- Extend RetrieveEngineRegistry with byStoreID map for DB store engines
- Add StoreRegistry interface and EngineFactory function type
- Create engine factory with per-driver SDK client construction
- Load VectorStore records from DB into registry at startup
- Wire Create/Delete to dynamically register/unregister engines
- Add comprehensive unit tests for registry and service
- Added a new logger for LLM calls, enabling detailed logging of model interactions, including request and response data.
- Introduced configuration options for enabling and specifying the log directory for LLM debug logs.
- Implemented cleanup for old log files to manage disk space effectively.
- Wrapped existing chat implementations to log calls when debug logging is enabled, enhancing traceability for model interactions.
Introduce KnowledgePostProcess task to decouple image multimodal
processing from downstream operations like summary, question
generation, and knowledge graph extraction.
This allows unifying the processing logic across documents and
images and ensures all text content, including from images,
is properly extracted before post-processing.
Multiple fixes for WeKnora Lite mode (SQLite, no Redis):
1. Redis nil pointer panic on FAQ import (knowledge.go)
- Add in-memory fallback (sync.Map) for FAQ import progress tracking
- Add nil guards for running task locks and progress queries
2. seq_id not auto-incrementing in SQLite (chunk.go, tag.go)
- GORM autoIncrement on non-PK columns doesn't work in SQLite
- Add AssignChunkSeqIDs() to pre-assign seq_ids before batch insert
- Add BeforeCreate hook for KnowledgeTag
- Use Unscoped() to include soft-deleted records in MAX(seq_id) query
3. NOW() function not available in SQLite (chunk.go)
- Replace raw SQL NOW() with time.Now() or datetime('now')
- Use dialector check for raw SQL that must differ between PG and SQLite
4. FAQ KB should reject file uploads (knowledge.go)
- Add kb.Type == "faq" check in CreateKnowledgeFromFile
5. Linux/macOS build compatibility (Makefile)
- Conditionally apply macOS-only linker flag based on uname
6. Add SQLite integration tests (chunk_sqlite_test.go)
- TestCreateChunks_SQLite_SeqIDAutoAssigned
- TestCreateChunks_SQLite_SeqIDContinuesFromExisting
- TestCreateChunks_SQLite_SeqIDUniqueAcrossKBs
- TestCreateChunks_SQLite_SeqIDAfterSoftDelete
- TestKnowledgeTag_SQLite_SeqIDAutoAssigned
- TestUpdateChunk_SQLite_NoNOWError
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Replaced references to Docreader credentials with WeKnoraCloud credentials across multiple services and handlers.
- Introduced a new CredentialsConfig structure to manage third-party provider credentials, specifically for WeKnoraCloud.
- Updated database schema to include a credentials column for storing WeKnoraCloud AppID and AppSecret.
- Enhanced methods for retrieving and utilizing WeKnoraCloud credentials, ensuring proper encryption and decryption during storage and retrieval.
This update improves the management of WeKnoraCloud credentials, streamlining the integration and enhancing security measures.
- Added tenantService to modelService for retrieving WeKnoraCloud credentials when not provided in model parameters.
- Implemented resolveWeKnoraCloudCredentials method to automatically fetch AppID and AppSecret from tenant configuration.
- Updated GetEmbeddingModel, GetEmbeddingModelForTenant, GetRerankModel, and GetChatModel methods to utilize the new credential resolution logic.
- Modified ModelParameters to encrypt and decrypt both APIKey and AppSecret for improved security during database operations.
This update streamlines credential management for WeKnoraCloud models, enhancing security and usability.
- Removed support for video file uploads across the application, including updates to the knowledge base and document processing services.
- Updated internationalization files to reflect the removal of video-related terminology, changing labels and descriptions to focus solely on audio processing.
- Adjusted file type handling to exclude video formats, ensuring users receive accurate feedback regarding supported file types.
- Enhanced error handling to provide clear messages when users attempt to upload unsupported video files.
This update streamlines the application by focusing on audio processing capabilities and improving user experience through clearer messaging.
- Changed 'Audio Processing' to 'Audio & Video' in English, Korean, Russian, and Chinese translations to reflect expanded functionality.
- Updated ASR configuration titles and descriptions to include video processing capabilities, enhancing user understanding of the feature.
- Renamed file type labels from 'Audio Files' to 'Audio & Video' across multiple languages for consistency and clarity.
- Enhanced document upload handling in the KnowledgeBase to filter unsupported file types, providing user feedback for filtered images, videos, and audio files.
This update improves the internationalization of the application and clarifies the capabilities of the ASR feature.
- Updated the query content to include metadata for uploaded images and attachments, improving the context provided to the assistant.
- Modified the attachment prompt format to use XML-like tags for better structure and readability, including metadata for file type and size.
- Enhanced error handling for unsupported file content extraction, providing clearer feedback to users.
This update improves the assistant's ability to process and respond to queries involving multimedia content.
- Introduced a new prompt template for document analysis, allowing the assistant to provide detailed responses based on attached documents.
- Updated the rewrite template descriptions to clarify the handling of image and document attachments, ensuring better user understanding of intent classification.
- Added a new intent type for document-only queries to improve response accuracy.
This update enhances the assistant's capabilities in processing and analyzing documents while refining the user experience in intent classification.
- Introduced a new WeKnoraCloudSettings component for managing APPID and APPSECRET.
- Added functionality to save WeKnoraCloud credentials without automatically creating models.
- Implemented credential status checks across various components to provide user feedback on configuration status.
- Updated API endpoints to handle credential saving and status retrieval.
- Enhanced UI elements to guide users in configuring WeKnoraCloud settings.
This update improves the integration of WeKnoraCloud by allowing users to manage their credentials more effectively and receive real-time feedback on their configuration status.
Add VectorStoreService with CRUD validation, duplicate checking (DB + env
stores), and engine-specific health checks for 6 vector database types.
Include VectorStoreResponse DTO, env store builder, engine type metadata,
and comprehensive unit tests.
Introduce the VectorStore domain model as a foundation for multi-store
vector DB architecture (Phase 1, PR 1/4).
- VectorStore entity with ConnectionConfig (AES-GCM encrypted) and IndexConfig
- VectorStoreRepository interface and GORM implementation (CRUD + duplicate check)
- PostgreSQL migration (000031) and SQLite migration (000001)
- Unit tests for types, encryption, validation, and helpers
- Define notionPage, notionBlock, notionParent, notionFile and cursor types
- Implement rate-limited HTTP client with context-aware retry and backoff
- Support search, page/block retrieval, database queries, and file downloads
- Add HasChildren field to Resource type, NotionChannel to knowledge types
- Add unit tests for types and client
- Added ASR configuration options to the knowledge base and model settings.
- Implemented ASR model selection and transcription capabilities in the knowledge processing pipeline.
- Enhanced file upload support to include audio formats for ASR processing.
- Updated localization files to include ASR-related labels and descriptions.
- Refactored model handling to accommodate ASR as a new model type.
Previously, only the original uploaded file was deleted via knowledge.FilePath.
Images extracted by the builtin parser (stored as individual S3/MinIO/local files
via ImageResolver) were never cleaned up, causing orphan files to accumulate.
- Add ListImageInfoByKnowledgeIDs repository method (no chunk_type filter)
- Add collectImageURLs utility with URL deduplication and JSON parse logging
- Add deleteExtractedImages helper (standalone, best-effort with error logging)
- Fix DeleteKnowledge: collect image URLs before errgroup, delete in file goroutine
- Fix DeleteKnowledgeList: bulk collect with KB-level fileSvc mapping
- Fix cleanupKnowledgeResources: collect before chunk deletion, delete after
- Fix ProcessKBDelete: collect before chunk deletion for KB-wide cleanup
- Add DefaultLanguage() that reads WEKNORA_LANGUAGE env with zh-CN fallback
- Replace hardcoded zh-CN in LanguageNameFromContext with DefaultLanguage()
- Unify middleware/language.go to use types.DefaultLanguage()
- Add Language field to DocumentProcessPayload (8 enqueue sites + worker restore)
- Add Language field to ImageMultimodalPayload (enqueue + worker restore)
- Propagate language from ImageMultimodalPayload to QuestionGenerationPayload
- Updated UpdateKnowledgeTagBatch method to include an authorizedKBID parameter for restricting updates to specific knowledge items.
- Implemented validation to ensure that all requested knowledge IDs belong to the authorized knowledge base.
- Enhanced GetKnowledgeBatch and UpdateKnowledgeTagBatch methods to incorporate agent-specific knowledge base access restrictions.
- Added utility functions to resolve allowed knowledge base IDs for agents based on their configuration.
- Updated relevant files to include provider registration, implementation, and metadata.
- Enhanced frontend components to support provider management and configuration.
- Added localization for new provider settings and messages.
- Implemented backend repository methods for CRUD operations on web search providers.
- Deleted WeCom document connector and callback handling code to streamline the datasource management.
- Removed associated localization entries and UI elements related to WeCom integration.
- Updated data source management logic to eliminate references to WeCom, enhancing maintainability and clarity.
- Adjusted error handling and logging to reflect the removal of WeCom-specific functionality.
- Improved logging for missing data sources, providing clearer warnings when a data source is not found.
- Updated sync log status to 'canceled' when a data source is deleted, ensuring accurate tracking of sync operations.
- Adjusted error handling to prevent unnecessary error returns, enhancing overall process stability.
- Added a new API for managing data sources, including CRUD operations and connection validation.
- Introduced UI components for data source settings, sync logs, and editor dialog, enhancing user experience in managing external data sources.
- Updated localization files to support new data source features in multiple languages.
- Implemented cron expression humanization for better scheduling visibility.
- Enhanced knowledge base editor to include data source management options.
The S3 storage adapter (s3.go) was added in e309e0b but the provider
scheme integration was incomplete — ParseProviderScheme() and frontend
security.ts were not updated, causing s3:// URLs to fail in the /files
proxy, VLM image processing, and frontend rendering.
Additionally, S3-compatible services (MinIO, Ceph, etc.) require
path-style addressing (endpoint/bucket/key) but the SDK client only
used virtual-hosted style. The deprecated WithEndpointResolver API
is replaced with BaseEndpoint, and path-style is auto-enabled for
non-AWS endpoints (detected by amazonaws.com in the URL).
Changes:
- types/knowledgebase.go: add "s3" to ParseProviderScheme()
- file/s3.go: auto path-style for S3-compatible endpoints + replace
deprecated WithEndpointResolver with BaseEndpoint
- frontend/security.ts: add s3 to 5 provider scheme allowlists
- knowledgebase_test.go: add ParseProviderScheme + InferStorage tests
- s3_test.go: add path-style detection + parseS3FilePath tests
When ParallelToolCalls is enabled in AgentConfig and the LLM returns
2+ tool calls, execute them concurrently via errgroup. Results are
collected in original order for deterministic observe-phase behavior.
Sequential execution remains the default. Parallel mode is opt-in
per agent configuration to avoid side effects with stateful tools.
Refactors executeToolCalls into composable helpers (runToolCall,
executeSingleToolCall, executeToolCallsParallel) for testability.
Fixes#707
- guard against empty content completion in analyzeResponse/executeLoop
with retry (max 2), nudge message, and fallback response
- propagate actual finish_reason through streaming pipeline instead of
hardcoding "stop" in streamThinkingToEventBus
- add FinishReason field to StreamResponse and streamLLMResult
- add finish marker chunk in processStreamDelta for empty content scenarios
- propagate lastFinishReason through EOF handler in processStream
- strengthen PureAgent system prompt with MCP tool guidelines and
graceful fallback instructions for unanswerable questions
- add unit tests for empty response bug and finish_reason propagation
- Updated context template to include runtime metadata such as current time and week, improving contextual awareness in user queries.
- Enhanced rewrite template with critical instructions for intent classification, ensuring that rewritten questions preserve essential entities and keywords.
- Refined intent classification logic to prioritize user intents more effectively, improving the accuracy of responses based on user queries.
- Added examples to clarify expected input and output formats for intent classification, enhancing usability for developers.
- Added a new API endpoint to fetch suggested questions based on the agent's associated knowledge bases.
- Implemented frontend components to display suggested questions in both chat and create chat views, enhancing user interaction.
- Updated localization files to include translations for suggested questions in English, Korean, Russian, and Chinese.
- Introduced debounce logic for fetching suggestions to optimize performance during knowledge base changes.
- Enhanced backend services to support fetching and returning suggested questions, improving the overall chat experience.
- Introduced a new `channel` field in the Knowledge struct and associated request types to track the source channel (e.g., "web", "api", "browser_extension").
- Updated various frontend components to display channel information and enhance user experience with channel labels.
- Enhanced localization files to support channel labels in English and Chinese.
- Modified backend services and database migrations to accommodate the new channel feature, ensuring consistent tracking across knowledge entries.
- Refactored related functions to integrate channel handling, improving overall knowledge management and context.
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