mirror of https://github.com/langgenius/dify.git
Merge branch 'main' into feat/queue-based-graph-engine
This commit is contained in:
-LAN-
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# AGENTS.md
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## Project Overview
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Dify is an open-source platform for developing LLM applications with an intuitive interface combining agentic AI workflows, RAG pipelines, agent capabilities, and model management.
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The codebase consists of:
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- **Backend API** (`/api`): Python Flask application with Domain-Driven Design architecture
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- **Frontend Web** (`/web`): Next.js 15 application with TypeScript and React 19
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- **Docker deployment** (`/docker`): Containerized deployment configurations
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## Development Commands
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### Backend (API)
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All Python commands must be prefixed with `uv run --project api`:
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```bash
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# Start development servers
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./dev/start-api # Start API server
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./dev/start-worker # Start Celery worker
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# Run tests
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uv run --project api pytest # Run all tests
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uv run --project api pytest tests/unit_tests/ # Unit tests only
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uv run --project api pytest tests/integration_tests/ # Integration tests
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# Code quality
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./dev/reformat # Run all formatters and linters
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uv run --project api ruff check --fix ./ # Fix linting issues
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uv run --project api ruff format ./ # Format code
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uv run --directory api basedpyright # Type checking
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```
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### Frontend (Web)
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```bash
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cd web
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pnpm lint # Run ESLint
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pnpm eslint-fix # Fix ESLint issues
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pnpm test # Run Jest tests
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```
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## Testing Guidelines
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### Backend Testing
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- Use `pytest` for all backend tests
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- Write tests first (TDD approach)
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- Test structure: Arrange-Act-Assert
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## Code Style Requirements
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### Python
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- Use type hints for all functions and class attributes
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- No `Any` types unless absolutely necessary
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- Implement special methods (`__repr__`, `__str__`) appropriately
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### TypeScript/JavaScript
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- Strict TypeScript configuration
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- ESLint with Prettier integration
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- Avoid `any` type
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## Important Notes
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- **Environment Variables**: Always use UV for Python commands: `uv run --project api <command>`
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- **Comments**: Only write meaningful comments that explain "why", not "what"
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- **File Creation**: Always prefer editing existing files over creating new ones
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- **Documentation**: Don't create documentation files unless explicitly requested
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- **Code Quality**: Always run `./dev/reformat` before committing backend changes
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## Common Development Tasks
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### Adding a New API Endpoint
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1. Create controller in `/api/controllers/`
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1. Add service logic in `/api/services/`
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1. Update routes in controller's `__init__.py`
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1. Write tests in `/api/tests/`
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## Project-Specific Conventions
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- All async tasks use Celery with Redis as broker
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- **Internationalization**: Frontend supports multiple languages with English (`web/i18n/en-US/`) as the source. All user-facing text must use i18n keys, no hardcoded strings. Edit corresponding module files in `en-US/` directory for translations.
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89
CLAUDE.md
89
CLAUDE.md
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@ -1,89 +0,0 @@
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# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Project Overview
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Dify is an open-source platform for developing LLM applications with an intuitive interface combining agentic AI workflows, RAG pipelines, agent capabilities, and model management.
|
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|
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The codebase consists of:
|
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|
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- **Backend API** (`/api`): Python Flask application with Domain-Driven Design architecture
|
||||
- **Frontend Web** (`/web`): Next.js 15 application with TypeScript and React 19
|
||||
- **Docker deployment** (`/docker`): Containerized deployment configurations
|
||||
|
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## Development Commands
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||||
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### Backend (API)
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|
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All Python commands must be prefixed with `uv run --project api`:
|
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|
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```bash
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# Start development servers
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./dev/start-api # Start API server
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./dev/start-worker # Start Celery worker
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# Run tests
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uv run --project api pytest # Run all tests
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uv run --project api pytest tests/unit_tests/ # Unit tests only
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uv run --project api pytest tests/integration_tests/ # Integration tests
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# Code quality
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./dev/reformat # Run all formatters and linters
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uv run --project api ruff check --fix ./ # Fix linting issues
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uv run --project api ruff format ./ # Format code
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uv run --directory api basedpyright # Type checking
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```
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### Frontend (Web)
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```bash
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cd web
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pnpm lint # Run ESLint
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pnpm eslint-fix # Fix ESLint issues
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pnpm test # Run Jest tests
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```
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|
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## Testing Guidelines
|
||||
|
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### Backend Testing
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||||
|
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- Use `pytest` for all backend tests
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- Write tests first (TDD approach)
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- Test structure: Arrange-Act-Assert
|
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|
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## Code Style Requirements
|
||||
|
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### Python
|
||||
|
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- Use type hints for all functions and class attributes
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- No `Any` types unless absolutely necessary
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- Implement special methods (`__repr__`, `__str__`) appropriately
|
||||
|
||||
### TypeScript/JavaScript
|
||||
|
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- Strict TypeScript configuration
|
||||
- ESLint with Prettier integration
|
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- Avoid `any` type
|
||||
|
||||
## Important Notes
|
||||
|
||||
- **Environment Variables**: Always use UV for Python commands: `uv run --project api <command>`
|
||||
- **Comments**: Only write meaningful comments that explain "why", not "what"
|
||||
- **File Creation**: Always prefer editing existing files over creating new ones
|
||||
- **Documentation**: Don't create documentation files unless explicitly requested
|
||||
- **Code Quality**: Always run `./dev/reformat` before committing backend changes
|
||||
|
||||
## Common Development Tasks
|
||||
|
||||
### Adding a New API Endpoint
|
||||
|
||||
1. Create controller in `/api/controllers/`
|
||||
1. Add service logic in `/api/services/`
|
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1. Update routes in controller's `__init__.py`
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1. Write tests in `/api/tests/`
|
||||
|
||||
## Project-Specific Conventions
|
||||
|
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- All async tasks use Celery with Redis as broker
|
||||
- **Internationalization**: Frontend supports multiple languages with English (`web/i18n/en-US/`) as the source. All user-facing text must use i18n keys, no hardcoded strings. Edit corresponding module files in `en-US/` directory for translations.
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@ -371,13 +371,14 @@ class WorkflowService:
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def _validate_llm_model_config(self, tenant_id: str, provider: str, model_name: str) -> None:
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"""
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Validate that an LLM model configuration can fetch valid credentials.
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Validate that an LLM model configuration can fetch valid credentials and has active status.
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This method attempts to get the model instance and validates that:
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1. The provider exists and is configured
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2. The model exists in the provider
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3. Credentials can be fetched for the model
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4. The credentials pass policy compliance checks
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5. The model status is ACTIVE (not NO_CONFIGURE, DISABLED, etc.)
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:param tenant_id: The tenant ID
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:param provider: The provider name
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@ -387,6 +388,7 @@ class WorkflowService:
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try:
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from core.model_manager import ModelManager
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from core.model_runtime.entities.model_entities import ModelType
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from core.provider_manager import ProviderManager
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# Get model instance to validate provider+model combination
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model_manager = ModelManager()
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@ -398,6 +400,22 @@ class WorkflowService:
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# via ProviderConfiguration.get_current_credentials() -> _check_credential_policy_compliance()
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# If it fails, an exception will be raised
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# Additionally, check the model status to ensure it's ACTIVE
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provider_manager = ProviderManager()
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provider_configurations = provider_manager.get_configurations(tenant_id)
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models = provider_configurations.get_models(provider=provider, model_type=ModelType.LLM)
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target_model = None
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for model in models:
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if model.model == model_name and model.provider.provider == provider:
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target_model = model
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break
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if target_model:
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target_model.raise_for_status()
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else:
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raise ValueError(f"Model {model_name} not found for provider {provider}")
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except Exception as e:
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raise ValueError(
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f"Failed to validate LLM model configuration (provider: {provider}, model: {model_name}): {str(e)}"
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