- Introduce `reasoning_content`, `suggested_questions`, `citations`, and `audio_status` fields in conversation and app response schemas
- Conditionally set `audio_status` to `"pending"` only when `audio_url` is present
- Replace `model_dump` override with `@model_serializer(mode="wrap")` for cleaner serialization logic
- Change knowledge base validation failure from `RuntimeError` to warning + `continue` to avoid halting retrieval on invalid KB
- Consolidate node data retrieval from workflow_executions.output_data to unify storage access.
- Optimize the construction of messages and execution records to support opening suggestions.
- Eliminate redundant queries and storage logic to simplify the overall codebase structure.
- Augment workflow logs with execution status fields and loop node information.
- Refactor log service to handle distinct processing logic for workflows and agents.
- Construct message and node logs derived from workflow_executions data.
- Pass workspace_id to multimodal_service.process_files across app_chat_service, draft_run_service
- Fetch tenant_id from workspace in multimodal_service for proper file storage scoping
- Update image placeholder format from "[第N页 第M张图片]" to "[图片 第N页 第M张图片]" for clarity
- Add strict URL preservation rules to system prompt for agents handling document images
- Refactor _save_doc_image_to_storage to accept explicit tenant_id and workspace_id instead of inferring from FileMetadata
Added `allow_download` flag to citation config and `download_url` field to citation output. Implemented `/citations/{document_id}/download` endpoint to serve original files when enabled. Removed unused `files` field and `HttpRequestDataProcessing` model from HTTP request node config.
- Rectify exception propagation during node execution failures to ensure errors are correctly raised.
- Bolster workflow logging to support failed status records and persist node execution data, including loop nodes.
Added document image extraction capability for PDF and DOCX files, including page/index metadata and storage integration. Extended `process_files` with `document_image_recognition` flag to conditionally enable vision-based image processing when model supports it. Updated knowledge repository and workflow node logic to enforce status=1 checks. Added PyMuPDF dependency.
- feat(http_request): augment debugging capabilities with raw request generation and improved error handling.
- feat(app_log): extend session filtering logic to support retrieving all session types.
- feat(log): add 'process' field to node execution records for better data tracking.
- Fix episodic memory time filter to use UTC (datetime.fromtimestamp with tz=timezone.utc)
to match Neo4j stored UTC timestamps
- Add POST /v1/memory/analytics/generate_cache endpoint for cache generation via API Key
Modified files:
- api/app/services/memory_explicit_service.py
- api/app/controllers/service/user_memory_api_controller.py
- Parameterize SKIP/LIMIT in Cypher query instead of f-string interpolation
- Add UUID format validation in validate_end_user_in_workspace before DB query
- Update limit/depth Query descriptions to clarify auto-cap behavior in service layer
- Move uuid import to module level in api_key_utils.py
Modified files:
- api/app/services/memory_explicit_service.py
- api/app/core/api_key_utils.py
- api/app/controllers/service/user_memory_api_controller.py
- Augment HTTP request node capabilities and add generated curl commands for easier debugging.
feat(log): implement workflow execution logs and search functionality
- Add detailed logging for workflow node execution and enable search capabilities within application logs.
feat(auth): introduce middleware to verify application publication status
- Add a check to ensure the application is published before allowing access.
fix(converter): rectify variable handling logic in Dify converter
- Correct issues related to processing variables within the Dify converter module.
refactor(model): remove quota check decorator from model update operations
- Decouple quota validation from the model update process to streamline the logic.
Split explicit memory overview into two independent endpoints:
- GET /memory/explicit-memory/episodics: episodic memory paginated query
with date range filter (millisecond timestamp) and episodic type filter
using Neo4j datetime() for precise time comparison
- GET /memory/explicit-memory/semantics: semantic memory full list query
returns data as array directly
Modified files:
- api/app/controllers/memory_explicit_controller.py
- api/app/services/memory_explicit_service.py
- Fix write_router to use actual_end_user_id instead of end_user_id
- Add task status tracking via Redis in scheduler
- Expose task_id in memory write response
- Fix logging import path in scheduler
- Revert API Key rate limit handling to throw an error instead of auto-capping when exceeding the plan limit.
- Optimize terminal user quota check logic to validate only during new user creation, avoiding redundant checks.
- Add method to query terminal users by `workspace_id` and `other_id`.
- Add model reference resolution for LLM, Question Classifier, and Parameter Extractor nodes.
- Support parsing various model reference formats, including dictionaries, UUID strings, and name strings, when `model_id` is present.
- Add warning logs for cases where model resolution fails.
- Extract duplicate model binding logic into `_get_model_by_name_or_fallback`.
- Implement logic to prioritize workspace default configuration, falling back to the tenant's first available model if not found.
- Simplify binding code for embedding, rerank, and LLM models.
