BREAKING CHANGE: The `content` field in query response references is now
an array of strings instead of a concatenated string. This preserves
individual chunk boundaries when a single file has multiple chunks.
Changes:
- Update QueryResponse Pydantic model to accept List[str] for content
- Modify query_text endpoint to return content as list (query_routes.py:425)
- Modify query_text_stream endpoint to support chunk content enrichment
- Update OpenAPI schema and examples to reflect array structure
- Update API README with breaking change notice and migration guide
- Fix RAGAS evaluation to flatten chunk content lists
Added comprehensive documentation for the new include_chunk_content parameter
that enables retrieval of actual chunk text content in API responses.
Documentation Updates:
- Added "Include Chunk Content in References" section to API README
- Explained use cases: RAG evaluation, debugging, citations, transparency
- Provided JSON request/response examples
- Clarified parameter interaction with include_references
OpenAPI/Swagger Examples:
- Added "Response with chunk content" example to /query endpoint
- Shows complete reference structure with content field
- Demonstrates realistic chunk text content
This makes the feature discoverable through:
1. API documentation (README.md)
2. Interactive Swagger UI (http://localhost:9621/docs)
3. Code examples for developers
**Critical Fix: Contexts vs Ground Truth**
- RAGAS metrics now evaluate actual retrieval performance
- Previously: Used ground_truth as contexts (always perfect scores)
- Now: Uses retrieved documents from LightRAG API (real evaluation)
**Changes to generate_rag_response (lines 100-156)**:
- Remove unused 'context' parameter
- Change return type: Dict[str, str] → Dict[str, Any]
- Extract contexts as list of strings from references[].text
- Return 'contexts' key instead of 'context' (JSON dump)
- Add response.raise_for_status() for better error handling
- Add httpx.HTTPStatusError exception handler
**Changes to evaluate_responses (lines 180-191)**:
- Line 183: Extract retrieved_contexts from rag_response
- Line 190: Use [retrieved_contexts] instead of [[ground_truth]]
- Now correctly evaluates: retrieval quality, not ground_truth quality
**Impact on RAGAS Metrics**:
- Context Precision: Now ranks actual retrieved docs by relevance
- Context Recall: Compares ground_truth against actual retrieval
- Faithfulness: Verifies answer based on actual retrieved contexts
- Answer Relevance: Unchanged (question-answer relevance)
Fixes incorrect evaluation methodology. Based on RAGAS documentation:
- contexts = retrieved documents from RAG system
- ground_truth = reference answer for context_recall metric
References:
- https://docs.ragas.io/en/stable/concepts/components/eval_dataset/
- https://docs.ragas.io/en/stable/concepts/metrics/
**Lint Fixes (ruff)**:
- Sort imports alphabetically (I001)
- Add blank line after import traceback (E302)
- Add trailing comma to dict literals (COM812)
- Reformat writer.writerow for readability (E501)
**Rename test_dataset.json → sample_dataset.json**:
- Avoids .gitignore pattern conflict (test_* is ignored)
- More descriptive name - it's a sample/template, not actual test data
- Updated all references in eval_rag_quality.py and README.md
Resolves lint-and-format CI check failure.
Addresses reviewer feedback about test dataset naming.
- Rename _build_llm_context to _build_context_str
- Change text_units_context to chunks_context
- Move string building before early return
- Update log messages and comments
- Consistent variable naming throughout
- Return bool from check_frontend_build()
- Add ⚠️ symbol to outdated versions
- Show tooltip with rebuild message
- Add translations for warning text
- Fix tailwind config filename typo
• Monitor pipeline busy->idle transitions
• Reload labels on dropdown open if needed
• Add onBeforeOpen callback to AsyncSelect
• Clear refresh flags after processing
• Improve label sync with backend state
