dify/api/core/app/apps
2024-10-10 16:34:06 +08:00
..
advanced_chat fix: missing usage of metadata in the chatflow app (#9167) 2024-10-10 16:34:06 +08:00
agent_chat feat: regenerate in Chat, agent and Chatflow app (#7661) 2024-09-22 03:15:11 +08:00
chat feat: regenerate in Chat, agent and Chatflow app (#7661) 2024-09-22 03:15:11 +08:00
completion
workflow Feat/add workflow sys params (#9108) 2024-10-10 11:15:52 +08:00
__init__.py
base_app_generate_response_converter.py fix: Assignment exception (#8663) 2024-09-23 15:23:52 +08:00
base_app_generator.py chore: refurish python code by applying Pylint linter rules (#8322) 2024-09-13 22:42:08 +08:00
base_app_queue_manager.py chore: refurish python code by applying Pylint linter rules (#8322) 2024-09-13 22:42:08 +08:00
base_app_runner.py fix:Spark's large language model token calculation error #7911 (#8755) 2024-09-25 14:51:42 +08:00
message_based_app_generator.py feat: regenerate in Chat, agent and Chatflow app (#7661) 2024-09-22 03:15:11 +08:00
message_based_app_queue_manager.py
README.md
workflow_app_runner.py
workflow_logging_callback.py

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 deattach 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