- Increase chunk_top_k from 10 to 20
- Reduce max_entity_tokens to 6000
- Reduce max_relation_tokens to 8000
- Update web UI default values
- Fix max_total_tokens to 30000
- Remove file_path and created_at fields from entity and relationship contexts
- Update token truncation to include full JSON serialization instead of content only
- Reset documents with PROCESSING/FAILED status to PENDING when they pass consistency checks
- Update doc_status storage and clear error messages/metadata on reset
• Replace pyuca with centralized utils function
• Add pinyin sort keys for file paths
• Update MongoDB indexes with zh collation
• Migrate existing indexes for compatibility
• Support Chinese chars in Redis/JSON storage
• Keep PostgreSQL sorting order controled by Database Collate order
- 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.
• Track chunk sources (E/R/C types)
• Log frequency and order metadata
• Preserve chunk_id through processing
• Add debug logging for chunk tracking
• Handle rerank and truncation operations
This ensures data consistency validation is part of the main processing pipeline and provides better monitoring of inconsistent document cleanup operations.
- Add _validate_and_fix_document_consistency() method to detect and fix documents with missing content in full_docs storage
- Integrate consistency check into apipeline_process_enqueue_documents() to automatically mark inconsistent documents as FAILED before processing
- Prevent processing errors caused by documents having status records but missing actual content data
