• 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
• 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
- Add env switch to toggle weighted polling vs vector-similarity strategy
- Implement similarity-based sorting with fallback to weighted
- Introduce batch vector read API for vector storage
- Implement vector store and retrive funtion for Nanovector DB
- Preserve default behavior (weighted polling selection method)
- Add missing query parameters (top_k, enable_rerank, max_tokens, etc.) to cache key generation in kg_query, naive_query, and extract_keywords_only functions
- Add queryparam field to CacheData structure and PostgreSQL storage for debugging
- Update PostgreSQL schema with automatic migration for queryparam JSONB column
- Prevent incorrect cache hits between queries with different parameters
Fixes issue where different query parameters incorrectly shared the same cached results.
- Delete quantize_embedding function
- Delete dequantize_embedding function
- Remove embedding fields from CacheData
- Update save_to_cache to exclude embedding data
- Clean up unused quantization-related code
Replace regex-based JSON extraction with json-repair for better handling of malformed LLM responses. Remove deprecated JSON parsing utilities and clean up keyword_extraction parameter across LLM providers.
- Remove locate_json_string_body_from_string() and convert_response_to_json()
- Use json-repair.loads() in extract_keywords_only() for robust parsing
- Clean up LLM interfaces and remove unused parameters
- Add json-repair dependency
This parameter is no longer used. Its removal simplifies the API and clarifies that token length management is handled by upstream text chunking logic rather than the embedding wrapper.
Refactored the LLM cache to a flat Key-Value (KV) structure, replacing the previous nested format. The old structure used the 'mode' as a key and stored specific cache content as JSON nested under it. This change significantly enhances cache recall efficiency.
- Merges 'mix' mode query handling into 'hybrid' mode, simplifying query logic by removing the dedicated `mix_kg_vector_query` function
- Standardizes vector search result by using JSON string format to build context
- Fixes a bug in `query_with_keywords` ensuring `hl_keywords` and `ll_keywords` are correctly passed to `kg_query_with_keywords`
This commit introduces `lightrag/constants.py` to centralize default values for various configurations across the API and core components.
Key changes:
- Added `constants.py` to centralize default values
- Improved the `get_env_value` function in `api/config.py` to correctly handle string "None" as a None value and to catch `TypeError` during value conversion.
- Updated the default `SUMMARY_LANGUAGE` to "English"
- Set default `WORKERS` to 2
