- Store file_path in full_docs storage
- Update PostgreSQL implementation by map file_path to doc_name
- Other storage implementation automatically handles the new field
- Add new aquery_llm/query_llm methods providing structured responses
- Consolidate /query and /query/stream endpoints to use unified aquery_llm
- Optimize cache handling by moving cache checks before LLM calls
- Implement custom metadata insertion as node properties during file upload.
- Add basic metadata filtering functionality to query API
--NOTE: While the base.py file has been modified, the base implementation is incomplete and untested. Only Neo4j database has been properly implemented and tested.
WIP: Query API is temporarily mocked for debugging. Full implementation with complex AND/OR filtering capabilities is in development.
# Conflicts:
# lightrag/base.py
# lightrag/lightrag.py
# lightrag/operate.py
• Add include_references param to QueryRequest
• Extend QueryResponse with references field
• Create unified QueryResult data structures
• Refactor kg_query and naive_query functions
• Update streaming to send references first
- Add enable_cot parameter to all LLM APIs
- Implement CoT for OpenAI with <think> tags
- Log warnings for unsupported providers
- Enable CoT in query operations
- Handle streaming and non-streaming CoT
- Read config from selected_rerank_func when env var missing
- Make api_key optional for rerank function
- Add response format validation with proper error handling
- Update Cohere rerank default to official API endpoint
- Reset documents with PROCESSING/FAILED status to PENDING when they pass consistency checks
- Update doc_status storage and clear error messages/metadata on reset
- Add apipeline_enqueue_error_documents function to LightRAG class for recording file processing errors in doc_status storage
- Enhance pipeline_enqueue_file with detailed error handling for all file processing stages:
* File access errors (permissions, not found)
* UTF-8 encoding errors
* Format-specific processing errors (PDF, DOCX, PPTX, XLSX)
* Content validation errors
* Unsupported file type errors
This implementation ensures all file extraction failures are properly tracked and recorded in the doc_status storage system, providing better visibility into document processing issues and enabling improved error monitoring and debugging capabilities.
