- Sync memory_count after Neo4j write and forgetting cycle
- Filter Neo4j end user list by memory_count > 0
- Filter RAG end user list by Memory knowledge chunk count
- Replace truthiness checks with 'is not None' for data.message in graph_data and community_graph endpoints to handle empty string correctly
- Remove Optional wrapper from GraphStatistics.edge_types since it already has a default_factory
- Add user_memory_schema.py with typed Pydantic models for all user memory
API responses: MemoryInsightReportData, UserSummaryData, GraphData,
MemoryTypeStatItem, cache result models, and RelationshipEvolutionData
- Refactor user_memory_controllers.py to construct schema instances and
return model_dump() instead of raw dicts
- Remove unused imports (datetime, timestamp_to_datetime, EndUserInfoResponse,
EndUserInfoCreate, EndUser)
- Replace plain image URLs with `<img src="..." data-url="...">` HTML tags in multimodal and document extractor services
- Propagate citations from workflow end events to client responses
- Update system prompts to instruct LLMs to render images using Markdown `` with strict UUID-preserving URL copying
* release/v0.3.2: (245 commits)
fix(conversation_schema): refine citations field type to Dict[str, Any]
fix(tool_controller): re-raise HTTPException to preserve original status codes
fix(workflow): add reasoning content, suggested questions, citations and audio status support
feat(workflow): augment logging queries and ameliorate error handling
fix(api_key): bypass publication check for SERVICE type API keys
fix(multimodal_service): add '文档内容：' prefix to document text and simplify image placeholder text
fix(api): convert config_id to string in write_router
fix(api): convert end_user_id to string in write_router
fix(multimodal_service): refactor image processing to use intermediate list before extending result
fix(web): node status ui
fix(api): correct import paths in memory_read and celery task command
fix(api): correct import paths in memory_read and celery task command
refactor(tool): flatten request body parameters for model exposure
fix(api): correct import paths in memory_read and celery task command
refactor(workflow): streamline node execution handling and log service logic
feat(web): http request add process
feat(web): workflow app logs
fix(app_chat_service,draft_run_service): move system_prompt augmentation before LangChainAgent instantiation
fix(app_chat_service,draft_run_service): move system_prompt augmentation before LangChainAgent instantiation
refactor(http_request): simplify request handling and remove unused fields
...
# Conflicts:
# api/app/controllers/file_controller.py
# api/app/tasks.py
- Augment log search with app type filtering to enable keyword searching within workflow_executions.
- Introduce execution sequence markers to ensure logs are displayed in the correct chronological order.
- Ameliorate error handling to capture successful node outputs alongside failure details.
- Rectify the processing of empty JSON bodies in HTTP request nodes.
- Fix relative imports in memory_read.py to use absolute app paths
- Change celery scheduler command from `python app/celery_task_scheduler.py` to `python -m app.celery_task_scheduler`
- 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.
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.
- 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.
Add external service APIs for memory detail queries
Provides memory data access endpoints for external service integration
Add utility functions for API key user resolution and end_user validation
Modified files:
- api/app/controllers/service/user_memory_api_controller.py
- api/app/core/api_key_utils.py
- api/app/controllers/service/__init__.py
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
- Refactor quota management logic to support usage checks scoped by workspace.
- Update quota statistics API to return granular quota details for each workspace.
- Revise default configuration settings for terminal user and model limits.
- Remove quota check decorators from the model controller.
- 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`.
- Replace direct memory agent service calls with unified MemoryService in read endpoint
- Update query preprocessor to use new prompt format and return structured queries
- Enhance MemorySearchResult model with filtering, merging, and ID tracking capabilities
- Add intermediate outputs display for problem split, perceptual retrieval, and search results
- Fix parameter alignment and remove unused history parameter in memory agent service
Change Body(...) to Body(None) for the message parameter which is never
used directly (request body is read via request.json() instead).
The required marker caused unnecessary 422 validation errors.
Split reset_agent_config into two independent methods for getting and resetting model parameters
Add functionality to read quota configuration from environment variables to the default free tier
