- Enhanced error handling in the indexing process to differentiate between actual failures and cases where no new documents are processed.
- Updated notification messages to reflect the status accurately, including a message for when no new items are synced.
- Standardized return values across various indexer tasks to return `None` on success, simplifying logging and error management.
- Introduced a new DocumentProcessingNotificationHandler to manage notifications for document processing stages.
- Updated existing notification methods to include detailed progress updates for various stages (queued, parsing, chunking, embedding, storing, completed, failed).
- Refactored NotificationService to support the new document processing notification type and metadata schema.
- Updated multiple document processing tasks to create and manage notifications throughout the processing lifecycle.
- Adjusted UI components to reflect changes in notification types and improve user experience during document uploads and processing.
- Removed the deprecated create_connector_indexed_notification method from NotificationService.
- Introduced new notification types and schemas in notification.types.ts to standardize notification handling.
- Updated useNotifications hook to utilize the new notification type definitions.
- Added notifications table to the database schema with replication support for Electric SQL.
- Developed NotificationService to manage indexing notifications, including creation, updates, and status tracking.
- Introduced NotificationButton and NotificationPopup components for displaying notifications in the UI.
- Enhanced useNotifications hook for real-time notification syncing using PGlite live queries.
- Updated package dependencies for Electric SQL and improved error handling in notification processes.
- Added Electric SQL service to docker-compose for real-time data synchronization.
- Introduced PostgreSQL configuration for logical replication and performance tuning.
- Created scripts for initializing Electric SQL user and electrifying tables.
- Implemented notification model and service in the backend.
- Developed ElectricProvider and useNotifications hook in the frontend for managing notifications.
- Updated environment variables and package dependencies for Electric SQL integration.
- Updated langchain-unstructured to version 1.0.0 and langchain to 1.2.0.
- Updated litellm to version 1.80.10 and grpcio versions based on Python version.
- Updated fastuuid to version 0.14.0 and langgraph to 1.0.5.
- Updated openai to version 2.12.0 and langgraph-sdk to 0.3.0.
- Added uuid-utils package version 0.12.0.
- Refactored imports in utils.py, chats_routes.py, and query_service.py to use langchain_core.messages.
- Modified the document extraction and citation formatting to accommodate a new structure that includes a `chunks` list for each document.
- Enhanced the citation format to reference `chunk_id` instead of `source_id`, ensuring accurate citations in the UI.
- Updated various components, including the connector service and reranker service, to handle the new document format and maintain compatibility with existing functionalities.
- Improved documentation and comments to reflect changes in the data structure and citation requirements.
Fixes typo in directory name and updates all import paths:
- Renamed surfsense_backend/app/retriver/ to surfsense_backend/app/retriever/
- Updated imports in db.py
- Updated imports in connector_service.py
-Introduce granular permissions for documents, chats, podcasts, and logs.
- Update routes to enforce permission checks for creating, reading, updating, and deleting resources. - Refactor user and search space interactions to align with RBAC model, removing ownership checks in favor of permission validation.
- Added new LLM providers including Google, Azure OpenAI, Bedrock, and others to the backend.
- Updated the model selection UI to dynamically display available models based on the selected provider.
- Enhanced the provider change handling to reset the model selection when the provider is changed.
- Improved the overall user experience by providing contextual information for model selection.
- Added `validate_llm_config` function to `llm_service.py` for validating LLM configurations via test API calls.
- Integrated validation in `create_llm_config` and `update_llm_config` routes in `llm_config_routes.py`, raising HTTP exceptions for invalid configurations.
- Enhanced error handling to provide detailed feedback on configuration issues.
- Introduced a fixed parameter order for AzureOpenAIEmbeddings to resolve compatibility issues.
- Updated the voice selection logic to include Azure voices in the podcaster utility.
- Modified the page limit service to use a more efficient method for retrieving users.
- Add BAIDU_SEARCH_API connector type to support Chinese web search
- Implement search_baidu() method in connector_service.py
- Add frontend configuration page for Baidu Search API
- Create Alembic migration for new enum values
- Add validation rules and agent integration
- Support configurable model, search source, and deep search options
- Update .gitignore to exclude .env.local and other env files
Addresses integration with Chinese search ecosystem for better local market support.
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