Remove pyseekdb (#243)

* feat: Add native hybird search (#197)

* 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

* feat: User Profile Support native language output (#198)

* support native language

* support native language

* add docs

* Reconstruct LLM setting (#200)

* 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.

* refactor: unify configuration governance for agent, core, and server modules (#199)

* Reconstruct setting in Rerank,Vector,Graph (#202)

* 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 (#220)

* Oceanbase Native Hybrid Search Cases (#223)

* oceanbase native language case

* Oceanbase Native Hybrid Search Cases

* Optimise searching in Intelligent mode And fix SILICONFLOW_LLM_BASE_URL bug (#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.

* add enable_native_hybrid in benchmark

* 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

* Fix unit test issues caused by setting changes (#228)

* 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

* Fixed run failure caused by incorrect folder name (#229)

* 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

* remove pyseekdb

---------

Co-authored-by: jingshun.tq <35712518+Teingi@users.noreply.github.com>
Co-authored-by: Chifang <40140008+Ripcord55@users.noreply.github.com>

Author: 3 people

pyproject.toml

@@ -36,7 +36,6 @@ dependencies = [
     "slowapi>=0.1.9",
     "click>=8.0.0",
     "rank-bm25>=0.2.2",
-    "pyseekdb>=1.0.0",
     "pyobvector>=0.2.24,<0.3.0",
     "jieba>=0.42.1",
     "azure-identity>=1.24.0",

src/powermem/storage/config/pyseekdb.py

@@ -90,53 +90,6 @@ def get_supported_providers(cls) -> list:
         """
         return list(BaseVectorStoreConfig._registry.keys())
 
-        # 2. Get config_cls from registry
-        config_cls = BaseVectorStoreConfig.get_provider_config_cls(provider_name) or BaseVectorStoreConfig
-
-        # 3. Handle config parameter
-        if isinstance(config, dict):
-            # Convert dict to provider config instance
-            provider_config = config_cls(**config)
-        elif isinstance(config, BaseVectorStoreConfig):
-            # Use config instance directly
-            provider_config = config
-        else:
-            raise TypeError(f"config must be BaseVectorStoreConfig or dict, got {type(config)}")
-
-        # 4. Export to dict for VectorStore constructor
-        config_dict = provider_config.model_dump(exclude_none=True)
-
-        # 5. Create VectorStore instance
-        vector_store_class = load_class(class_path)
-        return vector_store_class(**config_dict)
-
-    @classmethod
-    def register_provider(cls, name: str, class_path: str, config_class=None):
-        """
-        Register a new vector store provider.
-
-        Args:
-            name (str): Provider name
-            class_path (str): Full path to VectorStore class
-            config_class: Configuration class for the provider (defaults to BaseVectorStoreConfig)
-        """
-        if config_class is None:
-            config_class = BaseVectorStoreConfig
-
-        # Register directly in BaseVectorStoreConfig registry
-        BaseVectorStoreConfig._registry[name] = config_class
-        BaseVectorStoreConfig._class_paths[name] = class_path
-
-    @classmethod
-    def get_supported_providers(cls) -> list:
-        """
-        Get list of supported providers.
-
-        Returns:
-            list: List of supported provider names
-        """
-        return list(BaseVectorStoreConfig._registry.keys())
-
     @classmethod
     def reset(cls, instance):
         instance.reset()