dify/api/core/app/apps
QuantumGhost 10b738a296
feat: Persist Variables for Enhanced Debugging Workflow (#20699)
This pull request introduces a feature aimed at improving the debugging experience during workflow editing. With the addition of variable persistence, the system will automatically retain the output variables from previously executed nodes. These persisted variables can then be reused when debugging subsequent nodes, eliminating the need for repetitive manual input.

By streamlining this aspect of the workflow, the feature minimizes user errors and significantly reduces debugging effort, offering a smoother and more efficient experience.

Key highlights of this change:

- Automatic persistence of output variables for executed nodes.
- Reuse of persisted variables to simplify input steps for nodes requiring them (e.g., `code`, `template`, `variable_assigner`).
- Enhanced debugging experience with reduced friction.

Closes #19735.
2025-06-24 09:05:29 +08:00
..
advanced_chat feat: Persist Variables for Enhanced Debugging Workflow (#20699) 2025-06-24 09:05:29 +08:00
agent_chat feat: Persist Variables for Enhanced Debugging Workflow (#20699) 2025-06-24 09:05:29 +08:00
chat feat: Persist Variables for Enhanced Debugging Workflow (#20699) 2025-06-24 09:05:29 +08:00
common feat: Persist Variables for Enhanced Debugging Workflow (#20699) 2025-06-24 09:05:29 +08:00
completion feat: Persist Variables for Enhanced Debugging Workflow (#20699) 2025-06-24 09:05:29 +08:00
workflow feat: Persist Variables for Enhanced Debugging Workflow (#20699) 2025-06-24 09:05:29 +08:00
README.md fix: some typos using typos (#11374) 2024-12-05 13:24:06 +08:00
__init__.py FEAT: NEW WORKFLOW ENGINE (#3160) 2024-04-08 18:51:46 +08:00
base_app_generate_response_converter.py Introduce Plugins (#13836) 2025-02-17 17:05:13 +08:00
base_app_generator.py fix: implement robust file type checks to align with existing logic (#17557) 2025-04-16 19:21:50 +08:00
base_app_queue_manager.py Introduce Plugins (#13836) 2025-02-17 17:05:13 +08:00
base_app_runner.py 🐛 Fix(Gemini LLM): Support Gemini 0.2.x plugin on agent app (#20794) 2025-06-12 00:49:38 +08:00
message_based_app_generator.py feat(workflow): domain model for workflow node execution (#19430) 2025-05-17 00:56:16 +08:00
message_based_app_queue_manager.py chore: apply pep8-naming rules for naming convention (#8261) 2024-09-11 16:40:52 +08:00
workflow_app_runner.py feat: Persist Variables for Enhanced Debugging Workflow (#20699) 2025-06-24 09:05:29 +08:00

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