` in `backends/advanced/init.py` to utilize `ConfigManager` for loading and updating configurations, simplifying the setup process. - Removed redundant methods for loading and saving `config.yml` directly in `ChronicleSetup`, as these are now managed by `ConfigManager`. - Enhanced user feedback during configuration updates, including success messages for changes made to configuration files. * Refactor transcription provider configuration and enhance setup process - Updated `.env.template` to clarify speech-to-text configuration and removed deprecated options for Mistral. - Modified `docker-compose.yml` to streamline environment variable management by removing unused Mistral keys. - Enhanced `ChronicleSetup` in `init.py` to provide clearer user feedback and updated the transcription provider selection process to rely on `config.yml`. - Improved error handling in the websocket controller to determine the transcription provider from the model registry instead of environment variables. - Updated health check routes to reflect the new method of retrieving the transcription provider from `config.yml`. - Adjusted `config.yml.template` to include comments on transcription provider options for better user guidance. * Enhance ConfigManager with deep merge functionality - Updated the `update_memory_config` method to perform a deep merge of updates into the memory configuration, ensuring nested dictionaries are merged correctly. - Added a new `_deep_merge` method to handle recursive merging of dictionaries, improving configuration management capabilities. * Refactor run-test.sh and enhance memory extraction tests - Removed deprecated environment variable handling for TRANSCRIPTION_PROVIDER in `run-test.sh`, streamlining the configuration process. - Introduced a new `run-custom.sh` script for executing Robot tests with custom configurations, improving test flexibility. - Enhanced memory extraction tests in `audio_keywords.robot` and `memory_keywords.robot` to include detailed assertions and result handling. - Updated `queue_keywords.robot` to fail fast if a job is in a 'failed' state when expecting 'completed', improving error handling. - Refactored `test_env.py` to load environment variables with correct precedence, ensuring better configuration management. * unify tests to robot test, add some more clean up * Update health check configuration in docker-compose-test.yml (#241) - Increased the number of retries from 5 to 10 for improved resilience during service readiness checks. - Extended the start period from 30s to 60s to allow more time for services to initialize before health checks commence. * Add step to create test configuration file in robot-tests.yml - Introduced a new step in the GitHub Actions workflow to copy the test configuration file from tests/configs/deepgram-openai.yml to a new config/config.yml. - Added logging to confirm the creation of the test config file, improving visibility during the test setup process. * remove cache step since not required * coderabbit comments * Refactor ConfigManager error handling for configuration file loading - Updated the ConfigManager to raise RuntimeError exceptions when the configuration file is not found or is invalid, improving error visibility and user guidance. - Removed fallback behavior that previously returned the current directory, ensuring users are explicitly informed about missing or invalid configuration files. * Refactor _find_repo_root method in ConfigManager - Updated the _find_repo_root method to locate the repository root using the __file__ location instead of searching for config/config.yml, simplifying the logic and improving reliability. - Removed the previous error handling that raised a RuntimeError if the configuration file was not found, as the new approach assumes config_manager.py is always at the repo root. * Enhance speaker recognition service integration and error handling (#245) * Enhance speaker recognition service integration and error handling - Updated `docker-compose-test.yml` to enable speaker recognition in the test environment and added a new `speaker-service-test` service for testing purposes. - Refactored `run-test.sh` to improve the execution of Robot Framework tests from the repository root. - Enhanced error handling in `speaker_recognition_client.py` to return detailed error messages for connection issues. - Improved error logging in `speaker_jobs.py` to handle and report errors from the speaker recognition service more effectively. - Updated `Dockerfile` to copy the full source code after dependencies are cached, ensuring all necessary files are included in the image. * Remove integration tests workflow and enhance robot tests with HF_TOKEN verification - Deleted the `integration-tests.yml` workflow file to streamline CI processes. - Updated `robot-tests.yml` to include verification for the new `HF_TOKEN` secret, ensuring all required secrets are checked before running tests. * Fix key access in system admin tests to use string indexing for speakers data * Refactor Robot Framework tests and enhance error handling in memory services - Removed the creation of the test environment file from the GitHub Actions workflow to streamline setup. - Updated the Robot Framework tests to utilize a unified test script for improved consistency. - Enhanced error messages in the MemoryService class to provide more context on connection failures for LLM and vector store providers. - Added critical checks for API key presence in the OpenAIProvider class to ensure valid credentials are provided before proceeding. - Adjusted various test setup scripts to use a centralized BACKEND_DIR variable for better maintainability and clarity. * Refactor test container cleanup in run-robot-tests.sh - Updated the script to dynamically construct container names from docker-compose services, improving maintainability and reducing hardcoded values. - Enhanced the cleanup process for stuck test containers by utilizing the COMPOSE_PROJECT_NAME variable. * Enhance run-robot-tests.sh for improved logging and cleanup - Set absolute paths for consistent directory references to simplify navigation. - Capture container logs, status, and resource usage for better debugging. - Refactor cleanup process to utilize dynamic backend directory references, improving maintainability. - Ensure proper navigation back to the tests directory after operations. * Add speaker recognition configuration and update test script defaults - Introduced speaker recognition settings in config.yml.template, allowing for easy enable/disable and service URL configuration. - Updated run-robot-tests.sh to use a test-specific configuration file that disables speaker recognition for improved CI performance. - Modified deepgram-openai.yml to disable speaker recognition during CI tests to enhance execution speed. * Refactor speaker recognition configuration management - Updated docker-compose-test.yml to clarify speaker recognition settings, now controlled via config.yml for improved CI performance. - Enhanced model_registry.py to include a dedicated speaker_recognition field for better configuration handling. - Modified speaker_recognition_client.py to load configuration from config.yml, allowing for dynamic enabling/disabling of the speaker recognition service based on the configuration. * Add minimum worker count verification to infrastructure tests - Introduced a new keyword to verify that the minimum number of workers are registered, enhancing the robustness of health checks. - Updated the worker count validation test to include a wait mechanism for worker registration, improving test reliability. - Clarified comments regarding expected worker counts to reflect the distinction between RQ and audio stream workers. * Update configuration management and enhance model handling - Added OBSIDIAN_ENABLED configuration to ChronicleSetup for improved feature toggling. - Introduced speaker_recognition configuration handling in model_registry.py to streamline model loading. - Refactored imports in deepgram.py to improve clarity and reduce redundancy. * Refactor configuration management in wizard and ChronicleSetup (#246) * Refactor configuration management in wizard and ChronicleSetup - Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling. - Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth. - Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers. * Fix string formatting for error message in ChronicleSetup --------- Co-authored-by: 01PrathamS <pratham21btai35@karnavatiuniversity.edu.in> Co-authored-by: Stu Alexandere <thestumonkey@gmail.com> Co-authored-by: Stuart Alexander <stu@theawesome.co.uk> Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
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* audio upload extension with gdrive credentials * FIX: API parameters * UPDATE: tmp files cleanup n code refactored as per review * REFACTOR: minor refactor as per review * REFACTOR: minor update as per review * UPDATE: gdrive sync logic * REFACTOR: code update as per gdrive and update credential client * REFACTOR: validation updated - as per review from CR * UPDATE: code has been refactore for UUID for diffrent audio upload sources * REFACTOR: updated code as per review * Update documentation and configuration to reflect the transition from 'friend-backend' to 'chronicle-backend' across various files, including setup instructions, Docker configurations, and service logs. * Update test script to use docker-compose-test.yml for all test-related operations * Added standard MIT license * Fix/cleanup model (#219) * refactor memory * add config * docstring * more cleanup * code quality * code quality * unused return * DOTTED GET * Refactor Docker and CI configurations - Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process. - Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services. - Added new dependencies for Google API clients in `uv.lock` to support upcoming features. * Update configuration files for model providers and Docker setup - Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram. - Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving. - Updated memory configuration endpoint to accept plain text for YAML input. * Update transcription job handling to format speaker IDs - Changed variable name from `speaker_name` to `speaker_id` for clarity. - Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling. * Remove loading of backend .env file in test environment setup - Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests. * Enhance configuration management and setup wizard - Updated README to reflect the new setup wizard process. - Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers. - Improved user feedback during configuration updates, including success messages for configuration file updates. - Enabled backup of existing `config.yml` before saving changes. * Enhance HTTPS configuration in setup wizard - Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates. - Improved user prompts for server IP/domain input during HTTPS setup. - Updated default behavior to use existing IP or localhost based on user input. - Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access. * Add source parameter to audio file writing in websocket controller - Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * fix/broken-tests (#230) * refactor memory * add config * docstring * more cleanup * code quality * code quality * unused return * DOTTED GET * Refactor Docker and CI configurations - Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process. - Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services. - Added new dependencies for Google API clients in `uv.lock` to support upcoming features. * Update configuration files for model providers and Docker setup - Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram. - Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving. - Updated memory configuration endpoint to accept plain text for YAML input. * Update transcription job handling to format speaker IDs - Changed variable name from `speaker_name` to `speaker_id` for clarity. - Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling. * Remove loading of backend .env file in test environment setup - Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests. * Enhance configuration management and setup wizard - Updated README to reflect the new setup wizard process. - Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers. - Improved user feedback during configuration updates, including success messages for configuration file updates. - Enabled backup of existing `config.yml` before saving changes. * Enhance HTTPS configuration in setup wizard - Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates. - Improved user prompts for server IP/domain input during HTTPS setup. - Updated default behavior to use existing IP or localhost based on user input. - Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access. * Add source parameter to audio file writing in websocket controller - Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking. * Refactor error handling in system controller and update memory config routes - Replaced ValueError with HTTPException for better error handling in `save_diarization_settings` and `validate_memory_config` functions. - Introduced a new Pydantic model, `MemoryConfigRequest`, for validating memory configuration requests in the system routes. - Updated the `validate_memory_config` endpoint to accept the new request model, improving input handling and validation. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * Feat/add obsidian 3 (#233) * obsidian support * neo4j comment * cleanup code * unused line * unused line * Fix MemoryEntry object usage in chat service * comment * feat(obsidian): add obsidian memory search integration to chat * unit test * use rq * neo4j service * typefix * test fix * cleanup * cleanup * version changes * profile * remove unused imports * Refactor memory configuration validation endpoints - Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation. - Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input. - Adjusted the API call in the frontend to point to the new validation endpoint. * Refactor health check model configuration loading - Updated the health check function to load model configuration from the models registry instead of the root config. - Improved error handling by logging warnings when model configuration loading fails. --------- Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com> * Update .gitignore to exclude all files in app/ios and app/android directories (#238) * fix: Copy full source code in speaker-recognition Dockerfile (#243) Adds COPY src/ src/ step after dependency installation to ensure all source files are available in the Docker image. This improves build caching while ensuring complete source code is present. * Enhance configuration management and add new setup scripts (#235) * Enhance configuration management and add new setup scripts - Updated .gitignore to include config.yml and its template. - Added config.yml.template for default configuration settings. - Introduced restart.sh script for service management. - Enhanced services.py to load config.yml and check for Obsidian/Neo4j integration. - Updated wizard.py to prompt for Obsidian/Neo4j configuration during setup and create config.yml from template if it doesn't exist. * Refactor transcription providers and enhance configuration management - Updated Docker Compose files to include the new Neo4j service configuration. - Added support for Obsidian/Neo4j integration in the setup process. - Refactored transcription providers to utilize a registry-driven approach for Deepgram and Parakeet. - Enhanced error handling and logging in transcription processes. - Improved environment variable management in test scripts to prioritize command-line overrides. - Removed deprecated Parakeet provider implementation and streamlined audio stream workers. * Update configuration management and enhance file structure, add test-matrix (#237) * Update configuration management and enhance file structure - Refactored configuration file paths to use a dedicated `config/` directory, including updates to `config.yml` and its template. - Modified service scripts to load the new configuration path for `config.yml`. - Enhanced `.gitignore` to include the new configuration files and templates. - Updated documentation to reflect changes in configuration file locations and usage. - Improved setup scripts to ensure proper creation and management of configuration files. - Added new test configurations for various provider combinations to streamline testing processes. * Add test requirements and clean up imports in wizard.py - Introduced a new `test-requirements.txt` file to manage testing dependencies. - Removed redundant import of `shutil` in `wizard.py` to improve code clarity. * Add ConfigManager for unified configuration management - Introduced a new `config_manager.py` module to handle reading and writing configurations from `config.yml` and `.env` files, ensuring backward compatibility. - Refactored `ChronicleSetup` in `backends/advanced/init.py` to utilize `ConfigManager` for loading and updating configurations, simplifying the setup process. - Removed redundant methods for loading and saving `config.yml` directly in `ChronicleSetup`, as these are now managed by `ConfigManager`. - Enhanced user feedback during configuration updates, including success messages for changes made to configuration files. * Refactor transcription provider configuration and enhance setup process - Updated `.env.template` to clarify speech-to-text configuration and removed deprecated options for Mistral. - Modified `docker-compose.yml` to streamline environment variable management by removing unused Mistral keys. - Enhanced `ChronicleSetup` in `init.py` to provide clearer user feedback and updated the transcription provider selection process to rely on `config.yml`. - Improved error handling in the websocket controller to determine the transcription provider from the model registry instead of environment variables. - Updated health check routes to reflect the new method of retrieving the transcription provider from `config.yml`. - Adjusted `config.yml.template` to include comments on transcription provider options for better user guidance. * Enhance ConfigManager with deep merge functionality - Updated the `update_memory_config` method to perform a deep merge of updates into the memory configuration, ensuring nested dictionaries are merged correctly. - Added a new `_deep_merge` method to handle recursive merging of dictionaries, improving configuration management capabilities. * Refactor run-test.sh and enhance memory extraction tests - Removed deprecated environment variable handling for TRANSCRIPTION_PROVIDER in `run-test.sh`, streamlining the configuration process. - Introduced a new `run-custom.sh` script for executing Robot tests with custom configurations, improving test flexibility. - Enhanced memory extraction tests in `audio_keywords.robot` and `memory_keywords.robot` to include detailed assertions and result handling. - Updated `queue_keywords.robot` to fail fast if a job is in a 'failed' state when expecting 'completed', improving error handling. - Refactored `test_env.py` to load environment variables with correct precedence, ensuring better configuration management. * unify tests to robot test, add some more clean up * Update health check configuration in docker-compose-test.yml (#241) - Increased the number of retries from 5 to 10 for improved resilience during service readiness checks. - Extended the start period from 30s to 60s to allow more time for services to initialize before health checks commence. * Add step to create test configuration file in robot-tests.yml - Introduced a new step in the GitHub Actions workflow to copy the test configuration file from tests/configs/deepgram-openai.yml to a new config/config.yml. - Added logging to confirm the creation of the test config file, improving visibility during the test setup process. * remove cache step since not required * coderabbit comments * Refactor ConfigManager error handling for configuration file loading - Updated the ConfigManager to raise RuntimeError exceptions when the configuration file is not found or is invalid, improving error visibility and user guidance. - Removed fallback behavior that previously returned the current directory, ensuring users are explicitly informed about missing or invalid configuration files. * Refactor _find_repo_root method in ConfigManager - Updated the _find_repo_root method to locate the repository root using the __file__ location instead of searching for config/config.yml, simplifying the logic and improving reliability. - Removed the previous error handling that raised a RuntimeError if the configuration file was not found, as the new approach assumes config_manager.py is always at the repo root. * Enhance speaker recognition service integration and error handling (#245) * Enhance speaker recognition service integration and error handling - Updated `docker-compose-test.yml` to enable speaker recognition in the test environment and added a new `speaker-service-test` service for testing purposes. - Refactored `run-test.sh` to improve the execution of Robot Framework tests from the repository root. - Enhanced error handling in `speaker_recognition_client.py` to return detailed error messages for connection issues. - Improved error logging in `speaker_jobs.py` to handle and report errors from the speaker recognition service more effectively. - Updated `Dockerfile` to copy the full source code after dependencies are cached, ensuring all necessary files are included in the image. * Remove integration tests workflow and enhance robot tests with HF_TOKEN verification - Deleted the `integration-tests.yml` workflow file to streamline CI processes. - Updated `robot-tests.yml` to include verification for the new `HF_TOKEN` secret, ensuring all required secrets are checked before running tests. * Fix key access in system admin tests to use string indexing for speakers data * Refactor Robot Framework tests and enhance error handling in memory services - Removed the creation of the test environment file from the GitHub Actions workflow to streamline setup. - Updated the Robot Framework tests to utilize a unified test script for improved consistency. - Enhanced error messages in the MemoryService class to provide more context on connection failures for LLM and vector store providers. - Added critical checks for API key presence in the OpenAIProvider class to ensure valid credentials are provided before proceeding. - Adjusted various test setup scripts to use a centralized BACKEND_DIR variable for better maintainability and clarity. * Refactor test container cleanup in run-robot-tests.sh - Updated the script to dynamically construct container names from docker-compose services, improving maintainability and reducing hardcoded values. - Enhanced the cleanup process for stuck test containers by utilizing the COMPOSE_PROJECT_NAME variable. * Enhance run-robot-tests.sh for improved logging and cleanup - Set absolute paths for consistent directory references to simplify navigation. - Capture container logs, status, and resource usage for better debugging. - Refactor cleanup process to utilize dynamic backend directory references, improving maintainability. - Ensure proper navigation back to the tests directory after operations. * Add speaker recognition configuration and update test script defaults - Introduced speaker recognition settings in config.yml.template, allowing for easy enable/disable and service URL configuration. - Updated run-robot-tests.sh to use a test-specific configuration file that disables speaker recognition for improved CI performance. - Modified deepgram-openai.yml to disable speaker recognition during CI tests to enhance execution speed. * Refactor speaker recognition configuration management - Updated docker-compose-test.yml to clarify speaker recognition settings, now controlled via config.yml for improved CI performance. - Enhanced model_registry.py to include a dedicated speaker_recognition field for better configuration handling. - Modified speaker_recognition_client.py to load configuration from config.yml, allowing for dynamic enabling/disabling of the speaker recognition service based on the configuration. * Add minimum worker count verification to infrastructure tests - Introduced a new keyword to verify that the minimum number of workers are registered, enhancing the robustness of health checks. - Updated the worker count validation test to include a wait mechanism for worker registration, improving test reliability. - Clarified comments regarding expected worker counts to reflect the distinction between RQ and audio stream workers. * Update configuration management and enhance model handling - Added OBSIDIAN_ENABLED configuration to ChronicleSetup for improved feature toggling. - Introduced speaker_recognition configuration handling in model_registry.py to streamline model loading. - Refactored imports in deepgram.py to improve clarity and reduce redundancy. * Refactor configuration management in wizard and ChronicleSetup (#246) * Refactor configuration management in wizard and ChronicleSetup - Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling. - Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth. - Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers. * Fix string formatting for error message in ChronicleSetup * added JWT issuers for audience auth for service interop and shared us… (#250) * added JWT issuers for audience auth for service interop and shared user accounts * amended default value in line wioth code --------- Co-authored-by: 01PrathamS <pratham21btai35@karnavatiuniversity.edu.in> Co-authored-by: Stu Alexandere <thestumonkey@gmail.com> Co-authored-by: Stuart Alexander <stu@theawesome.co.uk> Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
AnkushMalaker
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Feb 19, 2026
* audio upload extension with gdrive credentials
* FIX: API parameters
* UPDATE: tmp files cleanup n code refactored as per review
* REFACTOR: minor refactor as per review
* REFACTOR: minor update as per review
* UPDATE: gdrive sync logic
* REFACTOR: code update as per gdrive and update credential client
* REFACTOR: validation updated - as per review from CR
* UPDATE: code has been refactore for UUID for diffrent audio upload sources
* REFACTOR: updated code as per review
* Update documentation and configuration to reflect the transition from 'friend-backend' to 'chronicle-backend' across various files, including setup instructions, Docker configurations, and service logs.
* Update test script to use docker-compose-test.yml for all test-related operations
* Added standard MIT license
* Fix/cleanup model (#219)
* refactor memory
* add config
* docstring
* more cleanup
* code quality
* code quality
* unused return
* DOTTED GET
* Refactor Docker and CI configurations
- Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process.
- Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services.
- Added new dependencies for Google API clients in `uv.lock` to support upcoming features.
* Update configuration files for model providers and Docker setup
- Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram.
- Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving.
- Updated memory configuration endpoint to accept plain text for YAML input.
* Update transcription job handling to format speaker IDs
- Changed variable name from `speaker_name` to `speaker_id` for clarity.
- Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling.
* Remove loading of backend .env file in test environment setup
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
* Enhance configuration management and setup wizard
- Updated README to reflect the new setup wizard process.
- Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers.
- Improved user feedback during configuration updates, including success messages for configuration file updates.
- Enabled backup of existing `config.yml` before saving changes.
* Enhance HTTPS configuration in setup wizard
- Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates.
- Improved user prompts for server IP/domain input during HTTPS setup.
- Updated default behavior to use existing IP or localhost based on user input.
- Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access.
* Add source parameter to audio file writing in websocket controller
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* fix/broken-tests (#230)
* refactor memory
* add config
* docstring
* more cleanup
* code quality
* code quality
* unused return
* DOTTED GET
* Refactor Docker and CI configurations
- Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process.
- Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services.
- Added new dependencies for Google API clients in `uv.lock` to support upcoming features.
* Update configuration files for model providers and Docker setup
- Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram.
- Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving.
- Updated memory configuration endpoint to accept plain text for YAML input.
* Update transcription job handling to format speaker IDs
- Changed variable name from `speaker_name` to `speaker_id` for clarity.
- Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling.
* Remove loading of backend .env file in test environment setup
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
* Enhance configuration management and setup wizard
- Updated README to reflect the new setup wizard process.
- Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers.
- Improved user feedback during configuration updates, including success messages for configuration file updates.
- Enabled backup of existing `config.yml` before saving changes.
* Enhance HTTPS configuration in setup wizard
- Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates.
- Improved user prompts for server IP/domain input during HTTPS setup.
- Updated default behavior to use existing IP or localhost based on user input.
- Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access.
* Add source parameter to audio file writing in websocket controller
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
* Refactor error handling in system controller and update memory config routes
- Replaced ValueError with HTTPException for better error handling in `save_diarization_settings` and `validate_memory_config` functions.
- Introduced a new Pydantic model, `MemoryConfigRequest`, for validating memory configuration requests in the system routes.
- Updated the `validate_memory_config` endpoint to accept the new request model, improving input handling and validation.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* Feat/add obsidian 3 (#233)
* obsidian support
* neo4j comment
* cleanup code
* unused line
* unused line
* Fix MemoryEntry object usage in chat service
* comment
* feat(obsidian): add obsidian memory search integration to chat
* unit test
* use rq
* neo4j service
* typefix
* test fix
* cleanup
* cleanup
* version changes
* profile
* remove unused imports
* Refactor memory configuration validation endpoints
- Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation.
- Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input.
- Adjusted the API call in the frontend to point to the new validation endpoint.
* Refactor health check model configuration loading
- Updated the health check function to load model configuration from the models registry instead of the root config.
- Improved error handling by logging warnings when model configuration loading fails.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* Update .gitignore to exclude all files in app/ios and app/android directories (#238)
* fix: Copy full source code in speaker-recognition Dockerfile (#243)
Adds COPY src/ src/ step after dependency installation to ensure
all source files are available in the Docker image. This improves
build caching while ensuring complete source code is present.
* Enhance configuration management and add new setup scripts (#235)
* Enhance configuration management and add new setup scripts
- Updated .gitignore to include config.yml and its template.
- Added config.yml.template for default configuration settings.
- Introduced restart.sh script for service management.
- Enhanced services.py to load config.yml and check for Obsidian/Neo4j integration.
- Updated wizard.py to prompt for Obsidian/Neo4j configuration during setup and create config.yml from template if it doesn't exist.
* Refactor transcription providers and enhance configuration management
- Updated Docker Compose files to include the new Neo4j service configuration.
- Added support for Obsidian/Neo4j integration in the setup process.
- Refactored transcription providers to utilize a registry-driven approach for Deepgram and Parakeet.
- Enhanced error handling and logging in transcription processes.
- Improved environment variable management in test scripts to prioritize command-line overrides.
- Removed deprecated Parakeet provider implementation and streamlined audio stream workers.
* Update configuration management and enhance file structure, add test-matrix (#237)
* Update configuration management and enhance file structure
- Refactored configuration file paths to use a dedicated `config/` directory, including updates to `config.yml` and its template.
- Modified service scripts to load the new configuration path for `config.yml`.
- Enhanced `.gitignore` to include the new configuration files and templates.
- Updated documentation to reflect changes in configuration file locations and usage.
- Improved setup scripts to ensure proper creation and management of configuration files.
- Added new test configurations for various provider combinations to streamline testing processes.
* Add test requirements and clean up imports in wizard.py
- Introduced a new `test-requirements.txt` file to manage testing dependencies.
- Removed redundant import of `shutil` in `wizard.py` to improve code clarity.
* Add ConfigManager for unified configuration management
- Introduced a new `config_manager.py` module to handle reading and writing configurations from `config.yml` and `.env` files, ensuring backward compatibility.
- Refactored `ChronicleSetup` in `backends/advanced/init.py` to utilize `ConfigManager` for loading and updating configurations, simplifying the setup process.
- Removed redundant methods for loading and saving `config.yml` directly in `ChronicleSetup`, as these are now managed by `ConfigManager`.
- Enhanced user feedback during configuration updates, including success messages for changes made to configuration files.
* Refactor transcription provider configuration and enhance setup process
- Updated `.env.template` to clarify speech-to-text configuration and removed deprecated options for Mistral.
- Modified `docker-compose.yml` to streamline environment variable management by removing unused Mistral keys.
- Enhanced `ChronicleSetup` in `init.py` to provide clearer user feedback and updated the transcription provider selection process to rely on `config.yml`.
- Improved error handling in the websocket controller to determine the transcription provider from the model registry instead of environment variables.
- Updated health check routes to reflect the new method of retrieving the transcription provider from `config.yml`.
- Adjusted `config.yml.template` to include comments on transcription provider options for better user guidance.
* Enhance ConfigManager with deep merge functionality
- Updated the `update_memory_config` method to perform a deep merge of updates into the memory configuration, ensuring nested dictionaries are merged correctly.
- Added a new `_deep_merge` method to handle recursive merging of dictionaries, improving configuration management capabilities.
* Refactor run-test.sh and enhance memory extraction tests
- Removed deprecated environment variable handling for TRANSCRIPTION_PROVIDER in `run-test.sh`, streamlining the configuration process.
- Introduced a new `run-custom.sh` script for executing Robot tests with custom configurations, improving test flexibility.
- Enhanced memory extraction tests in `audio_keywords.robot` and `memory_keywords.robot` to include detailed assertions and result handling.
- Updated `queue_keywords.robot` to fail fast if a job is in a 'failed' state when expecting 'completed', improving error handling.
- Refactored `test_env.py` to load environment variables with correct precedence, ensuring better configuration management.
* unify tests to robot test, add some more clean up
* Update health check configuration in docker-compose-test.yml (#241)
- Increased the number of retries from 5 to 10 for improved resilience during service readiness checks.
- Extended the start period from 30s to 60s to allow more time for services to initialize before health checks commence.
* Add step to create test configuration file in robot-tests.yml
- Introduced a new step in the GitHub Actions workflow to copy the test configuration file from tests/configs/deepgram-openai.yml to a new config/config.yml.
- Added logging to confirm the creation of the test config file, improving visibility during the test setup process.
* remove cache step since not required
* coderabbit comments
* Refactor ConfigManager error handling for configuration file loading
- Updated the ConfigManager to raise RuntimeError exceptions when the configuration file is not found or is invalid, improving error visibility and user guidance.
- Removed fallback behavior that previously returned the current directory, ensuring users are explicitly informed about missing or invalid configuration files.
* Refactor _find_repo_root method in ConfigManager
- Updated the _find_repo_root method to locate the repository root using the __file__ location instead of searching for config/config.yml, simplifying the logic and improving reliability.
- Removed the previous error handling that raised a RuntimeError if the configuration file was not found, as the new approach assumes config_manager.py is always at the repo root.
* Enhance speaker recognition service integration and error handling (#245)
* Enhance speaker recognition service integration and error handling
- Updated `docker-compose-test.yml` to enable speaker recognition in the test environment and added a new `speaker-service-test` service for testing purposes.
- Refactored `run-test.sh` to improve the execution of Robot Framework tests from the repository root.
- Enhanced error handling in `speaker_recognition_client.py` to return detailed error messages for connection issues.
- Improved error logging in `speaker_jobs.py` to handle and report errors from the speaker recognition service more effectively.
- Updated `Dockerfile` to copy the full source code after dependencies are cached, ensuring all necessary files are included in the image.
* Remove integration tests workflow and enhance robot tests with HF_TOKEN verification
- Deleted the `integration-tests.yml` workflow file to streamline CI processes.
- Updated `robot-tests.yml` to include verification for the new `HF_TOKEN` secret, ensuring all required secrets are checked before running tests.
* Fix key access in system admin tests to use string indexing for speakers data
* Refactor Robot Framework tests and enhance error handling in memory services
- Removed the creation of the test environment file from the GitHub Actions workflow to streamline setup.
- Updated the Robot Framework tests to utilize a unified test script for improved consistency.
- Enhanced error messages in the MemoryService class to provide more context on connection failures for LLM and vector store providers.
- Added critical checks for API key presence in the OpenAIProvider class to ensure valid credentials are provided before proceeding.
- Adjusted various test setup scripts to use a centralized BACKEND_DIR variable for better maintainability and clarity.
* Refactor test container cleanup in run-robot-tests.sh
- Updated the script to dynamically construct container names from docker-compose services, improving maintainability and reducing hardcoded values.
- Enhanced the cleanup process for stuck test containers by utilizing the COMPOSE_PROJECT_NAME variable.
* Enhance run-robot-tests.sh for improved logging and cleanup
- Set absolute paths for consistent directory references to simplify navigation.
- Capture container logs, status, and resource usage for better debugging.
- Refactor cleanup process to utilize dynamic backend directory references, improving maintainability.
- Ensure proper navigation back to the tests directory after operations.
* Add speaker recognition configuration and update test script defaults
- Introduced speaker recognition settings in config.yml.template, allowing for easy enable/disable and service URL configuration.
- Updated run-robot-tests.sh to use a test-specific configuration file that disables speaker recognition for improved CI performance.
- Modified deepgram-openai.yml to disable speaker recognition during CI tests to enhance execution speed.
* Refactor speaker recognition configuration management
- Updated docker-compose-test.yml to clarify speaker recognition settings, now controlled via config.yml for improved CI performance.
- Enhanced model_registry.py to include a dedicated speaker_recognition field for better configuration handling.
- Modified speaker_recognition_client.py to load configuration from config.yml, allowing for dynamic enabling/disabling of the speaker recognition service based on the configuration.
* Add minimum worker count verification to infrastructure tests
- Introduced a new keyword to verify that the minimum number of workers are registered, enhancing the robustness of health checks.
- Updated the worker count validation test to include a wait mechanism for worker registration, improving test reliability.
- Clarified comments regarding expected worker counts to reflect the distinction between RQ and audio stream workers.
* Update configuration management and enhance model handling
- Added OBSIDIAN_ENABLED configuration to ChronicleSetup for improved feature toggling.
- Introduced speaker_recognition configuration handling in model_registry.py to streamline model loading.
- Refactored imports in deepgram.py to improve clarity and reduce redundancy.
* Refactor configuration management in wizard and ChronicleSetup (#246)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* added JWT issuers for audience auth for service interop and shared us… (#250)
* added JWT issuers for audience auth for service interop and shared user accounts
* amended default value in line wioth code
* Feat/edit chat system prompt (#247)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* Enhance chat configuration management and UI integration
- Updated `services.py` to allow service restart with an option to recreate containers, addressing WSL2 bind mount issues.
- Added new chat configuration management functions in `system_controller.py` for loading, saving, and validating chat prompts.
- Introduced `ChatSettings` component in the web UI for admin users to manage chat configurations easily.
- Updated API service methods in `api.ts` to support chat configuration endpoints.
- Integrated chat settings into the system management page for better accessibility.
* Refactor backend shutdown process and enhance chat service configuration logging
- Updated `start.sh` to improve shutdown handling by explicitly killing the backend process if running.
- Modified `chat_service.py` to enhance logging for loading chat system prompts, providing clearer feedback on configuration usage.
- Added a new `chat` field in `model_registry.py` for better chat service configuration management.
- Updated vector store query parameters in `vector_stores.py` for improved clarity and functionality.
- Enhanced the chat component in the web UI to conditionally auto-scroll based on message sending status.
* Return JSONResponse instead of raw result
* Refactor headers creation in system admin tests
* Make config.yml writable for admin updates
* Docs consolidation (#257)
* Enhance setup documentation and convenience scripts
- Updated the interactive setup wizard instructions to recommend using the convenience script `./wizard.sh` for easier configuration.
- Added detailed instructions for uploading and processing existing audio files via the API, including example commands for single and multiple file uploads.
- Introduced a new section on HAVPE relay configuration for ESP32 audio streaming, providing environment variable setup and command examples.
- Clarified the distributed deployment setup, including GPU and backend separation instructions, and added benefits of using Tailscale for networking.
- Removed outdated `getting-started.md` and `SETUP_SCRIPTS.md` files to streamline documentation and avoid redundancy.
* Update setup instructions and enhance service management scripts
- Replaced direct command instructions with convenience scripts (`./wizard.sh` and `./start.sh`) for easier setup and service management.
- Added detailed usage of convenience scripts for checking service status, restarting, and stopping services.
- Clarified the distinction between convenience scripts and direct command usage for improved user guidance.
* Update speaker recognition models and documentation
- Changed the speaker diarization model from `pyannote/speaker-diarization-3.1` to `pyannote/speaker-diarization-community-1` across multiple files for consistency.
- Updated README files to reflect the new model and its usage instructions, ensuring users have the correct links and information for setup.
- Enhanced clarity in configuration settings related to speaker recognition.
* Docs consolidation (#258)
* Enhance setup documentation and convenience scripts
- Updated the interactive setup wizard instructions to recommend using the convenience script `./wizard.sh` for easier configuration.
- Added detailed instructions for uploading and processing existing audio files via the API, including example commands for single and multiple file uploads.
- Introduced a new section on HAVPE relay configuration for ESP32 audio streaming, providing environment variable setup and command examples.
- Clarified the distributed deployment setup, including GPU and backend separation instructions, and added benefits of using Tailscale for networking.
- Removed outdated `getting-started.md` and `SETUP_SCRIPTS.md` files to streamline documentation and avoid redundancy.
* Update setup instructions and enhance service management scripts
- Replaced direct command instructions with convenience scripts (`./wizard.sh` and `./start.sh`) for easier setup and service management.
- Added detailed usage of convenience scripts for checking service status, restarting, and stopping services.
- Clarified the distinction between convenience scripts and direct command usage for improved user guidance.
* Update speaker recognition models and documentation
- Changed the speaker diarization model from `pyannote/speaker-diarization-3.1` to `pyannote/speaker-diarization-community-1` across multiple files for consistency.
- Updated README files to reflect the new model and its usage instructions, ensuring users have the correct links and information for setup.
- Enhanced clarity in configuration settings related to speaker recognition.
* Enhance transcription provider selection and update HTTPS documentation
- Added a new function in `wizard.py` to prompt users for their preferred transcription provider, allowing options for Deepgram, Parakeet ASR, or none.
- Updated the service setup logic to automatically include ASR services if Parakeet is selected.
- Introduced a new documentation file on SSL certificates and HTTPS setup, detailing the importance of HTTPS for secure connections and microphone access.
- Removed outdated HTTPS setup documentation from `backends/advanced/Docs/HTTPS_SETUP.md` to streamline resources.
* Remove HTTPS setup scripts and related configurations
- Deleted `init-https.sh`, `setup-https.sh`, and `nginx.conf.template` as part of the transition to a new HTTPS setup process.
- Updated `README.md` to reflect the new automatic HTTPS configuration via the setup wizard.
- Adjusted `init.py` to remove references to the deleted HTTPS scripts and ensure proper handling of Caddyfile generation for SSL.
- Streamlined documentation to clarify the new approach for HTTPS setup and configuration management.
* Update quickstart.md (#268)
* v0.2 (#279)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* Enhance chat configuration management and UI integration
- Updated `services.py` to allow service restart with an option to recreate containers, addressing WSL2 bind mount issues.
- Added new chat configuration management functions in `system_controller.py` for loading, saving, and validating chat prompts.
- Introduced `ChatSettings` component in the web UI for admin users to manage chat configurations easily.
- Updated API service methods in `api.ts` to support chat configuration endpoints.
- Integrated chat settings into the system management page for better accessibility.
* Refactor backend shutdown process and enhance chat service configuration logging
- Updated `start.sh` to improve shutdown handling by explicitly killing the backend process if running.
- Modified `chat_service.py` to enhance logging for loading chat system prompts, providing clearer feedback on configuration usage.
- Added a new `chat` field in `model_registry.py` for better chat service configuration management.
- Updated vector store query parameters in `vector_stores.py` for improved clarity and functionality.
- Enhanced the chat component in the web UI to conditionally auto-scroll based on message sending status.
* Implement plugin system for enhanced functionality and configuration management
- Introduced a new plugin architecture to allow for extensibility in the Chronicle application.
- Added Home Assistant plugin for controlling devices via natural language commands triggered by wake words.
- Implemented plugin configuration management endpoints in the API for loading, saving, and validating plugin settings.
- Enhanced the web UI with a dedicated Plugins page for managing plugin configurations.
- Updated Docker Compose files to include Tailscale integration for remote service access.
- Refactored existing services to support plugin interactions during conversation and memory processing.
- Improved error handling and logging for plugin initialization and execution processes.
* Enhance configuration management and plugin system integration
- Updated .gitignore to include plugins.yml for security reasons.
- Modified start.sh to allow passing additional arguments during service startup.
- Refactored wizard.py to support new HF_TOKEN configuration prompts and improved handling of wake words in plugin settings.
- Introduced a new setup_hf_token_if_needed function to streamline Hugging Face token management.
- Enhanced the GitHub Actions workflow to create plugins.yml from a template, ensuring proper configuration setup.
- Added detailed comments and documentation in the plugins.yml.template for better user guidance on Home Assistant integration.
* Implement Redis integration for client-user mapping and enhance wake word processing
- Added asynchronous Redis support in ClientManager for tracking client-user relationships.
- Introduced `initialize_redis_for_client_manager` to set up Redis for cross-container mapping.
- Updated `create_client_state` to use asynchronous tracking for client-user relationships.
- Enhanced wake word processing in PluginRouter with normalization and command extraction.
- Refactored DeepgramStreamingConsumer to utilize async Redis lookups for user ID retrieval.
- Set TTL on Redis streams during client state cleanup for better resource management.
* Refactor Deepgram worker management and enhance text normalization
- Disabled the batch Deepgram worker in favor of the streaming worker to prevent race conditions.
- Updated text normalization in wake word processing to replace punctuation with spaces, preserving word boundaries.
- Enhanced regex pattern for wake word matching to allow optional punctuation and whitespace after the last part.
- Improved logging in DeepgramStreamingConsumer for better visibility of message processing and error handling.
* Add original prompt retrieval and restoration in chat configuration test
- Implemented retrieval of the original chat prompt before saving a custom prompt to ensure test isolation.
- Added restoration of the original prompt after the test to prevent interference with subsequent tests.
- Enhanced the test documentation for clarity on the purpose of these changes.
* Refactor test execution and enhance documentation for integration tests
- Simplified test execution commands in CLAUDE.md and quickstart.md for better usability.
- Added instructions for running tests from the project root and clarified the process for executing the complete Robot Framework test suite.
- Introduced a new Docker service for the Deepgram streaming worker in docker-compose-test.yml to improve testing capabilities.
- Updated system_admin_tests.robot to use a defined default prompt for restoration, enhancing test reliability and clarity.
* Enhance test environment cleanup and improve Deepgram worker management
- Updated `run-test.sh` and `run-robot-tests.sh` to improve cleanup processes, including handling permission issues with Docker.
- Introduced a new function `mark_session_complete` in `session_controller.py` to ensure atomic updates for session completion status.
- Refactored WebSocket and conversation job handling to utilize the new session completion function, enhancing reliability.
- Updated `start-workers.sh` to enable the batch Deepgram worker alongside the streaming worker for improved transcription capabilities.
- Enhanced test scripts to verify the status of Deepgram workers and ensure proper cleanup of test containers.
* Refactor worker management and introduce orchestrator for improved process handling
- Replaced the bash-based `start-workers.sh` script with a Python-based worker orchestrator for better process management and health monitoring.
- Updated `docker-compose.yml` to configure the new orchestrator and adjust worker definitions, including the addition of audio persistence and stream workers.
- Enhanced the Dockerfile to remove the old startup script and ensure the orchestrator is executable.
- Introduced new modules for orchestrator configuration, health monitoring, process management, and worker registry to streamline worker lifecycle management.
- Improved environment variable handling for worker configuration and health checks.
* oops
* oops2
* Remove legacy test runner script and update worker orchestration
- Deleted the `run-test.sh` script, which was used for local test execution.
- Updated Docker configurations to replace the `start-workers.sh` script with `worker_orchestrator.py` for improved worker management.
- Enhanced health monitoring and process management in the orchestrator to ensure better reliability and logging.
- Adjusted deployment configurations to reflect the new orchestrator setup.
* Add bulk restart mechanism for RQ worker registration loss
- Introduced a new method `_handle_registration_loss` to manage RQ worker registration loss, replicating the behavior of the previous bash script.
- Implemented a cooldown period to prevent frequent restarts during network issues.
- Added logging for bulk restart actions and their outcomes to enhance monitoring and debugging capabilities.
- Created a `_restart_all_rq_workers` method to facilitate the bulk restart of RQ workers, ensuring they re-register with Redis upon startup.
* Enhance plugin architecture with event-driven system and test integration
- Introduced a new Test Event Plugin to log all plugin events to an SQLite database for integration testing.
- Updated the plugin system to utilize event subscriptions instead of access levels, allowing for more flexible event handling.
- Refactored the PluginRouter to dispatch events based on subscriptions, improving the event-driven architecture.
- Enhanced Docker configurations to support development and testing environments with appropriate dependencies.
- Added comprehensive integration tests to verify the functionality of the event dispatch system and plugin interactions.
- Updated documentation and test configurations to reflect the new event-based plugin structure.
* Enhance Docker configurations and startup script for test mode
- Updated `docker-compose-test.yml` to include a test command for services, enabling a dedicated test mode.
- Modified `start.sh` to support a `--test` flag, allowing the FastAPI backend to run with test-specific configurations.
- Adjusted worker commands to utilize the `--group test` option in test mode for improved orchestration and management.
* Refactor test scripts for improved reliability and clarity
- Updated `run-robot-tests.sh` to enhance the verification of the Deepgram batch worker process, ensuring non-numeric characters are removed from the check.
- Modified `plugin_tests.robot` to use a more explicit method for checking the length of subscriptions and added a skip condition for unavailable audio files.
- Adjusted `plugin_event_tests.robot` to load the test audio file from a variable, improving test data management.
- Refactored `plugin_keywords.robot` to utilize clearer length checks for subscriptions and event parts, enhancing readability and maintainability.
* remove mistral deadcode; notebooks untouched
* Refactor audio streaming endpoints and improve documentation
- Updated WebSocket endpoints to use a unified format with codec parameters (`/ws?codec=pcm` and `/ws?codec=opus`) for audio streaming, replacing the previous `/ws_pcm` and `/ws_omi` endpoints.
- Enhanced documentation to reflect the new endpoint structure and clarify audio processing capabilities.
- Removed deprecated audio cropping functionality and related configurations to streamline the audio processing workflow.
- Updated various components and scripts to align with the new endpoint structure, ensuring consistent usage across the application.
* Enhance testing infrastructure and API routes for plugin events
- Updated `docker-compose-test.yml` to introduce low speech detection thresholds for testing, improving the accuracy of speech detection during tests.
- Added new test-only API routes in `test_routes.py` for clearing and retrieving plugin events, ensuring a clean state between tests.
- Refactored existing test scripts to utilize the new API endpoints for event management, enhancing test reliability and clarity.
- Improved logging and error handling in various components to facilitate debugging during test execution.
- Adjusted environment variable handling in test setup scripts to streamline configuration and improve flexibility.
* Add audio pipeline architecture documentation and improve audio persistence worker configuration
- Introduced a comprehensive documentation file detailing the audio pipeline architecture, covering data flow, processing stages, and key components.
- Enhanced the audio persistence worker setup by implementing multiple concurrent workers to improve audio processing efficiency.
- Adjusted sleep intervals in the audio streaming persistence job for better responsiveness and event loop yielding.
- Updated test script to run the full suite of integration tests from the specified directory, ensuring thorough testing coverage.
* Add test container setup and teardown scripts
- Introduced `setup-test-containers.sh` for streamlined startup of test containers, including health checks and environment variable loading.
- Added `teardown-test-containers.sh` for simplified container shutdown, with options to remove volumes.
- Enhanced user feedback with color-coded messages for better visibility during test setup and teardown processes.
* Update worker count validation and websocket disconnect tests
- Adjusted worker count expectations in the Worker Count Validation Test to reflect an increase from 7 to 9 workers, accounting for additional audio persistence workers.
- Enhanced the WebSocket Disconnect Conversation End Reason Test by adding steps to maintain audio streaming during disconnection, ensuring accurate simulation of network dropout scenarios.
- Improved comments for clarity and added critical notes regarding inactivity timeout handling.
* Refactor audio storage to MongoDB chunks and enhance cleanup settings management
- Replaced the legacy AudioFile model with AudioChunkDocument for storing audio data in MongoDB, optimizing storage and retrieval.
- Introduced CleanupSettings dataclass for managing soft-deletion configurations, including auto-cleanup and retention days.
- Added admin API routes for retrieving and saving cleanup settings, ensuring better control over data retention policies.
- Updated audio processing workflows to utilize MongoDB chunks, removing dependencies on disk-based audio files.
- Enhanced tests to validate the new audio chunk storage and cleanup functionalities, ensuring robust integration with existing systems.
* Refactor audio processing to utilize MongoDB chunks and enhance job handling
- Removed audio file path parameters from various functions, transitioning to audio data retrieval from MongoDB chunks.
- Updated the `start_post_conversation_jobs` function to reflect changes in audio handling, ensuring jobs reconstruct audio from database chunks.
- Enhanced the `transcribe_full_audio_job` and `recognise_speakers_job` to process audio directly from memory, eliminating the need for temporary files.
- Improved error handling and logging for audio data retrieval, ensuring better feedback during processing.
- Added a new utility function for converting PCM data to WAV format in memory, streamlining audio format handling.
* Refactor speaker recognition client to use in-memory audio data
- Updated methods to accept audio data as bytes instead of file paths, enhancing performance by eliminating disk I/O.
- Improved logging to reflect in-memory audio processing, providing better insights during speaker identification and diarization.
- Streamlined audio data handling in the `diarize_identify_match` and `diarize_and_identify` methods, ensuring consistency across the client.
- Removed temporary file handling, simplifying the audio processing workflow and reducing potential file system errors.
* Add mock providers and update testing workflows for API-independent execution
- Introduced `MockLLMProvider` and `MockTranscriptionProvider` to facilitate testing without external API dependencies, allowing for consistent and controlled test environments.
- Created `run-no-api-tests.sh` script to execute tests that do not require API keys, ensuring separation of API-dependent and independent tests.
- Updated Robot Framework test configurations to utilize mock services, enhancing test reliability and reducing external dependencies.
- Modified existing test workflows to include new configurations and ensure proper handling of results for tests excluding API keys.
- Added `mock-services.yml` configuration to disable external API services while maintaining core functionality for testing purposes.
- Enhanced documentation to reflect the new tagging system for tests requiring API keys, improving clarity on test execution requirements.
* Enhance testing documentation and workflows for API key separation
- Updated CLAUDE.md to clarify test execution modes, emphasizing the separation of tests requiring API keys from those that do not.
- Expanded the testing guidelines in TESTING_GUIDELINES.md to detail the organization of tests based on API dependencies, including tagging conventions and execution paths.
- Improved mock-services.yml to include dummy configurations for LLM and embedding services, ensuring tests can run without actual API calls.
- Added comprehensive documentation on GitHub workflows for different test scenarios, enhancing clarity for contributors and maintainers.
* Update test configurations and documentation for API key management
- Modified `plugins.yml.template` to implement event subscriptions for the Home Assistant plugin, enhancing its event-driven capabilities.
- Revised `README.md` to clarify test execution processes, emphasizing the distinction between tests requiring API keys and those that do not.
- Updated `mock-services.yml` to streamline mock configurations, ensuring compatibility with the new testing workflows.
- Added `requires-api-keys` tags to relevant test cases across various test files, improving organization and clarity regarding API dependencies.
- Enhanced documentation for test scripts and configurations, providing clearer guidance for contributors on executing tests based on API key requirements.
* Add optional service profile to Docker Compose test configuration
* Refactor audio processing and job handling for transcription workflows
- Updated `upload_and_process_audio_files` and `start_post_conversation_jobs` to enqueue transcription jobs separately for file uploads, ensuring accurate processing order.
- Enhanced logging to provide clearer insights into job enqueuing and processing stages.
- Removed batch transcription from the post-conversation job chain for streaming audio, utilizing the streaming transcript directly.
- Introduced word-level timestamps in the `Conversation` model to improve transcript detail and accuracy.
- Updated tests to reflect changes in job handling and ensure proper verification of post-conversation processing.
* Remove unnecessary network aliases from speaker service in Docker Compose configuration
* Add network aliases for speaker service in Docker Compose configuration
* Refactor Conversation model to use string for provider field
- Updated the `Conversation` model to replace the `TranscriptProvider` enum with a string type for the `provider` field, allowing for greater flexibility in provider names.
- Adjusted related job functions to accommodate this change, simplifying provider handling in the transcription workflow.
* Enhance configuration and model handling for waveform data
- Updated Docker Compose files to mount the entire config directory, allowing for better management of configuration files.
- Introduced a new `WaveformData` model to store pre-computed waveform visualization data, improving UI performance by enabling waveform display without real-time decoding.
- Enhanced the `app_factory` and `job` models to include the new `WaveformData` model, ensuring proper initialization and data handling.
- Implemented waveform generation logic in a new worker module, allowing for on-demand waveform creation from audio chunks.
- Added API endpoints for retrieving and generating waveform data, improving the overall audio processing capabilities.
- Updated tests to cover new functionality and ensure robustness in waveform data handling.
* Add SDK testing scripts for authentication, conversation retrieval, and audio upload
- Introduced three new test scripts: `sdk_test_auth.py`, `sdk_test_conversations.py`, and `sdk_test_upload.py`.
- Each script tests different functionalities of the SDK, including authentication, conversation retrieval, and audio file uploads.
- The scripts utilize the `ChronicleClient` to perform operations and print results for verification.
- Enhanced testing capabilities for the SDK, ensuring robust validation of core features.
* Enhance audio processing and conversation handling for large files
- Added configuration options for speaker recognition chunking in `.env.template`, allowing for better management of large audio files.
- Updated `get_conversations` function to include an `include_deleted` parameter for filtering conversations based on their deletion status.
- Enhanced `finalize_session` method in `AudioStreamProducer` to send an end marker to Redis, ensuring proper session closure.
- Introduced `reconstruct_audio_segments` function to yield audio segments with overlap for efficient processing of lengthy conversations.
- Implemented merging of overlapping speaker segments to improve accuracy in speaker recognition.
- Added integration tests for WebSocket streaming transcription to validate the end_marker functionality and overall transcription flow.
* archive
* Implement annotation system and enhance audio processing capabilities
- Introduced a new annotation model to support user edits and AI-powered suggestions for memories and transcripts.
- Added annotation routes for CRUD operations, enabling the creation and management of annotations via the API.
- Enhanced the audio processing workflow to support fetching audio segments from the backend, improving speaker recognition accuracy.
- Updated the speaker recognition client to handle conversation-based audio fetching, allowing for better management of large audio files.
- Implemented a cron job for generating AI suggestions on potential errors in transcripts and memories, improving user experience and content accuracy.
- Enhanced the web UI to support inline editing of transcript segments and memory content, providing a more interactive user experience.
- Updated configuration files to support new features and improve overall system flexibility.
* Implement OmegaConf-based configuration management for backend settings
- Introduced a new configuration loader using OmegaConf for unified management of backend settings.
- Updated existing configuration functions to leverage the new loader, enhancing flexibility and maintainability.
- Added support for environment variable interpolation in configuration files.
- Refactored various components to retrieve settings from the new configuration system, improving consistency across the application.
- Updated requirements to include OmegaConf as a dependency.
- Enhanced documentation and comments for clarity on configuration management.
* Refactor .env.template and remove unused diarization configuration
- Updated the .env.template to clarify its purpose for secret values and streamline setup instructions.
- Removed the deprecated diarization_config.json.template file, as it is no longer needed.
- Added new environment variables for Langfuse and Tailscale integration to enhance observability and remote service access.
* Implement legacy environment variable syntax support in configuration loader
- Added custom OmegaConf resolvers to handle legacy ${VAR:-default} syntax for backward compatibility.
- Introduced a preprocessing function to convert legacy syntax in YAML files to OmegaConf-compatible format.
- Updated the load_config function to utilize the new preprocessing for loading defaults and user configurations.
- Enhanced documentation for clarity on the new legacy syntax handling.
* Add plugins configuration path retrieval and refactor usage
- Introduced a new function `get_plugins_yml_path` to centralize the retrieval of the plugins.yml file path.
- Updated `system_controller.py` and `plugin_service.py` to use the new function for improved maintainability and consistency in accessing the plugins configuration.
- Enhanced code clarity by removing hardcoded paths and utilizing the centralized configuration method.
* Unify plugin terminology and fix memory job dependencies
Plugin terminology: subscriptions→events, trigger→condition
Memory jobs: no longer blocked by disabled speaker recognition
* Update Docker Compose configuration and enhance system routes
- Updated Docker Compose files to mount the entire config directory, consolidating configuration management.
- Refactored the `save_diarization_settings` function to improve clarity and maintainability by renaming it to `save_diarization_settings_controller`.
- Enhanced the System component in the web UI to include configuration diagnostics, providing better visibility into system health and issues.
* circular import
* Refactor testing infrastructure and enhance container management
- Updated the testing documentation to reflect a new Makefile-based approach for running tests and managing containers.
- Introduced new scripts for container management, including starting, stopping, restarting, and cleaning containers while preserving logs.
- Added a cleanup script to handle data ownership and permissions correctly.
- Implemented a logging system that saves container logs automatically before cleanup.
- Enhanced the README with detailed instructions for running tests and managing the test environment.
* Add Email Summarizer Plugin and SMTP Email Service
- Introduced the Email Summarizer Plugin that automatically sends email summaries upon conversation completion.
- Implemented SMTP Email Service for sending emails, supporting HTML and plain text formats with TLS/SSL encryption.
- Added configuration options for SMTP settings in the .env.template and plugins.yml.template.
- Created comprehensive documentation for plugin development and usage, including a new plugin generation script.
- Enhanced testing coverage for the Email Summarizer Plugin and SMTP Email Service to ensure reliability and functionality.
* Refactor plugin management and introduce Email Summarizer setup
- Removed the static PLUGINS dictionary and replaced it with a dynamic discovery mechanism for plugins.
- Implemented a new setup process for plugins, allowing for configuration via individual setup scripts.
- Added the Email Summarizer plugin with a dedicated setup script for SMTP configuration.
- Enhanced the main setup flow to support community plugins and their configuration.
- Cleaned up unused functions related to plugin configuration and streamlined the overall plugin setup process.
* Enhance plugin configuration and documentation
- Updated the .env.template to include new configuration options for the Home Assistant and Email Summarizer plugins, including server URLs, tokens, and additional settings.
- Refactored Docker Compose files to correctly mount plugin configuration paths.
- Introduced comprehensive documentation for plugin configuration architecture, detailing the separation of concerns for orchestration, settings, and secrets.
- Added individual configuration files for the Home Assistant and Email Summarizer plugins, ensuring proper management of non-secret settings and environment variable references.
- Improved the plugin loading process to merge configurations from multiple sources, enhancing flexibility and maintainability.
* Refactor plugin setup process to allow interactive user input
- Updated the plugin setup script to run interactively, enabling plugins to prompt for user input during configuration.
- Removed output capturing to facilitate real-time interaction and improved error messaging to include exit codes for better debugging.
* Add shared setup utilities for interactive configuration
- Introduced `setup_utils.py` containing functions for reading environment variables, prompting user input, and masking sensitive values.
- Refactored existing code in `wizard.py` and `init.py` to utilize these shared utilities, improving code reuse and maintainability.
- Updated documentation to include usage examples for the new utilities in plugin setup scripts, enhancing developer experience and clarity.
* Enhance plugin security architecture and configuration management
- Introduced a three-file separation for plugin configuration to improve security:
- `backends/advanced/.env` for secrets (gitignored)
- `config/plugins.yml` for orchestration with environment variable references
- `plugins/{plugin_id}/config.yml` for non-secret defaults
- Updated documentation to emphasize the importance of using `${ENV_VAR}` syntax for sensitive data and provided examples of correct usage.
- Enhanced the Email Summarizer plugin setup process to automatically update `config/plugins.yml` with environment variable references, ensuring secrets are not hardcoded.
- Added new fields to the User model for notification email management and improved error logging in user-related functions.
- Refactored audio chunk utilities to use a consistent method for fetching conversation metadata.
* Refactor backend components for improved functionality and stability
- Added a new parameter `transcript_version_id` to the `open_conversation_job` function to support streaming transcript versioning.
- Enhanced error handling in `check_enrolled_speakers_job` and `recognise_speakers_job` to allow conversations to proceed even when the speaker service is unavailable, improving resilience.
- Updated `send_to_adv.py` to support dynamic WebSocket and HTTP protocols based on environment settings, enhancing configuration flexibility.
- Introduced a background task in `send_to_adv.py` to handle incoming messages from the backend, ensuring connection stability and logging interim results.
* Refactor plugin setup timing to enhance configuration flow
* Refactor save_diarization_settings_controller to improve validation and error handling
- Updated the controller to filter out invalid settings instead of raising an error for each unknown key, allowing for more flexible input.
- Added a check to reject requests with no valid settings provided, enhancing robustness.
- Adjusted logging to reflect the filtered settings being saved.
* Refactor audio processing and conversation management for improved deduplication and tracking
* Refactor audio and email handling for improved functionality and security
- Updated `mask_value` function to handle whitespace more effectively.
- Enhanced `create_plugin` to remove existing directories when using the `--force` option.
- Changed logging level from error to debug for existing admin user checks.
- Improved client ID generation logging for clarity.
- Removed unused fields from conversation creation.
- Added HTML escaping in email templates to prevent XSS attacks.
- Updated audio file download function to include user ID for better tracking.
- Adjusted WebSocket connection settings to respect SSL verification based on environment variables.
* Refactor audio upload functionality to remove unused parameters
- Removed `auto_generate_client` and `folder` parameters from audio upload functions to streamline the API.
- Updated related function calls and documentation to reflect these changes, enhancing clarity and reducing complexity.
* Refactor Email Summarizer plugin configuration for improved clarity and security
- Removed outdated migration instructions from `plugin-configuration.md` to streamline documentation.
- Enhanced `README.md` to clearly outline the three-file separation for plugin configuration, emphasizing the roles of `.env`, `config.yml`, and `plugins.yml`.
- Updated `setup.py` to reflect changes in orchestration settings, ensuring only relevant configurations are included in `config/plugins.yml`.
- Improved security messaging to highlight the importance of not committing secrets to version control.
* Update API key configuration in config.yml.template to use environment variable syntax for improved flexibility and security. This change standardizes the way API keys are referenced across different models and services. (#273)
Co-authored-by: roshan.john <roshanjohn1460@gmail.com>
* Refactor Redis job queue cleanup process for improved success tracking
- Replaced total job count with separate counters for successful and failed jobs during Redis queue cleanup.
- Enhanced logging to provide detailed feedback on the number of jobs cleared and any failures encountered.
- Improved error handling to ensure job counts are accurately reflected even when exceptions occur.
* fix tests
* Update CI workflows to use 'docker compose' for log retrieval and added container status check
- Replaced 'docker logs' commands with 'docker compose -f docker-compose-test.yml logs' for consistency across workflows.
- Added a check for running containers before saving logs to enhance debugging capabilities.
* test fixes
* FIX StreamingTranscriptionConsumer to support cumulative audio timestamp adjustments
- Added `audio_offset_seconds` to track cumulative audio duration for accurate timestamp adjustments across transcription sessions.
- Updated `store_final_result` method to adjust word and segment timestamps based on cumulative audio offset.
- Improved logging to reflect changes in audio offset after storing results.
- Modified Makefile and documentation to clarify test execution options, including new tags for slow and SDK tests, enhancing test organization and execution clarity.
* Enhance test container setup and improve error messages in integration tests
- Set `COMPOSE_PROJECT_NAME` for test containers to ensure consistent naming.
- Consolidated error messages in the `websocket_transcription_e2e_test.robot` file for clarity, improving readability and debugging.
* Improve WebSocket closing logic and enhance integration test teardown
- Added timeout handling for WebSocket closure in `AudioStreamClient` to prevent hanging and ensure clean disconnection.
- Updated integration tests to log the total chunks sent when closing audio streams, improving clarity on resource management during test teardown.
* Refactor job status handling to align with RQ standards
- Updated job status checks across various modules to use "started" and "finished" instead of "processing" and "completed" for consistency with RQ's naming conventions.
- Adjusted related logging and response messages to reflect the new status terminology.
- Simplified Docker Compose project name handling in test scripts to avoid conflicts and improve clarity in test environment setup.
* Update test configurations and improve audio inactivity handling
- Increased `SPEECH_INACTIVITY_THRESHOLD_SECONDS` to 20 seconds in `docker-compose-test.yml` for better audio duration handling during tests.
- Refactored session handling in `session_controller.py` to clarify client ID usage.
- Updated `conversation_utils.py` to track speech activity using audio timestamps, enhancing accuracy in inactivity detection.
- Simplified test scripts by removing unnecessary `COMPOSE_PROJECT_NAME` references, aligning with the new project naming convention.
- Adjusted integration tests to reflect changes in inactivity timeout and ensure proper handling of audio timestamps.
* Refactor audio processing and enhance error handling
- Updated `worker_orchestrator.py` to use `logger.exception` for improved error logging.
- Changed default MongoDB database name from "friend-lite" to "chronicle" in multiple files for consistency.
- Added a new method `close_stream_without_stop` in `audio_stream_client.py` to handle abrupt WebSocket disconnections.
- Enhanced audio validation in `audio_utils.py` to support automatic resampling of audio data if sample rates do not match.
- Improved logging in various modules to provide clearer insights during audio processing and event dispatching.
* Enhance Docker command handling and configuration management
- Updated `run_compose_command` to support separate build commands for services, including profile management for backend and speaker-recognition services.
- Improved error handling and output streaming during Docker command execution.
- Added `ensure_docker_network` function to verify and create the required Docker network before starting services.
- Refactored configuration files to utilize `oc.env` for environment variable management, ensuring better compatibility and flexibility across different environments.
* Enhance configuration loading to support custom config file paths
- Added support for the CONFIG_FILE environment variable to allow specifying custom configuration files for testing.
- Implemented logic to handle both absolute paths and relative filenames for the configuration file, improving flexibility in configuration management.
* Update test scripts to use TEST_CONFIG_FILE for configuration management
- Replaced CONFIG_FILE with TEST_CONFIG_FILE in both run-no-api-tests.sh and run-robot-tests.sh to standardize configuration file usage.
- Updated paths to point to mock and deepgram-openai configuration files inside the container, improving clarity and consistency in test setups.
* Refactor audio upload response handling and improve error reporting
- Updated `upload_and_process_audio_files` to return appropriate HTTP status codes based on upload results: 400 for all failures, 207 for partial successes, and 200 for complete success.
- Enhanced error messages in the audio upload tests to provide clearer feedback on upload failures, including specific error details for better debugging.
- Adjusted test scripts to ensure consistent handling of conversation IDs in job metadata, improving validation checks for job creation.
* Refactor audio processing and job handling to improve transcription management
- Updated `upload_and_process_audio_files` to check for transcription provider availability before enqueueing jobs, enhancing error handling and logging.
- Modified `start_post_conversation_jobs` to conditionally enqueue memory extraction jobs based on configuration, improving flexibility in job management.
- Enhanced event dispatch job dependencies to only include jobs that were actually enqueued, ensuring accurate job tracking.
- Added `is_transcription_available` function to check transcription provider status, improving modularity and clarity in the transcription workflow.
* Enhance integration tests for plugin events and improve error handling
- Updated integration tests to filter plugin events by conversation ID, ensuring accurate event tracking and reducing noise from fixture events.
- Improved error messages in event verification to include conversation ID context, enhancing clarity during test failures.
- Refactored audio upload handling to check for transcription job creation, allowing for more robust conversation polling and error reporting.
- Added new keyword to verify conversation end reasons, improving test coverage for conversation state validation.
* Enhance speaker recognition testing and audio processing
- Added mock speaker recognition client to facilitate testing without resource-intensive dependencies.
- Updated Docker Compose configurations to include mock speaker client for test environments.
- Refactored audio segment reconstruction to ensure precise clipping based on time boundaries.
- Improved error handling in transcription jobs and speaker recognition workflows to enhance robustness.
- Adjusted integration tests to utilize real-time pacing for audio chunk streaming, improving test accuracy.
* Refactor audio chunk retrieval and enhance logging in audio processing
- Introduced logging for audio chunk requests to improve traceability.
- Replaced manual audio chunk processing with a dedicated `reconstruct_audio_segment` function for better clarity and efficiency.
- Improved error handling during audio reconstruction to provide more informative responses in case of failures.
- Cleaned up imports and removed redundant code related to audio chunk calculations.
* Refactor mock speaker recognition client and improve testing structure
- Replaced direct import of mock client with a structured import from the new testing module.
- Introduced a dedicated `mock_speaker_client.py` to provide a mock implementation for speaker recognition, facilitating testing without heavy dependencies.
- Added an `__init__.py` file in the testing directory to organize testing utilities and mocks.
* Enhance conversation model to include word-level timestamps and improve transcript handling
- Added a new `words` field to the `Conversation` model for storing word-level timestamps.
- Updated methods to handle word data during transcript version creation, ensuring compatibility with speaker recognition.
- Refactored conversation job processing to utilize the new word structure, improving data integrity and access.
- Enhanced speaker recognition job to read words from the new standardized location, ensuring backward compatibility with legacy data.
* Implement speaker reprocessing feature and enhance timeout calculation
- Added a new endpoint to reprocess speaker identification for existing transcripts, creating a new version with re-identified speakers.
- Introduced a method to calculate proportional t…
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* audio upload extension with gdrive credentials
* FIX: API parameters
* UPDATE: tmp files cleanup n code refactored as per review
* REFACTOR: minor refactor as per review
* REFACTOR: minor update as per review
* UPDATE: gdrive sync logic
* REFACTOR: code update as per gdrive and update credential client
* REFACTOR: validation updated - as per review from CR
* UPDATE: code has been refactore for UUID for diffrent audio upload sources
* REFACTOR: updated code as per review
* Update documentation and configuration to reflect the transition from 'friend-backend' to 'chronicle-backend' across various files, including setup instructions, Docker configurations, and service logs.
* Update test script to use docker-compose-test.yml for all test-related operations
* Added standard MIT license
* Fix/cleanup model (#219)
* refactor memory
* add config
* docstring
* more cleanup
* code quality
* code quality
* unused return
* DOTTED GET
* Refactor Docker and CI configurations
- Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process.
- Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services.
- Added new dependencies for Google API clients in `uv.lock` to support upcoming features.
* Update configuration files for model providers and Docker setup
- Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram.
- Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving.
- Updated memory configuration endpoint to accept plain text for YAML input.
* Update transcription job handling to format speaker IDs
- Changed variable name from `speaker_name` to `speaker_id` for clarity.
- Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling.
* Remove loading of backend .env file in test environment setup
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
* Enhance configuration management and setup wizard
- Updated README to reflect the new setup wizard process.
- Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers.
- Improved user feedback during configuration updates, including success messages for configuration file updates.
- Enabled backup of existing `config.yml` before saving changes.
* Enhance HTTPS configuration in setup wizard
- Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates.
- Improved user prompts for server IP/domain input during HTTPS setup.
- Updated default behavior to use existing IP or localhost based on user input.
- Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access.
* Add source parameter to audio file writing in websocket controller
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* fix/broken-tests (#230)
* refactor memory
* add config
* docstring
* more cleanup
* code quality
* code quality
* unused return
* DOTTED GET
* Refactor Docker and CI configurations
- Removed the creation of `memory_config.yaml` from the CI workflow to streamline the process.
- Updated Docker Compose files to mount `config.yml` for model registry and memory settings in both services.
- Added new dependencies for Google API clients in `uv.lock` to support upcoming features.
* Update configuration files for model providers and Docker setup
- Changed LLM, embedding, and STT providers in `config.yml` to OpenAI and Deepgram.
- Removed read-only flag from `config.yml` in Docker Compose files to allow UI configuration saving.
- Updated memory configuration endpoint to accept plain text for YAML input.
* Update transcription job handling to format speaker IDs
- Changed variable name from `speaker_name` to `speaker_id` for clarity.
- Added logic to convert integer speaker IDs from Deepgram to string format for consistent speaker labeling.
* Remove loading of backend .env file in test environment setup
- Eliminated the code that loads the .env file from the backends/advanced directory, simplifying the environment configuration for tests.
* Enhance configuration management and setup wizard
- Updated README to reflect the new setup wizard process.
- Added functionality to load and save `config.yml` in the setup wizard, including default configurations for LLM and memory providers.
- Improved user feedback during configuration updates, including success messages for configuration file updates.
- Enabled backup of existing `config.yml` before saving changes.
* Enhance HTTPS configuration in setup wizard
- Added functionality to check for existing SERVER_IP in the environment file and prompt the user to reuse or enter a new IP for SSL certificates.
- Improved user prompts for server IP/domain input during HTTPS setup.
- Updated default behavior to use existing IP or localhost based on user input.
- Changed RECORD_ONLY_ENROLLED_SPEAKERS setting in the .env template to false for broader access.
* Add source parameter to audio file writing in websocket controller
- Included a new `source` parameter with the value "websocket" in the `_process_batch_audio_complete` function to enhance audio file context tracking.
* Refactor error handling in system controller and update memory config routes
- Replaced ValueError with HTTPException for better error handling in `save_diarization_settings` and `validate_memory_config` functions.
- Introduced a new Pydantic model, `MemoryConfigRequest`, for validating memory configuration requests in the system routes.
- Updated the `validate_memory_config` endpoint to accept the new request model, improving input handling and validation.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* Feat/add obsidian 3 (#233)
* obsidian support
* neo4j comment
* cleanup code
* unused line
* unused line
* Fix MemoryEntry object usage in chat service
* comment
* feat(obsidian): add obsidian memory search integration to chat
* unit test
* use rq
* neo4j service
* typefix
* test fix
* cleanup
* cleanup
* version changes
* profile
* remove unused imports
* Refactor memory configuration validation endpoints
- Removed the deprecated `validate_memory_config_raw` endpoint and replaced it with a new endpoint that accepts plain text for validation.
- Updated the existing `validate_memory_config` endpoint to clarify that it now accepts JSON input.
- Adjusted the API call in the frontend to point to the new validation endpoint.
* Refactor health check model configuration loading
- Updated the health check function to load model configuration from the models registry instead of the root config.
- Improved error handling by logging warnings when model configuration loading fails.
---------
Co-authored-by: 0xrushi <6279035+0xrushi@users.noreply.github.com>
* Update .gitignore to exclude all files in app/ios and app/android directories (#238)
* fix: Copy full source code in speaker-recognition Dockerfile (#243)
Adds COPY src/ src/ step after dependency installation to ensure
all source files are available in the Docker image. This improves
build caching while ensuring complete source code is present.
* Enhance configuration management and add new setup scripts (#235)
* Enhance configuration management and add new setup scripts
- Updated .gitignore to include config.yml and its template.
- Added config.yml.template for default configuration settings.
- Introduced restart.sh script for service management.
- Enhanced services.py to load config.yml and check for Obsidian/Neo4j integration.
- Updated wizard.py to prompt for Obsidian/Neo4j configuration during setup and create config.yml from template if it doesn't exist.
* Refactor transcription providers and enhance configuration management
- Updated Docker Compose files to include the new Neo4j service configuration.
- Added support for Obsidian/Neo4j integration in the setup process.
- Refactored transcription providers to utilize a registry-driven approach for Deepgram and Parakeet.
- Enhanced error handling and logging in transcription processes.
- Improved environment variable management in test scripts to prioritize command-line overrides.
- Removed deprecated Parakeet provider implementation and streamlined audio stream workers.
* Update configuration management and enhance file structure, add test-matrix (#237)
* Update configuration management and enhance file structure
- Refactored configuration file paths to use a dedicated `config/` directory, including updates to `config.yml` and its template.
- Modified service scripts to load the new configuration path for `config.yml`.
- Enhanced `.gitignore` to include the new configuration files and templates.
- Updated documentation to reflect changes in configuration file locations and usage.
- Improved setup scripts to ensure proper creation and management of configuration files.
- Added new test configurations for various provider combinations to streamline testing processes.
* Add test requirements and clean up imports in wizard.py
- Introduced a new `test-requirements.txt` file to manage testing dependencies.
- Removed redundant import of `shutil` in `wizard.py` to improve code clarity.
* Add ConfigManager for unified configuration management
- Introduced a new `config_manager.py` module to handle reading and writing configurations from `config.yml` and `.env` files, ensuring backward compatibility.
- Refactored `ChronicleSetup` in `backends/advanced/init.py` to utilize `ConfigManager` for loading and updating configurations, simplifying the setup process.
- Removed redundant methods for loading and saving `config.yml` directly in `ChronicleSetup`, as these are now managed by `ConfigManager`.
- Enhanced user feedback during configuration updates, including success messages for changes made to configuration files.
* Refactor transcription provider configuration and enhance setup process
- Updated `.env.template` to clarify speech-to-text configuration and removed deprecated options for Mistral.
- Modified `docker-compose.yml` to streamline environment variable management by removing unused Mistral keys.
- Enhanced `ChronicleSetup` in `init.py` to provide clearer user feedback and updated the transcription provider selection process to rely on `config.yml`.
- Improved error handling in the websocket controller to determine the transcription provider from the model registry instead of environment variables.
- Updated health check routes to reflect the new method of retrieving the transcription provider from `config.yml`.
- Adjusted `config.yml.template` to include comments on transcription provider options for better user guidance.
* Enhance ConfigManager with deep merge functionality
- Updated the `update_memory_config` method to perform a deep merge of updates into the memory configuration, ensuring nested dictionaries are merged correctly.
- Added a new `_deep_merge` method to handle recursive merging of dictionaries, improving configuration management capabilities.
* Refactor run-test.sh and enhance memory extraction tests
- Removed deprecated environment variable handling for TRANSCRIPTION_PROVIDER in `run-test.sh`, streamlining the configuration process.
- Introduced a new `run-custom.sh` script for executing Robot tests with custom configurations, improving test flexibility.
- Enhanced memory extraction tests in `audio_keywords.robot` and `memory_keywords.robot` to include detailed assertions and result handling.
- Updated `queue_keywords.robot` to fail fast if a job is in a 'failed' state when expecting 'completed', improving error handling.
- Refactored `test_env.py` to load environment variables with correct precedence, ensuring better configuration management.
* unify tests to robot test, add some more clean up
* Update health check configuration in docker-compose-test.yml (#241)
- Increased the number of retries from 5 to 10 for improved resilience during service readiness checks.
- Extended the start period from 30s to 60s to allow more time for services to initialize before health checks commence.
* Add step to create test configuration file in robot-tests.yml
- Introduced a new step in the GitHub Actions workflow to copy the test configuration file from tests/configs/deepgram-openai.yml to a new config/config.yml.
- Added logging to confirm the creation of the test config file, improving visibility during the test setup process.
* remove cache step since not required
* coderabbit comments
* Refactor ConfigManager error handling for configuration file loading
- Updated the ConfigManager to raise RuntimeError exceptions when the configuration file is not found or is invalid, improving error visibility and user guidance.
- Removed fallback behavior that previously returned the current directory, ensuring users are explicitly informed about missing or invalid configuration files.
* Refactor _find_repo_root method in ConfigManager
- Updated the _find_repo_root method to locate the repository root using the __file__ location instead of searching for config/config.yml, simplifying the logic and improving reliability.
- Removed the previous error handling that raised a RuntimeError if the configuration file was not found, as the new approach assumes config_manager.py is always at the repo root.
* Enhance speaker recognition service integration and error handling (#245)
* Enhance speaker recognition service integration and error handling
- Updated `docker-compose-test.yml` to enable speaker recognition in the test environment and added a new `speaker-service-test` service for testing purposes.
- Refactored `run-test.sh` to improve the execution of Robot Framework tests from the repository root.
- Enhanced error handling in `speaker_recognition_client.py` to return detailed error messages for connection issues.
- Improved error logging in `speaker_jobs.py` to handle and report errors from the speaker recognition service more effectively.
- Updated `Dockerfile` to copy the full source code after dependencies are cached, ensuring all necessary files are included in the image.
* Remove integration tests workflow and enhance robot tests with HF_TOKEN verification
- Deleted the `integration-tests.yml` workflow file to streamline CI processes.
- Updated `robot-tests.yml` to include verification for the new `HF_TOKEN` secret, ensuring all required secrets are checked before running tests.
* Fix key access in system admin tests to use string indexing for speakers data
* Refactor Robot Framework tests and enhance error handling in memory services
- Removed the creation of the test environment file from the GitHub Actions workflow to streamline setup.
- Updated the Robot Framework tests to utilize a unified test script for improved consistency.
- Enhanced error messages in the MemoryService class to provide more context on connection failures for LLM and vector store providers.
- Added critical checks for API key presence in the OpenAIProvider class to ensure valid credentials are provided before proceeding.
- Adjusted various test setup scripts to use a centralized BACKEND_DIR variable for better maintainability and clarity.
* Refactor test container cleanup in run-robot-tests.sh
- Updated the script to dynamically construct container names from docker-compose services, improving maintainability and reducing hardcoded values.
- Enhanced the cleanup process for stuck test containers by utilizing the COMPOSE_PROJECT_NAME variable.
* Enhance run-robot-tests.sh for improved logging and cleanup
- Set absolute paths for consistent directory references to simplify navigation.
- Capture container logs, status, and resource usage for better debugging.
- Refactor cleanup process to utilize dynamic backend directory references, improving maintainability.
- Ensure proper navigation back to the tests directory after operations.
* Add speaker recognition configuration and update test script defaults
- Introduced speaker recognition settings in config.yml.template, allowing for easy enable/disable and service URL configuration.
- Updated run-robot-tests.sh to use a test-specific configuration file that disables speaker recognition for improved CI performance.
- Modified deepgram-openai.yml to disable speaker recognition during CI tests to enhance execution speed.
* Refactor speaker recognition configuration management
- Updated docker-compose-test.yml to clarify speaker recognition settings, now controlled via config.yml for improved CI performance.
- Enhanced model_registry.py to include a dedicated speaker_recognition field for better configuration handling.
- Modified speaker_recognition_client.py to load configuration from config.yml, allowing for dynamic enabling/disabling of the speaker recognition service based on the configuration.
* Add minimum worker count verification to infrastructure tests
- Introduced a new keyword to verify that the minimum number of workers are registered, enhancing the robustness of health checks.
- Updated the worker count validation test to include a wait mechanism for worker registration, improving test reliability.
- Clarified comments regarding expected worker counts to reflect the distinction between RQ and audio stream workers.
* Update configuration management and enhance model handling
- Added OBSIDIAN_ENABLED configuration to ChronicleSetup for improved feature toggling.
- Introduced speaker_recognition configuration handling in model_registry.py to streamline model loading.
- Refactored imports in deepgram.py to improve clarity and reduce redundancy.
* Refactor configuration management in wizard and ChronicleSetup (#246)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* added JWT issuers for audience auth for service interop and shared us… (#250)
* added JWT issuers for audience auth for service interop and shared user accounts
* amended default value in line wioth code
* Feat/edit chat system prompt (#247)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* Enhance chat configuration management and UI integration
- Updated `services.py` to allow service restart with an option to recreate containers, addressing WSL2 bind mount issues.
- Added new chat configuration management functions in `system_controller.py` for loading, saving, and validating chat prompts.
- Introduced `ChatSettings` component in the web UI for admin users to manage chat configurations easily.
- Updated API service methods in `api.ts` to support chat configuration endpoints.
- Integrated chat settings into the system management page for better accessibility.
* Refactor backend shutdown process and enhance chat service configuration logging
- Updated `start.sh` to improve shutdown handling by explicitly killing the backend process if running.
- Modified `chat_service.py` to enhance logging for loading chat system prompts, providing clearer feedback on configuration usage.
- Added a new `chat` field in `model_registry.py` for better chat service configuration management.
- Updated vector store query parameters in `vector_stores.py` for improved clarity and functionality.
- Enhanced the chat component in the web UI to conditionally auto-scroll based on message sending status.
* Return JSONResponse instead of raw result
* Refactor headers creation in system admin tests
* Make config.yml writable for admin updates
* Docs consolidation (#257)
* Enhance setup documentation and convenience scripts
- Updated the interactive setup wizard instructions to recommend using the convenience script `./wizard.sh` for easier configuration.
- Added detailed instructions for uploading and processing existing audio files via the API, including example commands for single and multiple file uploads.
- Introduced a new section on HAVPE relay configuration for ESP32 audio streaming, providing environment variable setup and command examples.
- Clarified the distributed deployment setup, including GPU and backend separation instructions, and added benefits of using Tailscale for networking.
- Removed outdated `getting-started.md` and `SETUP_SCRIPTS.md` files to streamline documentation and avoid redundancy.
* Update setup instructions and enhance service management scripts
- Replaced direct command instructions with convenience scripts (`./wizard.sh` and `./start.sh`) for easier setup and service management.
- Added detailed usage of convenience scripts for checking service status, restarting, and stopping services.
- Clarified the distinction between convenience scripts and direct command usage for improved user guidance.
* Update speaker recognition models and documentation
- Changed the speaker diarization model from `pyannote/speaker-diarization-3.1` to `pyannote/speaker-diarization-community-1` across multiple files for consistency.
- Updated README files to reflect the new model and its usage instructions, ensuring users have the correct links and information for setup.
- Enhanced clarity in configuration settings related to speaker recognition.
* Docs consolidation (#258)
* Enhance setup documentation and convenience scripts
- Updated the interactive setup wizard instructions to recommend using the convenience script `./wizard.sh` for easier configuration.
- Added detailed instructions for uploading and processing existing audio files via the API, including example commands for single and multiple file uploads.
- Introduced a new section on HAVPE relay configuration for ESP32 audio streaming, providing environment variable setup and command examples.
- Clarified the distributed deployment setup, including GPU and backend separation instructions, and added benefits of using Tailscale for networking.
- Removed outdated `getting-started.md` and `SETUP_SCRIPTS.md` files to streamline documentation and avoid redundancy.
* Update setup instructions and enhance service management scripts
- Replaced direct command instructions with convenience scripts (`./wizard.sh` and `./start.sh`) for easier setup and service management.
- Added detailed usage of convenience scripts for checking service status, restarting, and stopping services.
- Clarified the distinction between convenience scripts and direct command usage for improved user guidance.
* Update speaker recognition models and documentation
- Changed the speaker diarization model from `pyannote/speaker-diarization-3.1` to `pyannote/speaker-diarization-community-1` across multiple files for consistency.
- Updated README files to reflect the new model and its usage instructions, ensuring users have the correct links and information for setup.
- Enhanced clarity in configuration settings related to speaker recognition.
* Enhance transcription provider selection and update HTTPS documentation
- Added a new function in `wizard.py` to prompt users for their preferred transcription provider, allowing options for Deepgram, Parakeet ASR, or none.
- Updated the service setup logic to automatically include ASR services if Parakeet is selected.
- Introduced a new documentation file on SSL certificates and HTTPS setup, detailing the importance of HTTPS for secure connections and microphone access.
- Removed outdated HTTPS setup documentation from `backends/advanced/Docs/HTTPS_SETUP.md` to streamline resources.
* Remove HTTPS setup scripts and related configurations
- Deleted `init-https.sh`, `setup-https.sh`, and `nginx.conf.template` as part of the transition to a new HTTPS setup process.
- Updated `README.md` to reflect the new automatic HTTPS configuration via the setup wizard.
- Adjusted `init.py` to remove references to the deleted HTTPS scripts and ensure proper handling of Caddyfile generation for SSL.
- Streamlined documentation to clarify the new approach for HTTPS setup and configuration management.
* Update quickstart.md (#268)
* v0.2 (#279)
* Refactor configuration management in wizard and ChronicleSetup
- Updated wizard.py to read Obsidian/Neo4j configuration from config.yml, enhancing flexibility and error handling.
- Refactored ChronicleSetup to utilize ConfigManager for loading and verifying config.yml, ensuring a single source of truth.
- Improved user feedback for missing configuration files and streamlined the setup process for memory and transcription providers.
* Fix string formatting for error message in ChronicleSetup
* Enhance chat configuration management and UI integration
- Updated `services.py` to allow service restart with an option to recreate containers, addressing WSL2 bind mount issues.
- Added new chat configuration management functions in `system_controller.py` for loading, saving, and validating chat prompts.
- Introduced `ChatSettings` component in the web UI for admin users to manage chat configurations easily.
- Updated API service methods in `api.ts` to support chat configuration endpoints.
- Integrated chat settings into the system management page for better accessibility.
* Refactor backend shutdown process and enhance chat service configuration logging
- Updated `start.sh` to improve shutdown handling by explicitly killing the backend process if running.
- Modified `chat_service.py` to enhance logging for loading chat system prompts, providing clearer feedback on configuration usage.
- Added a new `chat` field in `model_registry.py` for better chat service configuration management.
- Updated vector store query parameters in `vector_stores.py` for improved clarity and functionality.
- Enhanced the chat component in the web UI to conditionally auto-scroll based on message sending status.
* Implement plugin system for enhanced functionality and configuration management
- Introduced a new plugin architecture to allow for extensibility in the Chronicle application.
- Added Home Assistant plugin for controlling devices via natural language commands triggered by wake words.
- Implemented plugin configuration management endpoints in the API for loading, saving, and validating plugin settings.
- Enhanced the web UI with a dedicated Plugins page for managing plugin configurations.
- Updated Docker Compose files to include Tailscale integration for remote service access.
- Refactored existing services to support plugin interactions during conversation and memory processing.
- Improved error handling and logging for plugin initialization and execution processes.
* Enhance configuration management and plugin system integration
- Updated .gitignore to include plugins.yml for security reasons.
- Modified start.sh to allow passing additional arguments during service startup.
- Refactored wizard.py to support new HF_TOKEN configuration prompts and improved handling of wake words in plugin settings.
- Introduced a new setup_hf_token_if_needed function to streamline Hugging Face token management.
- Enhanced the GitHub Actions workflow to create plugins.yml from a template, ensuring proper configuration setup.
- Added detailed comments and documentation in the plugins.yml.template for better user guidance on Home Assistant integration.
* Implement Redis integration for client-user mapping and enhance wake word processing
- Added asynchronous Redis support in ClientManager for tracking client-user relationships.
- Introduced `initialize_redis_for_client_manager` to set up Redis for cross-container mapping.
- Updated `create_client_state` to use asynchronous tracking for client-user relationships.
- Enhanced wake word processing in PluginRouter with normalization and command extraction.
- Refactored DeepgramStreamingConsumer to utilize async Redis lookups for user ID retrieval.
- Set TTL on Redis streams during client state cleanup for better resource management.
* Refactor Deepgram worker management and enhance text normalization
- Disabled the batch Deepgram worker in favor of the streaming worker to prevent race conditions.
- Updated text normalization in wake word processing to replace punctuation with spaces, preserving word boundaries.
- Enhanced regex pattern for wake word matching to allow optional punctuation and whitespace after the last part.
- Improved logging in DeepgramStreamingConsumer for better visibility of message processing and error handling.
* Add original prompt retrieval and restoration in chat configuration test
- Implemented retrieval of the original chat prompt before saving a custom prompt to ensure test isolation.
- Added restoration of the original prompt after the test to prevent interference with subsequent tests.
- Enhanced the test documentation for clarity on the purpose of these changes.
* Refactor test execution and enhance documentation for integration tests
- Simplified test execution commands in CLAUDE.md and quickstart.md for better usability.
- Added instructions for running tests from the project root and clarified the process for executing the complete Robot Framework test suite.
- Introduced a new Docker service for the Deepgram streaming worker in docker-compose-test.yml to improve testing capabilities.
- Updated system_admin_tests.robot to use a defined default prompt for restoration, enhancing test reliability and clarity.
* Enhance test environment cleanup and improve Deepgram worker management
- Updated `run-test.sh` and `run-robot-tests.sh` to improve cleanup processes, including handling permission issues with Docker.
- Introduced a new function `mark_session_complete` in `session_controller.py` to ensure atomic updates for session completion status.
- Refactored WebSocket and conversation job handling to utilize the new session completion function, enhancing reliability.
- Updated `start-workers.sh` to enable the batch Deepgram worker alongside the streaming worker for improved transcription capabilities.
- Enhanced test scripts to verify the status of Deepgram workers and ensure proper cleanup of test containers.
* Refactor worker management and introduce orchestrator for improved process handling
- Replaced the bash-based `start-workers.sh` script with a Python-based worker orchestrator for better process management and health monitoring.
- Updated `docker-compose.yml` to configure the new orchestrator and adjust worker definitions, including the addition of audio persistence and stream workers.
- Enhanced the Dockerfile to remove the old startup script and ensure the orchestrator is executable.
- Introduced new modules for orchestrator configuration, health monitoring, process management, and worker registry to streamline worker lifecycle management.
- Improved environment variable handling for worker configuration and health checks.
* oops
* oops2
* Remove legacy test runner script and update worker orchestration
- Deleted the `run-test.sh` script, which was used for local test execution.
- Updated Docker configurations to replace the `start-workers.sh` script with `worker_orchestrator.py` for improved worker management.
- Enhanced health monitoring and process management in the orchestrator to ensure better reliability and logging.
- Adjusted deployment configurations to reflect the new orchestrator setup.
* Add bulk restart mechanism for RQ worker registration loss
- Introduced a new method `_handle_registration_loss` to manage RQ worker registration loss, replicating the behavior of the previous bash script.
- Implemented a cooldown period to prevent frequent restarts during network issues.
- Added logging for bulk restart actions and their outcomes to enhance monitoring and debugging capabilities.
- Created a `_restart_all_rq_workers` method to facilitate the bulk restart of RQ workers, ensuring they re-register with Redis upon startup.
* Enhance plugin architecture with event-driven system and test integration
- Introduced a new Test Event Plugin to log all plugin events to an SQLite database for integration testing.
- Updated the plugin system to utilize event subscriptions instead of access levels, allowing for more flexible event handling.
- Refactored the PluginRouter to dispatch events based on subscriptions, improving the event-driven architecture.
- Enhanced Docker configurations to support development and testing environments with appropriate dependencies.
- Added comprehensive integration tests to verify the functionality of the event dispatch system and plugin interactions.
- Updated documentation and test configurations to reflect the new event-based plugin structure.
* Enhance Docker configurations and startup script for test mode
- Updated `docker-compose-test.yml` to include a test command for services, enabling a dedicated test mode.
- Modified `start.sh` to support a `--test` flag, allowing the FastAPI backend to run with test-specific configurations.
- Adjusted worker commands to utilize the `--group test` option in test mode for improved orchestration and management.
* Refactor test scripts for improved reliability and clarity
- Updated `run-robot-tests.sh` to enhance the verification of the Deepgram batch worker process, ensuring non-numeric characters are removed from the check.
- Modified `plugin_tests.robot` to use a more explicit method for checking the length of subscriptions and added a skip condition for unavailable audio files.
- Adjusted `plugin_event_tests.robot` to load the test audio file from a variable, improving test data management.
- Refactored `plugin_keywords.robot` to utilize clearer length checks for subscriptions and event parts, enhancing readability and maintainability.
* remove mistral deadcode; notebooks untouched
* Refactor audio streaming endpoints and improve documentation
- Updated WebSocket endpoints to use a unified format with codec parameters (`/ws?codec=pcm` and `/ws?codec=opus`) for audio streaming, replacing the previous `/ws_pcm` and `/ws_omi` endpoints.
- Enhanced documentation to reflect the new endpoint structure and clarify audio processing capabilities.
- Removed deprecated audio cropping functionality and related configurations to streamline the audio processing workflow.
- Updated various components and scripts to align with the new endpoint structure, ensuring consistent usage across the application.
* Enhance testing infrastructure and API routes for plugin events
- Updated `docker-compose-test.yml` to introduce low speech detection thresholds for testing, improving the accuracy of speech detection during tests.
- Added new test-only API routes in `test_routes.py` for clearing and retrieving plugin events, ensuring a clean state between tests.
- Refactored existing test scripts to utilize the new API endpoints for event management, enhancing test reliability and clarity.
- Improved logging and error handling in various components to facilitate debugging during test execution.
- Adjusted environment variable handling in test setup scripts to streamline configuration and improve flexibility.
* Add audio pipeline architecture documentation and improve audio persistence worker configuration
- Introduced a comprehensive documentation file detailing the audio pipeline architecture, covering data flow, processing stages, and key components.
- Enhanced the audio persistence worker setup by implementing multiple concurrent workers to improve audio processing efficiency.
- Adjusted sleep intervals in the audio streaming persistence job for better responsiveness and event loop yielding.
- Updated test script to run the full suite of integration tests from the specified directory, ensuring thorough testing coverage.
* Add test container setup and teardown scripts
- Introduced `setup-test-containers.sh` for streamlined startup of test containers, including health checks and environment variable loading.
- Added `teardown-test-containers.sh` for simplified container shutdown, with options to remove volumes.
- Enhanced user feedback with color-coded messages for better visibility during test setup and teardown processes.
* Update worker count validation and websocket disconnect tests
- Adjusted worker count expectations in the Worker Count Validation Test to reflect an increase from 7 to 9 workers, accounting for additional audio persistence workers.
- Enhanced the WebSocket Disconnect Conversation End Reason Test by adding steps to maintain audio streaming during disconnection, ensuring accurate simulation of network dropout scenarios.
- Improved comments for clarity and added critical notes regarding inactivity timeout handling.
* Refactor audio storage to MongoDB chunks and enhance cleanup settings management
- Replaced the legacy AudioFile model with AudioChunkDocument for storing audio data in MongoDB, optimizing storage and retrieval.
- Introduced CleanupSettings dataclass for managing soft-deletion configurations, including auto-cleanup and retention days.
- Added admin API routes for retrieving and saving cleanup settings, ensuring better control over data retention policies.
- Updated audio processing workflows to utilize MongoDB chunks, removing dependencies on disk-based audio files.
- Enhanced tests to validate the new audio chunk storage and cleanup functionalities, ensuring robust integration with existing systems.
* Refactor audio processing to utilize MongoDB chunks and enhance job handling
- Removed audio file path parameters from various functions, transitioning to audio data retrieval from MongoDB chunks.
- Updated the `start_post_conversation_jobs` function to reflect changes in audio handling, ensuring jobs reconstruct audio from database chunks.
- Enhanced the `transcribe_full_audio_job` and `recognise_speakers_job` to process audio directly from memory, eliminating the need for temporary files.
- Improved error handling and logging for audio data retrieval, ensuring better feedback during processing.
- Added a new utility function for converting PCM data to WAV format in memory, streamlining audio format handling.
* Refactor speaker recognition client to use in-memory audio data
- Updated methods to accept audio data as bytes instead of file paths, enhancing performance by eliminating disk I/O.
- Improved logging to reflect in-memory audio processing, providing better insights during speaker identification and diarization.
- Streamlined audio data handling in the `diarize_identify_match` and `diarize_and_identify` methods, ensuring consistency across the client.
- Removed temporary file handling, simplifying the audio processing workflow and reducing potential file system errors.
* Add mock providers and update testing workflows for API-independent execution
- Introduced `MockLLMProvider` and `MockTranscriptionProvider` to facilitate testing without external API dependencies, allowing for consistent and controlled test environments.
- Created `run-no-api-tests.sh` script to execute tests that do not require API keys, ensuring separation of API-dependent and independent tests.
- Updated Robot Framework test configurations to utilize mock services, enhancing test reliability and reducing external dependencies.
- Modified existing test workflows to include new configurations and ensure proper handling of results for tests excluding API keys.
- Added `mock-services.yml` configuration to disable external API services while maintaining core functionality for testing purposes.
- Enhanced documentation to reflect the new tagging system for tests requiring API keys, improving clarity on test execution requirements.
* Enhance testing documentation and workflows for API key separation
- Updated CLAUDE.md to clarify test execution modes, emphasizing the separation of tests requiring API keys from those that do not.
- Expanded the testing guidelines in TESTING_GUIDELINES.md to detail the organization of tests based on API dependencies, including tagging conventions and execution paths.
- Improved mock-services.yml to include dummy configurations for LLM and embedding services, ensuring tests can run without actual API calls.
- Added comprehensive documentation on GitHub workflows for different test scenarios, enhancing clarity for contributors and maintainers.
* Update test configurations and documentation for API key management
- Modified `plugins.yml.template` to implement event subscriptions for the Home Assistant plugin, enhancing its event-driven capabilities.
- Revised `README.md` to clarify test execution processes, emphasizing the distinction between tests requiring API keys and those that do not.
- Updated `mock-services.yml` to streamline mock configurations, ensuring compatibility with the new testing workflows.
- Added `requires-api-keys` tags to relevant test cases across various test files, improving organization and clarity regarding API dependencies.
- Enhanced documentation for test scripts and configurations, providing clearer guidance for contributors on executing tests based on API key requirements.
* Add optional service profile to Docker Compose test configuration
* Refactor audio processing and job handling for transcription workflows
- Updated `upload_and_process_audio_files` and `start_post_conversation_jobs` to enqueue transcription jobs separately for file uploads, ensuring accurate processing order.
- Enhanced logging to provide clearer insights into job enqueuing and processing stages.
- Removed batch transcription from the post-conversation job chain for streaming audio, utilizing the streaming transcript directly.
- Introduced word-level timestamps in the `Conversation` model to improve transcript detail and accuracy.
- Updated tests to reflect changes in job handling and ensure proper verification of post-conversation processing.
* Remove unnecessary network aliases from speaker service in Docker Compose configuration
* Add network aliases for speaker service in Docker Compose configuration
* Refactor Conversation model to use string for provider field
- Updated the `Conversation` model to replace the `TranscriptProvider` enum with a string type for the `provider` field, allowing for greater flexibility in provider names.
- Adjusted related job functions to accommodate this change, simplifying provider handling in the transcription workflow.
* Enhance configuration and model handling for waveform data
- Updated Docker Compose files to mount the entire config directory, allowing for better management of configuration files.
- Introduced a new `WaveformData` model to store pre-computed waveform visualization data, improving UI performance by enabling waveform display without real-time decoding.
- Enhanced the `app_factory` and `job` models to include the new `WaveformData` model, ensuring proper initialization and data handling.
- Implemented waveform generation logic in a new worker module, allowing for on-demand waveform creation from audio chunks.
- Added API endpoints for retrieving and generating waveform data, improving the overall audio processing capabilities.
- Updated tests to cover new functionality and ensure robustness in waveform data handling.
* Add SDK testing scripts for authentication, conversation retrieval, and audio upload
- Introduced three new test scripts: `sdk_test_auth.py`, `sdk_test_conversations.py`, and `sdk_test_upload.py`.
- Each script tests different functionalities of the SDK, including authentication, conversation retrieval, and audio file uploads.
- The scripts utilize the `ChronicleClient` to perform operations and print results for verification.
- Enhanced testing capabilities for the SDK, ensuring robust validation of core features.
* Enhance audio processing and conversation handling for large files
- Added configuration options for speaker recognition chunking in `.env.template`, allowing for better management of large audio files.
- Updated `get_conversations` function to include an `include_deleted` parameter for filtering conversations based on their deletion status.
- Enhanced `finalize_session` method in `AudioStreamProducer` to send an end marker to Redis, ensuring proper session closure.
- Introduced `reconstruct_audio_segments` function to yield audio segments with overlap for efficient processing of lengthy conversations.
- Implemented merging of overlapping speaker segments to improve accuracy in speaker recognition.
- Added integration tests for WebSocket streaming transcription to validate the end_marker functionality and overall transcription flow.
* archive
* Implement annotation system and enhance audio processing capabilities
- Introduced a new annotation model to support user edits and AI-powered suggestions for memories and transcripts.
- Added annotation routes for CRUD operations, enabling the creation and management of annotations via the API.
- Enhanced the audio processing workflow to support fetching audio segments from the backend, improving speaker recognition accuracy.
- Updated the speaker recognition client to handle conversation-based audio fetching, allowing for better management of large audio files.
- Implemented a cron job for generating AI suggestions on potential errors in transcripts and memories, improving user experience and content accuracy.
- Enhanced the web UI to support inline editing of transcript segments and memory content, providing a more interactive user experience.
- Updated configuration files to support new features and improve overall system flexibility.
* Implement OmegaConf-based configuration management for backend settings
- Introduced a new configuration loader using OmegaConf for unified management of backend settings.
- Updated existing configuration functions to leverage the new loader, enhancing flexibility and maintainability.
- Added support for environment variable interpolation in configuration files.
- Refactored various components to retrieve settings from the new configuration system, improving consistency across the application.
- Updated requirements to include OmegaConf as a dependency.
- Enhanced documentation and comments for clarity on configuration management.
* Refactor .env.template and remove unused diarization configuration
- Updated the .env.template to clarify its purpose for secret values and streamline setup instructions.
- Removed the deprecated diarization_config.json.template file, as it is no longer needed.
- Added new environment variables for Langfuse and Tailscale integration to enhance observability and remote service access.
* Implement legacy environment variable syntax support in configuration loader
- Added custom OmegaConf resolvers to handle legacy ${VAR:-default} syntax for backward compatibility.
- Introduced a preprocessing function to convert legacy syntax in YAML files to OmegaConf-compatible format.
- Updated the load_config function to utilize the new preprocessing for loading defaults and user configurations.
- Enhanced documentation for clarity on the new legacy syntax handling.
* Add plugins configuration path retrieval and refactor usage
- Introduced a new function `get_plugins_yml_path` to centralize the retrieval of the plugins.yml file path.
- Updated `system_controller.py` and `plugin_service.py` to use the new function for improved maintainability and consistency in accessing the plugins configuration.
- Enhanced code clarity by removing hardcoded paths and utilizing the centralized configuration method.
* Unify plugin terminology and fix memory job dependencies
Plugin terminology: subscriptions→events, trigger→condition
Memory jobs: no longer blocked by disabled speaker recognition
* Update Docker Compose configuration and enhance system routes
- Updated Docker Compose files to mount the entire config directory, consolidating configuration management.
- Refactored the `save_diarization_settings` function to improve clarity and maintainability by renaming it to `save_diarization_settings_controller`.
- Enhanced the System component in the web UI to include configuration diagnostics, providing better visibility into system health and issues.
* circular import
* Refactor testing infrastructure and enhance container management
- Updated the testing documentation to reflect a new Makefile-based approach for running tests and managing containers.
- Introduced new scripts for container management, including starting, stopping, restarting, and cleaning containers while preserving logs.
- Added a cleanup script to handle data ownership and permissions correctly.
- Implemented a logging system that saves container logs automatically before cleanup.
- Enhanced the README with detailed instructions for running tests and managing the test environment.
* Add Email Summarizer Plugin and SMTP Email Service
- Introduced the Email Summarizer Plugin that automatically sends email summaries upon conversation completion.
- Implemented SMTP Email Service for sending emails, supporting HTML and plain text formats with TLS/SSL encryption.
- Added configuration options for SMTP settings in the .env.template and plugins.yml.template.
- Created comprehensive documentation for plugin development and usage, including a new plugin generation script.
- Enhanced testing coverage for the Email Summarizer Plugin and SMTP Email Service to ensure reliability and functionality.
* Refactor plugin management and introduce Email Summarizer setup
- Removed the static PLUGINS dictionary and replaced it with a dynamic discovery mechanism for plugins.
- Implemented a new setup process for plugins, allowing for configuration via individual setup scripts.
- Added the Email Summarizer plugin with a dedicated setup script for SMTP configuration.
- Enhanced the main setup flow to support community plugins and their configuration.
- Cleaned up unused functions related to plugin configuration and streamlined the overall plugin setup process.
* Enhance plugin configuration and documentation
- Updated the .env.template to include new configuration options for the Home Assistant and Email Summarizer plugins, including server URLs, tokens, and additional settings.
- Refactored Docker Compose files to correctly mount plugin configuration paths.
- Introduced comprehensive documentation for plugin configuration architecture, detailing the separation of concerns for orchestration, settings, and secrets.
- Added individual configuration files for the Home Assistant and Email Summarizer plugins, ensuring proper management of non-secret settings and environment variable references.
- Improved the plugin loading process to merge configurations from multiple sources, enhancing flexibility and maintainability.
* Refactor plugin setup process to allow interactive user input
- Updated the plugin setup script to run interactively, enabling plugins to prompt for user input during configuration.
- Removed output capturing to facilitate real-time interaction and improved error messaging to include exit codes for better debugging.
* Add shared setup utilities for interactive configuration
- Introduced `setup_utils.py` containing functions for reading environment variables, prompting user input, and masking sensitive values.
- Refactored existing code in `wizard.py` and `init.py` to utilize these shared utilities, improving code reuse and maintainability.
- Updated documentation to include usage examples for the new utilities in plugin setup scripts, enhancing developer experience and clarity.
* Enhance plugin security architecture and configuration management
- Introduced a three-file separation for plugin configuration to improve security:
- `backends/advanced/.env` for secrets (gitignored)
- `config/plugins.yml` for orchestration with environment variable references
- `plugins/{plugin_id}/config.yml` for non-secret defaults
- Updated documentation to emphasize the importance of using `${ENV_VAR}` syntax for sensitive data and provided examples of correct usage.
- Enhanced the Email Summarizer plugin setup process to automatically update `config/plugins.yml` with environment variable references, ensuring secrets are not hardcoded.
- Added new fields to the User model for notification email management and improved error logging in user-related functions.
- Refactored audio chunk utilities to use a consistent method for fetching conversation metadata.
* Refactor backend components for improved functionality and stability
- Added a new parameter `transcript_version_id` to the `open_conversation_job` function to support streaming transcript versioning.
- Enhanced error handling in `check_enrolled_speakers_job` and `recognise_speakers_job` to allow conversations to proceed even when the speaker service is unavailable, improving resilience.
- Updated `send_to_adv.py` to support dynamic WebSocket and HTTP protocols based on environment settings, enhancing configuration flexibility.
- Introduced a background task in `send_to_adv.py` to handle incoming messages from the backend, ensuring connection stability and logging interim results.
* Refactor plugin setup timing to enhance configuration flow
* Refactor save_diarization_settings_controller to improve validation and error handling
- Updated the controller to filter out invalid settings instead of raising an error for each unknown key, allowing for more flexible input.
- Added a check to reject requests with no valid settings provided, enhancing robustness.
- Adjusted logging to reflect the filtered settings being saved.
* Refactor audio processing and conversation management for improved deduplication and tracking
* Refactor audio and email handling for improved functionality and security
- Updated `mask_value` function to handle whitespace more effectively.
- Enhanced `create_plugin` to remove existing directories when using the `--force` option.
- Changed logging level from error to debug for existing admin user checks.
- Improved client ID generation logging for clarity.
- Removed unused fields from conversation creation.
- Added HTML escaping in email templates to prevent XSS attacks.
- Updated audio file download function to include user ID for better tracking.
- Adjusted WebSocket connection settings to respect SSL verification based on environment variables.
* Refactor audio upload functionality to remove unused parameters
- Removed `auto_generate_client` and `folder` parameters from audio upload functions to streamline the API.
- Updated related function calls and documentation to reflect these changes, enhancing clarity and reducing complexity.
* Refactor Email Summarizer plugin configuration for improved clarity and security
- Removed outdated migration instructions from `plugin-configuration.md` to streamline documentation.
- Enhanced `README.md` to clearly outline the three-file separation for plugin configuration, emphasizing the roles of `.env`, `config.yml`, and `plugins.yml`.
- Updated `setup.py` to reflect changes in orchestration settings, ensuring only relevant configurations are included in `config/plugins.yml`.
- Improved security messaging to highlight the importance of not committing secrets to version control.
* Update API key configuration in config.yml.template to use environment variable syntax for improved flexibility and security. This change standardizes the way API keys are referenced across different models and services. (#273)
Co-authored-by: roshan.john <roshanjohn1460@gmail.com>
* Refactor Redis job queue cleanup process for improved success tracking
- Replaced total job count with separate counters for successful and failed jobs during Redis queue cleanup.
- Enhanced logging to provide detailed feedback on the number of jobs cleared and any failures encountered.
- Improved error handling to ensure job counts are accurately reflected even when exceptions occur.
* fix tests
* Update CI workflows to use 'docker compose' for log retrieval and added container status check
- Replaced 'docker logs' commands with 'docker compose -f docker-compose-test.yml logs' for consistency across workflows.
- Added a check for running containers before saving logs to enhance debugging capabilities.
* test fixes
* FIX StreamingTranscriptionConsumer to support cumulative audio timestamp adjustments
- Added `audio_offset_seconds` to track cumulative audio duration for accurate timestamp adjustments across transcription sessions.
- Updated `store_final_result` method to adjust word and segment timestamps based on cumulative audio offset.
- Improved logging to reflect changes in audio offset after storing results.
- Modified Makefile and documentation to clarify test execution options, including new tags for slow and SDK tests, enhancing test organization and execution clarity.
* Enhance test container setup and improve error messages in integration tests
- Set `COMPOSE_PROJECT_NAME` for test containers to ensure consistent naming.
- Consolidated error messages in the `websocket_transcription_e2e_test.robot` file for clarity, improving readability and debugging.
* Improve WebSocket closing logic and enhance integration test teardown
- Added timeout handling for WebSocket closure in `AudioStreamClient` to prevent hanging and ensure clean disconnection.
- Updated integration tests to log the total chunks sent when closing audio streams, improving clarity on resource management during test teardown.
* Refactor job status handling to align with RQ standards
- Updated job status checks across various modules to use "started" and "finished" instead of "processing" and "completed" for consistency with RQ's naming conventions.
- Adjusted related logging and response messages to reflect the new status terminology.
- Simplified Docker Compose project name handling in test scripts to avoid conflicts and improve clarity in test environment setup.
* Update test configurations and improve audio inactivity handling
- Increased `SPEECH_INACTIVITY_THRESHOLD_SECONDS` to 20 seconds in `docker-compose-test.yml` for better audio duration handling during tests.
- Refactored session handling in `session_controller.py` to clarify client ID usage.
- Updated `conversation_utils.py` to track speech activity using audio timestamps, enhancing accuracy in inactivity detection.
- Simplified test scripts by removing unnecessary `COMPOSE_PROJECT_NAME` references, aligning with the new project naming convention.
- Adjusted integration tests to reflect changes in inactivity timeout and ensure proper handling of audio timestamps.
* Refactor audio processing and enhance error handling
- Updated `worker_orchestrator.py` to use `logger.exception` for improved error logging.
- Changed default MongoDB database name from "friend-lite" to "chronicle" in multiple files for consistency.
- Added a new method `close_stream_without_stop` in `audio_stream_client.py` to handle abrupt WebSocket disconnections.
- Enhanced audio validation in `audio_utils.py` to support automatic resampling of audio data if sample rates do not match.
- Improved logging in various modules to provide clearer insights during audio processing and event dispatching.
* Enhance Docker command handling and configuration management
- Updated `run_compose_command` to support separate build commands for services, including profile management for backend and speaker-recognition services.
- Improved error handling and output streaming during Docker command execution.
- Added `ensure_docker_network` function to verify and create the required Docker network before starting services.
- Refactored configuration files to utilize `oc.env` for environment variable management, ensuring better compatibility and flexibility across different environments.
* Enhance configuration loading to support custom config file paths
- Added support for the CONFIG_FILE environment variable to allow specifying custom configuration files for testing.
- Implemented logic to handle both absolute paths and relative filenames for the configuration file, improving flexibility in configuration management.
* Update test scripts to use TEST_CONFIG_FILE for configuration management
- Replaced CONFIG_FILE with TEST_CONFIG_FILE in both run-no-api-tests.sh and run-robot-tests.sh to standardize configuration file usage.
- Updated paths to point to mock and deepgram-openai configuration files inside the container, improving clarity and consistency in test setups.
* Refactor audio upload response handling and improve error reporting
- Updated `upload_and_process_audio_files` to return appropriate HTTP status codes based on upload results: 400 for all failures, 207 for partial successes, and 200 for complete success.
- Enhanced error messages in the audio upload tests to provide clearer feedback on upload failures, including specific error details for better debugging.
- Adjusted test scripts to ensure consistent handling of conversation IDs in job metadata, improving validation checks for job creation.
* Refactor audio processing and job handling to improve transcription management
- Updated `upload_and_process_audio_files` to check for transcription provider availability before enqueueing jobs, enhancing error handling and logging.
- Modified `start_post_conversation_jobs` to conditionally enqueue memory extraction jobs based on configuration, improving flexibility in job management.
- Enhanced event dispatch job dependencies to only include jobs that were actually enqueued, ensuring accurate job tracking.
- Added `is_transcription_available` function to check transcription provider status, improving modularity and clarity in the transcription workflow.
* Enhance integration tests for plugin events and improve error handling
- Updated integration tests to filter plugin events by conversation ID, ensuring accurate event tracking and reducing noise from fixture events.
- Improved error messages in event verification to include conversation ID context, enhancing clarity during test failures.
- Refactored audio upload handling to check for transcription job creation, allowing for more robust conversation polling and error reporting.
- Added new keyword to verify conversation end reasons, improving test coverage for conversation state validation.
* Enhance speaker recognition testing and audio processing
- Added mock speaker recognition client to facilitate testing without resource-intensive dependencies.
- Updated Docker Compose configurations to include mock speaker client for test environments.
- Refactored audio segment reconstruction to ensure precise clipping based on time boundaries.
- Improved error handling in transcription jobs and speaker recognition workflows to enhance robustness.
- Adjusted integration tests to utilize real-time pacing for audio chunk streaming, improving test accuracy.
* Refactor audio chunk retrieval and enhance logging in audio processing
- Introduced logging for audio chunk requests to improve traceability.
- Replaced manual audio chunk processing with a dedicated `reconstruct_audio_segment` function for better clarity and efficiency.
- Improved error handling during audio reconstruction to provide more informative responses in case of failures.
- Cleaned up imports and removed redundant code related to audio chunk calculations.
* Refactor mock speaker recognition client and improve testing structure
- Replaced direct import of mock client with a structured import from the new testing module.
- Introduced a dedicated `mock_speaker_client.py` to provide a mock implementation for speaker recognition, facilitating testing without heavy dependencies.
- Added an `__init__.py` file in the testing directory to organize testing utilities and mocks.
* Enhance conversation model to include word-level timestamps and improve transcript handling
- Added a new `words` field to the `Conversation` model for storing word-level timestamps.
- Updated methods to handle word data during transcript version creation, ensuring compatibility with speaker recognition.
- Refactored conversation job processing to utilize the new word structure, improving data integrity and access.
- Enhanced speaker recognition job to read words from the new standardized location, ensuring backward compatibility with legacy data.
* Implement speaker reprocessing feature and enhance timeout calculation
- Added a new endpoint to reprocess speaker identification for existing transcripts, creating a new version with re-identified speakers.
- Introduced a method…
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