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gcgj-dify-1.7.0/api/core/app/apps
-LAN- a6ea15e63c
Refactor/message cycle manage and knowledge retrieval (#20460)
Signed-off-by: -LAN- <laipz8200@outlook.com>
8 months ago
..
advanced_chat Refactor/message cycle manage and knowledge retrieval (#20460) 8 months ago
agent_chat fix(workflow): fetch user failed when workflow run in parallel mode (#20321) 8 months ago
chat fix: Copy request context and current user in app generators. (#20240) 8 months ago
common refactor(workflow): Rename workflow node execution models (#20458) 8 months ago
completion fix: Copy request context and current user in app generators. (#20240) 8 months ago
workflow Refactor/message cycle manage and knowledge retrieval (#20460) 8 months ago
README.md fix: some typos using typos (#11374) 1 year ago
__init__.py FEAT: NEW WORKFLOW ENGINE (#3160) 2 years ago
base_app_generate_response_converter.py Introduce Plugins (#13836) 12 months ago
base_app_generator.py fix: implement robust file type checks to align with existing logic (#17557) 10 months ago
base_app_queue_manager.py Introduce Plugins (#13836) 12 months ago
base_app_runner.py chore: docstring not match the function parameter (#17162) 10 months ago
message_based_app_generator.py feat(workflow): domain model for workflow node execution (#19430) 9 months ago
message_based_app_queue_manager.py chore: apply pep8-naming rules for naming convention (#8261) 1 year ago
workflow_app_runner.py refactor(workflow): Rename NodeRunMetadataKey to WorkflowNodeExecutionMetadataKey (#20457) 8 months ago

README.md

Guidelines for Database Connection Management in App Runner and Task Pipeline

Due to the presence of tasks in App Runner that require long execution times, such as LLM generation and external requests, Flask-Sqlalchemy's strategy for database connection pooling is to allocate one connection (transaction) per request. This approach keeps a connection occupied even during non-DB tasks, leading to the inability to acquire new connections during high concurrency requests due to multiple long-running tasks.

Therefore, the database operations in App Runner and Task Pipeline must ensure connections are closed immediately after use, and it's better to pass IDs rather than Model objects to avoid detach errors.

Examples:

  1. Creating a new record:

    app = App(id=1)
    db.session.add(app)
    db.session.commit()
    db.session.refresh(app)  # Retrieve table default values, like created_at, cached in the app object, won't affect after close
    
    # Handle non-long-running tasks or store the content of the App instance in memory (via variable assignment).
    
    db.session.close()
    
    return app.id
    
  2. Fetching a record from the table:

    app = db.session.query(App).filter(App.id == app_id).first()
    
    created_at = app.created_at
    
    db.session.close()
    
    # Handle tasks (include long-running).
    
    
  3. Updating a table field:

    app = db.session.query(App).filter(App.id == app_id).first()
    
    app.updated_at = time.utcnow()
    db.session.commit()
    db.session.close()
    
    return app_id