Conversation
* add sparse vector embedding * hybrid search add sparse vector search * add checking version logic * add qwen sparse vector * adjust weight * update sparse vector function * update sparse vector function * fix bug * fix bug * optimise function * optimise function * optimise function * optimise function * optimise function * optimise function * optimise function * fix bug * add migrate function * update alembic function * update alembic function * update alembic function * adjust file struct * update alembic * update version * optimise * fix bug * update * update schema update method * update schema update method * update schema update method * update schema update method * update schema update method * update migrate method * update migrate method * update env.example * update env.example * update migrate sparse vector * update migrate sparse vector * adjust threshold score logic * update remark * add guides and examples * add benchmark param * fix bug * fulltext parsers support * adjust enable sparse vector setting * adjust env.example * adjust docs * update version * fix bug * optimise check * adjust file construct * adjust file construct * add native search * add file * remove log * remove log * fix bug * update pyobvector * add rerank * adjust * add limit * adjust config
* support native language * support native language * add docs
* feat(llm): enhance configuration management with pydantic-settings - Introduced a unified configuration system for LLM providers using pydantic-settings. - Added provider-specific settings for Anthropic, Azure, DeepSeek, Ollama, OpenAI, Qwen, Vllm, and Zai. - Improved environment variable handling and validation through Field and AliasChoices. - Removed legacy initialization methods in favor of a cleaner, more maintainable structure. - Updated LLMFactory to utilize the new provider registration mechanism. * chore: Update LLM configuration management and improve environment variable handling - Refactor LLM configuration imports to use BaseLLMConfig. - Replace direct attribute access with getattr for safer environment variable retrieval. - Remove deprecated LLMConfig and streamline related code for better maintainability.
* feat(llm): enhance configuration management with pydantic-settings - Introduced a unified configuration system for LLM providers using pydantic-settings. - Added provider-specific settings for Anthropic, Azure, DeepSeek, Ollama, OpenAI, Qwen, Vllm, and Zai. - Improved environment variable handling and validation through Field and AliasChoices. - Removed legacy initialization methods in favor of a cleaner, more maintainable structure. - Updated LLMFactory to utilize the new provider registration mechanism. * chore: Update LLM configuration management and improve environment variable handling - Refactor LLM configuration imports to use BaseLLMConfig. - Replace direct attribute access with getattr for safer environment variable retrieval. - Remove deprecated LLMConfig and streamline related code for better maintainability. * feat: Enhance rerank configuration and integration - Introduced BaseRerankConfig for improved configuration management across rerank providers. - Updated rerank integration files to utilize the new base configuration structure. - Added support for additional configuration fields such as api_base_url and top_n. - Refactored rerank factory to accommodate new configuration handling and provider registration. - Removed deprecated RerankConfig and streamlined related code for better maintainability. - Updated API request handling in rerank classes to support custom HTTP clients. * * refactor(powermem): remove unused storage configuration management module - Removed `VectorStoreConfig` and `GraphStoreConfig` classes - Deleted associated validation logic and import statements - Streamlined codebase by eliminating unused components * feat(powermem): enhance sparse embedder configuration management - Introduced BaseSparseEmbedderConfig for unified sparse embedding configuration. - Updated MemoryConfig to utilize BaseSparseEmbedderConfig. - Refactored SparseEmbedderFactory to support new configuration handling. - Improved handling of sparse embedder settings across various components. * feat(powermem): enhance user profile storage with provider registration - Added a registry mechanism to UserProfileStoreBase for automatic provider registration. - Implemented class paths for OceanBase and SQLite user profile storage implementations. - Updated UserProfileStoreFactory to utilize the new registry for provider class retrieval. - Refactored imports to trigger auto-registration of user profile storage classes. - Improved handling of provider names in the factory for better compatibility. * feat(powermem): synchronize embedding model dimensions across configurations - Added logic to sync `embedding_model_dims` from the embedder to both `vector_store` and `graph_store` if not already set. - Updated `config_loader.py` and `configs.py` to ensure consistent embedding dimensions across components. * feat(powermem): enhance OceanBase configuration and query handling - Added `enable_native_hybrid` field to `OceanBaseConfig` for native hybrid search support. - Updated query handling in `OceanBaseVectorStore` to use a safe query format, preventing SQL injection risks.
* oceanbase native language case * Oceanbase Native Hybrid Search Cases
…RL bug (oceanbase#224) * Enhance memory operations with background threading support - Added a global background thread pool for asynchronous memory updates and deletions in the Memory class. - Updated the handling of memory updates and deletions to submit tasks to the background executor, improving performance and responsiveness. * format * Enhance SiliconFlowConfig API key handling - Updated `SiliconFlowConfig` to improve API key and base URL handling by adding new validation aliases for better compatibility.
# Conflicts: # benchmark/server/main.py # pyproject.toml # src/powermem/storage/configs.py # src/powermem/storage/factory.py # src/powermem/user_memory/user_memory.py
- Added backward compatibility for OceanBase by constructing connection arguments from vector store configuration. - Updated unit tests to verify the inclusion of internal settings in the configuration.
* Enhance configuration management for OceanBase in config_loader.py - Added backward compatibility for OceanBase by constructing connection arguments from vector store configuration. - Updated unit tests to verify the inclusion of internal settings in the configuration. * disable env file
# Conflicts: # tests/unit/test_config_loader.py
* Enhance configuration management for OceanBase in config_loader.py - Added backward compatibility for OceanBase by constructing connection arguments from vector store configuration. - Updated unit tests to verify the inclusion of internal settings in the configuration. * disable env file * Fixed run failure caused by incorrect folder name
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary
Remove pyseekdb