- Add entity_chunks & relation_chunks storage
- Implement KEEP/FIFO limit strategies
- Update env.example with new settings
- Add migration for chunk tracking data
- Support all KV storage
- Add get_doc_by_file_path to all storages
- Skip processed files in scan operation
- Check duplicates in upload endpoints
- Check duplicates in text insert APIs
- Return status info in duplicate responses
• Add workspace attribute to storage classes
• Use workspace-specific index names
• Implement Atlas Search with fallbacks
• Add entity search and popular labels
• Improve index migration strategy
• 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 get_all_nodes() and get_all_edges() methods to Neo4JStorage, PGGraphStorage, MongoGraphStorage, and MemgraphStorage classes. These methods return all nodes and edges in the graph with consistent formatting matching NetworkXStorage for compatibility across different storage backends.
Resolves 'coroutine' object has no attribute 'to_list' error in document pagination endpoint by adding missing await keyword before self._data.aggregate() call.
- Add file_path sorting support to all database backends (JSON, Redis, PostgreSQL, MongoDB)
- Implement smart column header switching between "ID" and "File Name" based on display mode
- Add automatic sort field switching when toggling between ID and file name display
- Create composite indexes for workspace+file_path in PostgreSQL and MongoDB for better query performance
- Update frontend to maintain sort state when switching display modes
- Add internationalization support for "fileName" in English and Chinese locales
This enhancement improves user experience by providing intuitive file-based sorting
while maintaining performance through optimized database indexes.
- Add pagination support to BaseDocStatusStorage interface and all implementations (PostgreSQL, MongoDB, Redis, JSON)
- Implement RESTful API endpoints for paginated document queries and status counts
- Create reusable pagination UI components with internationalization support
- Optimize performance with database-level pagination and efficient in-memory processing
- Maintain backward compatibility while adding configurable page sizes (10-200 items)
- Add metadata field to DocProcessingStatus with start_time and end_time tracking
- Record processing timestamps using Unix time format (seconds precision)
- Update all storage backends (JSON, MongoDB, Redis, PostgreSQL) for new field support
- Maintain backward compatibility with default values for existing data
- Add error_msg field for better error tracking during document processing
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.
- Support fetching all "default_" prefixed documents
- Maintain original behavior for other IDs
- Return dictionary of documents for "default"
- Keep backward compatibility
- Move $limit operation early in pipeline for "*" queries to reduce memory usage
- Remove memory-intensive $sort operation for large dataset queries
- Add fallback mechanism for memory limit errors with simple query
- Implement additional safety checks to enforce max_nodes limit
- Improve error handling and logging for memory-related issues
