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# Test Generation Checklist
Use this checklist when generating or reviewing tests for Dify frontend components.
## Pre-Generation
- [ ] Read the component source code completely
- [ ] Identify component type (component, hook, utility, page)
- [ ] Run `pnpm analyze-component <path>` if available
- [ ] Note complexity score and features detected
- [ ] Check for existing tests in the same directory
- [ ] **Identify ALL files in the directory** that need testing (not just index)
## Testing Strategy
### ⚠️ Incremental Workflow (CRITICAL for Multi-File)
- [ ] **NEVER generate all tests at once** - process one file at a time
- [ ] Order files by complexity: utilities → hooks → simple → complex → integration
- [ ] Create a todo list to track progress before starting
- [ ] For EACH file: write → run test → verify pass → then next
- [ ] **DO NOT proceed** to next file until current one passes
### Path-Level Coverage
- [ ] **Test ALL files** in the assigned directory/path
- [ ] List all components, hooks, utilities that need coverage
- [ ] Decide: single spec file (integration) or multiple spec files (unit)
### Complexity Assessment
- [ ] Run `pnpm analyze-component <path>` for complexity score
- [ ] **Complexity > 50**: Consider refactoring before testing
- [ ] **500+ lines**: Consider splitting before testing
- [ ] **30-50 complexity**: Use multiple describe blocks, organized structure
### Integration vs Mocking
- [ ] **DO NOT mock base components** (`Loading`, `Button`, `Tooltip`, etc.)
- [ ] Import real project components instead of mocking
- [ ] Only mock: API calls, complex context providers, third-party libs with side effects
- [ ] Prefer integration testing when using single spec file
## Required Test Sections
### All Components MUST Have
- [ ] **Rendering tests** - Component renders without crashing
- [ ] **Props tests** - Required props, optional props, default values
- [ ] **Edge cases** - null, undefined, empty values, boundaries
### Conditional Sections (Add When Feature Present)
| Feature | Add Tests For |
|---------|---------------|
| `useState` | Initial state, transitions, cleanup |
| `useEffect` | Execution, dependencies, cleanup |
| Event handlers | onClick, onChange, onSubmit, keyboard |
| API calls | Loading, success, error states |
| Routing | Navigation, params, query strings |
| `useCallback`/`useMemo` | Referential equality |
| Context | Provider values, consumer behavior |
| Forms | Validation, submission, error display |
## Code Quality Checklist
### Structure
- [ ] Uses `describe` blocks to group related tests
- [ ] Test names follow `should <behavior> when <condition>` pattern
- [ ] AAA pattern (Arrange-Act-Assert) is clear
- [ ] Comments explain complex test scenarios
### Mocks
- [ ] **DO NOT mock base components** (`@/app/components/base/*`)
- [ ] `jest.clearAllMocks()` in `beforeEach` (not `afterEach`)
- [ ] Shared mock state reset in `beforeEach`
- [ ] i18n mock returns keys (not empty strings)
- [ ] Router mocks match actual Next.js API
- [ ] Mocks reflect actual component conditional behavior
- [ ] Only mock: API services, complex context providers, third-party libs
### Queries
- [ ] Prefer semantic queries (`getByRole`, `getByLabelText`)
- [ ] Use `queryBy*` for absence assertions
- [ ] Use `findBy*` for async elements
- [ ] `getByTestId` only as last resort
### Async
- [ ] All async tests use `async/await`
- [ ] `waitFor` wraps async assertions
- [ ] Fake timers properly setup/teardown
- [ ] No floating promises
### TypeScript
- [ ] No `any` types without justification
- [ ] Mock data uses actual types from source
- [ ] Factory functions have proper return types
## Coverage Goals (Per File)
For the current file being tested:
- [ ] 100% function coverage
- [ ] 100% statement coverage
- [ ] >95% branch coverage
- [ ] >95% line coverage
## Post-Generation (Per File)
**Run these checks after EACH test file, not just at the end:**
- [ ] Run `pnpm test -- path/to/file.spec.tsx` - **MUST PASS before next file**
- [ ] Fix any failures immediately
- [ ] Mark file as complete in todo list
- [ ] Only then proceed to next file
### After All Files Complete
- [ ] Run full directory test: `pnpm test -- path/to/directory/`
- [ ] Check coverage report: `pnpm test -- --coverage`
- [ ] Run `pnpm lint:fix` on all test files
- [ ] Run `pnpm type-check:tsgo`
## Common Issues to Watch
### False Positives
```typescript
// ❌ Mock doesn't match actual behavior
jest.mock('./Component', () => () => <div>Mocked</div>)
// ✅ Mock matches actual conditional logic
jest.mock('./Component', () => ({ isOpen }: any) =>
isOpen ? <div>Content</div> : null
)
```
### State Leakage
```typescript
// ❌ Shared state not reset
let mockState = false
jest.mock('./useHook', () => () => mockState)
// ✅ Reset in beforeEach
beforeEach(() => {
mockState = false
})
```
### Async Race Conditions
```typescript
// ❌ Not awaited
it('loads data', () => {
render(<Component />)
expect(screen.getByText('Data')).toBeInTheDocument()
})
// ✅ Properly awaited
it('loads data', async () => {
render(<Component />)
await waitFor(() => {
expect(screen.getByText('Data')).toBeInTheDocument()
})
})
```
### Missing Edge Cases
Always test these scenarios:
- `null` / `undefined` inputs
- Empty strings / arrays / objects
- Boundary values (0, -1, MAX_INT)
- Error states
- Loading states
- Disabled states
## Quick Commands
```bash
# Run specific test
pnpm test -- path/to/file.spec.tsx
# Run with coverage
pnpm test -- --coverage path/to/file.spec.tsx
# Watch mode
pnpm test -- --watch path/to/file.spec.tsx
# Update snapshots (use sparingly)
pnpm test -- -u path/to/file.spec.tsx
# Analyze component
pnpm analyze-component path/to/component.tsx
# Review existing test
pnpm analyze-component path/to/component.tsx --review
```

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---
name: Dify Frontend Testing
description: Generate Jest + React Testing Library tests for Dify frontend components, hooks, and utilities. Triggers on testing, spec files, coverage, Jest, RTL, unit tests, integration tests, or write/review test requests.
---
# Dify Frontend Testing Skill
This skill enables Claude to generate high-quality, comprehensive frontend tests for the Dify project following established conventions and best practices.
> **⚠️ Authoritative Source**: This skill is derived from `web/testing/testing.md`. When in doubt, always refer to that document as the canonical specification.
## When to Apply This Skill
Apply this skill when the user:
- Asks to **write tests** for a component, hook, or utility
- Asks to **review existing tests** for completeness
- Mentions **Jest**, **React Testing Library**, **RTL**, or **spec files**
- Requests **test coverage** improvement
- Uses `pnpm analyze-component` output as context
- Mentions **testing**, **unit tests**, or **integration tests** for frontend code
- Wants to understand **testing patterns** in the Dify codebase
**Do NOT apply** when:
- User is asking about backend/API tests (Python/pytest)
- User is asking about E2E tests (Playwright/Cypress)
- User is only asking conceptual questions without code context
## Quick Reference
### Tech Stack
| Tool | Version | Purpose |
|------|---------|---------|
| Jest | 29.7 | Test runner |
| React Testing Library | 16.0 | Component testing |
| happy-dom | - | Test environment |
| nock | 14.0 | HTTP mocking |
| TypeScript | 5.x | Type safety |
### Key Commands
```bash
# Run all tests
pnpm test
# Watch mode
pnpm test -- --watch
# Run specific file
pnpm test -- path/to/file.spec.tsx
# Generate coverage report
pnpm test -- --coverage
# Analyze component complexity
pnpm analyze-component <path>
# Review existing test
pnpm analyze-component <path> --review
```
### File Naming
- Test files: `ComponentName.spec.tsx` (same directory as component)
- Integration tests: `web/__tests__/` directory
## Test Structure Template
```typescript
import { render, screen, fireEvent, waitFor } from '@testing-library/react'
import Component from './index'
// ✅ Import real project components (DO NOT mock these)
// import Loading from '@/app/components/base/loading'
// import { ChildComponent } from './child-component'
// ✅ Mock external dependencies only
jest.mock('@/service/api')
jest.mock('next/navigation', () => ({
useRouter: () => ({ push: jest.fn() }),
usePathname: () => '/test',
}))
// Shared state for mocks (if needed)
let mockSharedState = false
describe('ComponentName', () => {
beforeEach(() => {
jest.clearAllMocks() // ✅ Reset mocks BEFORE each test
mockSharedState = false // ✅ Reset shared state
})
// Rendering tests (REQUIRED)
describe('Rendering', () => {
it('should render without crashing', () => {
// Arrange
const props = { title: 'Test' }
// Act
render(<Component {...props} />)
// Assert
expect(screen.getByText('Test')).toBeInTheDocument()
})
})
// Props tests (REQUIRED)
describe('Props', () => {
it('should apply custom className', () => {
render(<Component className="custom" />)
expect(screen.getByRole('button')).toHaveClass('custom')
})
})
// User Interactions
describe('User Interactions', () => {
it('should handle click events', () => {
const handleClick = jest.fn()
render(<Component onClick={handleClick} />)
fireEvent.click(screen.getByRole('button'))
expect(handleClick).toHaveBeenCalledTimes(1)
})
})
// Edge Cases (REQUIRED)
describe('Edge Cases', () => {
it('should handle null data', () => {
render(<Component data={null} />)
expect(screen.getByText(/no data/i)).toBeInTheDocument()
})
it('should handle empty array', () => {
render(<Component items={[]} />)
expect(screen.getByText(/empty/i)).toBeInTheDocument()
})
})
})
```
## Testing Workflow (CRITICAL)
### ⚠️ Incremental Approach Required
**NEVER generate all test files at once.** For complex components or multi-file directories:
1. **Analyze & Plan**: List all files, order by complexity (simple → complex)
1. **Process ONE at a time**: Write test → Run test → Fix if needed → Next
1. **Verify before proceeding**: Do NOT continue to next file until current passes
```
For each file:
┌────────────────────────────────────────┐
│ 1. Write test │
│ 2. Run: pnpm test -- <file>.spec.tsx │
│ 3. PASS? → Mark complete, next file │
│ FAIL? → Fix first, then continue │
└────────────────────────────────────────┘
```
### Complexity-Based Order
Process in this order for multi-file testing:
1. 🟢 Utility functions (simplest)
1. 🟢 Custom hooks
1. 🟡 Simple components (presentational)
1. 🟡 Medium components (state, effects)
1. 🔴 Complex components (API, routing)
1. 🔴 Integration tests (index files - last)
### When to Refactor First
- **Complexity > 50**: Break into smaller pieces before testing
- **500+ lines**: Consider splitting before testing
- **Many dependencies**: Extract logic into hooks first
> 📖 See `guides/workflow.md` for complete workflow details and todo list format.
## Testing Strategy
### Path-Level Testing (Directory Testing)
When assigned to test a directory/path, test **ALL content** within that path:
- Test all components, hooks, utilities in the directory (not just `index` file)
- Use incremental approach: one file at a time, verify each before proceeding
- Goal: 100% coverage of ALL files in the directory
### Integration Testing First
**Prefer integration testing** when writing tests for a directory:
- ✅ **Import real project components** directly (including base components and siblings)
- ✅ **Only mock**: API services (`@/service/*`), `next/navigation`, complex context providers
- ❌ **DO NOT mock** base components (`@/app/components/base/*`)
- ❌ **DO NOT mock** sibling/child components in the same directory
> See [Test Structure Template](#test-structure-template) for correct import/mock patterns.
## Core Principles
### 1. AAA Pattern (Arrange-Act-Assert)
Every test should clearly separate:
- **Arrange**: Setup test data and render component
- **Act**: Perform user actions
- **Assert**: Verify expected outcomes
### 2. Black-Box Testing
- Test observable behavior, not implementation details
- Use semantic queries (getByRole, getByLabelText)
- Avoid testing internal state directly
- **Prefer pattern matching over hardcoded strings** in assertions:
```typescript
// ❌ Avoid: hardcoded text assertions
expect(screen.getByText('Loading...')).toBeInTheDocument()
// ✅ Better: role-based queries
expect(screen.getByRole('status')).toBeInTheDocument()
// ✅ Better: pattern matching
expect(screen.getByText(/loading/i)).toBeInTheDocument()
```
### 3. Single Behavior Per Test
Each test verifies ONE user-observable behavior:
```typescript
// ✅ Good: One behavior
it('should disable button when loading', () => {
render(<Button loading />)
expect(screen.getByRole('button')).toBeDisabled()
})
// ❌ Bad: Multiple behaviors
it('should handle loading state', () => {
render(<Button loading />)
expect(screen.getByRole('button')).toBeDisabled()
expect(screen.getByText('Loading...')).toBeInTheDocument()
expect(screen.getByRole('button')).toHaveClass('loading')
})
```
### 4. Semantic Naming
Use `should <behavior> when <condition>`:
```typescript
it('should show error message when validation fails')
it('should call onSubmit when form is valid')
it('should disable input when isReadOnly is true')
```
## Required Test Scenarios
### Always Required (All Components)
1. **Rendering**: Component renders without crashing
1. **Props**: Required props, optional props, default values
1. **Edge Cases**: null, undefined, empty values, boundary conditions
### Conditional (When Present)
| Feature | Test Focus |
|---------|-----------|
| `useState` | Initial state, transitions, cleanup |
| `useEffect` | Execution, dependencies, cleanup |
| Event handlers | All onClick, onChange, onSubmit, keyboard |
| API calls | Loading, success, error states |
| Routing | Navigation, params, query strings |
| `useCallback`/`useMemo` | Referential equality |
| Context | Provider values, consumer behavior |
| Forms | Validation, submission, error display |
## Coverage Goals (Per File)
For each test file generated, aim for:
- ✅ **100%** function coverage
- ✅ **100%** statement coverage
- ✅ **>95%** branch coverage
- ✅ **>95%** line coverage
> **Note**: For multi-file directories, process one file at a time with full coverage each. See `guides/workflow.md`.
## Detailed Guides
For more detailed information, refer to:
- `guides/workflow.md` - **Incremental testing workflow** (MUST READ for multi-file testing)
- `guides/mocking.md` - Mock patterns and best practices
- `guides/async-testing.md` - Async operations and API calls
- `guides/domain-components.md` - Workflow, Dataset, Configuration testing
- `guides/common-patterns.md` - Frequently used testing patterns
## Authoritative References
### Primary Specification (MUST follow)
- **`web/testing/testing.md`** - The canonical testing specification. This skill is derived from this document.
### Reference Examples in Codebase
- `web/utils/classnames.spec.ts` - Utility function tests
- `web/app/components/base/button/index.spec.tsx` - Component tests
- `web/__mocks__/provider-context.ts` - Mock factory example
### Project Configuration
- `web/jest.config.ts` - Jest configuration
- `web/jest.setup.ts` - Test environment setup
- `web/testing/analyze-component.js` - Component analysis tool

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# Async Testing Guide
## Core Async Patterns
### 1. waitFor - Wait for Condition
```typescript
import { render, screen, waitFor } from '@testing-library/react'
it('should load and display data', async () => {
render(<DataComponent />)
// Wait for element to appear
await waitFor(() => {
expect(screen.getByText('Loaded Data')).toBeInTheDocument()
})
})
it('should hide loading spinner after load', async () => {
render(<DataComponent />)
// Wait for element to disappear
await waitFor(() => {
expect(screen.queryByText('Loading...')).not.toBeInTheDocument()
})
})
```
### 2. findBy\* - Async Queries
```typescript
it('should show user name after fetch', async () => {
render(<UserProfile />)
// findBy returns a promise, auto-waits up to 1000ms
const userName = await screen.findByText('John Doe')
expect(userName).toBeInTheDocument()
// findByRole with options
const button = await screen.findByRole('button', { name: /submit/i })
expect(button).toBeEnabled()
})
```
### 3. userEvent for Async Interactions
```typescript
import userEvent from '@testing-library/user-event'
it('should submit form', async () => {
const user = userEvent.setup()
const onSubmit = jest.fn()
render(<Form onSubmit={onSubmit} />)
// userEvent methods are async
await user.type(screen.getByLabelText('Email'), 'test@example.com')
await user.click(screen.getByRole('button', { name: /submit/i }))
await waitFor(() => {
expect(onSubmit).toHaveBeenCalledWith({ email: 'test@example.com' })
})
})
```
## Fake Timers
### When to Use Fake Timers
- Testing components with `setTimeout`/`setInterval`
- Testing debounce/throttle behavior
- Testing animations or delayed transitions
- Testing polling or retry logic
### Basic Fake Timer Setup
```typescript
describe('Debounced Search', () => {
beforeEach(() => {
jest.useFakeTimers()
})
afterEach(() => {
jest.useRealTimers()
})
it('should debounce search input', async () => {
const onSearch = jest.fn()
render(<SearchInput onSearch={onSearch} debounceMs={300} />)
// Type in the input
fireEvent.change(screen.getByRole('textbox'), { target: { value: 'query' } })
// Search not called immediately
expect(onSearch).not.toHaveBeenCalled()
// Advance timers
jest.advanceTimersByTime(300)
// Now search is called
expect(onSearch).toHaveBeenCalledWith('query')
})
})
```
### Fake Timers with Async Code
```typescript
it('should retry on failure', async () => {
jest.useFakeTimers()
const fetchData = jest.fn()
.mockRejectedValueOnce(new Error('Network error'))
.mockResolvedValueOnce({ data: 'success' })
render(<RetryComponent fetchData={fetchData} retryDelayMs={1000} />)
// First call fails
await waitFor(() => {
expect(fetchData).toHaveBeenCalledTimes(1)
})
// Advance timer for retry
jest.advanceTimersByTime(1000)
// Second call succeeds
await waitFor(() => {
expect(fetchData).toHaveBeenCalledTimes(2)
expect(screen.getByText('success')).toBeInTheDocument()
})
jest.useRealTimers()
})
```
### Common Fake Timer Utilities
```typescript
// Run all pending timers
jest.runAllTimers()
// Run only pending timers (not new ones created during execution)
jest.runOnlyPendingTimers()
// Advance by specific time
jest.advanceTimersByTime(1000)
// Get current fake time
jest.now()
// Clear all timers
jest.clearAllTimers()
```
## API Testing Patterns
### Loading → Success → Error States
```typescript
describe('DataFetcher', () => {
beforeEach(() => {
jest.clearAllMocks()
})
it('should show loading state', () => {
mockedApi.fetchData.mockImplementation(() => new Promise(() => {})) // Never resolves
render(<DataFetcher />)
expect(screen.getByTestId('loading-spinner')).toBeInTheDocument()
})
it('should show data on success', async () => {
mockedApi.fetchData.mockResolvedValue({ items: ['Item 1', 'Item 2'] })
render(<DataFetcher />)
// Use findBy* for multiple async elements (better error messages than waitFor with multiple assertions)
const item1 = await screen.findByText('Item 1')
const item2 = await screen.findByText('Item 2')
expect(item1).toBeInTheDocument()
expect(item2).toBeInTheDocument()
expect(screen.queryByTestId('loading-spinner')).not.toBeInTheDocument()
})
it('should show error on failure', async () => {
mockedApi.fetchData.mockRejectedValue(new Error('Failed to fetch'))
render(<DataFetcher />)
await waitFor(() => {
expect(screen.getByText(/failed to fetch/i)).toBeInTheDocument()
})
})
it('should retry on error', async () => {
mockedApi.fetchData.mockRejectedValue(new Error('Network error'))
render(<DataFetcher />)
await waitFor(() => {
expect(screen.getByRole('button', { name: /retry/i })).toBeInTheDocument()
})
mockedApi.fetchData.mockResolvedValue({ items: ['Item 1'] })
fireEvent.click(screen.getByRole('button', { name: /retry/i }))
await waitFor(() => {
expect(screen.getByText('Item 1')).toBeInTheDocument()
})
})
})
```
### Testing Mutations
```typescript
it('should submit form and show success', async () => {
const user = userEvent.setup()
mockedApi.createItem.mockResolvedValue({ id: '1', name: 'New Item' })
render(<CreateItemForm />)
await user.type(screen.getByLabelText('Name'), 'New Item')
await user.click(screen.getByRole('button', { name: /create/i }))
// Button should be disabled during submission
expect(screen.getByRole('button', { name: /creating/i })).toBeDisabled()
await waitFor(() => {
expect(screen.getByText(/created successfully/i)).toBeInTheDocument()
})
expect(mockedApi.createItem).toHaveBeenCalledWith({ name: 'New Item' })
})
```
## useEffect Testing
### Testing Effect Execution
```typescript
it('should fetch data on mount', async () => {
const fetchData = jest.fn().mockResolvedValue({ data: 'test' })
render(<ComponentWithEffect fetchData={fetchData} />)
await waitFor(() => {
expect(fetchData).toHaveBeenCalledTimes(1)
})
})
```
### Testing Effect Dependencies
```typescript
it('should refetch when id changes', async () => {
const fetchData = jest.fn().mockResolvedValue({ data: 'test' })
const { rerender } = render(<ComponentWithEffect id="1" fetchData={fetchData} />)
await waitFor(() => {
expect(fetchData).toHaveBeenCalledWith('1')
})
rerender(<ComponentWithEffect id="2" fetchData={fetchData} />)
await waitFor(() => {
expect(fetchData).toHaveBeenCalledWith('2')
expect(fetchData).toHaveBeenCalledTimes(2)
})
})
```
### Testing Effect Cleanup
```typescript
it('should cleanup subscription on unmount', () => {
const subscribe = jest.fn()
const unsubscribe = jest.fn()
subscribe.mockReturnValue(unsubscribe)
const { unmount } = render(<SubscriptionComponent subscribe={subscribe} />)
expect(subscribe).toHaveBeenCalledTimes(1)
unmount()
expect(unsubscribe).toHaveBeenCalledTimes(1)
})
```
## Common Async Pitfalls
### ❌ Don't: Forget to await
```typescript
// Bad - test may pass even if assertion fails
it('should load data', () => {
render(<Component />)
waitFor(() => {
expect(screen.getByText('Data')).toBeInTheDocument()
})
})
// Good - properly awaited
it('should load data', async () => {
render(<Component />)
await waitFor(() => {
expect(screen.getByText('Data')).toBeInTheDocument()
})
})
```
### ❌ Don't: Use multiple assertions in single waitFor
```typescript
// Bad - if first assertion fails, won't know about second
await waitFor(() => {
expect(screen.getByText('Title')).toBeInTheDocument()
expect(screen.getByText('Description')).toBeInTheDocument()
})
// Good - separate waitFor or use findBy
const title = await screen.findByText('Title')
const description = await screen.findByText('Description')
expect(title).toBeInTheDocument()
expect(description).toBeInTheDocument()
```
### ❌ Don't: Mix fake timers with real async
```typescript
// Bad - fake timers don't work well with real Promises
jest.useFakeTimers()
await waitFor(() => {
expect(screen.getByText('Data')).toBeInTheDocument()
}) // May timeout!
// Good - use runAllTimers or advanceTimersByTime
jest.useFakeTimers()
render(<Component />)
jest.runAllTimers()
expect(screen.getByText('Data')).toBeInTheDocument()
```

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# Common Testing Patterns
## Query Priority
Use queries in this order (most to least preferred):
```typescript
// 1. getByRole - Most recommended (accessibility)
screen.getByRole('button', { name: /submit/i })
screen.getByRole('textbox', { name: /email/i })
screen.getByRole('heading', { level: 1 })
// 2. getByLabelText - Form fields
screen.getByLabelText('Email address')
screen.getByLabelText(/password/i)
// 3. getByPlaceholderText - When no label
screen.getByPlaceholderText('Search...')
// 4. getByText - Non-interactive elements
screen.getByText('Welcome to Dify')
screen.getByText(/loading/i)
// 5. getByDisplayValue - Current input value
screen.getByDisplayValue('current value')
// 6. getByAltText - Images
screen.getByAltText('Company logo')
// 7. getByTitle - Tooltip elements
screen.getByTitle('Close')
// 8. getByTestId - Last resort only!
screen.getByTestId('custom-element')
```
## Event Handling Patterns
### Click Events
```typescript
// Basic click
fireEvent.click(screen.getByRole('button'))
// With userEvent (preferred for realistic interaction)
const user = userEvent.setup()
await user.click(screen.getByRole('button'))
// Double click
await user.dblClick(screen.getByRole('button'))
// Right click
await user.pointer({ keys: '[MouseRight]', target: screen.getByRole('button') })
```
### Form Input
```typescript
const user = userEvent.setup()
// Type in input
await user.type(screen.getByRole('textbox'), 'Hello World')
// Clear and type
await user.clear(screen.getByRole('textbox'))
await user.type(screen.getByRole('textbox'), 'New value')
// Select option
await user.selectOptions(screen.getByRole('combobox'), 'option-value')
// Check checkbox
await user.click(screen.getByRole('checkbox'))
// Upload file
const file = new File(['content'], 'test.pdf', { type: 'application/pdf' })
await user.upload(screen.getByLabelText(/upload/i), file)
```
### Keyboard Events
```typescript
const user = userEvent.setup()
// Press Enter
await user.keyboard('{Enter}')
// Press Escape
await user.keyboard('{Escape}')
// Keyboard shortcut
await user.keyboard('{Control>}a{/Control}') // Ctrl+A
// Tab navigation
await user.tab()
// Arrow keys
await user.keyboard('{ArrowDown}')
await user.keyboard('{ArrowUp}')
```
## Component State Testing
### Testing State Transitions
```typescript
describe('Counter', () => {
it('should increment count', async () => {
const user = userEvent.setup()
render(<Counter initialCount={0} />)
// Initial state
expect(screen.getByText('Count: 0')).toBeInTheDocument()
// Trigger transition
await user.click(screen.getByRole('button', { name: /increment/i }))
// New state
expect(screen.getByText('Count: 1')).toBeInTheDocument()
})
})
```
### Testing Controlled Components
```typescript
describe('ControlledInput', () => {
it('should call onChange with new value', async () => {
const user = userEvent.setup()
const handleChange = jest.fn()
render(<ControlledInput value="" onChange={handleChange} />)
await user.type(screen.getByRole('textbox'), 'a')
expect(handleChange).toHaveBeenCalledWith('a')
})
it('should display controlled value', () => {
render(<ControlledInput value="controlled" onChange={jest.fn()} />)
expect(screen.getByRole('textbox')).toHaveValue('controlled')
})
})
```
## Conditional Rendering Testing
```typescript
describe('ConditionalComponent', () => {
it('should show loading state', () => {
render(<DataDisplay isLoading={true} data={null} />)
expect(screen.getByText(/loading/i)).toBeInTheDocument()
expect(screen.queryByTestId('data-content')).not.toBeInTheDocument()
})
it('should show error state', () => {
render(<DataDisplay isLoading={false} data={null} error="Failed to load" />)
expect(screen.getByText(/failed to load/i)).toBeInTheDocument()
})
it('should show data when loaded', () => {
render(<DataDisplay isLoading={false} data={{ name: 'Test' }} />)
expect(screen.getByText('Test')).toBeInTheDocument()
})
it('should show empty state when no data', () => {
render(<DataDisplay isLoading={false} data={[]} />)
expect(screen.getByText(/no data/i)).toBeInTheDocument()
})
})
```
## List Rendering Testing
```typescript
describe('ItemList', () => {
const items = [
{ id: '1', name: 'Item 1' },
{ id: '2', name: 'Item 2' },
{ id: '3', name: 'Item 3' },
]
it('should render all items', () => {
render(<ItemList items={items} />)
expect(screen.getAllByRole('listitem')).toHaveLength(3)
items.forEach(item => {
expect(screen.getByText(item.name)).toBeInTheDocument()
})
})
it('should handle item selection', async () => {
const user = userEvent.setup()
const onSelect = jest.fn()
render(<ItemList items={items} onSelect={onSelect} />)
await user.click(screen.getByText('Item 2'))
expect(onSelect).toHaveBeenCalledWith(items[1])
})
it('should handle empty list', () => {
render(<ItemList items={[]} />)
expect(screen.getByText(/no items/i)).toBeInTheDocument()
})
})
```
## Modal/Dialog Testing
```typescript
describe('Modal', () => {
it('should not render when closed', () => {
render(<Modal isOpen={false} onClose={jest.fn()} />)
expect(screen.queryByRole('dialog')).not.toBeInTheDocument()
})
it('should render when open', () => {
render(<Modal isOpen={true} onClose={jest.fn()} />)
expect(screen.getByRole('dialog')).toBeInTheDocument()
})
it('should call onClose when clicking overlay', async () => {
const user = userEvent.setup()
const handleClose = jest.fn()
render(<Modal isOpen={true} onClose={handleClose} />)
await user.click(screen.getByTestId('modal-overlay'))
expect(handleClose).toHaveBeenCalled()
})
it('should call onClose when pressing Escape', async () => {
const user = userEvent.setup()
const handleClose = jest.fn()
render(<Modal isOpen={true} onClose={handleClose} />)
await user.keyboard('{Escape}')
expect(handleClose).toHaveBeenCalled()
})
it('should trap focus inside modal', async () => {
const user = userEvent.setup()
render(
<Modal isOpen={true} onClose={jest.fn()}>
<button>First</button>
<button>Second</button>
</Modal>
)
// Focus should cycle within modal
await user.tab()
expect(screen.getByText('First')).toHaveFocus()
await user.tab()
expect(screen.getByText('Second')).toHaveFocus()
await user.tab()
expect(screen.getByText('First')).toHaveFocus() // Cycles back
})
})
```
## Form Testing
```typescript
describe('LoginForm', () => {
it('should submit valid form', async () => {
const user = userEvent.setup()
const onSubmit = jest.fn()
render(<LoginForm onSubmit={onSubmit} />)
await user.type(screen.getByLabelText(/email/i), 'test@example.com')
await user.type(screen.getByLabelText(/password/i), 'password123')
await user.click(screen.getByRole('button', { name: /sign in/i }))
expect(onSubmit).toHaveBeenCalledWith({
email: 'test@example.com',
password: 'password123',
})
})
it('should show validation errors', async () => {
const user = userEvent.setup()
render(<LoginForm onSubmit={jest.fn()} />)
// Submit empty form
await user.click(screen.getByRole('button', { name: /sign in/i }))
expect(screen.getByText(/email is required/i)).toBeInTheDocument()
expect(screen.getByText(/password is required/i)).toBeInTheDocument()
})
it('should validate email format', async () => {
const user = userEvent.setup()
render(<LoginForm onSubmit={jest.fn()} />)
await user.type(screen.getByLabelText(/email/i), 'invalid-email')
await user.click(screen.getByRole('button', { name: /sign in/i }))
expect(screen.getByText(/invalid email/i)).toBeInTheDocument()
})
it('should disable submit button while submitting', async () => {
const user = userEvent.setup()
const onSubmit = jest.fn(() => new Promise(resolve => setTimeout(resolve, 100)))
render(<LoginForm onSubmit={onSubmit} />)
await user.type(screen.getByLabelText(/email/i), 'test@example.com')
await user.type(screen.getByLabelText(/password/i), 'password123')
await user.click(screen.getByRole('button', { name: /sign in/i }))
expect(screen.getByRole('button', { name: /signing in/i })).toBeDisabled()
await waitFor(() => {
expect(screen.getByRole('button', { name: /sign in/i })).toBeEnabled()
})
})
})
```
## Data-Driven Tests with test.each
```typescript
describe('StatusBadge', () => {
test.each([
['success', 'bg-green-500'],
['warning', 'bg-yellow-500'],
['error', 'bg-red-500'],
['info', 'bg-blue-500'],
])('should apply correct class for %s status', (status, expectedClass) => {
render(<StatusBadge status={status} />)
expect(screen.getByTestId('status-badge')).toHaveClass(expectedClass)
})
test.each([
{ input: null, expected: 'Unknown' },
{ input: undefined, expected: 'Unknown' },
{ input: '', expected: 'Unknown' },
{ input: 'invalid', expected: 'Unknown' },
])('should show "Unknown" for invalid input: $input', ({ input, expected }) => {
render(<StatusBadge status={input} />)
expect(screen.getByText(expected)).toBeInTheDocument()
})
})
```
## Debugging Tips
```typescript
// Print entire DOM
screen.debug()
// Print specific element
screen.debug(screen.getByRole('button'))
// Log testing playground URL
screen.logTestingPlaygroundURL()
// Pretty print DOM
import { prettyDOM } from '@testing-library/react'
console.log(prettyDOM(screen.getByRole('dialog')))
// Check available roles
import { getRoles } from '@testing-library/react'
console.log(getRoles(container))
```
## Common Mistakes to Avoid
### ❌ Don't Use Implementation Details
```typescript
// Bad - testing implementation
expect(component.state.isOpen).toBe(true)
expect(wrapper.find('.internal-class').length).toBe(1)
// Good - testing behavior
expect(screen.getByRole('dialog')).toBeInTheDocument()
```
### ❌ Don't Forget Cleanup
```typescript
// Bad - may leak state between tests
it('test 1', () => {
render(<Component />)
})
// Good - cleanup is automatic with RTL, but reset mocks
beforeEach(() => {
jest.clearAllMocks()
})
```
### ❌ Don't Use Exact String Matching (Prefer Black-Box Assertions)
```typescript
// ❌ Bad - hardcoded strings are brittle
expect(screen.getByText('Submit Form')).toBeInTheDocument()
expect(screen.getByText('Loading...')).toBeInTheDocument()
// ✅ Good - role-based queries (most semantic)
expect(screen.getByRole('button', { name: /submit/i })).toBeInTheDocument()
expect(screen.getByRole('status')).toBeInTheDocument()
// ✅ Good - pattern matching (flexible)
expect(screen.getByText(/submit/i)).toBeInTheDocument()
expect(screen.getByText(/loading/i)).toBeInTheDocument()
// ✅ Good - test behavior, not exact UI text
expect(screen.getByRole('button')).toBeDisabled()
expect(screen.getByRole('alert')).toBeInTheDocument()
```
**Why prefer black-box assertions?**
- Text content may change (i18n, copy updates)
- Role-based queries test accessibility
- Pattern matching is resilient to minor changes
- Tests focus on behavior, not implementation details
### ❌ Don't Assert on Absence Without Query
```typescript
// Bad - throws if not found
expect(screen.getByText('Error')).not.toBeInTheDocument() // Error!
// Good - use queryBy for absence assertions
expect(screen.queryByText('Error')).not.toBeInTheDocument()
```

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@ -0,0 +1,523 @@
# Domain-Specific Component Testing
This guide covers testing patterns for Dify's domain-specific components.
## Workflow Components (`workflow/`)
Workflow components handle node configuration, data flow, and graph operations.
### Key Test Areas
1. **Node Configuration**
1. **Data Validation**
1. **Variable Passing**
1. **Edge Connections**
1. **Error Handling**
### Example: Node Configuration Panel
```typescript
import { render, screen, fireEvent, waitFor } from '@testing-library/react'
import userEvent from '@testing-library/user-event'
import NodeConfigPanel from './node-config-panel'
import { createMockNode, createMockWorkflowContext } from '@/__mocks__/workflow'
// Mock workflow context
jest.mock('@/app/components/workflow/hooks', () => ({
useWorkflowStore: () => mockWorkflowStore,
useNodesInteractions: () => mockNodesInteractions,
}))
let mockWorkflowStore = {
nodes: [],
edges: [],
updateNode: jest.fn(),
}
let mockNodesInteractions = {
handleNodeSelect: jest.fn(),
handleNodeDelete: jest.fn(),
}
describe('NodeConfigPanel', () => {
beforeEach(() => {
jest.clearAllMocks()
mockWorkflowStore = {
nodes: [],
edges: [],
updateNode: jest.fn(),
}
})
describe('Node Configuration', () => {
it('should render node type selector', () => {
const node = createMockNode({ type: 'llm' })
render(<NodeConfigPanel node={node} />)
expect(screen.getByLabelText(/model/i)).toBeInTheDocument()
})
it('should update node config on change', async () => {
const user = userEvent.setup()
const node = createMockNode({ type: 'llm' })
render(<NodeConfigPanel node={node} />)
await user.selectOptions(screen.getByLabelText(/model/i), 'gpt-4')
expect(mockWorkflowStore.updateNode).toHaveBeenCalledWith(
node.id,
expect.objectContaining({ model: 'gpt-4' })
)
})
})
describe('Data Validation', () => {
it('should show error for invalid input', async () => {
const user = userEvent.setup()
const node = createMockNode({ type: 'code' })
render(<NodeConfigPanel node={node} />)
// Enter invalid code
const codeInput = screen.getByLabelText(/code/i)
await user.clear(codeInput)
await user.type(codeInput, 'invalid syntax {{{')
await waitFor(() => {
expect(screen.getByText(/syntax error/i)).toBeInTheDocument()
})
})
it('should validate required fields', async () => {
const node = createMockNode({ type: 'http', data: { url: '' } })
render(<NodeConfigPanel node={node} />)
fireEvent.click(screen.getByRole('button', { name: /save/i }))
await waitFor(() => {
expect(screen.getByText(/url is required/i)).toBeInTheDocument()
})
})
})
describe('Variable Passing', () => {
it('should display available variables from upstream nodes', () => {
const upstreamNode = createMockNode({
id: 'node-1',
type: 'start',
data: { outputs: [{ name: 'user_input', type: 'string' }] },
})
const currentNode = createMockNode({
id: 'node-2',
type: 'llm',
})
mockWorkflowStore.nodes = [upstreamNode, currentNode]
mockWorkflowStore.edges = [{ source: 'node-1', target: 'node-2' }]
render(<NodeConfigPanel node={currentNode} />)
// Variable selector should show upstream variables
fireEvent.click(screen.getByRole('button', { name: /add variable/i }))
expect(screen.getByText('user_input')).toBeInTheDocument()
})
it('should insert variable into prompt template', async () => {
const user = userEvent.setup()
const node = createMockNode({ type: 'llm' })
render(<NodeConfigPanel node={node} />)
// Click variable button
await user.click(screen.getByRole('button', { name: /insert variable/i }))
await user.click(screen.getByText('user_input'))
const promptInput = screen.getByLabelText(/prompt/i)
expect(promptInput).toHaveValue(expect.stringContaining('{{user_input}}'))
})
})
})
```
## Dataset Components (`dataset/`)
Dataset components handle file uploads, data display, and search/filter operations.
### Key Test Areas
1. **File Upload**
1. **File Type Validation**
1. **Pagination**
1. **Search & Filtering**
1. **Data Format Handling**
### Example: Document Uploader
```typescript
import { render, screen, fireEvent, waitFor } from '@testing-library/react'
import userEvent from '@testing-library/user-event'
import DocumentUploader from './document-uploader'
jest.mock('@/service/datasets', () => ({
uploadDocument: jest.fn(),
parseDocument: jest.fn(),
}))
import * as datasetService from '@/service/datasets'
const mockedService = datasetService as jest.Mocked<typeof datasetService>
describe('DocumentUploader', () => {
beforeEach(() => {
jest.clearAllMocks()
})
describe('File Upload', () => {
it('should accept valid file types', async () => {
const user = userEvent.setup()
const onUpload = jest.fn()
mockedService.uploadDocument.mockResolvedValue({ id: 'doc-1' })
render(<DocumentUploader onUpload={onUpload} />)
const file = new File(['content'], 'test.pdf', { type: 'application/pdf' })
const input = screen.getByLabelText(/upload/i)
await user.upload(input, file)
await waitFor(() => {
expect(mockedService.uploadDocument).toHaveBeenCalledWith(
expect.any(FormData)
)
})
})
it('should reject invalid file types', async () => {
const user = userEvent.setup()
render(<DocumentUploader />)
const file = new File(['content'], 'test.exe', { type: 'application/x-msdownload' })
const input = screen.getByLabelText(/upload/i)
await user.upload(input, file)
expect(screen.getByText(/unsupported file type/i)).toBeInTheDocument()
expect(mockedService.uploadDocument).not.toHaveBeenCalled()
})
it('should show upload progress', async () => {
const user = userEvent.setup()
// Mock upload with progress
mockedService.uploadDocument.mockImplementation(() => {
return new Promise((resolve) => {
setTimeout(() => resolve({ id: 'doc-1' }), 100)
})
})
render(<DocumentUploader />)
const file = new File(['content'], 'test.pdf', { type: 'application/pdf' })
await user.upload(screen.getByLabelText(/upload/i), file)
expect(screen.getByRole('progressbar')).toBeInTheDocument()
await waitFor(() => {
expect(screen.queryByRole('progressbar')).not.toBeInTheDocument()
})
})
})
describe('Error Handling', () => {
it('should handle upload failure', async () => {
const user = userEvent.setup()
mockedService.uploadDocument.mockRejectedValue(new Error('Upload failed'))
render(<DocumentUploader />)
const file = new File(['content'], 'test.pdf', { type: 'application/pdf' })
await user.upload(screen.getByLabelText(/upload/i), file)
await waitFor(() => {
expect(screen.getByText(/upload failed/i)).toBeInTheDocument()
})
})
it('should allow retry after failure', async () => {
const user = userEvent.setup()
mockedService.uploadDocument
.mockRejectedValueOnce(new Error('Network error'))
.mockResolvedValueOnce({ id: 'doc-1' })
render(<DocumentUploader />)
const file = new File(['content'], 'test.pdf', { type: 'application/pdf' })
await user.upload(screen.getByLabelText(/upload/i), file)
await waitFor(() => {
expect(screen.getByRole('button', { name: /retry/i })).toBeInTheDocument()
})
await user.click(screen.getByRole('button', { name: /retry/i }))
await waitFor(() => {
expect(screen.getByText(/uploaded successfully/i)).toBeInTheDocument()
})
})
})
})
```
### Example: Document List with Pagination
```typescript
describe('DocumentList', () => {
describe('Pagination', () => {
it('should load first page on mount', async () => {
mockedService.getDocuments.mockResolvedValue({
data: [{ id: '1', name: 'Doc 1' }],
total: 50,
page: 1,
pageSize: 10,
})
render(<DocumentList datasetId="ds-1" />)
await waitFor(() => {
expect(screen.getByText('Doc 1')).toBeInTheDocument()
})
expect(mockedService.getDocuments).toHaveBeenCalledWith('ds-1', { page: 1 })
})
it('should navigate to next page', async () => {
const user = userEvent.setup()
mockedService.getDocuments.mockResolvedValue({
data: [{ id: '1', name: 'Doc 1' }],
total: 50,
page: 1,
pageSize: 10,
})
render(<DocumentList datasetId="ds-1" />)
await waitFor(() => {
expect(screen.getByText('Doc 1')).toBeInTheDocument()
})
mockedService.getDocuments.mockResolvedValue({
data: [{ id: '11', name: 'Doc 11' }],
total: 50,
page: 2,
pageSize: 10,
})
await user.click(screen.getByRole('button', { name: /next/i }))
await waitFor(() => {
expect(screen.getByText('Doc 11')).toBeInTheDocument()
})
})
})
describe('Search & Filtering', () => {
it('should filter by search query', async () => {
const user = userEvent.setup()
jest.useFakeTimers()
render(<DocumentList datasetId="ds-1" />)
await user.type(screen.getByPlaceholderText(/search/i), 'test query')
// Debounce
jest.advanceTimersByTime(300)
await waitFor(() => {
expect(mockedService.getDocuments).toHaveBeenCalledWith(
'ds-1',
expect.objectContaining({ search: 'test query' })
)
})
jest.useRealTimers()
})
})
})
```
## Configuration Components (`app/configuration/`, `config/`)
Configuration components handle forms, validation, and data persistence.
### Key Test Areas
1. **Form Validation**
1. **Save/Reset**
1. **Required vs Optional Fields**
1. **Configuration Persistence**
1. **Error Feedback**
### Example: App Configuration Form
```typescript
import { render, screen, fireEvent, waitFor } from '@testing-library/react'
import userEvent from '@testing-library/user-event'
import AppConfigForm from './app-config-form'
jest.mock('@/service/apps', () => ({
updateAppConfig: jest.fn(),
getAppConfig: jest.fn(),
}))
import * as appService from '@/service/apps'
const mockedService = appService as jest.Mocked<typeof appService>
describe('AppConfigForm', () => {
const defaultConfig = {
name: 'My App',
description: '',
icon: 'default',
openingStatement: '',
}
beforeEach(() => {
jest.clearAllMocks()
mockedService.getAppConfig.mockResolvedValue(defaultConfig)
})
describe('Form Validation', () => {
it('should require app name', async () => {
const user = userEvent.setup()
render(<AppConfigForm appId="app-1" />)
await waitFor(() => {
expect(screen.getByLabelText(/name/i)).toHaveValue('My App')
})
// Clear name field
await user.clear(screen.getByLabelText(/name/i))
await user.click(screen.getByRole('button', { name: /save/i }))
expect(screen.getByText(/name is required/i)).toBeInTheDocument()
expect(mockedService.updateAppConfig).not.toHaveBeenCalled()
})
it('should validate name length', async () => {
const user = userEvent.setup()
render(<AppConfigForm appId="app-1" />)
await waitFor(() => {
expect(screen.getByLabelText(/name/i)).toBeInTheDocument()
})
// Enter very long name
await user.clear(screen.getByLabelText(/name/i))
await user.type(screen.getByLabelText(/name/i), 'a'.repeat(101))
expect(screen.getByText(/name must be less than 100 characters/i)).toBeInTheDocument()
})
it('should allow empty optional fields', async () => {
const user = userEvent.setup()
mockedService.updateAppConfig.mockResolvedValue({ success: true })
render(<AppConfigForm appId="app-1" />)
await waitFor(() => {
expect(screen.getByLabelText(/name/i)).toHaveValue('My App')
})
// Leave description empty (optional)
await user.click(screen.getByRole('button', { name: /save/i }))
await waitFor(() => {
expect(mockedService.updateAppConfig).toHaveBeenCalled()
})
})
})
describe('Save/Reset Functionality', () => {
it('should save configuration', async () => {
const user = userEvent.setup()
mockedService.updateAppConfig.mockResolvedValue({ success: true })
render(<AppConfigForm appId="app-1" />)
await waitFor(() => {
expect(screen.getByLabelText(/name/i)).toHaveValue('My App')
})
await user.clear(screen.getByLabelText(/name/i))
await user.type(screen.getByLabelText(/name/i), 'Updated App')
await user.click(screen.getByRole('button', { name: /save/i }))
await waitFor(() => {
expect(mockedService.updateAppConfig).toHaveBeenCalledWith(
'app-1',
expect.objectContaining({ name: 'Updated App' })
)
})
expect(screen.getByText(/saved successfully/i)).toBeInTheDocument()
})
it('should reset to default values', async () => {
const user = userEvent.setup()
render(<AppConfigForm appId="app-1" />)
await waitFor(() => {
expect(screen.getByLabelText(/name/i)).toHaveValue('My App')
})
// Make changes
await user.clear(screen.getByLabelText(/name/i))
await user.type(screen.getByLabelText(/name/i), 'Changed Name')
// Reset
await user.click(screen.getByRole('button', { name: /reset/i }))
expect(screen.getByLabelText(/name/i)).toHaveValue('My App')
})
it('should show unsaved changes warning', async () => {
const user = userEvent.setup()
render(<AppConfigForm appId="app-1" />)
await waitFor(() => {
expect(screen.getByLabelText(/name/i)).toHaveValue('My App')
})
// Make changes
await user.type(screen.getByLabelText(/name/i), ' Updated')
expect(screen.getByText(/unsaved changes/i)).toBeInTheDocument()
})
})
describe('Error Handling', () => {
it('should show error on save failure', async () => {
const user = userEvent.setup()
mockedService.updateAppConfig.mockRejectedValue(new Error('Server error'))
render(<AppConfigForm appId="app-1" />)
await waitFor(() => {
expect(screen.getByLabelText(/name/i)).toHaveValue('My App')
})
await user.click(screen.getByRole('button', { name: /save/i }))
await waitFor(() => {
expect(screen.getByText(/failed to save/i)).toBeInTheDocument()
})
})
})
})
```

View File

@ -0,0 +1,353 @@
# Mocking Guide for Dify Frontend Tests
## ⚠️ Important: What NOT to Mock
### DO NOT Mock Base Components
**Never mock components from `@/app/components/base/`** such as:
- `Loading`, `Spinner`
- `Button`, `Input`, `Select`
- `Tooltip`, `Modal`, `Dropdown`
- `Icon`, `Badge`, `Tag`
**Why?**
- Base components will have their own dedicated tests
- Mocking them creates false positives (tests pass but real integration fails)
- Using real components tests actual integration behavior
```typescript
// ❌ WRONG: Don't mock base components
jest.mock('@/app/components/base/loading', () => () => <div>Loading</div>)
jest.mock('@/app/components/base/button', () => ({ children }: any) => <button>{children}</button>)
// ✅ CORRECT: Import and use real base components
import Loading from '@/app/components/base/loading'
import Button from '@/app/components/base/button'
// They will render normally in tests
```
### What TO Mock
Only mock these categories:
1. **API services** (`@/service/*`) - Network calls
1. **Complex context providers** - When setup is too difficult
1. **Third-party libraries with side effects** - `next/navigation`, external SDKs
1. **i18n** - Always mock to return keys
## Mock Placement
| Location | Purpose |
|----------|---------|
| `web/__mocks__/` | Reusable mocks shared across multiple test files |
| Test file | Test-specific mocks, inline with `jest.mock()` |
## Essential Mocks
### 1. i18n (Always Required)
```typescript
jest.mock('react-i18next', () => ({
useTranslation: () => ({
t: (key: string) => key,
}),
}))
```
### 2. Next.js Router
```typescript
const mockPush = jest.fn()
const mockReplace = jest.fn()
jest.mock('next/navigation', () => ({
useRouter: () => ({
push: mockPush,
replace: mockReplace,
back: jest.fn(),
prefetch: jest.fn(),
}),
usePathname: () => '/current-path',
useSearchParams: () => new URLSearchParams('?key=value'),
}))
describe('Component', () => {
beforeEach(() => {
jest.clearAllMocks()
})
it('should navigate on click', () => {
render(<Component />)
fireEvent.click(screen.getByRole('button'))
expect(mockPush).toHaveBeenCalledWith('/expected-path')
})
})
```
### 3. Portal Components (with Shared State)
```typescript
// ⚠️ Important: Use shared state for components that depend on each other
let mockPortalOpenState = false
jest.mock('@/app/components/base/portal-to-follow-elem', () => ({
PortalToFollowElem: ({ children, open, ...props }: any) => {
mockPortalOpenState = open || false // Update shared state
return <div data-testid="portal" data-open={open}>{children}</div>
},
PortalToFollowElemContent: ({ children }: any) => {
// ✅ Matches actual: returns null when portal is closed
if (!mockPortalOpenState) return null
return <div data-testid="portal-content">{children}</div>
},
PortalToFollowElemTrigger: ({ children }: any) => (
<div data-testid="portal-trigger">{children}</div>
),
}))
describe('Component', () => {
beforeEach(() => {
jest.clearAllMocks()
mockPortalOpenState = false // ✅ Reset shared state
})
})
```
### 4. API Service Mocks
```typescript
import * as api from '@/service/api'
jest.mock('@/service/api')
const mockedApi = api as jest.Mocked<typeof api>
describe('Component', () => {
beforeEach(() => {
jest.clearAllMocks()
// Setup default mock implementation
mockedApi.fetchData.mockResolvedValue({ data: [] })
})
it('should show data on success', async () => {
mockedApi.fetchData.mockResolvedValue({ data: [{ id: 1 }] })
render(<Component />)
await waitFor(() => {
expect(screen.getByText('1')).toBeInTheDocument()
})
})
it('should show error on failure', async () => {
mockedApi.fetchData.mockRejectedValue(new Error('Network error'))
render(<Component />)
await waitFor(() => {
expect(screen.getByText(/error/i)).toBeInTheDocument()
})
})
})
```
### 5. HTTP Mocking with Nock
```typescript
import nock from 'nock'
const GITHUB_HOST = 'https://api.github.com'
const GITHUB_PATH = '/repos/owner/repo'
const mockGithubApi = (status: number, body: Record<string, unknown>, delayMs = 0) => {
return nock(GITHUB_HOST)
.get(GITHUB_PATH)
.delay(delayMs)
.reply(status, body)
}
describe('GithubComponent', () => {
afterEach(() => {
nock.cleanAll()
})
it('should display repo info', async () => {
mockGithubApi(200, { name: 'dify', stars: 1000 })
render(<GithubComponent />)
await waitFor(() => {
expect(screen.getByText('dify')).toBeInTheDocument()
})
})
it('should handle API error', async () => {
mockGithubApi(500, { message: 'Server error' })
render(<GithubComponent />)
await waitFor(() => {
expect(screen.getByText(/error/i)).toBeInTheDocument()
})
})
})
```
### 6. Context Providers
```typescript
import { ProviderContext } from '@/context/provider-context'
import { createMockProviderContextValue, createMockPlan } from '@/__mocks__/provider-context'
describe('Component with Context', () => {
it('should render for free plan', () => {
const mockContext = createMockPlan('sandbox')
render(
<ProviderContext.Provider value={mockContext}>
<Component />
</ProviderContext.Provider>
)
expect(screen.getByText('Upgrade')).toBeInTheDocument()
})
it('should render for pro plan', () => {
const mockContext = createMockPlan('professional')
render(
<ProviderContext.Provider value={mockContext}>
<Component />
</ProviderContext.Provider>
)
expect(screen.queryByText('Upgrade')).not.toBeInTheDocument()
})
})
```
### 7. SWR / React Query
```typescript
// SWR
jest.mock('swr', () => ({
__esModule: true,
default: jest.fn(),
}))
import useSWR from 'swr'
const mockedUseSWR = useSWR as jest.Mock
describe('Component with SWR', () => {
it('should show loading state', () => {
mockedUseSWR.mockReturnValue({
data: undefined,
error: undefined,
isLoading: true,
})
render(<Component />)
expect(screen.getByText(/loading/i)).toBeInTheDocument()
})
})
// React Query
import { QueryClient, QueryClientProvider } from '@tanstack/react-query'
const createTestQueryClient = () => new QueryClient({
defaultOptions: {
queries: { retry: false },
mutations: { retry: false },
},
})
const renderWithQueryClient = (ui: React.ReactElement) => {
const queryClient = createTestQueryClient()
return render(
<QueryClientProvider client={queryClient}>
{ui}
</QueryClientProvider>
)
}
```
## Mock Best Practices
### ✅ DO
1. **Use real base components** - Import from `@/app/components/base/` directly
1. **Use real project components** - Prefer importing over mocking
1. **Reset mocks in `beforeEach`**, not `afterEach`
1. **Match actual component behavior** in mocks (when mocking is necessary)
1. **Use factory functions** for complex mock data
1. **Import actual types** for type safety
1. **Reset shared mock state** in `beforeEach`
### ❌ DON'T
1. **Don't mock base components** (`Loading`, `Button`, `Tooltip`, etc.)
1. Don't mock components you can import directly
1. Don't create overly simplified mocks that miss conditional logic
1. Don't forget to clean up nock after each test
1. Don't use `any` types in mocks without necessity
### Mock Decision Tree
```
Need to use a component in test?
├─ Is it from @/app/components/base/*?
│ └─ YES → Import real component, DO NOT mock
├─ Is it a project component?
│ └─ YES → Prefer importing real component
│ Only mock if setup is extremely complex
├─ Is it an API service (@/service/*)?
│ └─ YES → Mock it
├─ Is it a third-party lib with side effects?
│ └─ YES → Mock it (next/navigation, external SDKs)
└─ Is it i18n?
└─ YES → Mock to return keys
```
## Factory Function Pattern
```typescript
// __mocks__/data-factories.ts
import type { User, Project } from '@/types'
export const createMockUser = (overrides: Partial<User> = {}): User => ({
id: 'user-1',
name: 'Test User',
email: 'test@example.com',
role: 'member',
createdAt: new Date().toISOString(),
...overrides,
})
export const createMockProject = (overrides: Partial<Project> = {}): Project => ({
id: 'project-1',
name: 'Test Project',
description: 'A test project',
owner: createMockUser(),
members: [],
createdAt: new Date().toISOString(),
...overrides,
})
// Usage in tests
it('should display project owner', () => {
const project = createMockProject({
owner: createMockUser({ name: 'John Doe' }),
})
render(<ProjectCard project={project} />)
expect(screen.getByText('John Doe')).toBeInTheDocument()
})
```

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# Testing Workflow Guide
This guide defines the workflow for generating tests, especially for complex components or directories with multiple files.
## Scope Clarification
This guide addresses **multi-file workflow** (how to process multiple test files). For coverage requirements within a single test file, see `web/testing/testing.md` § Coverage Goals.
| Scope | Rule |
|-------|------|
| **Single file** | Complete coverage in one generation (100% function, >95% branch) |
| **Multi-file directory** | Process one file at a time, verify each before proceeding |
## ⚠️ Critical Rule: Incremental Approach for Multi-File Testing
When testing a **directory with multiple files**, **NEVER generate all test files at once.** Use an incremental, verify-as-you-go approach.
### Why Incremental?
| Batch Approach (❌) | Incremental Approach (✅) |
|---------------------|---------------------------|
| Generate 5+ tests at once | Generate 1 test at a time |
| Run tests only at the end | Run test immediately after each file |
| Multiple failures compound | Single point of failure, easy to debug |
| Hard to identify root cause | Clear cause-effect relationship |
| Mock issues affect many files | Mock issues caught early |
| Messy git history | Clean, atomic commits possible |
## Single File Workflow
When testing a **single component, hook, or utility**:
```
1. Read source code completely
2. Run `pnpm analyze-component <path>` (if available)
3. Check complexity score and features detected
4. Write the test file
5. Run test: `pnpm test -- <file>.spec.tsx`
6. Fix any failures
7. Verify coverage meets goals (100% function, >95% branch)
```
## Directory/Multi-File Workflow (MUST FOLLOW)
When testing a **directory or multiple files**, follow this strict workflow:
### Step 1: Analyze and Plan
1. **List all files** that need tests in the directory
1. **Categorize by complexity**:
- 🟢 **Simple**: Utility functions, simple hooks, presentational components
- 🟡 **Medium**: Components with state, effects, or event handlers
- 🔴 **Complex**: Components with API calls, routing, or many dependencies
1. **Order by dependency**: Test dependencies before dependents
1. **Create a todo list** to track progress
### Step 2: Determine Processing Order
Process files in this recommended order:
```
1. Utility functions (simplest, no React)
2. Custom hooks (isolated logic)
3. Simple presentational components (few/no props)
4. Medium complexity components (state, effects)
5. Complex components (API, routing, many deps)
6. Container/index components (integration tests - last)
```
**Rationale**:
- Simpler files help establish mock patterns
- Hooks used by components should be tested first
- Integration tests (index files) depend on child components working
### Step 3: Process Each File Incrementally
**For EACH file in the ordered list:**
```
┌─────────────────────────────────────────────┐
│ 1. Write test file │
│ 2. Run: pnpm test -- <file>.spec.tsx │
│ 3. If FAIL → Fix immediately, re-run │
│ 4. If PASS → Mark complete in todo list │
│ 5. ONLY THEN proceed to next file │
└─────────────────────────────────────────────┘
```
**DO NOT proceed to the next file until the current one passes.**
### Step 4: Final Verification
After all individual tests pass:
```bash
# Run all tests in the directory together
pnpm test -- path/to/directory/
# Check coverage
pnpm test -- --coverage path/to/directory/
```
## Component Complexity Guidelines
Use `pnpm analyze-component <path>` to assess complexity before testing.
### 🔴 Very Complex Components (Complexity > 50)
**Consider refactoring BEFORE testing:**
- Break component into smaller, testable pieces
- Extract complex logic into custom hooks
- Separate container and presentational layers
**If testing as-is:**
- Use integration tests for complex workflows
- Use `test.each()` for data-driven testing
- Multiple `describe` blocks for organization
- Consider testing major sections separately
### 🟡 Medium Complexity (Complexity 30-50)
- Group related tests in `describe` blocks
- Test integration scenarios between internal parts
- Focus on state transitions and side effects
- Use helper functions to reduce test complexity
### 🟢 Simple Components (Complexity < 30)
- Standard test structure
- Focus on props, rendering, and edge cases
- Usually straightforward to test
### 📏 Large Files (500+ lines)
Regardless of complexity score:
- **Strongly consider refactoring** before testing
- If testing as-is, test major sections separately
- Create helper functions for test setup
- May need multiple test files
## Todo List Format
When testing multiple files, use a todo list like this:
```
Testing: path/to/directory/
Ordered by complexity (simple → complex):
☐ utils/helper.ts [utility, simple]
☐ hooks/use-custom-hook.ts [hook, simple]
☐ empty-state.tsx [component, simple]
☐ item-card.tsx [component, medium]
☐ list.tsx [component, complex]
☐ index.tsx [integration]
Progress: 0/6 complete
```
Update status as you complete each:
- ☐ → ⏳ (in progress)
- ⏳ → ✅ (complete and verified)
- ⏳ → ❌ (blocked, needs attention)
## When to Stop and Verify
**Always run tests after:**
- Completing a test file
- Making changes to fix a failure
- Modifying shared mocks
- Updating test utilities or helpers
**Signs you should pause:**
- More than 2 consecutive test failures
- Mock-related errors appearing
- Unclear why a test is failing
- Test passing but coverage unexpectedly low
## Common Pitfalls to Avoid
### ❌ Don't: Generate Everything First
```
# BAD: Writing all files then testing
Write component-a.spec.tsx
Write component-b.spec.tsx
Write component-c.spec.tsx
Write component-d.spec.tsx
Run pnpm test ← Multiple failures, hard to debug
```
### ✅ Do: Verify Each Step
```
# GOOD: Incremental with verification
Write component-a.spec.tsx
Run pnpm test -- component-a.spec.tsx ✅
Write component-b.spec.tsx
Run pnpm test -- component-b.spec.tsx ✅
...continue...
```
### ❌ Don't: Skip Verification for "Simple" Components
Even simple components can have:
- Import errors
- Missing mock setup
- Incorrect assumptions about props
**Always verify, regardless of perceived simplicity.**
### ❌ Don't: Continue When Tests Fail
Failing tests compound:
- A mock issue in file A affects files B, C, D
- Fixing A later requires revisiting all dependent tests
- Time wasted on debugging cascading failures
**Fix failures immediately before proceeding.**
## Integration with Claude's Todo Feature
When using Claude for multi-file testing:
1. **Ask Claude to create a todo list** before starting
1. **Request one file at a time** or ensure Claude processes incrementally
1. **Verify each test passes** before asking for the next
1. **Mark todos complete** as you progress
Example prompt:
```
Test all components in `path/to/directory/`.
First, analyze the directory and create a todo list ordered by complexity.
Then, process ONE file at a time, waiting for my confirmation that tests pass
before proceeding to the next.
```
## Summary Checklist
Before starting multi-file testing:
- [ ] Listed all files needing tests
- [ ] Ordered by complexity (simple → complex)
- [ ] Created todo list for tracking
- [ ] Understand dependencies between files
During testing:
- [ ] Processing ONE file at a time
- [ ] Running tests after EACH file
- [ ] Fixing failures BEFORE proceeding
- [ ] Updating todo list progress
After completion:
- [ ] All individual tests pass
- [ ] Full directory test run passes
- [ ] Coverage goals met
- [ ] Todo list shows all complete

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/**
* Test Template for React Components
*
* WHY THIS STRUCTURE?
* - Organized sections make tests easy to navigate and maintain
* - Mocks at top ensure consistent test isolation
* - Factory functions reduce duplication and improve readability
* - describe blocks group related scenarios for better debugging
*
* INSTRUCTIONS:
* 1. Replace `ComponentName` with your component name
* 2. Update import path
* 3. Add/remove test sections based on component features (use analyze-component)
* 4. Follow AAA pattern: Arrange Act Assert
*
* RUN FIRST: pnpm analyze-component <path> to identify required test scenarios
*/
import { render, screen, fireEvent, waitFor } from '@testing-library/react'
import userEvent from '@testing-library/user-event'
// import ComponentName from './index'
// ============================================================================
// Mocks
// ============================================================================
// WHY: Mocks must be hoisted to top of file (Jest requirement).
// They run BEFORE imports, so keep them before component imports.
// i18n (always required in Dify)
// WHY: Returns key instead of translation so tests don't depend on i18n files
jest.mock('react-i18next', () => ({
useTranslation: () => ({
t: (key: string) => key,
}),
}))
// Router (if component uses useRouter, usePathname, useSearchParams)
// WHY: Isolates tests from Next.js routing, enables testing navigation behavior
// const mockPush = jest.fn()
// jest.mock('next/navigation', () => ({
// useRouter: () => ({ push: mockPush }),
// usePathname: () => '/test-path',
// }))
// API services (if component fetches data)
// WHY: Prevents real network calls, enables testing all states (loading/success/error)
// jest.mock('@/service/api')
// import * as api from '@/service/api'
// const mockedApi = api as jest.Mocked<typeof api>
// Shared mock state (for portal/dropdown components)
// WHY: Portal components like PortalToFollowElem need shared state between
// parent and child mocks to correctly simulate open/close behavior
// let mockOpenState = false
// ============================================================================
// Test Data Factories
// ============================================================================
// WHY FACTORIES?
// - Avoid hard-coded test data scattered across tests
// - Easy to create variations with overrides
// - Type-safe when using actual types from source
// - Single source of truth for default test values
// const createMockProps = (overrides = {}) => ({
// // Default props that make component render successfully
// ...overrides,
// })
// const createMockItem = (overrides = {}) => ({
// id: 'item-1',
// name: 'Test Item',
// ...overrides,
// })
// ============================================================================
// Test Helpers
// ============================================================================
// const renderComponent = (props = {}) => {
// return render(<ComponentName {...createMockProps(props)} />)
// }
// ============================================================================
// Tests
// ============================================================================
describe('ComponentName', () => {
// WHY beforeEach with clearAllMocks?
// - Ensures each test starts with clean slate
// - Prevents mock call history from leaking between tests
// - MUST be beforeEach (not afterEach) to reset BEFORE assertions like toHaveBeenCalledTimes
beforeEach(() => {
jest.clearAllMocks()
// Reset shared mock state if used (CRITICAL for portal/dropdown tests)
// mockOpenState = false
})
// --------------------------------------------------------------------------
// Rendering Tests (REQUIRED - Every component MUST have these)
// --------------------------------------------------------------------------
// WHY: Catches import errors, missing providers, and basic render issues
describe('Rendering', () => {
it('should render without crashing', () => {
// Arrange - Setup data and mocks
// const props = createMockProps()
// Act - Render the component
// render(<ComponentName {...props} />)
// Assert - Verify expected output
// Prefer getByRole for accessibility; it's what users "see"
// expect(screen.getByRole('...')).toBeInTheDocument()
})
it('should render with default props', () => {
// WHY: Verifies component works without optional props
// render(<ComponentName />)
// expect(screen.getByText('...')).toBeInTheDocument()
})
})
// --------------------------------------------------------------------------
// Props Tests (REQUIRED - Every component MUST test prop behavior)
// --------------------------------------------------------------------------
// WHY: Props are the component's API contract. Test them thoroughly.
describe('Props', () => {
it('should apply custom className', () => {
// WHY: Common pattern in Dify - components should merge custom classes
// render(<ComponentName className="custom-class" />)
// expect(screen.getByTestId('component')).toHaveClass('custom-class')
})
it('should use default values for optional props', () => {
// WHY: Verifies TypeScript defaults work at runtime
// render(<ComponentName />)
// expect(screen.getByRole('...')).toHaveAttribute('...', 'default-value')
})
})
// --------------------------------------------------------------------------
// User Interactions (if component has event handlers - on*, handle*)
// --------------------------------------------------------------------------
// WHY: Event handlers are core functionality. Test from user's perspective.
describe('User Interactions', () => {
it('should call onClick when clicked', async () => {
// WHY userEvent over fireEvent?
// - userEvent simulates real user behavior (focus, hover, then click)
// - fireEvent is lower-level, doesn't trigger all browser events
// const user = userEvent.setup()
// const handleClick = jest.fn()
// render(<ComponentName onClick={handleClick} />)
//
// await user.click(screen.getByRole('button'))
//
// expect(handleClick).toHaveBeenCalledTimes(1)
})
it('should call onChange when value changes', async () => {
// const user = userEvent.setup()
// const handleChange = jest.fn()
// render(<ComponentName onChange={handleChange} />)
//
// await user.type(screen.getByRole('textbox'), 'new value')
//
// expect(handleChange).toHaveBeenCalled()
})
})
// --------------------------------------------------------------------------
// State Management (if component uses useState/useReducer)
// --------------------------------------------------------------------------
// WHY: Test state through observable UI changes, not internal state values
describe('State Management', () => {
it('should update state on interaction', async () => {
// WHY test via UI, not state?
// - State is implementation detail; UI is what users see
// - If UI works correctly, state must be correct
// const user = userEvent.setup()
// render(<ComponentName />)
//
// // Initial state - verify what user sees
// expect(screen.getByText('Initial')).toBeInTheDocument()
//
// // Trigger state change via user action
// await user.click(screen.getByRole('button'))
//
// // New state - verify UI updated
// expect(screen.getByText('Updated')).toBeInTheDocument()
})
})
// --------------------------------------------------------------------------
// Async Operations (if component fetches data - useSWR, useQuery, fetch)
// --------------------------------------------------------------------------
// WHY: Async operations have 3 states users experience: loading, success, error
describe('Async Operations', () => {
it('should show loading state', () => {
// WHY never-resolving promise?
// - Keeps component in loading state for assertion
// - Alternative: use fake timers
// mockedApi.fetchData.mockImplementation(() => new Promise(() => {}))
// render(<ComponentName />)
//
// expect(screen.getByText(/loading/i)).toBeInTheDocument()
})
it('should show data on success', async () => {
// WHY waitFor?
// - Component updates asynchronously after fetch resolves
// - waitFor retries assertion until it passes or times out
// mockedApi.fetchData.mockResolvedValue({ items: ['Item 1'] })
// render(<ComponentName />)
//
// await waitFor(() => {
// expect(screen.getByText('Item 1')).toBeInTheDocument()
// })
})
it('should show error on failure', async () => {
// mockedApi.fetchData.mockRejectedValue(new Error('Network error'))
// render(<ComponentName />)
//
// await waitFor(() => {
// expect(screen.getByText(/error/i)).toBeInTheDocument()
// })
})
})
// --------------------------------------------------------------------------
// Edge Cases (REQUIRED - Every component MUST handle edge cases)
// --------------------------------------------------------------------------
// WHY: Real-world data is messy. Components must handle:
// - Null/undefined from API failures or optional fields
// - Empty arrays/strings from user clearing data
// - Boundary values (0, MAX_INT, special characters)
describe('Edge Cases', () => {
it('should handle null value', () => {
// WHY test null specifically?
// - API might return null for missing data
// - Prevents "Cannot read property of null" in production
// render(<ComponentName value={null} />)
// expect(screen.getByText(/no data/i)).toBeInTheDocument()
})
it('should handle undefined value', () => {
// WHY test undefined separately from null?
// - TypeScript treats them differently
// - Optional props are undefined, not null
// render(<ComponentName value={undefined} />)
// expect(screen.getByText(/no data/i)).toBeInTheDocument()
})
it('should handle empty array', () => {
// WHY: Empty state often needs special UI (e.g., "No items yet")
// render(<ComponentName items={[]} />)
// expect(screen.getByText(/empty/i)).toBeInTheDocument()
})
it('should handle empty string', () => {
// WHY: Empty strings are truthy in JS but visually empty
// render(<ComponentName text="" />)
// expect(screen.getByText(/placeholder/i)).toBeInTheDocument()
})
})
// --------------------------------------------------------------------------
// Accessibility (optional but recommended for Dify's enterprise users)
// --------------------------------------------------------------------------
// WHY: Dify has enterprise customers who may require accessibility compliance
describe('Accessibility', () => {
it('should have accessible name', () => {
// WHY getByRole with name?
// - Tests that screen readers can identify the element
// - Enforces proper labeling practices
// render(<ComponentName label="Test Label" />)
// expect(screen.getByRole('button', { name: /test label/i })).toBeInTheDocument()
})
it('should support keyboard navigation', async () => {
// WHY: Some users can't use a mouse
// const user = userEvent.setup()
// render(<ComponentName />)
//
// await user.tab()
// expect(screen.getByRole('button')).toHaveFocus()
})
})
})

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/**
* Test Template for Custom Hooks
*
* Instructions:
* 1. Replace `useHookName` with your hook name
* 2. Update import path
* 3. Add/remove test sections based on hook features
*/
import { renderHook, act, waitFor } from '@testing-library/react'
// import { useHookName } from './use-hook-name'
// ============================================================================
// Mocks
// ============================================================================
// API services (if hook fetches data)
// jest.mock('@/service/api')
// import * as api from '@/service/api'
// const mockedApi = api as jest.Mocked<typeof api>
// ============================================================================
// Test Helpers
// ============================================================================
// Wrapper for hooks that need context
// const createWrapper = (contextValue = {}) => {
// return ({ children }: { children: React.ReactNode }) => (
// <SomeContext.Provider value={contextValue}>
// {children}
// </SomeContext.Provider>
// )
// }
// ============================================================================
// Tests
// ============================================================================
describe('useHookName', () => {
beforeEach(() => {
jest.clearAllMocks()
})
// --------------------------------------------------------------------------
// Initial State
// --------------------------------------------------------------------------
describe('Initial State', () => {
it('should return initial state', () => {
// const { result } = renderHook(() => useHookName())
//
// expect(result.current.value).toBe(initialValue)
// expect(result.current.isLoading).toBe(false)
})
it('should accept initial value from props', () => {
// const { result } = renderHook(() => useHookName({ initialValue: 'custom' }))
//
// expect(result.current.value).toBe('custom')
})
})
// --------------------------------------------------------------------------
// State Updates
// --------------------------------------------------------------------------
describe('State Updates', () => {
it('should update value when setValue is called', () => {
// const { result } = renderHook(() => useHookName())
//
// act(() => {
// result.current.setValue('new value')
// })
//
// expect(result.current.value).toBe('new value')
})
it('should reset to initial value', () => {
// const { result } = renderHook(() => useHookName({ initialValue: 'initial' }))
//
// act(() => {
// result.current.setValue('changed')
// })
// expect(result.current.value).toBe('changed')
//
// act(() => {
// result.current.reset()
// })
// expect(result.current.value).toBe('initial')
})
})
// --------------------------------------------------------------------------
// Async Operations
// --------------------------------------------------------------------------
describe('Async Operations', () => {
it('should fetch data on mount', async () => {
// mockedApi.fetchData.mockResolvedValue({ data: 'test' })
//
// const { result } = renderHook(() => useHookName())
//
// // Initially loading
// expect(result.current.isLoading).toBe(true)
//
// // Wait for data
// await waitFor(() => {
// expect(result.current.isLoading).toBe(false)
// })
//
// expect(result.current.data).toEqual({ data: 'test' })
})
it('should handle fetch error', async () => {
// mockedApi.fetchData.mockRejectedValue(new Error('Network error'))
//
// const { result } = renderHook(() => useHookName())
//
// await waitFor(() => {
// expect(result.current.error).toBeTruthy()
// })
//
// expect(result.current.error?.message).toBe('Network error')
})
it('should refetch when dependency changes', async () => {
// mockedApi.fetchData.mockResolvedValue({ data: 'test' })
//
// const { result, rerender } = renderHook(
// ({ id }) => useHookName(id),
// { initialProps: { id: '1' } }
// )
//
// await waitFor(() => {
// expect(mockedApi.fetchData).toHaveBeenCalledWith('1')
// })
//
// rerender({ id: '2' })
//
// await waitFor(() => {
// expect(mockedApi.fetchData).toHaveBeenCalledWith('2')
// })
})
})
// --------------------------------------------------------------------------
// Side Effects
// --------------------------------------------------------------------------
describe('Side Effects', () => {
it('should call callback when value changes', () => {
// const callback = jest.fn()
// const { result } = renderHook(() => useHookName({ onChange: callback }))
//
// act(() => {
// result.current.setValue('new value')
// })
//
// expect(callback).toHaveBeenCalledWith('new value')
})
it('should cleanup on unmount', () => {
// const cleanup = jest.fn()
// jest.spyOn(window, 'addEventListener')
// jest.spyOn(window, 'removeEventListener')
//
// const { unmount } = renderHook(() => useHookName())
//
// expect(window.addEventListener).toHaveBeenCalled()
//
// unmount()
//
// expect(window.removeEventListener).toHaveBeenCalled()
})
})
// --------------------------------------------------------------------------
// Edge Cases
// --------------------------------------------------------------------------
describe('Edge Cases', () => {
it('should handle null input', () => {
// const { result } = renderHook(() => useHookName(null))
//
// expect(result.current.value).toBeNull()
})
it('should handle rapid updates', () => {
// const { result } = renderHook(() => useHookName())
//
// act(() => {
// result.current.setValue('1')
// result.current.setValue('2')
// result.current.setValue('3')
// })
//
// expect(result.current.value).toBe('3')
})
})
// --------------------------------------------------------------------------
// With Context (if hook uses context)
// --------------------------------------------------------------------------
describe('With Context', () => {
it('should use context value', () => {
// const wrapper = createWrapper({ someValue: 'context-value' })
// const { result } = renderHook(() => useHookName(), { wrapper })
//
// expect(result.current.contextValue).toBe('context-value')
})
})
})

View File

@ -0,0 +1,154 @@
/**
* Test Template for Utility Functions
*
* Instructions:
* 1. Replace `utilityFunction` with your function name
* 2. Update import path
* 3. Use test.each for data-driven tests
*/
// import { utilityFunction } from './utility'
// ============================================================================
// Tests
// ============================================================================
describe('utilityFunction', () => {
// --------------------------------------------------------------------------
// Basic Functionality
// --------------------------------------------------------------------------
describe('Basic Functionality', () => {
it('should return expected result for valid input', () => {
// expect(utilityFunction('input')).toBe('expected-output')
})
it('should handle multiple arguments', () => {
// expect(utilityFunction('a', 'b', 'c')).toBe('abc')
})
})
// --------------------------------------------------------------------------
// Data-Driven Tests
// --------------------------------------------------------------------------
describe('Input/Output Mapping', () => {
test.each([
// [input, expected]
['input1', 'output1'],
['input2', 'output2'],
['input3', 'output3'],
])('should return %s for input %s', (input, expected) => {
// expect(utilityFunction(input)).toBe(expected)
})
})
// --------------------------------------------------------------------------
// Edge Cases
// --------------------------------------------------------------------------
describe('Edge Cases', () => {
it('should handle empty string', () => {
// expect(utilityFunction('')).toBe('')
})
it('should handle null', () => {
// expect(utilityFunction(null)).toBe(null)
// or
// expect(() => utilityFunction(null)).toThrow()
})
it('should handle undefined', () => {
// expect(utilityFunction(undefined)).toBe(undefined)
// or
// expect(() => utilityFunction(undefined)).toThrow()
})
it('should handle empty array', () => {
// expect(utilityFunction([])).toEqual([])
})
it('should handle empty object', () => {
// expect(utilityFunction({})).toEqual({})
})
})
// --------------------------------------------------------------------------
// Boundary Conditions
// --------------------------------------------------------------------------
describe('Boundary Conditions', () => {
it('should handle minimum value', () => {
// expect(utilityFunction(0)).toBe(0)
})
it('should handle maximum value', () => {
// expect(utilityFunction(Number.MAX_SAFE_INTEGER)).toBe(...)
})
it('should handle negative numbers', () => {
// expect(utilityFunction(-1)).toBe(...)
})
})
// --------------------------------------------------------------------------
// Type Coercion (if applicable)
// --------------------------------------------------------------------------
describe('Type Handling', () => {
it('should handle numeric string', () => {
// expect(utilityFunction('123')).toBe(123)
})
it('should handle boolean', () => {
// expect(utilityFunction(true)).toBe(...)
})
})
// --------------------------------------------------------------------------
// Error Cases
// --------------------------------------------------------------------------
describe('Error Handling', () => {
it('should throw for invalid input', () => {
// expect(() => utilityFunction('invalid')).toThrow('Error message')
})
it('should throw with specific error type', () => {
// expect(() => utilityFunction('invalid')).toThrow(ValidationError)
})
})
// --------------------------------------------------------------------------
// Complex Objects (if applicable)
// --------------------------------------------------------------------------
describe('Object Handling', () => {
it('should preserve object structure', () => {
// const input = { a: 1, b: 2 }
// expect(utilityFunction(input)).toEqual({ a: 1, b: 2 })
})
it('should handle nested objects', () => {
// const input = { nested: { deep: 'value' } }
// expect(utilityFunction(input)).toEqual({ nested: { deep: 'transformed' } })
})
it('should not mutate input', () => {
// const input = { a: 1 }
// const inputCopy = { ...input }
// utilityFunction(input)
// expect(input).toEqual(inputCopy)
})
})
// --------------------------------------------------------------------------
// Array Handling (if applicable)
// --------------------------------------------------------------------------
describe('Array Handling', () => {
it('should process all elements', () => {
// expect(utilityFunction([1, 2, 3])).toEqual([2, 4, 6])
})
it('should handle single element array', () => {
// expect(utilityFunction([1])).toEqual([2])
})
it('should preserve order', () => {
// expect(utilityFunction(['c', 'a', 'b'])).toEqual(['c', 'a', 'b'])
})
})
})

5
.coveragerc Normal file
View File

@ -0,0 +1,5 @@
[run]
omit =
api/tests/*
api/migrations/*
api/core/rag/datasource/vdb/*

View File

@ -1,12 +0,0 @@
# Copilot Instructions
GitHub Copilot must follow the unified frontend testing requirements documented in `web/testing/testing.md`.
Key reminders:
- Generate tests using the mandated tech stack, naming, and code style (AAA pattern, `fireEvent`, descriptive test names, cleans up mocks).
- Cover rendering, prop combinations, and edge cases by default; extend coverage for hooks, routing, async flows, and domain-specific components when applicable.
- Target >95% line and branch coverage and 100% function/statement coverage.
- Apply the project's mocking conventions for i18n, toast notifications, and Next.js utilities.
Any suggestions from Copilot that conflict with `web/testing/testing.md` should be revised before acceptance.

View File

@ -71,18 +71,18 @@ jobs:
run: |
cp api/tests/integration_tests/.env.example api/tests/integration_tests/.env
- name: Run Workflow
run: uv run --project api bash dev/pytest/pytest_workflow.sh
- name: Run Tool
run: uv run --project api bash dev/pytest/pytest_tools.sh
- name: Run TestContainers
run: uv run --project api bash dev/pytest/pytest_testcontainers.sh
- name: Run Unit tests
- name: Run API Tests
env:
STORAGE_TYPE: opendal
OPENDAL_SCHEME: fs
OPENDAL_FS_ROOT: /tmp/dify-storage
run: |
uv run --project api bash dev/pytest/pytest_unit_tests.sh
uv run --project api pytest \
--timeout "${PYTEST_TIMEOUT:-180}" \
api/tests/integration_tests/workflow \
api/tests/integration_tests/tools \
api/tests/test_containers_integration_tests \
api/tests/unit_tests
- name: Coverage Summary
run: |
@ -94,4 +94,3 @@ jobs:
echo "### Test Coverage Summary :test_tube:" >> $GITHUB_STEP_SUMMARY
echo "Total Coverage: ${TOTAL_COVERAGE}%" >> $GITHUB_STEP_SUMMARY
uv run --project api coverage report --format=markdown >> $GITHUB_STEP_SUMMARY

View File

@ -13,11 +13,12 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
# Use uv to ensure we have the same ruff version in CI and locally.
- uses: astral-sh/setup-uv@v6
- uses: actions/setup-python@v5
with:
python-version: "3.11"
- uses: astral-sh/setup-uv@v6
- run: |
cd api
uv sync --dev
@ -35,10 +36,11 @@ jobs:
- name: ast-grep
run: |
uvx --from ast-grep-cli sg --pattern 'db.session.query($WHATEVER).filter($HERE)' --rewrite 'db.session.query($WHATEVER).where($HERE)' -l py --update-all
uvx --from ast-grep-cli sg --pattern 'session.query($WHATEVER).filter($HERE)' --rewrite 'session.query($WHATEVER).where($HERE)' -l py --update-all
uvx --from ast-grep-cli sg -p '$A = db.Column($$$B)' -r '$A = mapped_column($$$B)' -l py --update-all
uvx --from ast-grep-cli sg -p '$A : $T = db.Column($$$B)' -r '$A : $T = mapped_column($$$B)' -l py --update-all
# ast-grep exits 1 if no matches are found; allow idempotent runs.
uvx --from ast-grep-cli ast-grep --pattern 'db.session.query($WHATEVER).filter($HERE)' --rewrite 'db.session.query($WHATEVER).where($HERE)' -l py --update-all || true
uvx --from ast-grep-cli ast-grep --pattern 'session.query($WHATEVER).filter($HERE)' --rewrite 'session.query($WHATEVER).where($HERE)' -l py --update-all || true
uvx --from ast-grep-cli ast-grep -p '$A = db.Column($$$B)' -r '$A = mapped_column($$$B)' -l py --update-all || true
uvx --from ast-grep-cli ast-grep -p '$A : $T = db.Column($$$B)' -r '$A : $T = mapped_column($$$B)' -l py --update-all || true
# Convert Optional[T] to T | None (ignoring quoted types)
cat > /tmp/optional-rule.yml << 'EOF'
id: convert-optional-to-union
@ -56,14 +58,15 @@ jobs:
pattern: $T
fix: $T | None
EOF
uvx --from ast-grep-cli sg scan --inline-rules "$(cat /tmp/optional-rule.yml)" --update-all
uvx --from ast-grep-cli ast-grep scan . --inline-rules "$(cat /tmp/optional-rule.yml)" --update-all
# Fix forward references that were incorrectly converted (Python doesn't support "Type" | None syntax)
find . -name "*.py" -type f -exec sed -i.bak -E 's/"([^"]+)" \| None/Optional["\1"]/g; s/'"'"'([^'"'"']+)'"'"' \| None/Optional['"'"'\1'"'"']/g' {} \;
find . -name "*.py.bak" -type f -delete
# mdformat breaks YAML front matter in markdown files. Add --exclude for directories containing YAML front matter.
- name: mdformat
run: |
uvx mdformat .
uvx --python 3.13 mdformat . --exclude ".claude/skills/**"
- name: Install pnpm
uses: pnpm/action-setup@v4
@ -84,7 +87,6 @@ jobs:
- name: oxlint
working-directory: ./web
run: |
pnpx oxlint --fix
run: pnpm exec oxlint --config .oxlintrc.json --fix .
- uses: autofix-ci/action@635ffb0c9798bd160680f18fd73371e355b85f27

View File

@ -0,0 +1,21 @@
name: Semantic Pull Request
on:
pull_request:
types:
- opened
- edited
- reopened
- synchronize
jobs:
lint:
name: Validate PR title
permissions:
pull-requests: read
runs-on: ubuntu-latest
steps:
- name: Check title
uses: amannn/action-semantic-pull-request@v6.1.1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

1
.gitignore vendored
View File

@ -189,6 +189,7 @@ docker/volumes/matrixone/*
docker/volumes/mysql/*
docker/volumes/seekdb/*
!docker/volumes/oceanbase/init.d
docker/volumes/iris/*
docker/nginx/conf.d/default.conf
docker/nginx/ssl/*

1
.nvmrc Normal file
View File

@ -0,0 +1 @@
22.11.0

View File

@ -1,5 +0,0 @@
# Windsurf Testing Rules
- Use `web/testing/testing.md` as the single source of truth for frontend automated testing.
- Honor every requirement in that document when generating or accepting tests.
- When proposing or saving tests, re-read that document and follow every requirement.

View File

@ -626,7 +626,17 @@ QUEUE_MONITOR_ALERT_EMAILS=
QUEUE_MONITOR_INTERVAL=30
# Swagger UI configuration
SWAGGER_UI_ENABLED=true
# SECURITY: Swagger UI is automatically disabled in PRODUCTION environment (DEPLOY_ENV=PRODUCTION)
# to prevent API information disclosure.
#
# Behavior:
# - DEPLOY_ENV=PRODUCTION + SWAGGER_UI_ENABLED not set -> Swagger DISABLED (secure default)
# - DEPLOY_ENV=DEVELOPMENT/TESTING + SWAGGER_UI_ENABLED not set -> Swagger ENABLED
# - SWAGGER_UI_ENABLED=true -> Swagger ENABLED (overrides environment check)
# - SWAGGER_UI_ENABLED=false -> Swagger DISABLED (explicit disable)
#
# For development, you can uncomment below or set DEPLOY_ENV=DEVELOPMENT
# SWAGGER_UI_ENABLED=false
SWAGGER_UI_PATH=/swagger-ui.html
# Whether to encrypt dataset IDs when exporting DSL files (default: true)

View File

@ -83,6 +83,7 @@ def initialize_extensions(app: DifyApp):
ext_redis,
ext_request_logging,
ext_sentry,
ext_session_factory,
ext_set_secretkey,
ext_storage,
ext_timezone,
@ -114,6 +115,7 @@ def initialize_extensions(app: DifyApp):
ext_commands,
ext_otel,
ext_request_logging,
ext_session_factory,
]
for ext in extensions:
short_name = ext.__name__.split(".")[-1]

View File

@ -1221,9 +1221,19 @@ class WorkflowLogConfig(BaseSettings):
class SwaggerUIConfig(BaseSettings):
SWAGGER_UI_ENABLED: bool = Field(
description="Whether to enable Swagger UI in api module",
default=True,
"""
Configuration for Swagger UI documentation.
Security Note: Swagger UI is automatically disabled in PRODUCTION environment
to prevent API information disclosure. Set SWAGGER_UI_ENABLED=true explicitly
to enable in production if needed.
"""
SWAGGER_UI_ENABLED: bool | None = Field(
description="Whether to enable Swagger UI in api module. "
"Automatically disabled in PRODUCTION environment for security. "
"Set to true explicitly to enable in production.",
default=None,
)
SWAGGER_UI_PATH: str = Field(
@ -1231,6 +1241,23 @@ class SwaggerUIConfig(BaseSettings):
default="/swagger-ui.html",
)
@property
def swagger_ui_enabled(self) -> bool:
"""
Compute whether Swagger UI should be enabled.
If SWAGGER_UI_ENABLED is explicitly set, use that value.
Otherwise, disable in PRODUCTION environment for security.
"""
if self.SWAGGER_UI_ENABLED is not None:
return self.SWAGGER_UI_ENABLED
# Auto-disable in production environment
import os
deploy_env = os.environ.get("DEPLOY_ENV", "PRODUCTION")
return deploy_env.upper() != "PRODUCTION"
class TenantIsolatedTaskQueueConfig(BaseSettings):
TENANT_ISOLATED_TASK_CONCURRENCY: int = Field(

View File

@ -26,6 +26,7 @@ from .vdb.clickzetta_config import ClickzettaConfig
from .vdb.couchbase_config import CouchbaseConfig
from .vdb.elasticsearch_config import ElasticsearchConfig
from .vdb.huawei_cloud_config import HuaweiCloudConfig
from .vdb.iris_config import IrisVectorConfig
from .vdb.lindorm_config import LindormConfig
from .vdb.matrixone_config import MatrixoneConfig
from .vdb.milvus_config import MilvusConfig
@ -336,6 +337,7 @@ class MiddlewareConfig(
ChromaConfig,
ClickzettaConfig,
HuaweiCloudConfig,
IrisVectorConfig,
MilvusConfig,
AlibabaCloudMySQLConfig,
MyScaleConfig,

View File

@ -0,0 +1,91 @@
"""Configuration for InterSystems IRIS vector database."""
from pydantic import Field, PositiveInt, model_validator
from pydantic_settings import BaseSettings
class IrisVectorConfig(BaseSettings):
"""Configuration settings for IRIS vector database connection and pooling."""
IRIS_HOST: str | None = Field(
description="Hostname or IP address of the IRIS server.",
default="localhost",
)
IRIS_SUPER_SERVER_PORT: PositiveInt | None = Field(
description="Port number for IRIS connection.",
default=1972,
)
IRIS_USER: str | None = Field(
description="Username for IRIS authentication.",
default="_SYSTEM",
)
IRIS_PASSWORD: str | None = Field(
description="Password for IRIS authentication.",
default="Dify@1234",
)
IRIS_SCHEMA: str | None = Field(
description="Schema name for IRIS tables.",
default="dify",
)
IRIS_DATABASE: str | None = Field(
description="Database namespace for IRIS connection.",
default="USER",
)
IRIS_CONNECTION_URL: str | None = Field(
description="Full connection URL for IRIS (overrides individual fields if provided).",
default=None,
)
IRIS_MIN_CONNECTION: PositiveInt = Field(
description="Minimum number of connections in the pool.",
default=1,
)
IRIS_MAX_CONNECTION: PositiveInt = Field(
description="Maximum number of connections in the pool.",
default=3,
)
IRIS_TEXT_INDEX: bool = Field(
description="Enable full-text search index using %iFind.Index.Basic.",
default=True,
)
IRIS_TEXT_INDEX_LANGUAGE: str = Field(
description="Language for full-text search index (e.g., 'en', 'ja', 'zh', 'de').",
default="en",
)
@model_validator(mode="before")
@classmethod
def validate_config(cls, values: dict) -> dict:
"""Validate IRIS configuration values.
Args:
values: Configuration dictionary
Returns:
Validated configuration dictionary
Raises:
ValueError: If required fields are missing or pool settings are invalid
"""
# Only validate required fields if IRIS is being used as the vector store
# This allows the config to be loaded even when IRIS is not in use
# vector_store = os.environ.get("VECTOR_STORE", "")
# We rely on Pydantic defaults for required fields if they are missing from env.
# Strict existence check is removed to allow defaults to work.
min_conn = values.get("IRIS_MIN_CONNECTION", 1)
max_conn = values.get("IRIS_MAX_CONNECTION", 3)
if min_conn > max_conn:
raise ValueError("IRIS_MIN_CONNECTION must be less than or equal to IRIS_MAX_CONNECTION")
return values

View File

@ -20,6 +20,7 @@ language_timezone_mapping = {
"sl-SI": "Europe/Ljubljana",
"th-TH": "Asia/Bangkok",
"id-ID": "Asia/Jakarta",
"ar-TN": "Africa/Tunis",
}
languages = list(language_timezone_mapping.keys())

View File

@ -6,19 +6,20 @@ from flask import request
from flask_restx import Resource
from pydantic import BaseModel, Field, field_validator
from sqlalchemy import select
from sqlalchemy.orm import Session
from werkzeug.exceptions import NotFound, Unauthorized
P = ParamSpec("P")
R = TypeVar("R")
from configs import dify_config
from constants.languages import supported_language
from controllers.console import console_ns
from controllers.console.wraps import only_edition_cloud
from core.db.session_factory import session_factory
from extensions.ext_database import db
from libs.token import extract_access_token
from models.model import App, InstalledApp, RecommendedApp
P = ParamSpec("P")
R = TypeVar("R")
DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
@ -90,7 +91,7 @@ class InsertExploreAppListApi(Resource):
privacy_policy = site.privacy_policy or payload.privacy_policy or ""
custom_disclaimer = site.custom_disclaimer or payload.custom_disclaimer or ""
with Session(db.engine) as session:
with session_factory.create_session() as session:
recommended_app = session.execute(
select(RecommendedApp).where(RecommendedApp.app_id == payload.app_id)
).scalar_one_or_none()
@ -138,7 +139,7 @@ class InsertExploreAppApi(Resource):
@only_edition_cloud
@admin_required
def delete(self, app_id):
with Session(db.engine) as session:
with session_factory.create_session() as session:
recommended_app = session.execute(
select(RecommendedApp).where(RecommendedApp.app_id == str(app_id))
).scalar_one_or_none()
@ -146,13 +147,13 @@ class InsertExploreAppApi(Resource):
if not recommended_app:
return {"result": "success"}, 204
with Session(db.engine) as session:
with session_factory.create_session() as session:
app = session.execute(select(App).where(App.id == recommended_app.app_id)).scalar_one_or_none()
if app:
app.is_public = False
with Session(db.engine) as session:
with session_factory.create_session() as session:
installed_apps = (
session.execute(
select(InstalledApp).where(

View File

@ -114,7 +114,7 @@ class AppTriggersApi(Resource):
@console_ns.route("/apps/<uuid:app_id>/trigger-enable")
class AppTriggerEnableApi(Resource):
@console_ns.expect(console_ns.models[ParserEnable.__name__], validate=True)
@console_ns.expect(console_ns.models[ParserEnable.__name__])
@setup_required
@login_required
@account_initialization_required

View File

@ -230,6 +230,7 @@ def _get_retrieval_methods_by_vector_type(vector_type: str | None, is_mock: bool
VectorType.CLICKZETTA,
VectorType.BAIDU,
VectorType.ALIBABACLOUD_MYSQL,
VectorType.IRIS,
}
semantic_methods = {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH.value]}
@ -422,7 +423,6 @@ class DatasetApi(Resource):
raise NotFound("Dataset not found.")
payload = DatasetUpdatePayload.model_validate(console_ns.payload or {})
payload_data = payload.model_dump(exclude_unset=True)
current_user, current_tenant_id = current_account_with_tenant()
# check embedding model setting
if (
@ -434,6 +434,7 @@ class DatasetApi(Resource):
dataset.tenant_id, payload.embedding_model_provider, payload.embedding_model
)
payload.is_multimodal = is_multimodal
payload_data = payload.model_dump(exclude_unset=True)
# The role of the current user in the ta table must be admin, owner, editor, or dataset_operator
DatasetPermissionService.check_permission(
current_user, dataset, payload.permission, payload.partial_member_list

View File

@ -26,7 +26,7 @@ console_ns.schema_model(Parser.__name__, Parser.model_json_schema(ref_template=D
@console_ns.route("/rag/pipelines/<uuid:pipeline_id>/workflows/published/datasource/nodes/<string:node_id>/preview")
class DataSourceContentPreviewApi(Resource):
@console_ns.expect(console_ns.models[Parser.__name__], validate=True)
@console_ns.expect(console_ns.models[Parser.__name__])
@setup_required
@login_required
@account_initialization_required

View File

@ -2,7 +2,7 @@ import logging
from typing import Any, Literal
from uuid import UUID
from pydantic import BaseModel, Field
from pydantic import BaseModel, Field, field_validator
from werkzeug.exceptions import InternalServerError, NotFound
import services
@ -52,10 +52,24 @@ class ChatMessagePayload(BaseModel):
inputs: dict[str, Any]
query: str
files: list[dict[str, Any]] | None = None
conversation_id: UUID | None = None
parent_message_id: UUID | None = None
conversation_id: str | None = None
parent_message_id: str | None = None
retriever_from: str = Field(default="explore_app")
@field_validator("conversation_id", "parent_message_id", mode="before")
@classmethod
def normalize_uuid(cls, value: str | UUID | None) -> str | None:
"""
Accept blank IDs and validate UUID format when provided.
"""
if not value:
return None
try:
return helper.uuid_value(value)
except ValueError as exc:
raise ValueError("must be a valid UUID") from exc
register_schema_models(console_ns, CompletionMessagePayload, ChatMessagePayload)

View File

@ -3,7 +3,7 @@ from uuid import UUID
from flask import request
from flask_restx import marshal_with
from pydantic import BaseModel, Field
from pydantic import BaseModel, Field, model_validator
from sqlalchemy.orm import Session
from werkzeug.exceptions import NotFound
@ -30,9 +30,16 @@ class ConversationListQuery(BaseModel):
class ConversationRenamePayload(BaseModel):
name: str
name: str | None = None
auto_generate: bool = False
@model_validator(mode="after")
def validate_name_requirement(self):
if not self.auto_generate:
if self.name is None or not self.name.strip():
raise ValueError("name is required when auto_generate is false")
return self
register_schema_models(console_ns, ConversationListQuery, ConversationRenamePayload)

View File

@ -230,7 +230,7 @@ class ModelProviderModelApi(Resource):
return {"result": "success"}, 200
@console_ns.expect(console_ns.models[ParserDeleteModels.__name__], validate=True)
@console_ns.expect(console_ns.models[ParserDeleteModels.__name__])
@setup_required
@login_required
@is_admin_or_owner_required
@ -282,9 +282,10 @@ class ModelProviderModelCredentialApi(Resource):
tenant_id=tenant_id, provider_name=provider
)
else:
model_type = args.model_type
# Normalize model_type to the origin value stored in DB (e.g., "text-generation" for LLM)
normalized_model_type = args.model_type.to_origin_model_type()
available_credentials = model_provider_service.provider_manager.get_provider_model_available_credentials(
tenant_id=tenant_id, provider_name=provider, model_type=model_type, model_name=args.model
tenant_id=tenant_id, provider_name=provider, model_type=normalized_model_type, model_name=args.model
)
return jsonable_encoder(

View File

@ -46,8 +46,8 @@ class PluginDebuggingKeyApi(Resource):
class ParserList(BaseModel):
page: int = Field(default=1)
page_size: int = Field(default=256)
page: int = Field(default=1, ge=1, description="Page number")
page_size: int = Field(default=256, ge=1, le=256, description="Page size (1-256)")
reg(ParserList)
@ -106,8 +106,8 @@ class ParserPluginIdentifierQuery(BaseModel):
class ParserTasks(BaseModel):
page: int
page_size: int
page: int = Field(default=1, ge=1, description="Page number")
page_size: int = Field(default=256, ge=1, le=256, description="Page size (1-256)")
class ParserMarketplaceUpgrade(BaseModel):

View File

@ -4,7 +4,7 @@ from uuid import UUID
from flask import request
from flask_restx import Resource
from pydantic import BaseModel, Field
from pydantic import BaseModel, Field, field_validator
from werkzeug.exceptions import BadRequest, InternalServerError, NotFound
import services
@ -52,11 +52,23 @@ class ChatRequestPayload(BaseModel):
query: str
files: list[dict[str, Any]] | None = None
response_mode: Literal["blocking", "streaming"] | None = None
conversation_id: UUID | None = None
conversation_id: str | None = Field(default=None, description="Conversation UUID")
retriever_from: str = Field(default="dev")
auto_generate_name: bool = Field(default=True, description="Auto generate conversation name")
workflow_id: str | None = Field(default=None, description="Workflow ID for advanced chat")
@field_validator("conversation_id", mode="before")
@classmethod
def normalize_conversation_id(cls, value: str | UUID | None) -> str | None:
"""Allow missing or blank conversation IDs; enforce UUID format when provided."""
if not value:
return None
try:
return helper.uuid_value(value)
except ValueError as exc:
raise ValueError("conversation_id must be a valid UUID") from exc
register_schema_models(service_api_ns, CompletionRequestPayload, ChatRequestPayload)

View File

@ -4,7 +4,7 @@ from uuid import UUID
from flask import request
from flask_restx import Resource
from flask_restx._http import HTTPStatus
from pydantic import BaseModel, Field
from pydantic import BaseModel, Field, model_validator
from sqlalchemy.orm import Session
from werkzeug.exceptions import BadRequest, NotFound
@ -37,9 +37,16 @@ class ConversationListQuery(BaseModel):
class ConversationRenamePayload(BaseModel):
name: str = Field(description="New conversation name")
name: str | None = Field(default=None, description="New conversation name (required if auto_generate is false)")
auto_generate: bool = Field(default=False, description="Auto-generate conversation name")
@model_validator(mode="after")
def validate_name_requirement(self):
if not self.auto_generate:
if self.name is None or not self.name.strip():
raise ValueError("name is required when auto_generate is false")
return self
class ConversationVariablesQuery(BaseModel):
last_id: UUID | None = Field(default=None, description="Last variable ID for pagination")

View File

@ -33,7 +33,7 @@ def trigger_endpoint(endpoint_id: str):
if response:
break
if not response:
logger.error("Endpoint not found for {endpoint_id}")
logger.info("Endpoint not found for %s", endpoint_id)
return jsonify({"error": "Endpoint not found"}), 404
return response
except ValueError as e:

View File

@ -62,8 +62,7 @@ from core.app.task_pipeline.message_cycle_manager import MessageCycleManager
from core.base.tts import AppGeneratorTTSPublisher, AudioTrunk
from core.model_runtime.entities.llm_entities import LLMUsage
from core.model_runtime.utils.encoders import jsonable_encoder
from core.ops.entities.trace_entity import TraceTaskName
from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
from core.ops.ops_trace_manager import TraceQueueManager
from core.workflow.enums import WorkflowExecutionStatus
from core.workflow.nodes import NodeType
from core.workflow.repositories.draft_variable_repository import DraftVariableSaverFactory
@ -73,7 +72,7 @@ from extensions.ext_database import db
from libs.datetime_utils import naive_utc_now
from models import Account, Conversation, EndUser, Message, MessageFile
from models.enums import CreatorUserRole
from models.workflow import Workflow, WorkflowNodeExecutionModel
from models.workflow import Workflow
logger = logging.getLogger(__name__)
@ -581,7 +580,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
with self._database_session() as session:
# Save message
self._save_message(session=session, graph_runtime_state=resolved_state, trace_manager=trace_manager)
self._save_message(session=session, graph_runtime_state=resolved_state)
yield workflow_finish_resp
elif event.stopped_by in (
@ -591,7 +590,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
# When hitting input-moderation or annotation-reply, the workflow will not start
with self._database_session() as session:
# Save message
self._save_message(session=session, trace_manager=trace_manager)
self._save_message(session=session)
yield self._message_end_to_stream_response()
@ -600,7 +599,6 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
event: QueueAdvancedChatMessageEndEvent,
*,
graph_runtime_state: GraphRuntimeState | None = None,
trace_manager: TraceQueueManager | None = None,
**kwargs,
) -> Generator[StreamResponse, None, None]:
"""Handle advanced chat message end events."""
@ -618,7 +616,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
# Save message
with self._database_session() as session:
self._save_message(session=session, graph_runtime_state=resolved_state, trace_manager=trace_manager)
self._save_message(session=session, graph_runtime_state=resolved_state)
yield self._message_end_to_stream_response()
@ -772,13 +770,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
if self._conversation_name_generate_thread:
logger.debug("Conversation name generation running as daemon thread")
def _save_message(
self,
*,
session: Session,
graph_runtime_state: GraphRuntimeState | None = None,
trace_manager: TraceQueueManager | None = None,
):
def _save_message(self, *, session: Session, graph_runtime_state: GraphRuntimeState | None = None):
message = self._get_message(session=session)
# If there are assistant files, remove markdown image links from answer
@ -817,14 +809,6 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
metadata = self._task_state.metadata.model_dump()
message.message_metadata = json.dumps(jsonable_encoder(metadata))
# Extract model provider and model_id from workflow node executions for tracing
if message.workflow_run_id:
model_info = self._extract_model_info_from_workflow(session, message.workflow_run_id)
if model_info:
message.model_provider = model_info.get("provider")
message.model_id = model_info.get("model")
message_files = [
MessageFile(
message_id=message.id,
@ -842,68 +826,6 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
]
session.add_all(message_files)
# Trigger MESSAGE_TRACE for tracing integrations
if trace_manager:
trace_manager.add_trace_task(
TraceTask(
TraceTaskName.MESSAGE_TRACE, conversation_id=self._conversation_id, message_id=self._message_id
)
)
def _extract_model_info_from_workflow(self, session: Session, workflow_run_id: str) -> dict[str, str] | None:
"""
Extract model provider and model_id from workflow node executions.
Returns dict with 'provider' and 'model' keys, or None if not found.
"""
try:
# Query workflow node executions for LLM or Agent nodes
stmt = (
select(WorkflowNodeExecutionModel)
.where(WorkflowNodeExecutionModel.workflow_run_id == workflow_run_id)
.where(WorkflowNodeExecutionModel.node_type.in_(["llm", "agent"]))
.order_by(WorkflowNodeExecutionModel.created_at.desc())
.limit(1)
)
node_execution = session.scalar(stmt)
if not node_execution:
return None
# Try to extract from execution_metadata for agent nodes
if node_execution.execution_metadata:
try:
metadata = json.loads(node_execution.execution_metadata)
agent_log = metadata.get("agent_log", [])
# Look for the first agent thought with provider info
for log_entry in agent_log:
entry_metadata = log_entry.get("metadata", {})
provider_str = entry_metadata.get("provider")
if provider_str:
# Parse format like "langgenius/deepseek/deepseek"
parts = provider_str.split("/")
if len(parts) >= 3:
return {"provider": parts[1], "model": parts[2]}
elif len(parts) == 2:
return {"provider": parts[0], "model": parts[1]}
except (json.JSONDecodeError, KeyError, AttributeError) as e:
logger.debug("Failed to parse execution_metadata: %s", e)
# Try to extract from process_data for llm nodes
if node_execution.process_data:
try:
process_data = json.loads(node_execution.process_data)
provider = process_data.get("model_provider")
model = process_data.get("model_name")
if provider and model:
return {"provider": provider, "model": model}
except (json.JSONDecodeError, KeyError) as e:
logger.debug("Failed to parse process_data: %s", e)
return None
except Exception as e:
logger.warning("Failed to extract model info from workflow: %s", e)
return None
def _seed_graph_runtime_state_from_queue_manager(self) -> None:
"""Bootstrap the cached runtime state from the queue manager when present."""
candidate = self._base_task_pipeline.queue_manager.graph_runtime_state

View File

@ -40,9 +40,6 @@ class EasyUITaskState(TaskState):
"""
llm_result: LLMResult
first_token_time: float | None = None
last_token_time: float | None = None
is_streaming_response: bool = False
class WorkflowTaskState(TaskState):

View File

@ -332,12 +332,6 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
if not self._task_state.llm_result.prompt_messages:
self._task_state.llm_result.prompt_messages = chunk.prompt_messages
# Track streaming response times
if self._task_state.first_token_time is None:
self._task_state.first_token_time = time.perf_counter()
self._task_state.is_streaming_response = True
self._task_state.last_token_time = time.perf_counter()
# handle output moderation chunk
should_direct_answer = self._handle_output_moderation_chunk(cast(str, delta_text))
if should_direct_answer:
@ -404,18 +398,6 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
message.total_price = usage.total_price
message.currency = usage.currency
self._task_state.llm_result.usage.latency = message.provider_response_latency
# Add streaming metrics to usage if available
if self._task_state.is_streaming_response and self._task_state.first_token_time:
start_time = self.start_at
first_token_time = self._task_state.first_token_time
last_token_time = self._task_state.last_token_time or first_token_time
usage.time_to_first_token = round(first_token_time - start_time, 3)
usage.time_to_generate = round(last_token_time - first_token_time, 3)
# Update metadata with the complete usage info
self._task_state.metadata.usage = usage
message.message_metadata = self._task_state.metadata.model_dump_json()
if trace_manager:

0
api/core/db/__init__.py Normal file
View File

View File

@ -0,0 +1,38 @@
from sqlalchemy import Engine
from sqlalchemy.orm import Session, sessionmaker
_session_maker: sessionmaker | None = None
def configure_session_factory(engine: Engine, expire_on_commit: bool = False):
"""Configure the global session factory"""
global _session_maker
_session_maker = sessionmaker(bind=engine, expire_on_commit=expire_on_commit)
def get_session_maker() -> sessionmaker:
if _session_maker is None:
raise RuntimeError("Session factory not configured. Call configure_session_factory() first.")
return _session_maker
def create_session() -> Session:
return get_session_maker()()
# Class wrapper for convenience
class SessionFactory:
@staticmethod
def configure(engine: Engine, expire_on_commit: bool = False):
configure_session_factory(engine, expire_on_commit)
@staticmethod
def get_session_maker() -> sessionmaker:
return get_session_maker()
@staticmethod
def create_session() -> Session:
return create_session()
session_factory = SessionFactory()

View File

@ -1,4 +1,4 @@
from pydantic import BaseModel
from pydantic import BaseModel, Field
class PreviewDetail(BaseModel):
@ -20,7 +20,7 @@ class IndexingEstimate(BaseModel):
class PipelineDataset(BaseModel):
id: str
name: str
description: str
description: str | None = Field(default="", description="knowledge dataset description")
chunk_structure: str

View File

@ -213,12 +213,23 @@ class MCPProviderEntity(BaseModel):
return None
def retrieve_tokens(self) -> OAuthTokens | None:
"""OAuth tokens if available"""
"""Retrieve OAuth tokens if authentication is complete.
Returns:
OAuthTokens if the provider has been authenticated, None otherwise.
"""
if not self.credentials:
return None
credentials = self.decrypt_credentials()
access_token = credentials.get("access_token", "")
# Return None if access_token is empty to avoid generating invalid "Authorization: Bearer " header.
# Note: We don't check for whitespace-only strings here because:
# 1. OAuth servers don't return whitespace-only access tokens in practice
# 2. Even if they did, the server would return 401, triggering the OAuth flow correctly
if not access_token:
return None
return OAuthTokens(
access_token=credentials.get("access_token", ""),
access_token=access_token,
token_type=credentials.get("token_type", DEFAULT_TOKEN_TYPE),
expires_in=int(credentials.get("expires_in", str(DEFAULT_EXPIRES_IN)) or DEFAULT_EXPIRES_IN),
refresh_token=credentials.get("refresh_token", ""),

View File

@ -72,15 +72,22 @@ class LLMGenerator:
prompt_messages=list(prompts), model_parameters={"max_tokens": 500, "temperature": 1}, stream=False
)
answer = cast(str, response.message.content)
cleaned_answer = re.sub(r"^.*(\{.*\}).*$", r"\1", answer, flags=re.DOTALL)
if cleaned_answer is None:
if answer is None:
return ""
try:
result_dict = json.loads(cleaned_answer)
answer = result_dict["Your Output"]
result_dict = json.loads(answer)
except json.JSONDecodeError:
logger.exception("Failed to generate name after answer, use query instead")
result_dict = json_repair.loads(answer)
if not isinstance(result_dict, dict):
answer = query
else:
output = result_dict.get("Your Output")
if isinstance(output, str) and output.strip():
answer = output.strip()
else:
answer = query
name = answer.strip()
if len(name) > 75:
@ -554,11 +561,16 @@ class LLMGenerator:
prompt_messages=list(prompt_messages), model_parameters=model_parameters, stream=False
)
generated_raw = cast(str, response.message.content)
generated_raw = response.message.get_text_content()
first_brace = generated_raw.find("{")
last_brace = generated_raw.rfind("}")
return {**json.loads(generated_raw[first_brace : last_brace + 1])}
if first_brace == -1 or last_brace == -1 or last_brace < first_brace:
raise ValueError(f"Could not find a valid JSON object in response: {generated_raw}")
json_str = generated_raw[first_brace : last_brace + 1]
data = json_repair.loads(json_str)
if not isinstance(data, dict):
raise TypeError(f"Expected a JSON object, but got {type(data).__name__}")
return data
except InvokeError as e:
error = str(e)
return {"error": f"Failed to generate code. Error: {error}"}

View File

@ -6,7 +6,13 @@ from datetime import datetime, timedelta
from typing import Any, Union, cast
from urllib.parse import urlparse
from openinference.semconv.trace import OpenInferenceMimeTypeValues, OpenInferenceSpanKindValues, SpanAttributes
from openinference.semconv.trace import (
MessageAttributes,
OpenInferenceMimeTypeValues,
OpenInferenceSpanKindValues,
SpanAttributes,
ToolCallAttributes,
)
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter as GrpcOTLPSpanExporter
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter as HttpOTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
@ -95,14 +101,14 @@ def setup_tracer(arize_phoenix_config: ArizeConfig | PhoenixConfig) -> tuple[tra
def datetime_to_nanos(dt: datetime | None) -> int:
"""Convert datetime to nanoseconds since epoch. If None, use current time."""
"""Convert datetime to nanoseconds since epoch for Arize/Phoenix."""
if dt is None:
dt = datetime.now()
return int(dt.timestamp() * 1_000_000_000)
def error_to_string(error: Exception | str | None) -> str:
"""Convert an error to a string with traceback information."""
"""Convert an error to a string with traceback information for Arize/Phoenix."""
error_message = "Empty Stack Trace"
if error:
if isinstance(error, Exception):
@ -114,7 +120,7 @@ def error_to_string(error: Exception | str | None) -> str:
def set_span_status(current_span: Span, error: Exception | str | None = None):
"""Set the status of the current span based on the presence of an error."""
"""Set the status of the current span based on the presence of an error for Arize/Phoenix."""
if error:
error_string = error_to_string(error)
current_span.set_status(Status(StatusCode.ERROR, error_string))
@ -138,10 +144,17 @@ def set_span_status(current_span: Span, error: Exception | str | None = None):
def safe_json_dumps(obj: Any) -> str:
"""A convenience wrapper around `json.dumps` that ensures that any object can be safely encoded."""
"""A convenience wrapper to ensure that any object can be safely encoded for Arize/Phoenix."""
return json.dumps(obj, default=str, ensure_ascii=False)
def wrap_span_metadata(metadata, **kwargs):
"""Add common metatada to all trace entity types for Arize/Phoenix."""
metadata["created_from"] = "Dify"
metadata.update(kwargs)
return metadata
class ArizePhoenixDataTrace(BaseTraceInstance):
def __init__(
self,
@ -183,16 +196,27 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
raise
def workflow_trace(self, trace_info: WorkflowTraceInfo):
workflow_metadata = {
"workflow_run_id": trace_info.workflow_run_id or "",
"message_id": trace_info.message_id or "",
"workflow_app_log_id": trace_info.workflow_app_log_id or "",
"status": trace_info.workflow_run_status or "",
"status_message": trace_info.error or "",
"level": "ERROR" if trace_info.error else "DEFAULT",
"total_tokens": trace_info.total_tokens or 0,
}
workflow_metadata.update(trace_info.metadata)
file_list = trace_info.file_list if isinstance(trace_info.file_list, list) else []
metadata = wrap_span_metadata(
trace_info.metadata,
trace_id=trace_info.trace_id or "",
message_id=trace_info.message_id or "",
status=trace_info.workflow_run_status or "",
status_message=trace_info.error or "",
level="ERROR" if trace_info.error else "DEFAULT",
trace_entity_type="workflow",
conversation_id=trace_info.conversation_id or "",
workflow_app_log_id=trace_info.workflow_app_log_id or "",
workflow_id=trace_info.workflow_id or "",
tenant_id=trace_info.tenant_id or "",
workflow_run_id=trace_info.workflow_run_id or "",
workflow_run_elapsed_time=trace_info.workflow_run_elapsed_time or 0,
workflow_run_version=trace_info.workflow_run_version or "",
total_tokens=trace_info.total_tokens or 0,
file_list=safe_json_dumps(file_list),
query=trace_info.query or "",
)
dify_trace_id = trace_info.trace_id or trace_info.message_id or trace_info.workflow_run_id
self.ensure_root_span(dify_trace_id)
@ -201,10 +225,12 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
workflow_span = self.tracer.start_span(
name=TraceTaskName.WORKFLOW_TRACE.value,
attributes={
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.workflow_run_inputs, ensure_ascii=False),
SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.workflow_run_outputs, ensure_ascii=False),
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
SpanAttributes.METADATA: json.dumps(workflow_metadata, ensure_ascii=False),
SpanAttributes.INPUT_VALUE: safe_json_dumps(trace_info.workflow_run_inputs),
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OUTPUT_VALUE: safe_json_dumps(trace_info.workflow_run_outputs),
SpanAttributes.OUTPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.METADATA: safe_json_dumps(metadata),
SpanAttributes.SESSION_ID: trace_info.conversation_id or "",
},
start_time=datetime_to_nanos(trace_info.start_time),
@ -257,6 +283,7 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
"app_id": app_id,
"app_name": node_execution.title,
"status": node_execution.status,
"status_message": node_execution.error or "",
"level": "ERROR" if node_execution.status == "failed" else "DEFAULT",
}
)
@ -290,11 +317,11 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
node_span = self.tracer.start_span(
name=node_execution.node_type,
attributes={
SpanAttributes.OPENINFERENCE_SPAN_KIND: span_kind.value,
SpanAttributes.INPUT_VALUE: safe_json_dumps(inputs_value),
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OUTPUT_VALUE: safe_json_dumps(outputs_value),
SpanAttributes.OUTPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OPENINFERENCE_SPAN_KIND: span_kind.value,
SpanAttributes.METADATA: safe_json_dumps(node_metadata),
SpanAttributes.SESSION_ID: trace_info.conversation_id or "",
},
@ -339,30 +366,37 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
def message_trace(self, trace_info: MessageTraceInfo):
if trace_info.message_data is None:
logger.warning("[Arize/Phoenix] Message data is None, skipping message trace.")
return
file_list = cast(list[str], trace_info.file_list) or []
file_list = trace_info.file_list if isinstance(trace_info.file_list, list) else []
message_file_data: MessageFile | None = trace_info.message_file_data
if message_file_data is not None:
file_url = f"{self.file_base_url}/{message_file_data.url}" if message_file_data else ""
file_list.append(file_url)
message_metadata = {
"message_id": trace_info.message_id or "",
"conversation_mode": str(trace_info.conversation_mode or ""),
"user_id": trace_info.message_data.from_account_id or "",
"file_list": json.dumps(file_list),
"status": trace_info.message_data.status or "",
"status_message": trace_info.error or "",
"level": "ERROR" if trace_info.error else "DEFAULT",
"total_tokens": trace_info.total_tokens or 0,
"prompt_tokens": trace_info.message_tokens or 0,
"completion_tokens": trace_info.answer_tokens or 0,
"ls_provider": trace_info.message_data.model_provider or "",
"ls_model_name": trace_info.message_data.model_id or "",
}
message_metadata.update(trace_info.metadata)
metadata = wrap_span_metadata(
trace_info.metadata,
trace_id=trace_info.trace_id or "",
message_id=trace_info.message_id or "",
status=trace_info.message_data.status or "",
status_message=trace_info.error or "",
level="ERROR" if trace_info.error else "DEFAULT",
trace_entity_type="message",
conversation_model=trace_info.conversation_model or "",
message_tokens=trace_info.message_tokens or 0,
answer_tokens=trace_info.answer_tokens or 0,
total_tokens=trace_info.total_tokens or 0,
conversation_mode=trace_info.conversation_mode or "",
gen_ai_server_time_to_first_token=trace_info.gen_ai_server_time_to_first_token or 0,
llm_streaming_time_to_generate=trace_info.llm_streaming_time_to_generate or 0,
is_streaming_request=trace_info.is_streaming_request or False,
user_id=trace_info.message_data.from_account_id or "",
file_list=safe_json_dumps(file_list),
model_provider=trace_info.message_data.model_provider or "",
model_id=trace_info.message_data.model_id or "",
)
# Add end user data if available
if trace_info.message_data.from_end_user_id:
@ -370,14 +404,16 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
db.session.query(EndUser).where(EndUser.id == trace_info.message_data.from_end_user_id).first()
)
if end_user_data is not None:
message_metadata["end_user_id"] = end_user_data.session_id
metadata["end_user_id"] = end_user_data.session_id
attributes = {
SpanAttributes.INPUT_VALUE: trace_info.message_data.query,
SpanAttributes.OUTPUT_VALUE: trace_info.message_data.answer,
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
SpanAttributes.METADATA: json.dumps(message_metadata, ensure_ascii=False),
SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
SpanAttributes.INPUT_VALUE: trace_info.message_data.query,
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.TEXT.value,
SpanAttributes.OUTPUT_VALUE: trace_info.message_data.answer,
SpanAttributes.OUTPUT_MIME_TYPE: OpenInferenceMimeTypeValues.TEXT.value,
SpanAttributes.METADATA: safe_json_dumps(metadata),
SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id or "",
}
dify_trace_id = trace_info.trace_id or trace_info.message_id
@ -393,8 +429,10 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
try:
# Convert outputs to string based on type
outputs_mime_type = OpenInferenceMimeTypeValues.TEXT.value
if isinstance(trace_info.outputs, dict | list):
outputs_str = json.dumps(trace_info.outputs, ensure_ascii=False)
outputs_str = safe_json_dumps(trace_info.outputs)
outputs_mime_type = OpenInferenceMimeTypeValues.JSON.value
elif isinstance(trace_info.outputs, str):
outputs_str = trace_info.outputs
else:
@ -402,10 +440,12 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
llm_attributes = {
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.LLM.value,
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
SpanAttributes.INPUT_VALUE: safe_json_dumps(trace_info.inputs),
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OUTPUT_VALUE: outputs_str,
SpanAttributes.METADATA: json.dumps(message_metadata, ensure_ascii=False),
SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
SpanAttributes.OUTPUT_MIME_TYPE: outputs_mime_type,
SpanAttributes.METADATA: safe_json_dumps(metadata),
SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id or "",
}
llm_attributes.update(self._construct_llm_attributes(trace_info.inputs))
if trace_info.total_tokens is not None and trace_info.total_tokens > 0:
@ -449,16 +489,20 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
def moderation_trace(self, trace_info: ModerationTraceInfo):
if trace_info.message_data is None:
logger.warning("[Arize/Phoenix] Message data is None, skipping moderation trace.")
return
metadata = {
"message_id": trace_info.message_id,
"tool_name": "moderation",
"status": trace_info.message_data.status,
"status_message": trace_info.message_data.error or "",
"level": "ERROR" if trace_info.message_data.error else "DEFAULT",
}
metadata.update(trace_info.metadata)
metadata = wrap_span_metadata(
trace_info.metadata,
trace_id=trace_info.trace_id or "",
message_id=trace_info.message_id or "",
status=trace_info.message_data.status or "",
status_message=trace_info.message_data.error or "",
level="ERROR" if trace_info.message_data.error else "DEFAULT",
trace_entity_type="moderation",
model_provider=trace_info.message_data.model_provider or "",
model_id=trace_info.message_data.model_id or "",
)
dify_trace_id = trace_info.trace_id or trace_info.message_id
self.ensure_root_span(dify_trace_id)
@ -467,18 +511,19 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
span = self.tracer.start_span(
name=TraceTaskName.MODERATION_TRACE.value,
attributes={
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
SpanAttributes.OUTPUT_VALUE: json.dumps(
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.TOOL.value,
SpanAttributes.INPUT_VALUE: safe_json_dumps(trace_info.inputs),
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OUTPUT_VALUE: safe_json_dumps(
{
"action": trace_info.action,
"flagged": trace_info.flagged,
"action": trace_info.action,
"preset_response": trace_info.preset_response,
"inputs": trace_info.inputs,
},
ensure_ascii=False,
"query": trace_info.query,
}
),
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
SpanAttributes.OUTPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.METADATA: safe_json_dumps(metadata),
},
start_time=datetime_to_nanos(trace_info.start_time),
context=root_span_context,
@ -494,22 +539,28 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo):
if trace_info.message_data is None:
logger.warning("[Arize/Phoenix] Message data is None, skipping suggested question trace.")
return
start_time = trace_info.start_time or trace_info.message_data.created_at
end_time = trace_info.end_time or trace_info.message_data.updated_at
metadata = {
"message_id": trace_info.message_id,
"tool_name": "suggested_question",
"status": trace_info.status,
"status_message": trace_info.error or "",
"level": "ERROR" if trace_info.error else "DEFAULT",
"total_tokens": trace_info.total_tokens,
"ls_provider": trace_info.model_provider or "",
"ls_model_name": trace_info.model_id or "",
}
metadata.update(trace_info.metadata)
metadata = wrap_span_metadata(
trace_info.metadata,
trace_id=trace_info.trace_id or "",
message_id=trace_info.message_id or "",
status=trace_info.status or "",
status_message=trace_info.status_message or "",
level=trace_info.level or "",
trace_entity_type="suggested_question",
total_tokens=trace_info.total_tokens or 0,
from_account_id=trace_info.from_account_id or "",
agent_based=trace_info.agent_based or False,
from_source=trace_info.from_source or "",
model_provider=trace_info.model_provider or "",
model_id=trace_info.model_id or "",
workflow_run_id=trace_info.workflow_run_id or "",
)
dify_trace_id = trace_info.trace_id or trace_info.message_id
self.ensure_root_span(dify_trace_id)
@ -518,10 +569,12 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
span = self.tracer.start_span(
name=TraceTaskName.SUGGESTED_QUESTION_TRACE.value,
attributes={
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.suggested_question, ensure_ascii=False),
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.TOOL.value,
SpanAttributes.INPUT_VALUE: safe_json_dumps(trace_info.inputs),
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OUTPUT_VALUE: safe_json_dumps(trace_info.suggested_question),
SpanAttributes.OUTPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.METADATA: safe_json_dumps(metadata),
},
start_time=datetime_to_nanos(start_time),
context=root_span_context,
@ -537,21 +590,23 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo):
if trace_info.message_data is None:
logger.warning("[Arize/Phoenix] Message data is None, skipping dataset retrieval trace.")
return
start_time = trace_info.start_time or trace_info.message_data.created_at
end_time = trace_info.end_time or trace_info.message_data.updated_at
metadata = {
"message_id": trace_info.message_id,
"tool_name": "dataset_retrieval",
"status": trace_info.message_data.status,
"status_message": trace_info.message_data.error or "",
"level": "ERROR" if trace_info.message_data.error else "DEFAULT",
"ls_provider": trace_info.message_data.model_provider or "",
"ls_model_name": trace_info.message_data.model_id or "",
}
metadata.update(trace_info.metadata)
metadata = wrap_span_metadata(
trace_info.metadata,
trace_id=trace_info.trace_id or "",
message_id=trace_info.message_id or "",
status=trace_info.message_data.status or "",
status_message=trace_info.error or "",
level="ERROR" if trace_info.error else "DEFAULT",
trace_entity_type="dataset_retrieval",
model_provider=trace_info.message_data.model_provider or "",
model_id=trace_info.message_data.model_id or "",
)
dify_trace_id = trace_info.trace_id or trace_info.message_id
self.ensure_root_span(dify_trace_id)
@ -560,20 +615,20 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
span = self.tracer.start_span(
name=TraceTaskName.DATASET_RETRIEVAL_TRACE.value,
attributes={
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
SpanAttributes.OUTPUT_VALUE: json.dumps({"documents": trace_info.documents}, ensure_ascii=False),
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.RETRIEVER.value,
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
"start_time": start_time.isoformat() if start_time else "",
"end_time": end_time.isoformat() if end_time else "",
SpanAttributes.INPUT_VALUE: safe_json_dumps(trace_info.inputs),
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OUTPUT_VALUE: safe_json_dumps({"documents": trace_info.documents}),
SpanAttributes.OUTPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.METADATA: safe_json_dumps(metadata),
},
start_time=datetime_to_nanos(start_time),
context=root_span_context,
)
try:
if trace_info.message_data.error:
set_span_status(span, trace_info.message_data.error)
if trace_info.error:
set_span_status(span, trace_info.error)
else:
set_span_status(span)
finally:
@ -584,30 +639,34 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
logger.warning("[Arize/Phoenix] Message data is None, skipping tool trace.")
return
metadata = {
"message_id": trace_info.message_id,
"tool_config": json.dumps(trace_info.tool_config, ensure_ascii=False),
}
metadata = wrap_span_metadata(
trace_info.metadata,
trace_id=trace_info.trace_id or "",
message_id=trace_info.message_id or "",
status=trace_info.message_data.status or "",
status_message=trace_info.error or "",
level="ERROR" if trace_info.error else "DEFAULT",
trace_entity_type="tool",
tool_config=safe_json_dumps(trace_info.tool_config),
time_cost=trace_info.time_cost or 0,
file_url=trace_info.file_url or "",
)
dify_trace_id = trace_info.trace_id or trace_info.message_id
self.ensure_root_span(dify_trace_id)
root_span_context = self.propagator.extract(carrier=self.carrier)
tool_params_str = (
json.dumps(trace_info.tool_parameters, ensure_ascii=False)
if isinstance(trace_info.tool_parameters, dict)
else str(trace_info.tool_parameters)
)
span = self.tracer.start_span(
name=trace_info.tool_name,
attributes={
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.tool_inputs, ensure_ascii=False),
SpanAttributes.OUTPUT_VALUE: trace_info.tool_outputs,
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.TOOL.value,
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
SpanAttributes.INPUT_VALUE: safe_json_dumps(trace_info.tool_inputs),
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OUTPUT_VALUE: trace_info.tool_outputs,
SpanAttributes.OUTPUT_MIME_TYPE: OpenInferenceMimeTypeValues.TEXT.value,
SpanAttributes.METADATA: safe_json_dumps(metadata),
SpanAttributes.TOOL_NAME: trace_info.tool_name,
SpanAttributes.TOOL_PARAMETERS: tool_params_str,
SpanAttributes.TOOL_PARAMETERS: safe_json_dumps(trace_info.tool_parameters),
},
start_time=datetime_to_nanos(trace_info.start_time),
context=root_span_context,
@ -623,16 +682,22 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
def generate_name_trace(self, trace_info: GenerateNameTraceInfo):
if trace_info.message_data is None:
logger.warning("[Arize/Phoenix] Message data is None, skipping generate name trace.")
return
metadata = {
"project_name": self.project,
"message_id": trace_info.message_id,
"status": trace_info.message_data.status,
"status_message": trace_info.message_data.error or "",
"level": "ERROR" if trace_info.message_data.error else "DEFAULT",
}
metadata.update(trace_info.metadata)
metadata = wrap_span_metadata(
trace_info.metadata,
trace_id=trace_info.trace_id or "",
message_id=trace_info.message_id or "",
status=trace_info.message_data.status or "",
status_message=trace_info.message_data.error or "",
level="ERROR" if trace_info.message_data.error else "DEFAULT",
trace_entity_type="generate_name",
model_provider=trace_info.message_data.model_provider or "",
model_id=trace_info.message_data.model_id or "",
conversation_id=trace_info.conversation_id or "",
tenant_id=trace_info.tenant_id,
)
dify_trace_id = trace_info.trace_id or trace_info.message_id or trace_info.conversation_id
self.ensure_root_span(dify_trace_id)
@ -641,13 +706,13 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
span = self.tracer.start_span(
name=TraceTaskName.GENERATE_NAME_TRACE.value,
attributes={
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.outputs, ensure_ascii=False),
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
"start_time": trace_info.start_time.isoformat() if trace_info.start_time else "",
"end_time": trace_info.end_time.isoformat() if trace_info.end_time else "",
SpanAttributes.INPUT_VALUE: safe_json_dumps(trace_info.inputs),
SpanAttributes.INPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.OUTPUT_VALUE: safe_json_dumps(trace_info.outputs),
SpanAttributes.OUTPUT_MIME_TYPE: OpenInferenceMimeTypeValues.JSON.value,
SpanAttributes.METADATA: safe_json_dumps(metadata),
SpanAttributes.SESSION_ID: trace_info.conversation_id or "",
},
start_time=datetime_to_nanos(trace_info.start_time),
context=root_span_context,
@ -688,32 +753,85 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
raise ValueError(f"[Arize/Phoenix] API check failed: {str(e)}")
def get_project_url(self):
"""Build a redirect URL that forwards the user to the correct project for Arize/Phoenix."""
try:
if self.arize_phoenix_config.endpoint == "https://otlp.arize.com":
return "https://app.arize.com/"
else:
return f"{self.arize_phoenix_config.endpoint}/projects/"
project_name = self.arize_phoenix_config.project
endpoint = self.arize_phoenix_config.endpoint.rstrip("/")
# Arize
if isinstance(self.arize_phoenix_config, ArizeConfig):
return f"https://app.arize.com/?redirect_project_name={project_name}"
# Phoenix
return f"{endpoint}/projects/?redirect_project_name={project_name}"
except Exception as e:
logger.info("[Arize/Phoenix] Get run url failed: %s", str(e), exc_info=True)
raise ValueError(f"[Arize/Phoenix] Get run url failed: {str(e)}")
logger.info("[Arize/Phoenix] Failed to construct project URL: %s", str(e), exc_info=True)
raise ValueError(f"[Arize/Phoenix] Failed to construct project URL: {str(e)}")
def _construct_llm_attributes(self, prompts: dict | list | str | None) -> dict[str, str]:
"""Helper method to construct LLM attributes with passed prompts."""
attributes = {}
"""Construct LLM attributes with passed prompts for Arize/Phoenix."""
attributes: dict[str, str] = {}
def set_attribute(path: str, value: object) -> None:
"""Store an attribute safely as a string."""
if value is None:
return
try:
if isinstance(value, (dict, list)):
value = safe_json_dumps(value)
attributes[path] = str(value)
except Exception:
attributes[path] = str(value)
def set_message_attribute(message_index: int, key: str, value: object) -> None:
path = f"{SpanAttributes.LLM_INPUT_MESSAGES}.{message_index}.{key}"
set_attribute(path, value)
def set_tool_call_attributes(message_index: int, tool_index: int, tool_call: dict | object | None) -> None:
"""Extract and assign tool call details safely."""
if not tool_call:
return
def safe_get(obj, key, default=None):
if isinstance(obj, dict):
return obj.get(key, default)
return getattr(obj, key, default)
function_obj = safe_get(tool_call, "function", {})
function_name = safe_get(function_obj, "name", "")
function_args = safe_get(function_obj, "arguments", {})
call_id = safe_get(tool_call, "id", "")
base_path = (
f"{SpanAttributes.LLM_INPUT_MESSAGES}."
f"{message_index}.{MessageAttributes.MESSAGE_TOOL_CALLS}.{tool_index}"
)
set_attribute(f"{base_path}.{ToolCallAttributes.TOOL_CALL_FUNCTION_NAME}", function_name)
set_attribute(f"{base_path}.{ToolCallAttributes.TOOL_CALL_FUNCTION_ARGUMENTS_JSON}", function_args)
set_attribute(f"{base_path}.{ToolCallAttributes.TOOL_CALL_ID}", call_id)
# Handle list of messages
if isinstance(prompts, list):
for i, msg in enumerate(prompts):
if isinstance(msg, dict):
attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.{i}.message.content"] = msg.get("text", "")
attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.{i}.message.role"] = msg.get("role", "user")
# todo: handle assistant and tool role messages, as they don't always
# have a text field, but may have a tool_calls field instead
# e.g. 'tool_calls': [{'id': '98af3a29-b066-45a5-b4b1-46c74ddafc58',
# 'type': 'function', 'function': {'name': 'current_time', 'arguments': '{}'}}]}
elif isinstance(prompts, dict):
attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.content"] = json.dumps(prompts)
attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.role"] = "user"
elif isinstance(prompts, str):
attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.content"] = prompts
attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.role"] = "user"
for message_index, message in enumerate(prompts):
if not isinstance(message, dict):
continue
role = message.get("role", "user")
content = message.get("text") or message.get("content") or ""
set_message_attribute(message_index, MessageAttributes.MESSAGE_ROLE, role)
set_message_attribute(message_index, MessageAttributes.MESSAGE_CONTENT, content)
tool_calls = message.get("tool_calls") or []
if isinstance(tool_calls, list):
for tool_index, tool_call in enumerate(tool_calls):
set_tool_call_attributes(message_index, tool_index, tool_call)
# Handle single dict or plain string prompt
elif isinstance(prompts, (dict, str)):
set_message_attribute(0, MessageAttributes.MESSAGE_CONTENT, prompts)
set_message_attribute(0, MessageAttributes.MESSAGE_ROLE, "user")
return attributes

View File

@ -222,59 +222,6 @@ class TencentSpanBuilder:
links=links,
)
@staticmethod
def build_message_llm_span(
trace_info: MessageTraceInfo, trace_id: int, parent_span_id: int, user_id: str
) -> SpanData:
"""Build LLM span for message traces with detailed LLM attributes."""
status = Status(StatusCode.OK)
if trace_info.error:
status = Status(StatusCode.ERROR, trace_info.error)
# Extract model information from `metadata`` or `message_data`
trace_metadata = trace_info.metadata or {}
message_data = trace_info.message_data or {}
model_provider = trace_metadata.get("ls_provider") or (
message_data.get("model_provider", "") if isinstance(message_data, dict) else ""
)
model_name = trace_metadata.get("ls_model_name") or (
message_data.get("model_id", "") if isinstance(message_data, dict) else ""
)
inputs_str = str(trace_info.inputs or "")
outputs_str = str(trace_info.outputs or "")
attributes = {
GEN_AI_SESSION_ID: trace_metadata.get("conversation_id", ""),
GEN_AI_USER_ID: str(user_id),
GEN_AI_SPAN_KIND: GenAISpanKind.GENERATION.value,
GEN_AI_FRAMEWORK: "dify",
GEN_AI_MODEL_NAME: str(model_name),
GEN_AI_PROVIDER: str(model_provider),
GEN_AI_USAGE_INPUT_TOKENS: str(trace_info.message_tokens or 0),
GEN_AI_USAGE_OUTPUT_TOKENS: str(trace_info.answer_tokens or 0),
GEN_AI_USAGE_TOTAL_TOKENS: str(trace_info.total_tokens or 0),
GEN_AI_PROMPT: inputs_str,
GEN_AI_COMPLETION: outputs_str,
INPUT_VALUE: inputs_str,
OUTPUT_VALUE: outputs_str,
}
if trace_info.is_streaming_request:
attributes[GEN_AI_IS_STREAMING_REQUEST] = "true"
return SpanData(
trace_id=trace_id,
parent_span_id=parent_span_id,
span_id=TencentTraceUtils.convert_to_span_id(trace_info.message_id, "llm"),
name="GENERATION",
start_time=TencentSpanBuilder._get_time_nanoseconds(trace_info.start_time),
end_time=TencentSpanBuilder._get_time_nanoseconds(trace_info.end_time),
attributes=attributes,
status=status,
)
@staticmethod
def build_tool_span(trace_info: ToolTraceInfo, trace_id: int, parent_span_id: int) -> SpanData:
"""Build tool span."""

View File

@ -107,12 +107,8 @@ class TencentDataTrace(BaseTraceInstance):
links.append(TencentTraceUtils.create_link(trace_info.trace_id))
message_span = TencentSpanBuilder.build_message_span(trace_info, trace_id, str(user_id), links)
self.trace_client.add_span(message_span)
# Add LLM child span with detailed attributes
parent_span_id = TencentTraceUtils.convert_to_span_id(trace_info.message_id, "message")
llm_span = TencentSpanBuilder.build_message_llm_span(trace_info, trace_id, parent_span_id, str(user_id))
self.trace_client.add_span(llm_span)
self.trace_client.add_span(message_span)
self._record_message_llm_metrics(trace_info)

View File

@ -371,7 +371,7 @@ class RetrievalService:
include_segment_ids = set()
segment_child_map = {}
segment_file_map = {}
with Session(db.engine) as session:
with Session(bind=db.engine, expire_on_commit=False) as session:
# Process documents
for document in documents:
segment_id = None
@ -395,7 +395,7 @@ class RetrievalService:
session,
)
if attachment_info_dict:
attachment_info = attachment_info_dict["attchment_info"]
attachment_info = attachment_info_dict["attachment_info"]
segment_id = attachment_info_dict["segment_id"]
else:
child_index_node_id = document.metadata.get("doc_id")
@ -417,13 +417,6 @@ class RetrievalService:
DocumentSegment.status == "completed",
DocumentSegment.id == segment_id,
)
.options(
load_only(
DocumentSegment.id,
DocumentSegment.content,
DocumentSegment.answer,
)
)
.first()
)
@ -458,12 +451,21 @@ class RetrievalService:
"position": child_chunk.position,
"score": document.metadata.get("score", 0.0),
}
segment_child_map[segment.id]["child_chunks"].append(child_chunk_detail)
segment_child_map[segment.id]["max_score"] = max(
segment_child_map[segment.id]["max_score"], document.metadata.get("score", 0.0)
)
if segment.id in segment_child_map:
segment_child_map[segment.id]["child_chunks"].append(child_chunk_detail)
segment_child_map[segment.id]["max_score"] = max(
segment_child_map[segment.id]["max_score"], document.metadata.get("score", 0.0)
)
else:
segment_child_map[segment.id] = {
"max_score": document.metadata.get("score", 0.0),
"child_chunks": [child_chunk_detail],
}
if attachment_info:
segment_file_map[segment.id].append(attachment_info)
if segment.id in segment_file_map:
segment_file_map[segment.id].append(attachment_info)
else:
segment_file_map[segment.id] = [attachment_info]
else:
# Handle normal documents
segment = None
@ -475,7 +477,7 @@ class RetrievalService:
session,
)
if attachment_info_dict:
attachment_info = attachment_info_dict["attchment_info"]
attachment_info = attachment_info_dict["attachment_info"]
segment_id = attachment_info_dict["segment_id"]
document_segment_stmt = select(DocumentSegment).where(
DocumentSegment.dataset_id == dataset_document.dataset_id,
@ -684,7 +686,7 @@ class RetrievalService:
.first()
)
if attachment_binding:
attchment_info = {
attachment_info = {
"id": upload_file.id,
"name": upload_file.name,
"extension": "." + upload_file.extension,
@ -692,5 +694,5 @@ class RetrievalService:
"source_url": sign_upload_file(upload_file.id, upload_file.extension),
"size": upload_file.size,
}
return {"attchment_info": attchment_info, "segment_id": attachment_binding.segment_id}
return {"attachment_info": attachment_info, "segment_id": attachment_binding.segment_id}
return None

View File

@ -0,0 +1,407 @@
"""InterSystems IRIS vector database implementation for Dify.
This module provides vector storage and retrieval using IRIS native VECTOR type
with HNSW indexing for efficient similarity search.
"""
from __future__ import annotations
import json
import logging
import threading
import uuid
from contextlib import contextmanager
from typing import TYPE_CHECKING, Any
from configs import dify_config
from configs.middleware.vdb.iris_config import IrisVectorConfig
from core.rag.datasource.vdb.vector_base import BaseVector
from core.rag.datasource.vdb.vector_factory import AbstractVectorFactory
from core.rag.datasource.vdb.vector_type import VectorType
from core.rag.embedding.embedding_base import Embeddings
from core.rag.models.document import Document
from extensions.ext_redis import redis_client
from models.dataset import Dataset
if TYPE_CHECKING:
import iris
else:
try:
import iris
except ImportError:
iris = None # type: ignore[assignment]
logger = logging.getLogger(__name__)
# Singleton connection pool to minimize IRIS license usage
_pool_lock = threading.Lock()
_pool_instance: IrisConnectionPool | None = None
def get_iris_pool(config: IrisVectorConfig) -> IrisConnectionPool:
"""Get or create the global IRIS connection pool (singleton pattern)."""
global _pool_instance # pylint: disable=global-statement
with _pool_lock:
if _pool_instance is None:
logger.info("Initializing IRIS connection pool")
_pool_instance = IrisConnectionPool(config)
return _pool_instance
class IrisConnectionPool:
"""Thread-safe connection pool for IRIS database."""
def __init__(self, config: IrisVectorConfig) -> None:
self.config = config
self._pool: list[Any] = []
self._lock = threading.Lock()
self._min_size = config.IRIS_MIN_CONNECTION
self._max_size = config.IRIS_MAX_CONNECTION
self._in_use = 0
self._schemas_initialized: set[str] = set() # Cache for initialized schemas
self._initialize_pool()
def _initialize_pool(self) -> None:
for _ in range(self._min_size):
self._pool.append(self._create_connection())
def _create_connection(self) -> Any:
return iris.connect(
hostname=self.config.IRIS_HOST,
port=self.config.IRIS_SUPER_SERVER_PORT,
namespace=self.config.IRIS_DATABASE,
username=self.config.IRIS_USER,
password=self.config.IRIS_PASSWORD,
)
def get_connection(self) -> Any:
"""Get a connection from pool or create new if available."""
with self._lock:
if self._pool:
conn = self._pool.pop()
self._in_use += 1
return conn
if self._in_use < self._max_size:
conn = self._create_connection()
self._in_use += 1
return conn
raise RuntimeError("Connection pool exhausted")
def return_connection(self, conn: Any) -> None:
"""Return connection to pool after validating it."""
if not conn:
return
# Validate connection health
is_valid = False
try:
cursor = conn.cursor()
cursor.execute("SELECT 1")
cursor.close()
is_valid = True
except (OSError, RuntimeError) as e:
logger.debug("Connection validation failed: %s", e)
try:
conn.close()
except (OSError, RuntimeError):
pass
with self._lock:
self._pool.append(conn if is_valid else self._create_connection())
self._in_use -= 1
def ensure_schema_exists(self, schema: str) -> None:
"""Ensure schema exists in IRIS database.
This method is idempotent and thread-safe. It uses a memory cache to avoid
redundant database queries for already-verified schemas.
Args:
schema: Schema name to ensure exists
Raises:
Exception: If schema creation fails
"""
# Fast path: check cache first (no lock needed for read-only set lookup)
if schema in self._schemas_initialized:
return
# Slow path: acquire lock and check again (double-checked locking)
with self._lock:
if schema in self._schemas_initialized:
return
# Get a connection to check/create schema
conn = self._pool[0] if self._pool else self._create_connection()
cursor = conn.cursor()
try:
# Check if schema exists using INFORMATION_SCHEMA
check_sql = """
SELECT COUNT(*) FROM INFORMATION_SCHEMA.SCHEMATA
WHERE SCHEMA_NAME = ?
"""
cursor.execute(check_sql, (schema,)) # Must be tuple or list
exists = cursor.fetchone()[0] > 0
if not exists:
# Schema doesn't exist, create it
cursor.execute(f"CREATE SCHEMA {schema}")
conn.commit()
logger.info("Created schema: %s", schema)
else:
logger.debug("Schema already exists: %s", schema)
# Add to cache to skip future checks
self._schemas_initialized.add(schema)
except Exception as e:
conn.rollback()
logger.exception("Failed to ensure schema %s exists", schema)
raise
finally:
cursor.close()
def close_all(self) -> None:
"""Close all connections (application shutdown only)."""
with self._lock:
for conn in self._pool:
try:
conn.close()
except (OSError, RuntimeError):
pass
self._pool.clear()
self._in_use = 0
self._schemas_initialized.clear()
class IrisVector(BaseVector):
"""IRIS vector database implementation using native VECTOR type and HNSW indexing."""
def __init__(self, collection_name: str, config: IrisVectorConfig) -> None:
super().__init__(collection_name)
self.config = config
self.table_name = f"embedding_{collection_name}".upper()
self.schema = config.IRIS_SCHEMA or "dify"
self.pool = get_iris_pool(config)
def get_type(self) -> str:
return VectorType.IRIS
@contextmanager
def _get_cursor(self):
"""Context manager for database cursor with connection pooling."""
conn = self.pool.get_connection()
cursor = conn.cursor()
try:
yield cursor
conn.commit()
except Exception:
conn.rollback()
raise
finally:
cursor.close()
self.pool.return_connection(conn)
def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs) -> list[str]:
dimension = len(embeddings[0])
self._create_collection(dimension)
return self.add_texts(texts, embeddings)
def add_texts(self, documents: list[Document], embeddings: list[list[float]], **_kwargs) -> list[str]:
"""Add documents with embeddings to the collection."""
added_ids = []
with self._get_cursor() as cursor:
for i, doc in enumerate(documents):
doc_id = doc.metadata.get("doc_id", str(uuid.uuid4())) if doc.metadata else str(uuid.uuid4())
metadata = json.dumps(doc.metadata) if doc.metadata else "{}"
embedding_str = json.dumps(embeddings[i])
sql = f"INSERT INTO {self.schema}.{self.table_name} (id, text, meta, embedding) VALUES (?, ?, ?, ?)"
cursor.execute(sql, (doc_id, doc.page_content, metadata, embedding_str))
added_ids.append(doc_id)
return added_ids
def text_exists(self, id: str) -> bool: # pylint: disable=redefined-builtin
try:
with self._get_cursor() as cursor:
sql = f"SELECT 1 FROM {self.schema}.{self.table_name} WHERE id = ?"
cursor.execute(sql, (id,))
return cursor.fetchone() is not None
except (OSError, RuntimeError, ValueError):
return False
def delete_by_ids(self, ids: list[str]) -> None:
if not ids:
return
with self._get_cursor() as cursor:
placeholders = ",".join(["?" for _ in ids])
sql = f"DELETE FROM {self.schema}.{self.table_name} WHERE id IN ({placeholders})"
cursor.execute(sql, ids)
def delete_by_metadata_field(self, key: str, value: str) -> None:
"""Delete documents by metadata field (JSON LIKE pattern matching)."""
with self._get_cursor() as cursor:
pattern = f'%"{key}": "{value}"%'
sql = f"DELETE FROM {self.schema}.{self.table_name} WHERE meta LIKE ?"
cursor.execute(sql, (pattern,))
def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
"""Search similar documents using VECTOR_COSINE with HNSW index."""
top_k = kwargs.get("top_k", 4)
score_threshold = float(kwargs.get("score_threshold") or 0.0)
embedding_str = json.dumps(query_vector)
with self._get_cursor() as cursor:
sql = f"""
SELECT TOP {top_k} id, text, meta, VECTOR_COSINE(embedding, ?) as score
FROM {self.schema}.{self.table_name}
ORDER BY score DESC
"""
cursor.execute(sql, (embedding_str,))
docs = []
for row in cursor.fetchall():
if len(row) >= 4:
text, meta_str, score = row[1], row[2], float(row[3])
if score >= score_threshold:
metadata = json.loads(meta_str) if meta_str else {}
metadata["score"] = score
docs.append(Document(page_content=text, metadata=metadata))
return docs
def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
"""Search documents by full-text using iFind index or fallback to LIKE search."""
top_k = kwargs.get("top_k", 5)
with self._get_cursor() as cursor:
if self.config.IRIS_TEXT_INDEX:
# Use iFind full-text search with index
text_index_name = f"idx_{self.table_name}_text"
sql = f"""
SELECT TOP {top_k} id, text, meta
FROM {self.schema}.{self.table_name}
WHERE %ID %FIND search_index({text_index_name}, ?)
"""
cursor.execute(sql, (query,))
else:
# Fallback to LIKE search (inefficient for large datasets)
query_pattern = f"%{query}%"
sql = f"""
SELECT TOP {top_k} id, text, meta
FROM {self.schema}.{self.table_name}
WHERE text LIKE ?
"""
cursor.execute(sql, (query_pattern,))
docs = []
for row in cursor.fetchall():
if len(row) >= 3:
metadata = json.loads(row[2]) if row[2] else {}
docs.append(Document(page_content=row[1], metadata=metadata))
if not docs:
logger.info("Full-text search for '%s' returned no results", query)
return docs
def delete(self) -> None:
"""Delete the entire collection (drop table - permanent)."""
with self._get_cursor() as cursor:
sql = f"DROP TABLE {self.schema}.{self.table_name}"
cursor.execute(sql)
def _create_collection(self, dimension: int) -> None:
"""Create table with VECTOR column and HNSW index.
Uses Redis lock to prevent concurrent creation attempts across multiple
API server instances (api, worker, worker_beat).
"""
cache_key = f"vector_indexing_{self._collection_name}"
lock_name = f"{cache_key}_lock"
with redis_client.lock(lock_name, timeout=20): # pylint: disable=not-context-manager
if redis_client.get(cache_key):
return
# Ensure schema exists (idempotent, cached after first call)
self.pool.ensure_schema_exists(self.schema)
with self._get_cursor() as cursor:
# Create table with VECTOR column
sql = f"""
CREATE TABLE {self.schema}.{self.table_name} (
id VARCHAR(255) PRIMARY KEY,
text CLOB,
meta CLOB,
embedding VECTOR(DOUBLE, {dimension})
)
"""
logger.info("Creating table: %s.%s", self.schema, self.table_name)
cursor.execute(sql)
# Create HNSW index for vector similarity search
index_name = f"idx_{self.table_name}_embedding"
sql_index = (
f"CREATE INDEX {index_name} ON {self.schema}.{self.table_name} "
"(embedding) AS HNSW(Distance='Cosine')"
)
logger.info("Creating HNSW index: %s", index_name)
cursor.execute(sql_index)
logger.info("HNSW index created successfully: %s", index_name)
# Create full-text search index if enabled
logger.info(
"IRIS_TEXT_INDEX config value: %s (type: %s)",
self.config.IRIS_TEXT_INDEX,
type(self.config.IRIS_TEXT_INDEX),
)
if self.config.IRIS_TEXT_INDEX:
text_index_name = f"idx_{self.table_name}_text"
language = self.config.IRIS_TEXT_INDEX_LANGUAGE
# Fixed: Removed extra parentheses and corrected syntax
sql_text_index = f"""
CREATE INDEX {text_index_name} ON {self.schema}.{self.table_name} (text)
AS %iFind.Index.Basic
(LANGUAGE = '{language}', LOWER = 1, INDEXOPTION = 0)
"""
logger.info("Creating text index: %s with language: %s", text_index_name, language)
logger.info("SQL for text index: %s", sql_text_index)
cursor.execute(sql_text_index)
logger.info("Text index created successfully: %s", text_index_name)
else:
logger.warning("Text index creation skipped - IRIS_TEXT_INDEX is disabled")
redis_client.set(cache_key, 1, ex=3600)
class IrisVectorFactory(AbstractVectorFactory):
"""Factory for creating IrisVector instances."""
def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> IrisVector:
if dataset.index_struct_dict:
class_prefix: str = dataset.index_struct_dict["vector_store"]["class_prefix"]
collection_name = class_prefix
else:
dataset_id = dataset.id
collection_name = Dataset.gen_collection_name_by_id(dataset_id)
index_struct_dict = self.gen_index_struct_dict(VectorType.IRIS, collection_name)
dataset.index_struct = json.dumps(index_struct_dict)
return IrisVector(
collection_name=collection_name,
config=IrisVectorConfig(
IRIS_HOST=dify_config.IRIS_HOST,
IRIS_SUPER_SERVER_PORT=dify_config.IRIS_SUPER_SERVER_PORT,
IRIS_USER=dify_config.IRIS_USER,
IRIS_PASSWORD=dify_config.IRIS_PASSWORD,
IRIS_DATABASE=dify_config.IRIS_DATABASE,
IRIS_SCHEMA=dify_config.IRIS_SCHEMA,
IRIS_CONNECTION_URL=dify_config.IRIS_CONNECTION_URL,
IRIS_MIN_CONNECTION=dify_config.IRIS_MIN_CONNECTION,
IRIS_MAX_CONNECTION=dify_config.IRIS_MAX_CONNECTION,
IRIS_TEXT_INDEX=dify_config.IRIS_TEXT_INDEX,
IRIS_TEXT_INDEX_LANGUAGE=dify_config.IRIS_TEXT_INDEX_LANGUAGE,
),
)

View File

@ -187,6 +187,10 @@ class Vector:
from core.rag.datasource.vdb.clickzetta.clickzetta_vector import ClickzettaVectorFactory
return ClickzettaVectorFactory
case VectorType.IRIS:
from core.rag.datasource.vdb.iris.iris_vector import IrisVectorFactory
return IrisVectorFactory
case _:
raise ValueError(f"Vector store {vector_type} is not supported.")

View File

@ -32,3 +32,4 @@ class VectorType(StrEnum):
HUAWEI_CLOUD = "huawei_cloud"
MATRIXONE = "matrixone"
CLICKZETTA = "clickzetta"
IRIS = "iris"

View File

@ -1,7 +1,7 @@
"""Abstract interface for document loader implementations."""
import os
from typing import cast
from typing import TypedDict
import pandas as pd
from openpyxl import load_workbook
@ -10,6 +10,12 @@ from core.rag.extractor.extractor_base import BaseExtractor
from core.rag.models.document import Document
class Candidate(TypedDict):
idx: int
count: int
map: dict[int, str]
class ExcelExtractor(BaseExtractor):
"""Load Excel files.
@ -30,32 +36,38 @@ class ExcelExtractor(BaseExtractor):
file_extension = os.path.splitext(self._file_path)[-1].lower()
if file_extension == ".xlsx":
wb = load_workbook(self._file_path, data_only=True)
for sheet_name in wb.sheetnames:
sheet = wb[sheet_name]
data = sheet.values
cols = next(data, None)
if cols is None:
continue
df = pd.DataFrame(data, columns=cols)
df.dropna(how="all", inplace=True)
for index, row in df.iterrows():
page_content = []
for col_index, (k, v) in enumerate(row.items()):
if pd.notna(v):
cell = sheet.cell(
row=cast(int, index) + 2, column=col_index + 1
) # +2 to account for header and 1-based index
if cell.hyperlink:
value = f"[{v}]({cell.hyperlink.target})"
page_content.append(f'"{k}":"{value}"')
else:
page_content.append(f'"{k}":"{v}"')
documents.append(
Document(page_content=";".join(page_content), metadata={"source": self._file_path})
)
wb = load_workbook(self._file_path, read_only=True, data_only=True)
try:
for sheet_name in wb.sheetnames:
sheet = wb[sheet_name]
header_row_idx, column_map, max_col_idx = self._find_header_and_columns(sheet)
if not column_map:
continue
start_row = header_row_idx + 1
for row in sheet.iter_rows(min_row=start_row, max_col=max_col_idx, values_only=False):
if all(cell.value is None for cell in row):
continue
page_content = []
for col_idx, cell in enumerate(row):
value = cell.value
if col_idx in column_map:
col_name = column_map[col_idx]
if hasattr(cell, "hyperlink") and cell.hyperlink:
target = getattr(cell.hyperlink, "target", None)
if target:
value = f"[{value}]({target})"
if value is None:
value = ""
elif not isinstance(value, str):
value = str(value)
value = value.strip().replace('"', '\\"')
page_content.append(f'"{col_name}":"{value}"')
if page_content:
documents.append(
Document(page_content=";".join(page_content), metadata={"source": self._file_path})
)
finally:
wb.close()
elif file_extension == ".xls":
excel_file = pd.ExcelFile(self._file_path, engine="xlrd")
@ -63,9 +75,9 @@ class ExcelExtractor(BaseExtractor):
df = excel_file.parse(sheet_name=excel_sheet_name)
df.dropna(how="all", inplace=True)
for _, row in df.iterrows():
for _, series_row in df.iterrows():
page_content = []
for k, v in row.items():
for k, v in series_row.items():
if pd.notna(v):
page_content.append(f'"{k}":"{v}"')
documents.append(
@ -75,3 +87,61 @@ class ExcelExtractor(BaseExtractor):
raise ValueError(f"Unsupported file extension: {file_extension}")
return documents
def _find_header_and_columns(self, sheet, scan_rows=10) -> tuple[int, dict[int, str], int]:
"""
Scan first N rows to find the most likely header row.
Returns:
header_row_idx: 1-based index of the header row
column_map: Dict mapping 0-based column index to column name
max_col_idx: 1-based index of the last valid column (for iter_rows boundary)
"""
# Store potential candidates: (row_index, non_empty_count, column_map)
candidates: list[Candidate] = []
# Limit scan to avoid performance issues on huge files
# We iterate manually to control the read scope
for current_row_idx, row in enumerate(sheet.iter_rows(min_row=1, max_row=scan_rows, values_only=True), start=1):
# Filter out empty cells and build a temp map for this row
# col_idx is 0-based
row_map = {}
for col_idx, cell_value in enumerate(row):
if cell_value is not None and str(cell_value).strip():
row_map[col_idx] = str(cell_value).strip().replace('"', '\\"')
if not row_map:
continue
non_empty_count = len(row_map)
# Header selection heuristic (implemented):
# - Prefer the first row with at least 2 non-empty columns.
# - Fallback: choose the row with the most non-empty columns
# (tie-breaker: smaller row index).
candidates.append({"idx": current_row_idx, "count": non_empty_count, "map": row_map})
if not candidates:
return 0, {}, 0
# Choose the best candidate header row.
best_candidate: Candidate | None = None
# Strategy: prefer the first row with >= 2 non-empty columns; otherwise fallback.
for cand in candidates:
if cand["count"] >= 2:
best_candidate = cand
break
# Fallback: if no row has >= 2 columns, or all have 1, just take the one with max columns
if not best_candidate:
# Sort by count desc, then index asc
candidates.sort(key=lambda x: (-x["count"], x["idx"]))
best_candidate = candidates[0]
# Determine max_col_idx (1-based for openpyxl)
# It is the index of the last valid column in our map + 1
max_col_idx = max(best_candidate["map"].keys()) + 1
return best_candidate["idx"], best_candidate["map"], max_col_idx

View File

@ -84,22 +84,45 @@ class WordExtractor(BaseExtractor):
image_count = 0
image_map = {}
for rel in doc.part.rels.values():
for r_id, rel in doc.part.rels.items():
if "image" in rel.target_ref:
image_count += 1
if rel.is_external:
url = rel.target_ref
response = ssrf_proxy.get(url)
if not self._is_valid_url(url):
continue
try:
response = ssrf_proxy.get(url)
except Exception as e:
logger.warning("Failed to download image from URL: %s: %s", url, str(e))
continue
if response.status_code == 200:
image_ext = mimetypes.guess_extension(response.headers["Content-Type"])
image_ext = mimetypes.guess_extension(response.headers.get("Content-Type", ""))
if image_ext is None:
continue
file_uuid = str(uuid.uuid4())
file_key = "image_files/" + self.tenant_id + "/" + file_uuid + "." + image_ext
file_key = "image_files/" + self.tenant_id + "/" + file_uuid + image_ext
mime_type, _ = mimetypes.guess_type(file_key)
storage.save(file_key, response.content)
else:
continue
# save file to db
upload_file = UploadFile(
tenant_id=self.tenant_id,
storage_type=dify_config.STORAGE_TYPE,
key=file_key,
name=file_key,
size=0,
extension=str(image_ext),
mime_type=mime_type or "",
created_by=self.user_id,
created_by_role=CreatorUserRole.ACCOUNT,
created_at=naive_utc_now(),
used=True,
used_by=self.user_id,
used_at=naive_utc_now(),
)
db.session.add(upload_file)
# Use r_id as key for external images since target_part is undefined
image_map[r_id] = f"![image]({dify_config.FILES_URL}/files/{upload_file.id}/file-preview)"
else:
image_ext = rel.target_ref.split(".")[-1]
if image_ext is None:
@ -110,27 +133,28 @@ class WordExtractor(BaseExtractor):
mime_type, _ = mimetypes.guess_type(file_key)
storage.save(file_key, rel.target_part.blob)
# save file to db
upload_file = UploadFile(
tenant_id=self.tenant_id,
storage_type=dify_config.STORAGE_TYPE,
key=file_key,
name=file_key,
size=0,
extension=str(image_ext),
mime_type=mime_type or "",
created_by=self.user_id,
created_by_role=CreatorUserRole.ACCOUNT,
created_at=naive_utc_now(),
used=True,
used_by=self.user_id,
used_at=naive_utc_now(),
)
db.session.add(upload_file)
db.session.commit()
image_map[rel.target_part] = f"![image]({dify_config.FILES_URL}/files/{upload_file.id}/file-preview)"
# save file to db
upload_file = UploadFile(
tenant_id=self.tenant_id,
storage_type=dify_config.STORAGE_TYPE,
key=file_key,
name=file_key,
size=0,
extension=str(image_ext),
mime_type=mime_type or "",
created_by=self.user_id,
created_by_role=CreatorUserRole.ACCOUNT,
created_at=naive_utc_now(),
used=True,
used_by=self.user_id,
used_at=naive_utc_now(),
)
db.session.add(upload_file)
# Use target_part as key for internal images
image_map[rel.target_part] = (
f"![image]({dify_config.FILES_URL}/files/{upload_file.id}/file-preview)"
)
db.session.commit()
return image_map
def _table_to_markdown(self, table, image_map):
@ -186,11 +210,17 @@ class WordExtractor(BaseExtractor):
image_id = blip.get("{http://schemas.openxmlformats.org/officeDocument/2006/relationships}embed")
if not image_id:
continue
image_part = paragraph.part.rels[image_id].target_part
if image_part in image_map:
image_link = image_map[image_part]
paragraph_content.append(image_link)
rel = paragraph.part.rels.get(image_id)
if rel is None:
continue
# For external images, use image_id as key; for internal, use target_part
if rel.is_external:
if image_id in image_map:
paragraph_content.append(image_map[image_id])
else:
image_part = rel.target_part
if image_part in image_map:
paragraph_content.append(image_map[image_part])
else:
paragraph_content.append(run.text)
return "".join(paragraph_content).strip()
@ -227,6 +257,18 @@ class WordExtractor(BaseExtractor):
def parse_paragraph(paragraph):
paragraph_content = []
def append_image_link(image_id, has_drawing):
"""Helper to append image link from image_map based on relationship type."""
rel = doc.part.rels[image_id]
if rel.is_external:
if image_id in image_map and not has_drawing:
paragraph_content.append(image_map[image_id])
else:
image_part = rel.target_part
if image_part in image_map and not has_drawing:
paragraph_content.append(image_map[image_part])
for run in paragraph.runs:
if hasattr(run.element, "tag") and isinstance(run.element.tag, str) and run.element.tag.endswith("r"):
# Process drawing type images
@ -243,10 +285,18 @@ class WordExtractor(BaseExtractor):
"{http://schemas.openxmlformats.org/officeDocument/2006/relationships}embed"
)
if embed_id:
image_part = doc.part.related_parts.get(embed_id)
if image_part in image_map:
has_drawing = True
paragraph_content.append(image_map[image_part])
rel = doc.part.rels.get(embed_id)
if rel is not None and rel.is_external:
# External image: use embed_id as key
if embed_id in image_map:
has_drawing = True
paragraph_content.append(image_map[embed_id])
else:
# Internal image: use target_part as key
image_part = doc.part.related_parts.get(embed_id)
if image_part in image_map:
has_drawing = True
paragraph_content.append(image_map[image_part])
# Process pict type images
shape_elements = run.element.findall(
".//{http://schemas.openxmlformats.org/wordprocessingml/2006/main}pict"
@ -261,9 +311,7 @@ class WordExtractor(BaseExtractor):
"{http://schemas.openxmlformats.org/officeDocument/2006/relationships}id"
)
if image_id and image_id in doc.part.rels:
image_part = doc.part.rels[image_id].target_part
if image_part in image_map and not has_drawing:
paragraph_content.append(image_map[image_part])
append_image_link(image_id, has_drawing)
# Find imagedata element in VML
image_data = shape.find(".//{urn:schemas-microsoft-com:vml}imagedata")
if image_data is not None:
@ -271,9 +319,7 @@ class WordExtractor(BaseExtractor):
"{http://schemas.openxmlformats.org/officeDocument/2006/relationships}id"
)
if image_id and image_id in doc.part.rels:
image_part = doc.part.rels[image_id].target_part
if image_part in image_map and not has_drawing:
paragraph_content.append(image_map[image_part])
append_image_link(image_id, has_drawing)
if run.text.strip():
paragraph_content.append(run.text.strip())
return "".join(paragraph_content) if paragraph_content else ""

View File

@ -209,7 +209,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor):
if dataset.indexing_technique == "high_quality":
vector = Vector(dataset)
vector.create(documents)
if all_multimodal_documents:
if all_multimodal_documents and dataset.is_multimodal:
vector.create_multimodal(all_multimodal_documents)
elif dataset.indexing_technique == "economy":
keyword = Keyword(dataset)

View File

@ -312,7 +312,7 @@ class ParentChildIndexProcessor(BaseIndexProcessor):
vector = Vector(dataset)
if all_child_documents:
vector.create(all_child_documents)
if all_multimodal_documents:
if all_multimodal_documents and dataset.is_multimodal:
vector.create_multimodal(all_multimodal_documents)
def format_preview(self, chunks: Any) -> Mapping[str, Any]:

View File

@ -266,7 +266,7 @@ class DatasetRetrieval:
).all()
if attachments_with_bindings:
for _, upload_file in attachments_with_bindings:
attchment_info = File(
attachment_info = File(
id=upload_file.id,
filename=upload_file.name,
extension="." + upload_file.extension,
@ -280,7 +280,7 @@ class DatasetRetrieval:
storage_key=upload_file.key,
url=sign_upload_file(upload_file.id, upload_file.extension),
)
context_files.append(attchment_info)
context_files.append(attachment_info)
if show_retrieve_source:
for record in records:
segment = record.segment
@ -592,111 +592,116 @@ class DatasetRetrieval:
"""Handle retrieval end."""
with flask_app.app_context():
dify_documents = [document for document in documents if document.provider == "dify"]
segment_ids = []
segment_index_node_ids = []
if not dify_documents:
self._send_trace_task(message_id, documents, timer)
return
with Session(db.engine) as session:
for document in dify_documents:
if document.metadata is not None:
dataset_document_stmt = select(DatasetDocument).where(
DatasetDocument.id == document.metadata["document_id"]
)
dataset_document = session.scalar(dataset_document_stmt)
if dataset_document:
if dataset_document.doc_form == IndexStructureType.PARENT_CHILD_INDEX:
segment_id = None
if (
"doc_type" not in document.metadata
or document.metadata.get("doc_type") == DocType.TEXT
):
child_chunk_stmt = select(ChildChunk).where(
ChildChunk.index_node_id == document.metadata["doc_id"],
ChildChunk.dataset_id == dataset_document.dataset_id,
ChildChunk.document_id == dataset_document.id,
)
child_chunk = session.scalar(child_chunk_stmt)
if child_chunk:
segment_id = child_chunk.segment_id
elif (
"doc_type" in document.metadata
and document.metadata.get("doc_type") == DocType.IMAGE
):
attachment_info_dict = RetrievalService.get_segment_attachment_info(
dataset_document.dataset_id,
dataset_document.tenant_id,
document.metadata.get("doc_id") or "",
session,
)
if attachment_info_dict:
segment_id = attachment_info_dict["segment_id"]
# Collect all document_ids and batch fetch DatasetDocuments
document_ids = {
doc.metadata["document_id"]
for doc in dify_documents
if doc.metadata and "document_id" in doc.metadata
}
if not document_ids:
self._send_trace_task(message_id, documents, timer)
return
dataset_docs_stmt = select(DatasetDocument).where(DatasetDocument.id.in_(document_ids))
dataset_docs = session.scalars(dataset_docs_stmt).all()
dataset_doc_map = {str(doc.id): doc for doc in dataset_docs}
# Categorize documents by type and collect necessary IDs
parent_child_text_docs: list[tuple[Document, DatasetDocument]] = []
parent_child_image_docs: list[tuple[Document, DatasetDocument]] = []
normal_text_docs: list[tuple[Document, DatasetDocument]] = []
normal_image_docs: list[tuple[Document, DatasetDocument]] = []
for doc in dify_documents:
if not doc.metadata or "document_id" not in doc.metadata:
continue
dataset_doc = dataset_doc_map.get(doc.metadata["document_id"])
if not dataset_doc:
continue
is_image = doc.metadata.get("doc_type") == DocType.IMAGE
is_parent_child = dataset_doc.doc_form == IndexStructureType.PARENT_CHILD_INDEX
if is_parent_child:
if is_image:
parent_child_image_docs.append((doc, dataset_doc))
else:
parent_child_text_docs.append((doc, dataset_doc))
else:
if is_image:
normal_image_docs.append((doc, dataset_doc))
else:
normal_text_docs.append((doc, dataset_doc))
segment_ids_to_update: set[str] = set()
# Process PARENT_CHILD_INDEX text documents - batch fetch ChildChunks
if parent_child_text_docs:
index_node_ids = [doc.metadata["doc_id"] for doc, _ in parent_child_text_docs if doc.metadata]
if index_node_ids:
child_chunks_stmt = select(ChildChunk).where(ChildChunk.index_node_id.in_(index_node_ids))
child_chunks = session.scalars(child_chunks_stmt).all()
child_chunk_map = {chunk.index_node_id: chunk.segment_id for chunk in child_chunks}
for doc, _ in parent_child_text_docs:
if doc.metadata:
segment_id = child_chunk_map.get(doc.metadata["doc_id"])
if segment_id:
if segment_id not in segment_ids:
segment_ids.append(segment_id)
_ = (
session.query(DocumentSegment)
.where(DocumentSegment.id == segment_id)
.update(
{DocumentSegment.hit_count: DocumentSegment.hit_count + 1},
synchronize_session=False,
)
)
else:
query = None
if (
"doc_type" not in document.metadata
or document.metadata.get("doc_type") == DocType.TEXT
):
if document.metadata["doc_id"] not in segment_index_node_ids:
segment = (
session.query(DocumentSegment)
.where(DocumentSegment.index_node_id == document.metadata["doc_id"])
.first()
)
if segment:
segment_index_node_ids.append(document.metadata["doc_id"])
segment_ids.append(segment.id)
query = session.query(DocumentSegment).where(
DocumentSegment.id == segment.id
)
elif (
"doc_type" in document.metadata
and document.metadata.get("doc_type") == DocType.IMAGE
):
attachment_info_dict = RetrievalService.get_segment_attachment_info(
dataset_document.dataset_id,
dataset_document.tenant_id,
document.metadata.get("doc_id") or "",
session,
)
if attachment_info_dict:
segment_id = attachment_info_dict["segment_id"]
if segment_id not in segment_ids:
segment_ids.append(segment_id)
query = session.query(DocumentSegment).where(DocumentSegment.id == segment_id)
if query:
# if 'dataset_id' in document.metadata:
if "dataset_id" in document.metadata:
query = query.where(
DocumentSegment.dataset_id == document.metadata["dataset_id"]
)
segment_ids_to_update.add(str(segment_id))
# add hit count to document segment
query.update(
{DocumentSegment.hit_count: DocumentSegment.hit_count + 1},
synchronize_session=False,
)
# Process non-PARENT_CHILD_INDEX text documents - batch fetch DocumentSegments
if normal_text_docs:
index_node_ids = [doc.metadata["doc_id"] for doc, _ in normal_text_docs if doc.metadata]
if index_node_ids:
segments_stmt = select(DocumentSegment).where(DocumentSegment.index_node_id.in_(index_node_ids))
segments = session.scalars(segments_stmt).all()
segment_map = {seg.index_node_id: seg.id for seg in segments}
for doc, _ in normal_text_docs:
if doc.metadata:
segment_id = segment_map.get(doc.metadata["doc_id"])
if segment_id:
segment_ids_to_update.add(str(segment_id))
db.session.commit()
# Process IMAGE documents - batch fetch SegmentAttachmentBindings
all_image_docs = parent_child_image_docs + normal_image_docs
if all_image_docs:
attachment_ids = [
doc.metadata["doc_id"]
for doc, _ in all_image_docs
if doc.metadata and doc.metadata.get("doc_id")
]
if attachment_ids:
bindings_stmt = select(SegmentAttachmentBinding).where(
SegmentAttachmentBinding.attachment_id.in_(attachment_ids)
)
bindings = session.scalars(bindings_stmt).all()
segment_ids_to_update.update(str(binding.segment_id) for binding in bindings)
# get tracing instance
trace_manager: TraceQueueManager | None = (
self.application_generate_entity.trace_manager if self.application_generate_entity else None
)
if trace_manager:
trace_manager.add_trace_task(
TraceTask(
TraceTaskName.DATASET_RETRIEVAL_TRACE, message_id=message_id, documents=documents, timer=timer
# Batch update hit_count for all segments
if segment_ids_to_update:
session.query(DocumentSegment).where(DocumentSegment.id.in_(segment_ids_to_update)).update(
{DocumentSegment.hit_count: DocumentSegment.hit_count + 1},
synchronize_session=False,
)
session.commit()
self._send_trace_task(message_id, documents, timer)
def _send_trace_task(self, message_id: str | None, documents: list[Document], timer: dict | None):
"""Send trace task if trace manager is available."""
trace_manager: TraceQueueManager | None = (
self.application_generate_entity.trace_manager if self.application_generate_entity else None
)
if trace_manager:
trace_manager.add_trace_task(
TraceTask(
TraceTaskName.DATASET_RETRIEVAL_TRACE, message_id=message_id, documents=documents, timer=timer
)
)
def _on_query(
self,

View File

@ -101,6 +101,8 @@ class ToolFileMessageTransformer:
meta = message.meta or {}
mimetype = meta.get("mime_type", "application/octet-stream")
if not mimetype:
mimetype = "application/octet-stream"
# get filename from meta
filename = meta.get("filename", None)
# if message is str, encode it to bytes

View File

@ -13,5 +13,5 @@ def remove_leading_symbols(text: str) -> str:
"""
# Match Unicode ranges for punctuation and symbols
# FIXME this pattern is confused quick fix for #11868 maybe refactor it later
pattern = r"^[\u2000-\u206F\u2E00-\u2E7F\u3000-\u303F\"#$%&'()*+,./:;<=>?@^_`~]+"
pattern = r'^[\[\]\u2000-\u2025\u2027-\u206F\u2E00-\u2E7F\u3000-\u300F\u3011-\u303F"#$%&\'()*+,./:;<=>?@^_`~]+'
return re.sub(pattern, "", text)

View File

@ -221,7 +221,7 @@ class WorkflowToolProviderController(ToolProviderController):
session.query(WorkflowToolProvider)
.where(
WorkflowToolProvider.tenant_id == tenant_id,
WorkflowToolProvider.app_id == self.provider_id,
WorkflowToolProvider.id == self.provider_id,
)
.first()
)

View File

@ -59,7 +59,7 @@ class OutputVariableEntity(BaseModel):
"""
variable: str
value_type: OutputVariableType
value_type: OutputVariableType = OutputVariableType.ANY
value_selector: Sequence[str]
@field_validator("value_type", mode="before")

View File

@ -412,16 +412,20 @@ class Executor:
body_string += f"--{boundary}\r\n"
body_string += f'Content-Disposition: form-data; name="{key}"\r\n\r\n'
# decode content safely
try:
body_string += content.decode("utf-8")
except UnicodeDecodeError:
body_string += content.decode("utf-8", errors="replace")
body_string += "\r\n"
# Do not decode binary content; use a placeholder with file metadata instead.
# Includes filename, size, and MIME type for better logging context.
body_string += (
f"<file_content_binary: '{file_entry[1][0] or 'unknown'}', "
f"type='{file_entry[1][2] if len(file_entry[1]) > 2 else 'unknown'}', "
f"size={len(content)} bytes>\r\n"
)
body_string += f"--{boundary}--\r\n"
elif self.node_data.body:
if self.content:
# If content is bytes, do not decode it; show a placeholder with size.
# Provides content size information for binary data without exposing the raw bytes.
if isinstance(self.content, bytes):
body_string = self.content.decode("utf-8", errors="replace")
body_string = f"<binary_content: size={len(self.content)} bytes>"
else:
body_string = self.content
elif self.data and self.node_data.body.type == "x-www-form-urlencoded":

View File

@ -697,7 +697,7 @@ class LLMNode(Node[LLMNodeData]):
).all()
if attachments_with_bindings:
for _, upload_file in attachments_with_bindings:
attchment_info = File(
attachment_info = File(
id=upload_file.id,
filename=upload_file.name,
extension="." + upload_file.extension,
@ -711,7 +711,7 @@ class LLMNode(Node[LLMNodeData]):
storage_key=upload_file.key,
url=sign_upload_file(upload_file.id, upload_file.extension),
)
context_files.append(attchment_info)
context_files.append(attachment_info)
yield RunRetrieverResourceEvent(
retriever_resources=original_retriever_resource,
context=context_str.strip(),

View File

@ -15,4 +15,5 @@ def handle(sender: Dataset, **kwargs):
dataset.index_struct,
dataset.collection_binding_id,
dataset.doc_form,
dataset.pipeline_id,
)

View File

@ -9,11 +9,21 @@ FILES_HEADERS: tuple[str, ...] = (*BASE_CORS_HEADERS, HEADER_NAME_CSRF_TOKEN)
EXPOSED_HEADERS: tuple[str, ...] = ("X-Version", "X-Env", "X-Trace-Id")
def init_app(app: DifyApp):
# register blueprint routers
def _apply_cors_once(bp, /, **cors_kwargs):
"""Make CORS idempotent so blueprints can be reused across multiple app instances."""
if getattr(bp, "_dify_cors_applied", False):
return
from flask_cors import CORS
CORS(bp, **cors_kwargs)
bp._dify_cors_applied = True
def init_app(app: DifyApp):
# register blueprint routers
from controllers.console import bp as console_app_bp
from controllers.files import bp as files_bp
from controllers.inner_api import bp as inner_api_bp
@ -22,7 +32,7 @@ def init_app(app: DifyApp):
from controllers.trigger import bp as trigger_bp
from controllers.web import bp as web_bp
CORS(
_apply_cors_once(
service_api_bp,
allow_headers=list(SERVICE_API_HEADERS),
methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
@ -30,7 +40,7 @@ def init_app(app: DifyApp):
)
app.register_blueprint(service_api_bp)
CORS(
_apply_cors_once(
web_bp,
resources={r"/*": {"origins": dify_config.WEB_API_CORS_ALLOW_ORIGINS}},
supports_credentials=True,
@ -40,7 +50,7 @@ def init_app(app: DifyApp):
)
app.register_blueprint(web_bp)
CORS(
_apply_cors_once(
console_app_bp,
resources={r"/*": {"origins": dify_config.CONSOLE_CORS_ALLOW_ORIGINS}},
supports_credentials=True,
@ -50,7 +60,7 @@ def init_app(app: DifyApp):
)
app.register_blueprint(console_app_bp)
CORS(
_apply_cors_once(
files_bp,
allow_headers=list(FILES_HEADERS),
methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
@ -62,7 +72,7 @@ def init_app(app: DifyApp):
app.register_blueprint(mcp_bp)
# Register trigger blueprint with CORS for webhook calls
CORS(
_apply_cors_once(
trigger_bp,
allow_headers=["Content-Type", "Authorization", "X-App-Code"],
methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH", "HEAD"],

View File

@ -22,8 +22,8 @@ login_manager = flask_login.LoginManager()
@login_manager.request_loader
def load_user_from_request(request_from_flask_login):
"""Load user based on the request."""
# Skip authentication for documentation endpoints
if dify_config.SWAGGER_UI_ENABLED and request.path.endswith((dify_config.SWAGGER_UI_PATH, "/swagger.json")):
# Skip authentication for documentation endpoints (only when Swagger is enabled)
if dify_config.swagger_ui_enabled and request.path.endswith((dify_config.SWAGGER_UI_PATH, "/swagger.json")):
return None
auth_token = extract_access_token(request)

View File

@ -0,0 +1,7 @@
from core.db.session_factory import configure_session_factory
from extensions.ext_database import db
def init_app(app):
with app.app_context():
configure_session_factory(db.engine)

View File

@ -131,12 +131,28 @@ class ExternalApi(Api):
}
def __init__(self, app: Blueprint | Flask, *args, **kwargs):
import logging
import os
kwargs.setdefault("authorizations", self._authorizations)
kwargs.setdefault("security", "Bearer")
kwargs["add_specs"] = dify_config.SWAGGER_UI_ENABLED
kwargs["doc"] = dify_config.SWAGGER_UI_PATH if dify_config.SWAGGER_UI_ENABLED else False
# Security: Use computed swagger_ui_enabled which respects DEPLOY_ENV
swagger_enabled = dify_config.swagger_ui_enabled
kwargs["add_specs"] = swagger_enabled
kwargs["doc"] = dify_config.SWAGGER_UI_PATH if swagger_enabled else False
# manual separate call on construction and init_app to ensure configs in kwargs effective
super().__init__(app=None, *args, **kwargs)
self.init_app(app, **kwargs)
register_external_error_handlers(self)
# Security: Log warning when Swagger is enabled in production environment
deploy_env = os.environ.get("DEPLOY_ENV", "PRODUCTION")
if swagger_enabled and deploy_env.upper() == "PRODUCTION":
logger = logging.getLogger(__name__)
logger.warning(
"SECURITY WARNING: Swagger UI is ENABLED in PRODUCTION environment. "
"This may expose sensitive API documentation. "
"Set SWAGGER_UI_ENABLED=false or remove the explicit setting to disable."
)

View File

@ -107,7 +107,7 @@ def email(email):
EmailStr = Annotated[str, AfterValidator(email)]
def uuid_value(value):
def uuid_value(value: Any) -> str:
if value == "":
return str(value)
@ -215,7 +215,11 @@ def generate_text_hash(text: str) -> str:
def compact_generate_response(response: Union[Mapping, Generator, RateLimitGenerator]) -> Response:
if isinstance(response, dict):
return Response(response=json.dumps(jsonable_encoder(response)), status=200, mimetype="application/json")
return Response(
response=json.dumps(jsonable_encoder(response)),
status=200,
content_type="application/json; charset=utf-8",
)
else:
def generate() -> Generator:

View File

@ -1,4 +1,4 @@
"""empty message
"""mysql adaptation
Revision ID: 09cfdda155d1
Revises: 669ffd70119c
@ -97,11 +97,31 @@ def downgrade():
batch_op.alter_column('include_plugins',
existing_type=sa.JSON(),
type_=postgresql.ARRAY(sa.VARCHAR(length=255)),
existing_nullable=False)
existing_nullable=False,
postgresql_using="""
COALESCE(
regexp_replace(
replace(replace(include_plugins::text, '[', '{'), ']', '}'),
'"',
'',
'g'
)::varchar(255)[],
ARRAY[]::varchar(255)[]
)""")
batch_op.alter_column('exclude_plugins',
existing_type=sa.JSON(),
type_=postgresql.ARRAY(sa.VARCHAR(length=255)),
existing_nullable=False)
existing_nullable=False,
postgresql_using="""
COALESCE(
regexp_replace(
replace(replace(exclude_plugins::text, '[', '{'), ']', '}'),
'"',
'',
'g'
)::varchar(255)[],
ARRAY[]::varchar(255)[]
)""")
with op.batch_alter_table('external_knowledge_bindings', schema=None) as batch_op:
batch_op.alter_column('external_knowledge_id',

View File

@ -111,7 +111,11 @@ class App(Base):
else:
app_model_config = self.app_model_config
if app_model_config:
return app_model_config.pre_prompt
pre_prompt = app_model_config.pre_prompt or ""
# Truncate to 200 characters with ellipsis if using prompt as description
if len(pre_prompt) > 200:
return pre_prompt[:200] + "..."
return pre_prompt
else:
return ""
@ -259,7 +263,7 @@ class App(Base):
provider_id = tool.get("provider_id", "")
if provider_type == ToolProviderType.API:
if uuid.UUID(provider_id) not in existing_api_providers:
if provider_id not in existing_api_providers:
deleted_tools.append(
{
"type": ToolProviderType.API,
@ -835,7 +839,29 @@ class Conversation(Base):
@property
def status_count(self):
messages = db.session.scalars(select(Message).where(Message.conversation_id == self.id)).all()
from models.workflow import WorkflowRun
# Get all messages with workflow_run_id for this conversation
messages = db.session.scalars(
select(Message).where(Message.conversation_id == self.id, Message.workflow_run_id.isnot(None))
).all()
if not messages:
return None
# Batch load all workflow runs in a single query, filtered by this conversation's app_id
workflow_run_ids = [msg.workflow_run_id for msg in messages if msg.workflow_run_id]
workflow_runs = {}
if workflow_run_ids:
workflow_runs_query = db.session.scalars(
select(WorkflowRun).where(
WorkflowRun.id.in_(workflow_run_ids),
WorkflowRun.app_id == self.app_id, # Filter by this conversation's app_id
)
).all()
workflow_runs = {run.id: run for run in workflow_runs_query}
status_counts = {
WorkflowExecutionStatus.RUNNING: 0,
WorkflowExecutionStatus.SUCCEEDED: 0,
@ -845,18 +871,24 @@ class Conversation(Base):
}
for message in messages:
if message.workflow_run:
status_counts[WorkflowExecutionStatus(message.workflow_run.status)] += 1
# Guard against None to satisfy type checker and avoid invalid dict lookups
if message.workflow_run_id is None:
continue
workflow_run = workflow_runs.get(message.workflow_run_id)
if not workflow_run:
continue
return (
{
"success": status_counts[WorkflowExecutionStatus.SUCCEEDED],
"failed": status_counts[WorkflowExecutionStatus.FAILED],
"partial_success": status_counts[WorkflowExecutionStatus.PARTIAL_SUCCEEDED],
}
if messages
else None
)
try:
status_counts[WorkflowExecutionStatus(workflow_run.status)] += 1
except (ValueError, KeyError):
# Handle invalid status values gracefully
pass
return {
"success": status_counts[WorkflowExecutionStatus.SUCCEEDED],
"failed": status_counts[WorkflowExecutionStatus.FAILED],
"partial_success": status_counts[WorkflowExecutionStatus.PARTIAL_SUCCEEDED],
}
@property
def first_message(self):
@ -1255,13 +1287,9 @@ class Message(Base):
"id": self.id,
"app_id": self.app_id,
"conversation_id": self.conversation_id,
"model_provider": self.model_provider,
"model_id": self.model_id,
"inputs": self.inputs,
"query": self.query,
"message_tokens": self.message_tokens,
"answer_tokens": self.answer_tokens,
"provider_response_latency": self.provider_response_latency,
"total_price": self.total_price,
"message": self.message,
"answer": self.answer,
@ -1283,12 +1311,8 @@ class Message(Base):
id=data["id"],
app_id=data["app_id"],
conversation_id=data["conversation_id"],
model_provider=data.get("model_provider"),
model_id=data["model_id"],
inputs=data["inputs"],
message_tokens=data.get("message_tokens", 0),
answer_tokens=data.get("answer_tokens", 0),
provider_response_latency=data.get("provider_response_latency", 0.0),
total_price=data["total_price"],
query=data["query"],
message=data["message"],

View File

@ -1,6 +1,6 @@
[project]
name = "dify-api"
version = "1.10.1"
version = "1.11.1"
requires-python = ">=3.11,<3.13"
dependencies = [
@ -151,7 +151,7 @@ dev = [
"types-pywin32~=310.0.0",
"types-pyyaml~=6.0.12",
"types-regex~=2024.11.6",
"types-shapely~=2.0.0",
"types-shapely~=2.1.0",
"types-simplejson>=3.20.0",
"types-six>=1.17.0",
"types-tensorflow>=2.18.0",
@ -216,6 +216,7 @@ vdb = [
"pymochow==2.2.9",
"pyobvector~=0.2.17",
"qdrant-client==1.9.0",
"intersystems-irispython>=5.1.0",
"tablestore==6.3.7",
"tcvectordb~=1.6.4",
"tidb-vector==0.0.9",

View File

@ -1,5 +1,5 @@
[pytest]
addopts = --cov=./api --cov-report=json --cov-report=xml
addopts = --cov=./api --cov-report=json
env =
ANTHROPIC_API_KEY = sk-ant-api11-IamNotARealKeyJustForMockTestKawaiiiiiiiiii-NotBaka-ASkksz
AZURE_OPENAI_API_BASE = https://difyai-openai.openai.azure.com

View File

@ -118,7 +118,7 @@ class ConversationService:
app_model: App,
conversation_id: str,
user: Union[Account, EndUser] | None,
name: str,
name: str | None,
auto_generate: bool,
):
conversation = cls.get_conversation(app_model, conversation_id, user)

View File

@ -673,6 +673,8 @@ class DatasetService:
Returns:
str: Action to perform ('add', 'remove', 'update', or None)
"""
if "indexing_technique" not in data:
return None
if dataset.indexing_technique != data["indexing_technique"]:
if data["indexing_technique"] == "economy":
# Remove embedding model configuration for economy mode
@ -1634,6 +1636,20 @@ class DocumentService:
return [], ""
db.session.add(dataset_process_rule)
db.session.flush()
else:
# Fallback when no process_rule provided in knowledge_config:
# 1) reuse dataset.latest_process_rule if present
# 2) otherwise create an automatic rule
dataset_process_rule = getattr(dataset, "latest_process_rule", None)
if not dataset_process_rule:
dataset_process_rule = DatasetProcessRule(
dataset_id=dataset.id,
mode="automatic",
rules=json.dumps(DatasetProcessRule.AUTOMATIC_RULES),
created_by=account.id,
)
db.session.add(dataset_process_rule)
db.session.flush()
lock_name = f"add_document_lock_dataset_id_{dataset.id}"
try:
with redis_client.lock(lock_name, timeout=600):
@ -1645,65 +1661,67 @@ class DocumentService:
if not knowledge_config.data_source.info_list.file_info_list:
raise ValueError("File source info is required")
upload_file_list = knowledge_config.data_source.info_list.file_info_list.file_ids
for file_id in upload_file_list:
file = (
db.session.query(UploadFile)
.where(UploadFile.tenant_id == dataset.tenant_id, UploadFile.id == file_id)
.first()
files = (
db.session.query(UploadFile)
.where(
UploadFile.tenant_id == dataset.tenant_id,
UploadFile.id.in_(upload_file_list),
)
.all()
)
if len(files) != len(set(upload_file_list)):
raise FileNotExistsError("One or more files not found.")
# raise error if file not found
if not file:
raise FileNotExistsError()
file_name = file.name
file_names = [file.name for file in files]
db_documents = (
db.session.query(Document)
.where(
Document.dataset_id == dataset.id,
Document.tenant_id == current_user.current_tenant_id,
Document.data_source_type == "upload_file",
Document.enabled == True,
Document.name.in_(file_names),
)
.all()
)
documents_map = {document.name: document for document in db_documents}
for file in files:
data_source_info: dict[str, str | bool] = {
"upload_file_id": file_id,
"upload_file_id": file.id,
}
# check duplicate
if knowledge_config.duplicate:
document = (
db.session.query(Document)
.filter_by(
dataset_id=dataset.id,
tenant_id=current_user.current_tenant_id,
data_source_type="upload_file",
enabled=True,
name=file_name,
)
.first()
document = documents_map.get(file.name)
if knowledge_config.duplicate and document:
document.dataset_process_rule_id = dataset_process_rule.id
document.updated_at = naive_utc_now()
document.created_from = created_from
document.doc_form = knowledge_config.doc_form
document.doc_language = knowledge_config.doc_language
document.data_source_info = json.dumps(data_source_info)
document.batch = batch
document.indexing_status = "waiting"
db.session.add(document)
documents.append(document)
duplicate_document_ids.append(document.id)
continue
else:
document = DocumentService.build_document(
dataset,
dataset_process_rule.id,
knowledge_config.data_source.info_list.data_source_type,
knowledge_config.doc_form,
knowledge_config.doc_language,
data_source_info,
created_from,
position,
account,
file.name,
batch,
)
if document:
document.dataset_process_rule_id = dataset_process_rule.id
document.updated_at = naive_utc_now()
document.created_from = created_from
document.doc_form = knowledge_config.doc_form
document.doc_language = knowledge_config.doc_language
document.data_source_info = json.dumps(data_source_info)
document.batch = batch
document.indexing_status = "waiting"
db.session.add(document)
documents.append(document)
duplicate_document_ids.append(document.id)
continue
document = DocumentService.build_document(
dataset,
dataset_process_rule.id,
knowledge_config.data_source.info_list.data_source_type,
knowledge_config.doc_form,
knowledge_config.doc_language,
data_source_info,
created_from,
position,
account,
file_name,
batch,
)
db.session.add(document)
db.session.flush()
document_ids.append(document.id)
documents.append(document)
position += 1
db.session.add(document)
db.session.flush()
document_ids.append(document.id)
documents.append(document)
position += 1
elif knowledge_config.data_source.info_list.data_source_type == "notion_import":
notion_info_list = knowledge_config.data_source.info_list.notion_info_list # type: ignore
if not notion_info_list:
@ -2799,20 +2817,20 @@ class SegmentService:
db.session.add(binding)
db.session.commit()
# save vector index
try:
VectorService.create_segments_vector(
[args["keywords"]], [segment_document], dataset, document.doc_form
)
except Exception as e:
logger.exception("create segment index failed")
segment_document.enabled = False
segment_document.disabled_at = naive_utc_now()
segment_document.status = "error"
segment_document.error = str(e)
db.session.commit()
segment = db.session.query(DocumentSegment).where(DocumentSegment.id == segment_document.id).first()
return segment
# save vector index
try:
keywords = args.get("keywords")
keywords_list = [keywords] if keywords is not None else None
VectorService.create_segments_vector(keywords_list, [segment_document], dataset, document.doc_form)
except Exception as e:
logger.exception("create segment index failed")
segment_document.enabled = False
segment_document.disabled_at = naive_utc_now()
segment_document.status = "error"
segment_document.error = str(e)
db.session.commit()
segment = db.session.query(DocumentSegment).where(DocumentSegment.id == segment_document.id).first()
return segment
except LockNotOwnedError:
pass

View File

@ -178,8 +178,8 @@ class HitTestingService:
@classmethod
def hit_testing_args_check(cls, args):
query = args["query"]
attachment_ids = args["attachment_ids"]
query = args.get("query")
attachment_ids = args.get("attachment_ids")
if not attachment_ids and not query:
raise ValueError("Query or attachment_ids is required")

View File

@ -70,9 +70,28 @@ class ModelProviderService:
continue
provider_config = provider_configuration.custom_configuration.provider
model_config = provider_configuration.custom_configuration.models
models = provider_configuration.custom_configuration.models
can_added_models = provider_configuration.custom_configuration.can_added_models
# IMPORTANT: Never expose decrypted credentials in the provider list API.
# Sanitize custom model configurations by dropping the credentials payload.
sanitized_model_config = []
if models:
from core.entities.provider_entities import CustomModelConfiguration # local import to avoid cycles
for model in models:
sanitized_model_config.append(
CustomModelConfiguration(
model=model.model,
model_type=model.model_type,
credentials=None, # strip secrets from list view
current_credential_id=model.current_credential_id,
current_credential_name=model.current_credential_name,
available_model_credentials=model.available_model_credentials,
unadded_to_model_list=model.unadded_to_model_list,
)
)
provider_response = ProviderResponse(
tenant_id=tenant_id,
provider=provider_configuration.provider.provider,
@ -95,7 +114,7 @@ class ModelProviderService:
current_credential_id=getattr(provider_config, "current_credential_id", None),
current_credential_name=getattr(provider_config, "current_credential_name", None),
available_credentials=getattr(provider_config, "available_credentials", []),
custom_models=model_config,
custom_models=sanitized_model_config,
can_added_models=can_added_models,
),
system_configuration=SystemConfigurationResponse(

View File

@ -9,6 +9,7 @@ from core.rag.index_processor.index_processor_factory import IndexProcessorFacto
from core.tools.utils.web_reader_tool import get_image_upload_file_ids
from extensions.ext_database import db
from extensions.ext_storage import storage
from models import WorkflowType
from models.dataset import (
AppDatasetJoin,
Dataset,
@ -18,9 +19,11 @@ from models.dataset import (
DatasetQuery,
Document,
DocumentSegment,
Pipeline,
SegmentAttachmentBinding,
)
from models.model import UploadFile
from models.workflow import Workflow
logger = logging.getLogger(__name__)
@ -34,6 +37,7 @@ def clean_dataset_task(
index_struct: str,
collection_binding_id: str,
doc_form: str,
pipeline_id: str | None = None,
):
"""
Clean dataset when dataset deleted.
@ -135,6 +139,14 @@ def clean_dataset_task(
# delete dataset metadata
db.session.query(DatasetMetadata).where(DatasetMetadata.dataset_id == dataset_id).delete()
db.session.query(DatasetMetadataBinding).where(DatasetMetadataBinding.dataset_id == dataset_id).delete()
# delete pipeline and workflow
if pipeline_id:
db.session.query(Pipeline).where(Pipeline.id == pipeline_id).delete()
db.session.query(Workflow).where(
Workflow.tenant_id == tenant_id,
Workflow.app_id == pipeline_id,
Workflow.type == WorkflowType.RAG_PIPELINE,
).delete()
# delete files
if documents:
for document in documents:

View File

@ -2,6 +2,7 @@ import logging
from celery import shared_task
from configs import dify_config
from extensions.ext_database import db
from models import Account
from services.billing_service import BillingService
@ -14,7 +15,8 @@ logger = logging.getLogger(__name__)
def delete_account_task(account_id):
account = db.session.query(Account).where(Account.id == account_id).first()
try:
BillingService.delete_account(account_id)
if dify_config.BILLING_ENABLED:
BillingService.delete_account(account_id)
except Exception:
logger.exception("Failed to delete account %s from billing service.", account_id)
raise

View File

@ -0,0 +1,127 @@
app:
description: 'End node without value_type field reproduction'
icon: 🤖
icon_background: '#FFEAD5'
mode: workflow
name: end_node_without_value_type_field_reproduction
use_icon_as_answer_icon: false
dependencies: []
kind: app
version: 0.5.0
workflow:
conversation_variables: []
environment_variables: []
features:
file_upload:
allowed_file_extensions:
- .JPG
- .JPEG
- .PNG
- .GIF
- .WEBP
- .SVG
allowed_file_types:
- image
allowed_file_upload_methods:
- local_file
- remote_url
enabled: false
fileUploadConfig:
audio_file_size_limit: 50
batch_count_limit: 5
file_size_limit: 15
image_file_batch_limit: 10
image_file_size_limit: 10
single_chunk_attachment_limit: 10
video_file_size_limit: 100
workflow_file_upload_limit: 10
image:
enabled: false
number_limits: 3
transfer_methods:
- local_file
- remote_url
number_limits: 3
opening_statement: ''
retriever_resource:
enabled: true
sensitive_word_avoidance:
enabled: false
speech_to_text:
enabled: false
suggested_questions: []
suggested_questions_after_answer:
enabled: false
text_to_speech:
enabled: false
language: ''
voice: ''
graph:
edges:
- data:
isInIteration: false
isInLoop: false
sourceType: start
targetType: end
id: 1765423445456-source-1765423454810-target
source: '1765423445456'
sourceHandle: source
target: '1765423454810'
targetHandle: target
type: custom
zIndex: 0
nodes:
- data:
selected: false
title: 用户输入
type: start
variables:
- default: ''
hint: ''
label: query
max_length: 48
options: []
placeholder: ''
required: true
type: text-input
variable: query
height: 109
id: '1765423445456'
position:
x: -48
y: 261
positionAbsolute:
x: -48
y: 261
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 242
- data:
outputs:
- value_selector:
- '1765423445456'
- query
variable: query
selected: true
title: 输出
type: end
height: 88
id: '1765423454810'
position:
x: 382
y: 282
positionAbsolute:
x: 382
y: 282
selected: true
sourcePosition: right
targetPosition: left
type: custom
width: 242
viewport:
x: 139
y: -135
zoom: 1
rag_pipeline_variables: []

View File

@ -55,7 +55,7 @@ WEB_API_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,*
CONSOLE_CORS_ALLOW_ORIGINS=http://127.0.0.1:3000,*
# Vector database configuration
# support: weaviate, qdrant, milvus, myscale, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector, couchbase, vikingdb, upstash, lindorm, oceanbase
# support: weaviate, qdrant, milvus, myscale, relyt, pgvecto_rs, pgvector, pgvector, chroma, opensearch, tidb_vector, couchbase, vikingdb, upstash, lindorm, oceanbase, iris
VECTOR_STORE=weaviate
# Weaviate configuration
WEAVIATE_ENDPOINT=http://localhost:8080
@ -64,6 +64,20 @@ WEAVIATE_GRPC_ENABLED=false
WEAVIATE_BATCH_SIZE=100
WEAVIATE_TOKENIZATION=word
# InterSystems IRIS configuration
IRIS_HOST=localhost
IRIS_SUPER_SERVER_PORT=1972
IRIS_WEB_SERVER_PORT=52773
IRIS_USER=_SYSTEM
IRIS_PASSWORD=Dify@1234
IRIS_DATABASE=USER
IRIS_SCHEMA=dify
IRIS_CONNECTION_URL=
IRIS_MIN_CONNECTION=1
IRIS_MAX_CONNECTION=3
IRIS_TEXT_INDEX=true
IRIS_TEXT_INDEX_LANGUAGE=en
# Upload configuration
UPLOAD_FILE_SIZE_LIMIT=15

View File

@ -1,3 +1,4 @@
import os
import pathlib
import random
import secrets
@ -32,6 +33,10 @@ def _load_env():
_load_env()
# Override storage root to tmp to avoid polluting repo during local runs
os.environ["OPENDAL_FS_ROOT"] = "/tmp/dify-storage"
os.environ.setdefault("STORAGE_TYPE", "opendal")
os.environ.setdefault("OPENDAL_SCHEME", "fs")
_CACHED_APP = create_app()

View File

@ -0,0 +1,44 @@
"""Integration tests for IRIS vector database."""
from core.rag.datasource.vdb.iris.iris_vector import IrisVector, IrisVectorConfig
from tests.integration_tests.vdb.test_vector_store import (
AbstractVectorTest,
setup_mock_redis,
)
class IrisVectorTest(AbstractVectorTest):
"""Test suite for IRIS vector store implementation."""
def __init__(self):
"""Initialize IRIS vector test with hardcoded test configuration.
Note: Uses 'host.docker.internal' to connect from DevContainer to
host OS Docker, or 'localhost' when running directly on host OS.
"""
super().__init__()
self.vector = IrisVector(
collection_name=self.collection_name,
config=IrisVectorConfig(
IRIS_HOST="host.docker.internal",
IRIS_SUPER_SERVER_PORT=1972,
IRIS_USER="_SYSTEM",
IRIS_PASSWORD="Dify@1234",
IRIS_DATABASE="USER",
IRIS_SCHEMA="dify",
IRIS_CONNECTION_URL=None,
IRIS_MIN_CONNECTION=1,
IRIS_MAX_CONNECTION=3,
IRIS_TEXT_INDEX=True,
IRIS_TEXT_INDEX_LANGUAGE="en",
),
)
def test_iris_vector(setup_mock_redis) -> None:
"""Run all IRIS vector store tests.
Args:
setup_mock_redis: Pytest fixture for mock Redis setup
"""
IrisVectorTest().run_all_tests()

View File

@ -138,9 +138,9 @@ class DifyTestContainers:
logger.warning("Failed to create plugin database: %s", e)
# Set up storage environment variables
os.environ["STORAGE_TYPE"] = "opendal"
os.environ["OPENDAL_SCHEME"] = "fs"
os.environ["OPENDAL_FS_ROOT"] = "storage"
os.environ.setdefault("STORAGE_TYPE", "opendal")
os.environ.setdefault("OPENDAL_SCHEME", "fs")
os.environ.setdefault("OPENDAL_FS_ROOT", "/tmp/dify-storage")
# Start Redis container for caching and session management
# Redis is used for storing session data, cache entries, and temporary data
@ -348,6 +348,13 @@ def _create_app_with_containers() -> Flask:
"""
logger.info("Creating Flask application with test container configuration...")
# Ensure Redis client reconnects to the containerized Redis (no auth)
from extensions import ext_redis
ext_redis.redis_client._client = None
os.environ["REDIS_USERNAME"] = ""
os.environ["REDIS_PASSWORD"] = ""
# Re-create the config after environment variables have been set
from configs import dify_config
@ -486,3 +493,29 @@ def db_session_with_containers(flask_app_with_containers) -> Generator[Session,
finally:
session.close()
logger.debug("Database session closed")
@pytest.fixture(scope="package", autouse=True)
def mock_ssrf_proxy_requests():
"""
Avoid outbound network during containerized tests by stubbing SSRF proxy helpers.
"""
from unittest.mock import patch
import httpx
def _fake_request(method, url, **kwargs):
request = httpx.Request(method=method, url=url)
return httpx.Response(200, request=request, content=b"")
with (
patch("core.helper.ssrf_proxy.make_request", side_effect=_fake_request),
patch("core.helper.ssrf_proxy.get", side_effect=lambda url, **kw: _fake_request("GET", url, **kw)),
patch("core.helper.ssrf_proxy.post", side_effect=lambda url, **kw: _fake_request("POST", url, **kw)),
patch("core.helper.ssrf_proxy.put", side_effect=lambda url, **kw: _fake_request("PUT", url, **kw)),
patch("core.helper.ssrf_proxy.patch", side_effect=lambda url, **kw: _fake_request("PATCH", url, **kw)),
patch("core.helper.ssrf_proxy.delete", side_effect=lambda url, **kw: _fake_request("DELETE", url, **kw)),
patch("core.helper.ssrf_proxy.head", side_effect=lambda url, **kw: _fake_request("HEAD", url, **kw)),
):
yield

View File

@ -240,8 +240,7 @@ class TestShardedRedisBroadcastChannelIntegration:
for future in as_completed(producer_futures, timeout=30.0):
sent_msgs.update(future.result())
subscription.close()
consumer_received_msgs = consumer_future.result(timeout=30.0)
consumer_received_msgs = consumer_future.result(timeout=60.0)
assert sent_msgs == consumer_received_msgs

View File

@ -0,0 +1,182 @@
"""
Fixtures for trigger integration tests.
This module provides fixtures for creating test data (tenant, account, app)
and mock objects used across trigger-related tests.
"""
from __future__ import annotations
from collections.abc import Generator
from typing import Any
import pytest
from sqlalchemy.orm import Session
from models.account import Account, Tenant, TenantAccountJoin, TenantAccountRole
from models.model import App
@pytest.fixture
def tenant_and_account(db_session_with_containers: Session) -> Generator[tuple[Tenant, Account], None, None]:
"""
Create a tenant and account for testing.
This fixture creates a tenant, account, and their association,
then cleans up after the test completes.
Yields:
tuple[Tenant, Account]: The created tenant and account
"""
tenant = Tenant(name="trigger-e2e")
account = Account(name="tester", email="tester@example.com", interface_language="en-US")
db_session_with_containers.add_all([tenant, account])
db_session_with_containers.commit()
join = TenantAccountJoin(tenant_id=tenant.id, account_id=account.id, role=TenantAccountRole.OWNER.value)
db_session_with_containers.add(join)
db_session_with_containers.commit()
yield tenant, account
# Cleanup
db_session_with_containers.query(TenantAccountJoin).filter_by(tenant_id=tenant.id).delete()
db_session_with_containers.query(Account).filter_by(id=account.id).delete()
db_session_with_containers.query(Tenant).filter_by(id=tenant.id).delete()
db_session_with_containers.commit()
@pytest.fixture
def app_model(
db_session_with_containers: Session, tenant_and_account: tuple[Tenant, Account]
) -> Generator[App, None, None]:
"""
Create an app for testing.
This fixture creates a workflow app associated with the tenant and account,
then cleans up after the test completes.
Yields:
App: The created app
"""
tenant, account = tenant_and_account
app = App(
tenant_id=tenant.id,
name="trigger-app",
description="trigger e2e",
mode="workflow",
icon_type="emoji",
icon="robot",
icon_background="#FFEAD5",
enable_site=True,
enable_api=True,
api_rpm=100,
api_rph=1000,
is_demo=False,
is_public=False,
is_universal=False,
created_by=account.id,
)
db_session_with_containers.add(app)
db_session_with_containers.commit()
yield app
# Cleanup - delete related records first
from models.trigger import (
AppTrigger,
TriggerSubscription,
WorkflowPluginTrigger,
WorkflowSchedulePlan,
WorkflowTriggerLog,
WorkflowWebhookTrigger,
)
from models.workflow import Workflow
db_session_with_containers.query(WorkflowTriggerLog).filter_by(app_id=app.id).delete()
db_session_with_containers.query(WorkflowSchedulePlan).filter_by(app_id=app.id).delete()
db_session_with_containers.query(WorkflowWebhookTrigger).filter_by(app_id=app.id).delete()
db_session_with_containers.query(WorkflowPluginTrigger).filter_by(app_id=app.id).delete()
db_session_with_containers.query(AppTrigger).filter_by(app_id=app.id).delete()
db_session_with_containers.query(TriggerSubscription).filter_by(tenant_id=tenant.id).delete()
db_session_with_containers.query(Workflow).filter_by(app_id=app.id).delete()
db_session_with_containers.query(App).filter_by(id=app.id).delete()
db_session_with_containers.commit()
class MockCeleryGroup:
"""Mock for celery group() function that collects dispatched tasks."""
def __init__(self) -> None:
self.collected: list[dict[str, Any]] = []
self._applied = False
def __call__(self, items: Any) -> MockCeleryGroup:
self.collected = list(items)
return self
def apply_async(self) -> None:
self._applied = True
@property
def applied(self) -> bool:
return self._applied
class MockCelerySignature:
"""Mock for celery task signature that returns task info dict."""
def s(self, schedule_id: str) -> dict[str, str]:
return {"schedule_id": schedule_id}
@pytest.fixture
def mock_celery_group() -> MockCeleryGroup:
"""
Provide a mock celery group for testing task dispatch.
Returns:
MockCeleryGroup: Mock group that collects dispatched tasks
"""
return MockCeleryGroup()
@pytest.fixture
def mock_celery_signature() -> MockCelerySignature:
"""
Provide a mock celery signature for testing task dispatch.
Returns:
MockCelerySignature: Mock signature generator
"""
return MockCelerySignature()
class MockPluginSubscription:
"""Mock plugin subscription for testing plugin triggers."""
def __init__(
self,
subscription_id: str = "sub-1",
tenant_id: str = "tenant-1",
provider_id: str = "provider-1",
) -> None:
self.id = subscription_id
self.tenant_id = tenant_id
self.provider_id = provider_id
self.credentials: dict[str, str] = {"token": "secret"}
self.credential_type = "api-key"
def to_entity(self) -> MockPluginSubscription:
return self
@pytest.fixture
def mock_plugin_subscription() -> MockPluginSubscription:
"""
Provide a mock plugin subscription for testing.
Returns:
MockPluginSubscription: Mock subscription instance
"""
return MockPluginSubscription()

View File

@ -0,0 +1,911 @@
from __future__ import annotations
import importlib
import json
import time
from datetime import timedelta
from types import SimpleNamespace
from typing import Any
import pytest
from flask import Flask, Response
from flask.testing import FlaskClient
from sqlalchemy.orm import Session
from configs import dify_config
from core.plugin.entities.request import TriggerInvokeEventResponse
from core.trigger.debug import event_selectors
from core.trigger.debug.event_bus import TriggerDebugEventBus
from core.trigger.debug.event_selectors import PluginTriggerDebugEventPoller, WebhookTriggerDebugEventPoller
from core.trigger.debug.events import PluginTriggerDebugEvent, build_plugin_pool_key
from core.workflow.enums import NodeType
from libs.datetime_utils import naive_utc_now
from models.account import Account, Tenant
from models.enums import AppTriggerStatus, AppTriggerType, CreatorUserRole, WorkflowTriggerStatus
from models.model import App
from models.trigger import (
AppTrigger,
TriggerSubscription,
WorkflowPluginTrigger,
WorkflowSchedulePlan,
WorkflowTriggerLog,
WorkflowWebhookTrigger,
)
from models.workflow import Workflow
from schedule import workflow_schedule_task
from schedule.workflow_schedule_task import poll_workflow_schedules
from services import feature_service as feature_service_module
from services.trigger import webhook_service
from services.trigger.schedule_service import ScheduleService
from services.workflow_service import WorkflowService
from tasks import trigger_processing_tasks
from .conftest import MockCeleryGroup, MockCelerySignature, MockPluginSubscription
# Test constants
WEBHOOK_ID_PRODUCTION = "wh1234567890123456789012"
WEBHOOK_ID_DEBUG = "whdebug1234567890123456"
TEST_TRIGGER_URL = "https://trigger.example.com/base"
def _build_workflow_graph(root_node_id: str, trigger_type: NodeType) -> str:
"""Build a minimal workflow graph JSON for testing."""
node_data: dict[str, Any] = {"type": trigger_type.value, "title": "trigger"}
if trigger_type == NodeType.TRIGGER_WEBHOOK:
node_data.update(
{
"method": "POST",
"content_type": "application/json",
"headers": [],
"params": [],
"body": [],
}
)
graph = {
"nodes": [
{"id": root_node_id, "data": node_data},
{"id": "answer-1", "data": {"type": NodeType.ANSWER.value, "title": "answer"}},
],
"edges": [{"source": root_node_id, "target": "answer-1", "sourceHandle": "success"}],
}
return json.dumps(graph)
def test_publish_blocks_start_and_trigger_coexistence(
db_session_with_containers: Session,
tenant_and_account: tuple[Tenant, Account],
app_model: App,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Publishing should fail when both start and trigger nodes coexist."""
tenant, account = tenant_and_account
graph = {
"nodes": [
{"id": "start", "data": {"type": NodeType.START.value}},
{"id": "trig", "data": {"type": NodeType.TRIGGER_WEBHOOK.value}},
],
"edges": [],
}
draft_workflow = Workflow.new(
tenant_id=tenant.id,
app_id=app_model.id,
type="workflow",
version=Workflow.VERSION_DRAFT,
graph=json.dumps(graph),
features=json.dumps({}),
created_by=account.id,
environment_variables=[],
conversation_variables=[],
rag_pipeline_variables=[],
)
db_session_with_containers.add(draft_workflow)
db_session_with_containers.commit()
workflow_service = WorkflowService()
monkeypatch.setattr(
feature_service_module.FeatureService,
"get_system_features",
classmethod(lambda _cls: SimpleNamespace(plugin_manager=SimpleNamespace(enabled=False))),
)
monkeypatch.setattr("services.workflow_service.dify_config", SimpleNamespace(BILLING_ENABLED=False))
with pytest.raises(ValueError, match="Start node and trigger nodes cannot coexist"):
workflow_service.publish_workflow(session=db_session_with_containers, app_model=app_model, account=account)
def test_trigger_url_uses_config_base(monkeypatch: pytest.MonkeyPatch) -> None:
"""TRIGGER_URL config should be reflected in generated webhook and plugin endpoints."""
original_url = getattr(dify_config, "TRIGGER_URL", None)
try:
monkeypatch.setattr(dify_config, "TRIGGER_URL", TEST_TRIGGER_URL)
endpoint_module = importlib.reload(importlib.import_module("core.trigger.utils.endpoint"))
assert (
endpoint_module.generate_webhook_trigger_endpoint(WEBHOOK_ID_PRODUCTION)
== f"{TEST_TRIGGER_URL}/triggers/webhook/{WEBHOOK_ID_PRODUCTION}"
)
assert (
endpoint_module.generate_webhook_trigger_endpoint(WEBHOOK_ID_PRODUCTION, True)
== f"{TEST_TRIGGER_URL}/triggers/webhook-debug/{WEBHOOK_ID_PRODUCTION}"
)
assert (
endpoint_module.generate_plugin_trigger_endpoint_url("end-1") == f"{TEST_TRIGGER_URL}/triggers/plugin/end-1"
)
finally:
# Restore original config and reload module
if original_url is not None:
monkeypatch.setattr(dify_config, "TRIGGER_URL", original_url)
importlib.reload(importlib.import_module("core.trigger.utils.endpoint"))
def test_webhook_trigger_creates_trigger_log(
test_client_with_containers: FlaskClient,
db_session_with_containers: Session,
tenant_and_account: tuple[Tenant, Account],
app_model: App,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Production webhook trigger should create a trigger log in the database."""
tenant, account = tenant_and_account
webhook_node_id = "webhook-node"
graph_json = _build_workflow_graph(webhook_node_id, NodeType.TRIGGER_WEBHOOK)
published_workflow = Workflow.new(
tenant_id=tenant.id,
app_id=app_model.id,
type="workflow",
version=Workflow.version_from_datetime(naive_utc_now()),
graph=graph_json,
features=json.dumps({}),
created_by=account.id,
environment_variables=[],
conversation_variables=[],
rag_pipeline_variables=[],
)
db_session_with_containers.add(published_workflow)
app_model.workflow_id = published_workflow.id
db_session_with_containers.commit()
webhook_trigger = WorkflowWebhookTrigger(
app_id=app_model.id,
node_id=webhook_node_id,
tenant_id=tenant.id,
webhook_id=WEBHOOK_ID_PRODUCTION,
created_by=account.id,
)
app_trigger = AppTrigger(
tenant_id=tenant.id,
app_id=app_model.id,
node_id=webhook_node_id,
trigger_type=AppTriggerType.TRIGGER_WEBHOOK,
status=AppTriggerStatus.ENABLED,
title="webhook",
)
db_session_with_containers.add_all([webhook_trigger, app_trigger])
db_session_with_containers.commit()
def _fake_trigger_workflow_async(session: Session, user: Any, trigger_data: Any) -> SimpleNamespace:
log = WorkflowTriggerLog(
tenant_id=trigger_data.tenant_id,
app_id=trigger_data.app_id,
workflow_id=trigger_data.workflow_id,
root_node_id=trigger_data.root_node_id,
trigger_metadata=trigger_data.trigger_metadata.model_dump_json() if trigger_data.trigger_metadata else "{}",
trigger_type=trigger_data.trigger_type,
workflow_run_id=None,
outputs=None,
trigger_data=trigger_data.model_dump_json(),
inputs=json.dumps(dict(trigger_data.inputs)),
status=WorkflowTriggerStatus.SUCCEEDED,
error="",
queue_name="triggered_workflow_dispatcher",
celery_task_id="celery-test",
created_by_role=CreatorUserRole.ACCOUNT,
created_by=account.id,
)
session.add(log)
session.commit()
return SimpleNamespace(workflow_trigger_log_id=log.id, task_id=None, status="queued", queue="test")
monkeypatch.setattr(
webhook_service.AsyncWorkflowService,
"trigger_workflow_async",
_fake_trigger_workflow_async,
)
response = test_client_with_containers.post(f"/triggers/webhook/{webhook_trigger.webhook_id}", json={"foo": "bar"})
assert response.status_code == 200
db_session_with_containers.expire_all()
logs = db_session_with_containers.query(WorkflowTriggerLog).filter_by(app_id=app_model.id).all()
assert logs, "Webhook trigger should create trigger log"
@pytest.mark.parametrize("schedule_type", ["visual", "cron"])
def test_schedule_poll_dispatches_due_plan(
db_session_with_containers: Session,
tenant_and_account: tuple[Tenant, Account],
app_model: App,
mock_celery_group: MockCeleryGroup,
mock_celery_signature: MockCelerySignature,
monkeypatch: pytest.MonkeyPatch,
schedule_type: str,
) -> None:
"""Schedule plans (both visual and cron) should be polled and dispatched when due."""
tenant, _ = tenant_and_account
app_trigger = AppTrigger(
tenant_id=tenant.id,
app_id=app_model.id,
node_id=f"schedule-{schedule_type}",
trigger_type=AppTriggerType.TRIGGER_SCHEDULE,
status=AppTriggerStatus.ENABLED,
title=f"schedule-{schedule_type}",
)
plan = WorkflowSchedulePlan(
app_id=app_model.id,
node_id=f"schedule-{schedule_type}",
tenant_id=tenant.id,
cron_expression="* * * * *",
timezone="UTC",
next_run_at=naive_utc_now() - timedelta(minutes=1),
)
db_session_with_containers.add_all([app_trigger, plan])
db_session_with_containers.commit()
next_time = naive_utc_now() + timedelta(hours=1)
monkeypatch.setattr(workflow_schedule_task, "calculate_next_run_at", lambda *_args, **_kwargs: next_time)
monkeypatch.setattr(workflow_schedule_task, "group", mock_celery_group)
monkeypatch.setattr(workflow_schedule_task, "run_schedule_trigger", mock_celery_signature)
poll_workflow_schedules()
assert mock_celery_group.collected, f"Should dispatch signatures for due {schedule_type} schedules"
scheduled_ids = {sig["schedule_id"] for sig in mock_celery_group.collected}
assert plan.id in scheduled_ids
def test_schedule_visual_debug_poll_generates_event(monkeypatch: pytest.MonkeyPatch) -> None:
"""Visual mode schedule node should generate event in single-step debug."""
base_now = naive_utc_now()
monkeypatch.setattr(event_selectors, "naive_utc_now", lambda: base_now)
monkeypatch.setattr(
event_selectors,
"calculate_next_run_at",
lambda *_args, **_kwargs: base_now - timedelta(minutes=1),
)
node_config = {
"id": "schedule-visual",
"data": {
"type": NodeType.TRIGGER_SCHEDULE.value,
"mode": "visual",
"frequency": "daily",
"visual_config": {"time": "3:00 PM"},
"timezone": "UTC",
},
}
poller = event_selectors.ScheduleTriggerDebugEventPoller(
tenant_id="tenant",
user_id="user",
app_id="app",
node_config=node_config,
node_id="schedule-visual",
)
event = poller.poll()
assert event is not None
assert event.workflow_args["inputs"] == {}
def test_plugin_trigger_dispatches_and_debug_events(
test_client_with_containers: FlaskClient,
mock_plugin_subscription: MockPluginSubscription,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Plugin trigger endpoint should dispatch events and generate debug events."""
endpoint_id = "1cc7fa12-3f7b-4f6a-9c8d-1234567890ab"
debug_events: list[dict[str, Any]] = []
dispatched_payloads: list[dict[str, Any]] = []
def _fake_process_endpoint(_endpoint_id: str, _request: Any) -> Response:
dispatch_data = {
"user_id": "end-user",
"tenant_id": mock_plugin_subscription.tenant_id,
"endpoint_id": _endpoint_id,
"provider_id": mock_plugin_subscription.provider_id,
"subscription_id": mock_plugin_subscription.id,
"timestamp": int(time.time()),
"events": ["created", "updated"],
"request_id": f"req-{_endpoint_id}",
}
trigger_processing_tasks.dispatch_triggered_workflows_async.delay(dispatch_data)
return Response("ok", status=202)
monkeypatch.setattr(
"services.trigger.trigger_service.TriggerService.process_endpoint",
staticmethod(_fake_process_endpoint),
)
monkeypatch.setattr(
trigger_processing_tasks.TriggerDebugEventBus,
"dispatch",
staticmethod(lambda **kwargs: debug_events.append(kwargs) or 1),
)
def _fake_delay(dispatch_data: dict[str, Any]) -> None:
dispatched_payloads.append(dispatch_data)
trigger_processing_tasks.dispatch_trigger_debug_event(
events=dispatch_data["events"],
user_id=dispatch_data["user_id"],
timestamp=dispatch_data["timestamp"],
request_id=dispatch_data["request_id"],
subscription=mock_plugin_subscription,
)
monkeypatch.setattr(
trigger_processing_tasks.dispatch_triggered_workflows_async,
"delay",
staticmethod(_fake_delay),
)
response = test_client_with_containers.post(f"/triggers/plugin/{endpoint_id}", json={"hello": "world"})
assert response.status_code == 202
assert dispatched_payloads, "Plugin trigger should enqueue workflow dispatch payload"
assert debug_events, "Plugin trigger should dispatch debug events"
dispatched_event_names = {event["event"].name for event in debug_events}
assert dispatched_event_names == {"created", "updated"}
def test_webhook_debug_dispatches_event(
test_client_with_containers: FlaskClient,
db_session_with_containers: Session,
tenant_and_account: tuple[Tenant, Account],
app_model: App,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Webhook single-step debug should dispatch debug event and be pollable."""
tenant, account = tenant_and_account
webhook_node_id = "webhook-debug-node"
graph_json = _build_workflow_graph(webhook_node_id, NodeType.TRIGGER_WEBHOOK)
draft_workflow = Workflow.new(
tenant_id=tenant.id,
app_id=app_model.id,
type="workflow",
version=Workflow.VERSION_DRAFT,
graph=graph_json,
features=json.dumps({}),
created_by=account.id,
environment_variables=[],
conversation_variables=[],
rag_pipeline_variables=[],
)
db_session_with_containers.add(draft_workflow)
db_session_with_containers.commit()
webhook_trigger = WorkflowWebhookTrigger(
app_id=app_model.id,
node_id=webhook_node_id,
tenant_id=tenant.id,
webhook_id=WEBHOOK_ID_DEBUG,
created_by=account.id,
)
db_session_with_containers.add(webhook_trigger)
db_session_with_containers.commit()
debug_events: list[dict[str, Any]] = []
original_dispatch = TriggerDebugEventBus.dispatch
monkeypatch.setattr(
"controllers.trigger.webhook.TriggerDebugEventBus.dispatch",
lambda **kwargs: (debug_events.append(kwargs), original_dispatch(**kwargs))[1],
)
# Listener polls first to enter waiting pool
poller = WebhookTriggerDebugEventPoller(
tenant_id=tenant.id,
user_id=account.id,
app_id=app_model.id,
node_config=draft_workflow.get_node_config_by_id(webhook_node_id),
node_id=webhook_node_id,
)
assert poller.poll() is None
response = test_client_with_containers.post(
f"/triggers/webhook-debug/{webhook_trigger.webhook_id}",
json={"foo": "bar"},
headers={"Content-Type": "application/json"},
)
assert response.status_code == 200
assert debug_events, "Debug event should be sent to event bus"
# Second poll should get the event
event = poller.poll()
assert event is not None
assert event.workflow_args["inputs"]["webhook_body"]["foo"] == "bar"
assert debug_events[0]["pool_key"].endswith(f":{app_model.id}:{webhook_node_id}")
def test_plugin_single_step_debug_flow(
flask_app_with_containers: Flask,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Plugin single-step debug: listen -> dispatch event -> poller receives and returns variables."""
tenant_id = "tenant-1"
app_id = "app-1"
user_id = "user-1"
node_id = "plugin-node"
provider_id = "langgenius/provider-1/provider-1"
node_config = {
"id": node_id,
"data": {
"type": NodeType.TRIGGER_PLUGIN.value,
"title": "plugin",
"plugin_id": "plugin-1",
"plugin_unique_identifier": "plugin-1",
"provider_id": provider_id,
"event_name": "created",
"subscription_id": "sub-1",
"parameters": {},
},
}
# Start listening
poller = PluginTriggerDebugEventPoller(
tenant_id=tenant_id,
user_id=user_id,
app_id=app_id,
node_config=node_config,
node_id=node_id,
)
assert poller.poll() is None
from core.trigger.debug.events import build_plugin_pool_key
pool_key = build_plugin_pool_key(
tenant_id=tenant_id,
provider_id=provider_id,
subscription_id="sub-1",
name="created",
)
TriggerDebugEventBus.dispatch(
tenant_id=tenant_id,
event=PluginTriggerDebugEvent(
timestamp=int(time.time()),
user_id=user_id,
name="created",
request_id="req-1",
subscription_id="sub-1",
provider_id="provider-1",
),
pool_key=pool_key,
)
from core.plugin.entities.request import TriggerInvokeEventResponse
monkeypatch.setattr(
"services.trigger.trigger_service.TriggerService.invoke_trigger_event",
staticmethod(
lambda **_kwargs: TriggerInvokeEventResponse(
variables={"echo": "pong"},
cancelled=False,
)
),
)
event = poller.poll()
assert event is not None
assert event.workflow_args["inputs"]["echo"] == "pong"
def test_schedule_trigger_creates_trigger_log(
db_session_with_containers: Session,
tenant_and_account: tuple[Tenant, Account],
app_model: App,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Schedule trigger execution should create WorkflowTriggerLog in database."""
from tasks import workflow_schedule_tasks
tenant, account = tenant_and_account
# Create published workflow with schedule trigger node
schedule_node_id = "schedule-node"
graph = {
"nodes": [
{
"id": schedule_node_id,
"data": {
"type": NodeType.TRIGGER_SCHEDULE.value,
"title": "schedule",
"mode": "cron",
"cron_expression": "0 9 * * *",
"timezone": "UTC",
},
},
{"id": "answer-1", "data": {"type": NodeType.ANSWER.value, "title": "answer"}},
],
"edges": [{"source": schedule_node_id, "target": "answer-1", "sourceHandle": "success"}],
}
published_workflow = Workflow.new(
tenant_id=tenant.id,
app_id=app_model.id,
type="workflow",
version=Workflow.version_from_datetime(naive_utc_now()),
graph=json.dumps(graph),
features=json.dumps({}),
created_by=account.id,
environment_variables=[],
conversation_variables=[],
rag_pipeline_variables=[],
)
db_session_with_containers.add(published_workflow)
app_model.workflow_id = published_workflow.id
db_session_with_containers.commit()
# Create schedule plan
plan = WorkflowSchedulePlan(
app_id=app_model.id,
node_id=schedule_node_id,
tenant_id=tenant.id,
cron_expression="0 9 * * *",
timezone="UTC",
next_run_at=naive_utc_now() - timedelta(minutes=1),
)
app_trigger = AppTrigger(
tenant_id=tenant.id,
app_id=app_model.id,
node_id=schedule_node_id,
trigger_type=AppTriggerType.TRIGGER_SCHEDULE,
status=AppTriggerStatus.ENABLED,
title="schedule",
)
db_session_with_containers.add_all([plan, app_trigger])
db_session_with_containers.commit()
# Mock AsyncWorkflowService to create WorkflowTriggerLog
def _fake_trigger_workflow_async(session: Session, user: Any, trigger_data: Any) -> SimpleNamespace:
log = WorkflowTriggerLog(
tenant_id=trigger_data.tenant_id,
app_id=trigger_data.app_id,
workflow_id=published_workflow.id,
root_node_id=trigger_data.root_node_id,
trigger_metadata="{}",
trigger_type=AppTriggerType.TRIGGER_SCHEDULE,
workflow_run_id=None,
outputs=None,
trigger_data=trigger_data.model_dump_json(),
inputs=json.dumps(dict(trigger_data.inputs)),
status=WorkflowTriggerStatus.SUCCEEDED,
error="",
queue_name="schedule_executor",
celery_task_id="celery-schedule-test",
created_by_role=CreatorUserRole.ACCOUNT,
created_by=account.id,
)
session.add(log)
session.commit()
return SimpleNamespace(workflow_trigger_log_id=log.id, task_id=None, status="queued", queue="test")
monkeypatch.setattr(
workflow_schedule_tasks.AsyncWorkflowService,
"trigger_workflow_async",
_fake_trigger_workflow_async,
)
# Mock quota to avoid rate limiting
from enums import quota_type
monkeypatch.setattr(quota_type.QuotaType.TRIGGER, "consume", lambda _tenant_id: quota_type.unlimited())
# Execute schedule trigger
workflow_schedule_tasks.run_schedule_trigger(plan.id)
# Verify WorkflowTriggerLog was created
db_session_with_containers.expire_all()
logs = db_session_with_containers.query(WorkflowTriggerLog).filter_by(app_id=app_model.id).all()
assert logs, "Schedule trigger should create WorkflowTriggerLog"
assert logs[0].trigger_type == AppTriggerType.TRIGGER_SCHEDULE
assert logs[0].root_node_id == schedule_node_id
@pytest.mark.parametrize(
("mode", "frequency", "visual_config", "cron_expression", "expected_cron"),
[
# Visual mode: hourly
("visual", "hourly", {"on_minute": 30}, None, "30 * * * *"),
# Visual mode: daily
("visual", "daily", {"time": "3:00 PM"}, None, "0 15 * * *"),
# Visual mode: weekly
("visual", "weekly", {"time": "9:00 AM", "weekdays": ["mon", "wed", "fri"]}, None, "0 9 * * 1,3,5"),
# Visual mode: monthly
("visual", "monthly", {"time": "10:30 AM", "monthly_days": [1, 15]}, None, "30 10 1,15 * *"),
# Cron mode: direct expression
("cron", None, None, "*/5 * * * *", "*/5 * * * *"),
],
)
def test_schedule_visual_cron_conversion(
mode: str,
frequency: str | None,
visual_config: dict[str, Any] | None,
cron_expression: str | None,
expected_cron: str,
) -> None:
"""Schedule visual config should correctly convert to cron expression."""
node_config: dict[str, Any] = {
"id": "schedule-node",
"data": {
"type": NodeType.TRIGGER_SCHEDULE.value,
"mode": mode,
"timezone": "UTC",
},
}
if mode == "visual":
node_config["data"]["frequency"] = frequency
node_config["data"]["visual_config"] = visual_config
else:
node_config["data"]["cron_expression"] = cron_expression
config = ScheduleService.to_schedule_config(node_config)
assert config.cron_expression == expected_cron, f"Expected {expected_cron}, got {config.cron_expression}"
assert config.timezone == "UTC"
assert config.node_id == "schedule-node"
def test_plugin_trigger_full_chain_with_db_verification(
test_client_with_containers: FlaskClient,
db_session_with_containers: Session,
tenant_and_account: tuple[Tenant, Account],
app_model: App,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Plugin trigger should create WorkflowTriggerLog and WorkflowPluginTrigger records."""
tenant, account = tenant_and_account
# Create published workflow with plugin trigger node
plugin_node_id = "plugin-trigger-node"
provider_id = "langgenius/test-provider/test-provider"
subscription_id = "sub-plugin-test"
endpoint_id = "2cc7fa12-3f7b-4f6a-9c8d-1234567890ab"
graph = {
"nodes": [
{
"id": plugin_node_id,
"data": {
"type": NodeType.TRIGGER_PLUGIN.value,
"title": "plugin",
"plugin_id": "test-plugin",
"plugin_unique_identifier": "test-plugin",
"provider_id": provider_id,
"event_name": "test_event",
"subscription_id": subscription_id,
"parameters": {},
},
},
{"id": "answer-1", "data": {"type": NodeType.ANSWER.value, "title": "answer"}},
],
"edges": [{"source": plugin_node_id, "target": "answer-1", "sourceHandle": "success"}],
}
published_workflow = Workflow.new(
tenant_id=tenant.id,
app_id=app_model.id,
type="workflow",
version=Workflow.version_from_datetime(naive_utc_now()),
graph=json.dumps(graph),
features=json.dumps({}),
created_by=account.id,
environment_variables=[],
conversation_variables=[],
rag_pipeline_variables=[],
)
db_session_with_containers.add(published_workflow)
app_model.workflow_id = published_workflow.id
db_session_with_containers.commit()
# Create trigger subscription
subscription = TriggerSubscription(
name="test-subscription",
tenant_id=tenant.id,
user_id=account.id,
provider_id=provider_id,
endpoint_id=endpoint_id,
parameters={},
properties={},
credentials={"token": "test-secret"},
credential_type="api-key",
)
db_session_with_containers.add(subscription)
db_session_with_containers.commit()
# Update subscription_id to match the created subscription
graph["nodes"][0]["data"]["subscription_id"] = subscription.id
published_workflow.graph = json.dumps(graph)
db_session_with_containers.commit()
# Create WorkflowPluginTrigger
plugin_trigger = WorkflowPluginTrigger(
app_id=app_model.id,
tenant_id=tenant.id,
node_id=plugin_node_id,
provider_id=provider_id,
event_name="test_event",
subscription_id=subscription.id,
)
app_trigger = AppTrigger(
tenant_id=tenant.id,
app_id=app_model.id,
node_id=plugin_node_id,
trigger_type=AppTriggerType.TRIGGER_PLUGIN,
status=AppTriggerStatus.ENABLED,
title="plugin",
)
db_session_with_containers.add_all([plugin_trigger, app_trigger])
db_session_with_containers.commit()
# Track dispatched data
dispatched_data: list[dict[str, Any]] = []
def _fake_process_endpoint(_endpoint_id: str, _request: Any) -> Response:
dispatch_data = {
"user_id": "end-user",
"tenant_id": tenant.id,
"endpoint_id": _endpoint_id,
"provider_id": provider_id,
"subscription_id": subscription.id,
"timestamp": int(time.time()),
"events": ["test_event"],
"request_id": f"req-{_endpoint_id}",
}
dispatched_data.append(dispatch_data)
return Response("ok", status=202)
monkeypatch.setattr(
"services.trigger.trigger_service.TriggerService.process_endpoint",
staticmethod(_fake_process_endpoint),
)
response = test_client_with_containers.post(f"/triggers/plugin/{endpoint_id}", json={"test": "data"})
assert response.status_code == 202
assert dispatched_data, "Plugin trigger should dispatch event data"
assert dispatched_data[0]["subscription_id"] == subscription.id
assert dispatched_data[0]["events"] == ["test_event"]
# Verify database records exist
db_session_with_containers.expire_all()
plugin_triggers = (
db_session_with_containers.query(WorkflowPluginTrigger)
.filter_by(app_id=app_model.id, node_id=plugin_node_id)
.all()
)
assert plugin_triggers, "WorkflowPluginTrigger record should exist"
assert plugin_triggers[0].provider_id == provider_id
assert plugin_triggers[0].event_name == "test_event"
def test_plugin_debug_via_http_endpoint(
test_client_with_containers: FlaskClient,
db_session_with_containers: Session,
tenant_and_account: tuple[Tenant, Account],
app_model: App,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Plugin single-step debug via HTTP endpoint should dispatch debug event and be pollable."""
tenant, account = tenant_and_account
provider_id = "langgenius/debug-provider/debug-provider"
endpoint_id = "3cc7fa12-3f7b-4f6a-9c8d-1234567890ab"
event_name = "debug_event"
# Create subscription
subscription = TriggerSubscription(
name="debug-subscription",
tenant_id=tenant.id,
user_id=account.id,
provider_id=provider_id,
endpoint_id=endpoint_id,
parameters={},
properties={},
credentials={"token": "debug-secret"},
credential_type="api-key",
)
db_session_with_containers.add(subscription)
db_session_with_containers.commit()
# Create plugin trigger node config
node_id = "plugin-debug-node"
node_config = {
"id": node_id,
"data": {
"type": NodeType.TRIGGER_PLUGIN.value,
"title": "plugin-debug",
"plugin_id": "debug-plugin",
"plugin_unique_identifier": "debug-plugin",
"provider_id": provider_id,
"event_name": event_name,
"subscription_id": subscription.id,
"parameters": {},
},
}
# Start listening with poller
poller = PluginTriggerDebugEventPoller(
tenant_id=tenant.id,
user_id=account.id,
app_id=app_model.id,
node_config=node_config,
node_id=node_id,
)
assert poller.poll() is None, "First poll should return None (waiting)"
# Track debug events dispatched
debug_events: list[dict[str, Any]] = []
original_dispatch = TriggerDebugEventBus.dispatch
def _tracking_dispatch(**kwargs: Any) -> int:
debug_events.append(kwargs)
return original_dispatch(**kwargs)
monkeypatch.setattr(TriggerDebugEventBus, "dispatch", staticmethod(_tracking_dispatch))
# Mock process_endpoint to trigger debug event dispatch
def _fake_process_endpoint(_endpoint_id: str, _request: Any) -> Response:
# Simulate what happens inside process_endpoint + dispatch_triggered_workflows_async
pool_key = build_plugin_pool_key(
tenant_id=tenant.id,
provider_id=provider_id,
subscription_id=subscription.id,
name=event_name,
)
TriggerDebugEventBus.dispatch(
tenant_id=tenant.id,
event=PluginTriggerDebugEvent(
timestamp=int(time.time()),
user_id="end-user",
name=event_name,
request_id=f"req-{_endpoint_id}",
subscription_id=subscription.id,
provider_id=provider_id,
),
pool_key=pool_key,
)
return Response("ok", status=202)
monkeypatch.setattr(
"services.trigger.trigger_service.TriggerService.process_endpoint",
staticmethod(_fake_process_endpoint),
)
# Call HTTP endpoint
response = test_client_with_containers.post(f"/triggers/plugin/{endpoint_id}", json={"debug": "payload"})
assert response.status_code == 202
assert debug_events, "Debug event should be dispatched via HTTP endpoint"
assert debug_events[0]["event"].name == event_name
# Mock invoke_trigger_event for poller
monkeypatch.setattr(
"services.trigger.trigger_service.TriggerService.invoke_trigger_event",
staticmethod(
lambda **_kwargs: TriggerInvokeEventResponse(
variables={"http_debug": "success"},
cancelled=False,
)
),
)
# Second poll should receive the event
event = poller.poll()
assert event is not None, "Poller should receive debug event after HTTP trigger"
assert event.workflow_args["inputs"]["http_debug"] == "success"

View File

@ -26,16 +26,29 @@ redis_mock.hgetall = MagicMock(return_value={})
redis_mock.hdel = MagicMock()
redis_mock.incr = MagicMock(return_value=1)
# Ensure OpenDAL fs writes to tmp to avoid polluting workspace
os.environ.setdefault("OPENDAL_SCHEME", "fs")
os.environ.setdefault("OPENDAL_FS_ROOT", "/tmp/dify-storage")
os.environ.setdefault("STORAGE_TYPE", "opendal")
# Add the API directory to Python path to ensure proper imports
import sys
sys.path.insert(0, PROJECT_DIR)
# apply the mock to the Redis client in the Flask app
from extensions import ext_redis
redis_patcher = patch.object(ext_redis, "redis_client", redis_mock)
redis_patcher.start()
def _patch_redis_clients_on_loaded_modules():
"""Ensure any module-level redis_client references point to the shared redis_mock."""
import sys
for module in list(sys.modules.values()):
if module is None:
continue
if hasattr(module, "redis_client"):
module.redis_client = redis_mock
@pytest.fixture
@ -49,6 +62,15 @@ def _provide_app_context(app: Flask):
yield
@pytest.fixture(autouse=True)
def _patch_redis_clients():
"""Patch redis_client to MagicMock only for unit test executions."""
with patch.object(ext_redis, "redis_client", redis_mock):
_patch_redis_clients_on_loaded_modules()
yield
@pytest.fixture(autouse=True)
def reset_redis_mock():
"""reset the Redis mock before each test"""
@ -63,3 +85,20 @@ def reset_redis_mock():
redis_mock.hgetall.return_value = {}
redis_mock.hdel.return_value = None
redis_mock.incr.return_value = 1
# Keep any imported modules pointing at the mock between tests
_patch_redis_clients_on_loaded_modules()
@pytest.fixture(autouse=True)
def reset_secret_key():
"""Ensure SECRET_KEY-dependent logic sees an empty config value by default."""
from configs import dify_config
original = dify_config.SECRET_KEY
dify_config.SECRET_KEY = ""
try:
yield
finally:
dify_config.SECRET_KEY = original

View File

@ -0,0 +1,407 @@
"""Final working unit tests for admin endpoints - tests business logic directly."""
import uuid
from unittest.mock import Mock, patch
import pytest
from werkzeug.exceptions import NotFound, Unauthorized
from controllers.console.admin import InsertExploreAppPayload
from models.model import App, RecommendedApp
class TestInsertExploreAppPayload:
"""Test InsertExploreAppPayload validation."""
def test_valid_payload(self):
"""Test creating payload with valid data."""
payload_data = {
"app_id": str(uuid.uuid4()),
"desc": "Test app description",
"copyright": "© 2024 Test Company",
"privacy_policy": "https://example.com/privacy",
"custom_disclaimer": "Custom disclaimer text",
"language": "en-US",
"category": "Productivity",
"position": 1,
}
payload = InsertExploreAppPayload.model_validate(payload_data)
assert payload.app_id == payload_data["app_id"]
assert payload.desc == payload_data["desc"]
assert payload.copyright == payload_data["copyright"]
assert payload.privacy_policy == payload_data["privacy_policy"]
assert payload.custom_disclaimer == payload_data["custom_disclaimer"]
assert payload.language == payload_data["language"]
assert payload.category == payload_data["category"]
assert payload.position == payload_data["position"]
def test_minimal_payload(self):
"""Test creating payload with only required fields."""
payload_data = {
"app_id": str(uuid.uuid4()),
"language": "en-US",
"category": "Productivity",
"position": 1,
}
payload = InsertExploreAppPayload.model_validate(payload_data)
assert payload.app_id == payload_data["app_id"]
assert payload.desc is None
assert payload.copyright is None
assert payload.privacy_policy is None
assert payload.custom_disclaimer is None
assert payload.language == payload_data["language"]
assert payload.category == payload_data["category"]
assert payload.position == payload_data["position"]
def test_invalid_language(self):
"""Test payload with invalid language code."""
payload_data = {
"app_id": str(uuid.uuid4()),
"language": "invalid-lang",
"category": "Productivity",
"position": 1,
}
with pytest.raises(ValueError, match="invalid-lang is not a valid language"):
InsertExploreAppPayload.model_validate(payload_data)
class TestAdminRequiredDecorator:
"""Test admin_required decorator."""
def setup_method(self):
"""Set up test fixtures."""
# Mock dify_config
self.dify_config_patcher = patch("controllers.console.admin.dify_config")
self.mock_dify_config = self.dify_config_patcher.start()
self.mock_dify_config.ADMIN_API_KEY = "test-admin-key"
# Mock extract_access_token
self.token_patcher = patch("controllers.console.admin.extract_access_token")
self.mock_extract_token = self.token_patcher.start()
def teardown_method(self):
"""Clean up test fixtures."""
self.dify_config_patcher.stop()
self.token_patcher.stop()
def test_admin_required_success(self):
"""Test successful admin authentication."""
from controllers.console.admin import admin_required
@admin_required
def test_view():
return {"success": True}
self.mock_extract_token.return_value = "test-admin-key"
result = test_view()
assert result["success"] is True
def test_admin_required_invalid_token(self):
"""Test admin_required with invalid token."""
from controllers.console.admin import admin_required
@admin_required
def test_view():
return {"success": True}
self.mock_extract_token.return_value = "wrong-key"
with pytest.raises(Unauthorized, match="API key is invalid"):
test_view()
def test_admin_required_no_api_key_configured(self):
"""Test admin_required when no API key is configured."""
from controllers.console.admin import admin_required
self.mock_dify_config.ADMIN_API_KEY = None
@admin_required
def test_view():
return {"success": True}
with pytest.raises(Unauthorized, match="API key is invalid"):
test_view()
def test_admin_required_missing_authorization_header(self):
"""Test admin_required with missing authorization header."""
from controllers.console.admin import admin_required
@admin_required
def test_view():
return {"success": True}
self.mock_extract_token.return_value = None
with pytest.raises(Unauthorized, match="Authorization header is missing"):
test_view()
class TestExploreAppBusinessLogicDirect:
"""Test the core business logic of explore app management directly."""
def test_data_fusion_logic(self):
"""Test the data fusion logic between payload and site data."""
# Test cases for different data scenarios
test_cases = [
{
"name": "site_data_overrides_payload",
"payload": {"desc": "Payload desc", "copyright": "Payload copyright"},
"site": {"description": "Site desc", "copyright": "Site copyright"},
"expected": {
"desc": "Site desc",
"copyright": "Site copyright",
"privacy_policy": "",
"custom_disclaimer": "",
},
},
{
"name": "payload_used_when_no_site",
"payload": {"desc": "Payload desc", "copyright": "Payload copyright"},
"site": None,
"expected": {
"desc": "Payload desc",
"copyright": "Payload copyright",
"privacy_policy": "",
"custom_disclaimer": "",
},
},
{
"name": "empty_defaults_when_no_data",
"payload": {},
"site": None,
"expected": {"desc": "", "copyright": "", "privacy_policy": "", "custom_disclaimer": ""},
},
]
for case in test_cases:
# Simulate the data fusion logic
payload_desc = case["payload"].get("desc")
payload_copyright = case["payload"].get("copyright")
payload_privacy_policy = case["payload"].get("privacy_policy")
payload_custom_disclaimer = case["payload"].get("custom_disclaimer")
if case["site"]:
site_desc = case["site"].get("description")
site_copyright = case["site"].get("copyright")
site_privacy_policy = case["site"].get("privacy_policy")
site_custom_disclaimer = case["site"].get("custom_disclaimer")
# Site data takes precedence
desc = site_desc or payload_desc or ""
copyright = site_copyright or payload_copyright or ""
privacy_policy = site_privacy_policy or payload_privacy_policy or ""
custom_disclaimer = site_custom_disclaimer or payload_custom_disclaimer or ""
else:
# Use payload data or empty defaults
desc = payload_desc or ""
copyright = payload_copyright or ""
privacy_policy = payload_privacy_policy or ""
custom_disclaimer = payload_custom_disclaimer or ""
result = {
"desc": desc,
"copyright": copyright,
"privacy_policy": privacy_policy,
"custom_disclaimer": custom_disclaimer,
}
assert result == case["expected"], f"Failed test case: {case['name']}"
def test_app_visibility_logic(self):
"""Test that apps are made public when added to explore list."""
# Create a mock app
mock_app = Mock(spec=App)
mock_app.is_public = False
# Simulate the business logic
mock_app.is_public = True
assert mock_app.is_public is True
def test_recommended_app_creation_logic(self):
"""Test the creation of RecommendedApp objects."""
app_id = str(uuid.uuid4())
payload_data = {
"app_id": app_id,
"desc": "Test app description",
"copyright": "© 2024 Test Company",
"privacy_policy": "https://example.com/privacy",
"custom_disclaimer": "Custom disclaimer",
"language": "en-US",
"category": "Productivity",
"position": 1,
}
# Simulate the creation logic
recommended_app = Mock(spec=RecommendedApp)
recommended_app.app_id = payload_data["app_id"]
recommended_app.description = payload_data["desc"]
recommended_app.copyright = payload_data["copyright"]
recommended_app.privacy_policy = payload_data["privacy_policy"]
recommended_app.custom_disclaimer = payload_data["custom_disclaimer"]
recommended_app.language = payload_data["language"]
recommended_app.category = payload_data["category"]
recommended_app.position = payload_data["position"]
# Verify the data
assert recommended_app.app_id == app_id
assert recommended_app.description == "Test app description"
assert recommended_app.copyright == "© 2024 Test Company"
assert recommended_app.privacy_policy == "https://example.com/privacy"
assert recommended_app.custom_disclaimer == "Custom disclaimer"
assert recommended_app.language == "en-US"
assert recommended_app.category == "Productivity"
assert recommended_app.position == 1
def test_recommended_app_update_logic(self):
"""Test the update logic for existing RecommendedApp objects."""
mock_recommended_app = Mock(spec=RecommendedApp)
update_data = {
"desc": "Updated description",
"copyright": "© 2024 Updated",
"language": "fr-FR",
"category": "Tools",
"position": 2,
}
# Simulate the update logic
mock_recommended_app.description = update_data["desc"]
mock_recommended_app.copyright = update_data["copyright"]
mock_recommended_app.language = update_data["language"]
mock_recommended_app.category = update_data["category"]
mock_recommended_app.position = update_data["position"]
# Verify the updates
assert mock_recommended_app.description == "Updated description"
assert mock_recommended_app.copyright == "© 2024 Updated"
assert mock_recommended_app.language == "fr-FR"
assert mock_recommended_app.category == "Tools"
assert mock_recommended_app.position == 2
def test_app_not_found_error_logic(self):
"""Test error handling when app is not found."""
app_id = str(uuid.uuid4())
# Simulate app lookup returning None
found_app = None
# Test the error condition
if not found_app:
with pytest.raises(NotFound, match=f"App '{app_id}' is not found"):
raise NotFound(f"App '{app_id}' is not found")
def test_recommended_app_not_found_error_logic(self):
"""Test error handling when recommended app is not found for deletion."""
app_id = str(uuid.uuid4())
# Simulate recommended app lookup returning None
found_recommended_app = None
# Test the error condition
if not found_recommended_app:
with pytest.raises(NotFound, match=f"App '{app_id}' is not found in the explore list"):
raise NotFound(f"App '{app_id}' is not found in the explore list")
def test_database_session_usage_patterns(self):
"""Test the expected database session usage patterns."""
# Mock session usage patterns
mock_session = Mock()
# Test session.add pattern
mock_recommended_app = Mock(spec=RecommendedApp)
mock_session.add(mock_recommended_app)
mock_session.commit()
# Verify session was used correctly
mock_session.add.assert_called_once_with(mock_recommended_app)
mock_session.commit.assert_called_once()
# Test session.delete pattern
mock_recommended_app_to_delete = Mock(spec=RecommendedApp)
mock_session.delete(mock_recommended_app_to_delete)
mock_session.commit()
# Verify delete pattern
mock_session.delete.assert_called_once_with(mock_recommended_app_to_delete)
def test_payload_validation_integration(self):
"""Test payload validation in the context of the business logic."""
# Test valid payload
valid_payload_data = {
"app_id": str(uuid.uuid4()),
"desc": "Test app description",
"language": "en-US",
"category": "Productivity",
"position": 1,
}
# This should succeed
payload = InsertExploreAppPayload.model_validate(valid_payload_data)
assert payload.app_id == valid_payload_data["app_id"]
# Test invalid payload
invalid_payload_data = {
"app_id": str(uuid.uuid4()),
"language": "invalid-lang", # This should fail validation
"category": "Productivity",
"position": 1,
}
# This should raise an exception
with pytest.raises(ValueError, match="invalid-lang is not a valid language"):
InsertExploreAppPayload.model_validate(invalid_payload_data)
class TestExploreAppDataHandling:
"""Test specific data handling scenarios."""
def test_uuid_validation(self):
"""Test UUID validation and handling."""
# Test valid UUID
valid_uuid = str(uuid.uuid4())
# This should be a valid UUID
assert uuid.UUID(valid_uuid) is not None
# Test invalid UUID
invalid_uuid = "not-a-valid-uuid"
# This should raise a ValueError
with pytest.raises(ValueError):
uuid.UUID(invalid_uuid)
def test_language_validation(self):
"""Test language validation against supported languages."""
from constants.languages import supported_language
# Test supported language
assert supported_language("en-US") == "en-US"
assert supported_language("fr-FR") == "fr-FR"
# Test unsupported language
with pytest.raises(ValueError, match="invalid-lang is not a valid language"):
supported_language("invalid-lang")
def test_response_formatting(self):
"""Test API response formatting."""
# Test success responses
create_response = {"result": "success"}
update_response = {"result": "success"}
delete_response = None # 204 No Content returns None
assert create_response["result"] == "success"
assert update_response["result"] == "success"
assert delete_response is None
# Test status codes
create_status = 201 # Created
update_status = 200 # OK
delete_status = 204 # No Content
assert create_status == 201
assert update_status == 200
assert delete_status == 204

View File

@ -0,0 +1,25 @@
import uuid
import pytest
from pydantic import ValidationError
from controllers.service_api.app.completion import ChatRequestPayload
def test_chat_request_payload_accepts_blank_conversation_id():
payload = ChatRequestPayload.model_validate({"inputs": {}, "query": "hello", "conversation_id": ""})
assert payload.conversation_id is None
def test_chat_request_payload_validates_uuid():
conversation_id = str(uuid.uuid4())
payload = ChatRequestPayload.model_validate({"inputs": {}, "query": "hello", "conversation_id": conversation_id})
assert payload.conversation_id == conversation_id
def test_chat_request_payload_rejects_invalid_uuid():
with pytest.raises(ValidationError):
ChatRequestPayload.model_validate({"inputs": {}, "query": "hello", "conversation_id": "invalid"})

View File

@ -0,0 +1,20 @@
import pytest
from pydantic import ValidationError
from controllers.console.explore.conversation import ConversationRenamePayload as ConsolePayload
from controllers.service_api.app.conversation import ConversationRenamePayload as ServicePayload
@pytest.mark.parametrize("payload_cls", [ConsolePayload, ServicePayload])
def test_payload_allows_auto_generate_without_name(payload_cls):
payload = payload_cls.model_validate({"auto_generate": True})
assert payload.auto_generate is True
assert payload.name is None
@pytest.mark.parametrize("payload_cls", [ConsolePayload, ServicePayload])
@pytest.mark.parametrize("value", [None, "", " "])
def test_payload_requires_name_when_not_auto_generate(payload_cls, value):
with pytest.raises(ValidationError):
payload_cls.model_validate({"name": value, "auto_generate": False})

View File

@ -1,7 +1,10 @@
"""Primarily used for testing merged cell scenarios"""
from types import SimpleNamespace
from docx import Document
import core.rag.extractor.word_extractor as we
from core.rag.extractor.word_extractor import WordExtractor
@ -47,3 +50,85 @@ def test_parse_row():
extractor = object.__new__(WordExtractor)
for idx, row in enumerate(table.rows):
assert extractor._parse_row(row, {}, 3) == gt[idx]
def test_extract_images_from_docx(monkeypatch):
external_bytes = b"ext-bytes"
internal_bytes = b"int-bytes"
# Patch storage.save to capture writes
saves: list[tuple[str, bytes]] = []
def save(key: str, data: bytes):
saves.append((key, data))
monkeypatch.setattr(we, "storage", SimpleNamespace(save=save))
# Patch db.session to record adds/commit
class DummySession:
def __init__(self):
self.added = []
self.committed = False
def add(self, obj):
self.added.append(obj)
def commit(self):
self.committed = True
db_stub = SimpleNamespace(session=DummySession())
monkeypatch.setattr(we, "db", db_stub)
# Patch config values used for URL composition and storage type
monkeypatch.setattr(we.dify_config, "FILES_URL", "http://files.local", raising=False)
monkeypatch.setattr(we.dify_config, "STORAGE_TYPE", "local", raising=False)
# Patch UploadFile to avoid real DB models
class FakeUploadFile:
_i = 0
def __init__(self, **kwargs): # kwargs match the real signature fields
type(self)._i += 1
self.id = f"u{self._i}"
monkeypatch.setattr(we, "UploadFile", FakeUploadFile)
# Patch external image fetcher
def fake_get(url: str):
assert url == "https://example.com/image.png"
return SimpleNamespace(status_code=200, headers={"Content-Type": "image/png"}, content=external_bytes)
monkeypatch.setattr(we, "ssrf_proxy", SimpleNamespace(get=fake_get))
# A hashable internal part object with a blob attribute
class HashablePart:
def __init__(self, blob: bytes):
self.blob = blob
def __hash__(self) -> int: # ensure it can be used as a dict key like real docx parts
return id(self)
# Build a minimal doc object with both external and internal image rels
internal_part = HashablePart(blob=internal_bytes)
rel_ext = SimpleNamespace(is_external=True, target_ref="https://example.com/image.png")
rel_int = SimpleNamespace(is_external=False, target_ref="word/media/image1.png", target_part=internal_part)
doc = SimpleNamespace(part=SimpleNamespace(rels={"rId1": rel_ext, "rId2": rel_int}))
extractor = object.__new__(WordExtractor)
extractor.tenant_id = "t1"
extractor.user_id = "u1"
image_map = extractor._extract_images_from_docx(doc)
# Returned map should contain entries for external (keyed by rId) and internal (keyed by target_part)
assert set(image_map.keys()) == {"rId1", internal_part}
assert all(v.startswith("![image](") and v.endswith("/file-preview)") for v in image_map.values())
# Storage should receive both payloads
payloads = {data for _, data in saves}
assert external_bytes in payloads
assert internal_bytes in payloads
# DB interactions should be recorded
assert len(db_stub.session.added) == 2
assert db_stub.session.committed is True

View File

@ -0,0 +1,86 @@
import pytest
import core.tools.utils.message_transformer as mt
from core.tools.entities.tool_entities import ToolInvokeMessage
class _FakeToolFile:
def __init__(self, mimetype: str):
self.id = "fake-tool-file-id"
self.mimetype = mimetype
class _FakeToolFileManager:
"""Fake ToolFileManager to capture the mimetype passed in."""
last_call: dict | None = None
def __init__(self, *args, **kwargs):
pass
def create_file_by_raw(
self,
*,
user_id: str,
tenant_id: str,
conversation_id: str | None,
file_binary: bytes,
mimetype: str,
filename: str | None = None,
):
type(self).last_call = {
"user_id": user_id,
"tenant_id": tenant_id,
"conversation_id": conversation_id,
"file_binary": file_binary,
"mimetype": mimetype,
"filename": filename,
}
return _FakeToolFile(mimetype)
@pytest.fixture(autouse=True)
def _patch_tool_file_manager(monkeypatch):
# Patch the manager used inside the transformer module
monkeypatch.setattr(mt, "ToolFileManager", _FakeToolFileManager)
# also ensure predictable URL generation (no need to patch; uses id and extension only)
yield
_FakeToolFileManager.last_call = None
def _gen(messages):
yield from messages
def test_transform_tool_invoke_messages_mimetype_key_present_but_none():
# Arrange: a BLOB message whose meta contains a mime_type key set to None
blob = b"hello"
msg = ToolInvokeMessage(
type=ToolInvokeMessage.MessageType.BLOB,
message=ToolInvokeMessage.BlobMessage(blob=blob),
meta={"mime_type": None, "filename": "greeting"},
)
# Act
out = list(
mt.ToolFileMessageTransformer.transform_tool_invoke_messages(
messages=_gen([msg]),
user_id="u1",
tenant_id="t1",
conversation_id="c1",
)
)
# Assert: default to application/octet-stream when mime_type is present but None
assert _FakeToolFileManager.last_call is not None
assert _FakeToolFileManager.last_call["mimetype"] == "application/octet-stream"
# Should yield a BINARY_LINK (not IMAGE_LINK) and the URL ends with .bin
assert len(out) == 1
o = out[0]
assert o.type == ToolInvokeMessage.MessageType.BINARY_LINK
assert isinstance(o.message, ToolInvokeMessage.TextMessage)
assert o.message.text.endswith(".bin")
# meta is preserved (still contains mime_type: None)
assert "mime_type" in (o.meta or {})
assert o.meta["mime_type"] is None

View File

@ -0,0 +1,60 @@
"""
Test case for end node without value_type field (backward compatibility).
This test validates that end nodes work correctly even when the value_type
field is missing from the output configuration, ensuring backward compatibility
with older workflow definitions.
"""
from core.workflow.graph_events import (
GraphRunStartedEvent,
GraphRunSucceededEvent,
NodeRunStartedEvent,
NodeRunStreamChunkEvent,
NodeRunSucceededEvent,
)
from .test_table_runner import TableTestRunner, WorkflowTestCase
def test_end_node_without_value_type_field():
"""
Test that end node works without explicit value_type field.
The fixture implements a simple workflow that:
1. Takes a query input from start node
2. Passes it directly to end node
3. End node outputs the value without specifying value_type
4. Should correctly infer the type and output the value
This ensures backward compatibility with workflow definitions
created before value_type became a required field.
"""
fixture_name = "end_node_without_value_type_field_workflow"
case = WorkflowTestCase(
fixture_path=fixture_name,
inputs={"query": "test query"},
expected_outputs={"query": "test query"},
expected_event_sequence=[
# Graph start
GraphRunStartedEvent,
# Start node
NodeRunStartedEvent,
NodeRunStreamChunkEvent, # Start node streams the input value
NodeRunSucceededEvent,
# End node
NodeRunStartedEvent,
NodeRunSucceededEvent,
# Graph end
GraphRunSucceededEvent,
],
description="End node without value_type field should work correctly",
)
runner = TableTestRunner()
result = runner.run_test_case(case)
assert result.success, f"Test failed: {result.error}"
assert result.actual_outputs == {"query": "test query"}, (
f"Expected output to be {{'query': 'test query'}}, got {result.actual_outputs}"
)

View File

@ -1149,3 +1149,258 @@ class TestModelIntegration:
# Assert
assert site.app_id == app.id
assert app.enable_site is True
class TestConversationStatusCount:
"""Test suite for Conversation.status_count property N+1 query fix."""
def test_status_count_no_messages(self):
"""Test status_count returns None when conversation has no messages."""
# Arrange
conversation = Conversation(
app_id=str(uuid4()),
mode=AppMode.CHAT,
name="Test Conversation",
status="normal",
from_source="api",
)
conversation.id = str(uuid4())
# Mock the database query to return no messages
with patch("models.model.db.session.scalars") as mock_scalars:
mock_scalars.return_value.all.return_value = []
# Act
result = conversation.status_count
# Assert
assert result is None
def test_status_count_messages_without_workflow_runs(self):
"""Test status_count when messages have no workflow_run_id."""
# Arrange
app_id = str(uuid4())
conversation_id = str(uuid4())
conversation = Conversation(
app_id=app_id,
mode=AppMode.CHAT,
name="Test Conversation",
status="normal",
from_source="api",
)
conversation.id = conversation_id
# Mock the database query to return no messages with workflow_run_id
with patch("models.model.db.session.scalars") as mock_scalars:
mock_scalars.return_value.all.return_value = []
# Act
result = conversation.status_count
# Assert
assert result is None
def test_status_count_batch_loading_implementation(self):
"""Test that status_count uses batch loading instead of N+1 queries."""
# Arrange
from core.workflow.enums import WorkflowExecutionStatus
app_id = str(uuid4())
conversation_id = str(uuid4())
# Create workflow run IDs
workflow_run_id_1 = str(uuid4())
workflow_run_id_2 = str(uuid4())
workflow_run_id_3 = str(uuid4())
conversation = Conversation(
app_id=app_id,
mode=AppMode.CHAT,
name="Test Conversation",
status="normal",
from_source="api",
)
conversation.id = conversation_id
# Mock messages with workflow_run_id
mock_messages = [
MagicMock(
conversation_id=conversation_id,
workflow_run_id=workflow_run_id_1,
),
MagicMock(
conversation_id=conversation_id,
workflow_run_id=workflow_run_id_2,
),
MagicMock(
conversation_id=conversation_id,
workflow_run_id=workflow_run_id_3,
),
]
# Mock workflow runs with different statuses
mock_workflow_runs = [
MagicMock(
id=workflow_run_id_1,
status=WorkflowExecutionStatus.SUCCEEDED.value,
app_id=app_id,
),
MagicMock(
id=workflow_run_id_2,
status=WorkflowExecutionStatus.FAILED.value,
app_id=app_id,
),
MagicMock(
id=workflow_run_id_3,
status=WorkflowExecutionStatus.PARTIAL_SUCCEEDED.value,
app_id=app_id,
),
]
# Track database calls
calls_made = []
def mock_scalars(query):
calls_made.append(str(query))
mock_result = MagicMock()
# Return messages for the first query (messages with workflow_run_id)
if "messages" in str(query) and "conversation_id" in str(query):
mock_result.all.return_value = mock_messages
# Return workflow runs for the batch query
elif "workflow_runs" in str(query):
mock_result.all.return_value = mock_workflow_runs
else:
mock_result.all.return_value = []
return mock_result
# Act & Assert
with patch("models.model.db.session.scalars", side_effect=mock_scalars):
result = conversation.status_count
# Verify only 2 database queries were made (not N+1)
assert len(calls_made) == 2, f"Expected 2 queries, got {len(calls_made)}: {calls_made}"
# Verify the first query gets messages
assert "messages" in calls_made[0]
assert "conversation_id" in calls_made[0]
# Verify the second query batch loads workflow runs with proper filtering
assert "workflow_runs" in calls_made[1]
assert "app_id" in calls_made[1] # Security filter applied
assert "IN" in calls_made[1] # Batch loading with IN clause
# Verify correct status counts
assert result["success"] == 1 # One SUCCEEDED
assert result["failed"] == 1 # One FAILED
assert result["partial_success"] == 1 # One PARTIAL_SUCCEEDED
def test_status_count_app_id_filtering(self):
"""Test that status_count filters workflow runs by app_id for security."""
# Arrange
app_id = str(uuid4())
other_app_id = str(uuid4())
conversation_id = str(uuid4())
workflow_run_id = str(uuid4())
conversation = Conversation(
app_id=app_id,
mode=AppMode.CHAT,
name="Test Conversation",
status="normal",
from_source="api",
)
conversation.id = conversation_id
# Mock message with workflow_run_id
mock_messages = [
MagicMock(
conversation_id=conversation_id,
workflow_run_id=workflow_run_id,
),
]
calls_made = []
def mock_scalars(query):
calls_made.append(str(query))
mock_result = MagicMock()
if "messages" in str(query):
mock_result.all.return_value = mock_messages
elif "workflow_runs" in str(query):
# Return empty list because no workflow run matches the correct app_id
mock_result.all.return_value = [] # Workflow run filtered out by app_id
else:
mock_result.all.return_value = []
return mock_result
# Act
with patch("models.model.db.session.scalars", side_effect=mock_scalars):
result = conversation.status_count
# Assert - query should include app_id filter
workflow_query = calls_made[1]
assert "app_id" in workflow_query
# Since workflow run has wrong app_id, it shouldn't be included in counts
assert result["success"] == 0
assert result["failed"] == 0
assert result["partial_success"] == 0
def test_status_count_handles_invalid_workflow_status(self):
"""Test that status_count gracefully handles invalid workflow status values."""
# Arrange
app_id = str(uuid4())
conversation_id = str(uuid4())
workflow_run_id = str(uuid4())
conversation = Conversation(
app_id=app_id,
mode=AppMode.CHAT,
name="Test Conversation",
status="normal",
from_source="api",
)
conversation.id = conversation_id
mock_messages = [
MagicMock(
conversation_id=conversation_id,
workflow_run_id=workflow_run_id,
),
]
# Mock workflow run with invalid status
mock_workflow_runs = [
MagicMock(
id=workflow_run_id,
status="invalid_status", # Invalid status that should raise ValueError
app_id=app_id,
),
]
with patch("models.model.db.session.scalars") as mock_scalars:
# Mock the messages query
def mock_scalars_side_effect(query):
mock_result = MagicMock()
if "messages" in str(query):
mock_result.all.return_value = mock_messages
elif "workflow_runs" in str(query):
mock_result.all.return_value = mock_workflow_runs
else:
mock_result.all.return_value = []
return mock_result
mock_scalars.side_effect = mock_scalars_side_effect
# Act - should not raise exception
result = conversation.status_count
# Assert - should handle invalid status gracefully
assert result["success"] == 0
assert result["failed"] == 0
assert result["partial_success"] == 0

View File

@ -14,7 +14,9 @@ def get_example_bucket() -> str:
def get_opendal_bucket() -> str:
return "./dify"
import os
return os.environ.get("OPENDAL_FS_ROOT", "/tmp/dify-storage")
def get_example_filename() -> str:

View File

@ -21,20 +21,16 @@ class TestOpenDAL:
)
@pytest.fixture(scope="class", autouse=True)
def teardown_class(self, request):
def teardown_class(self):
"""Clean up after all tests in the class."""
def cleanup():
folder = Path(get_opendal_bucket())
if folder.exists() and folder.is_dir():
for item in folder.iterdir():
if item.is_file():
item.unlink()
elif item.is_dir():
item.rmdir()
folder.rmdir()
yield
return cleanup()
folder = Path(get_opendal_bucket())
if folder.exists() and folder.is_dir():
import shutil
shutil.rmtree(folder, ignore_errors=True)
def test_save_and_exists(self):
"""Test saving data and checking existence."""

View File

@ -0,0 +1,88 @@
import types
import pytest
from core.entities.provider_entities import CredentialConfiguration, CustomModelConfiguration
from core.model_runtime.entities.common_entities import I18nObject
from core.model_runtime.entities.model_entities import ModelType
from core.model_runtime.entities.provider_entities import ConfigurateMethod
from models.provider import ProviderType
from services.model_provider_service import ModelProviderService
class _FakeConfigurations:
def __init__(self, provider_configuration: types.SimpleNamespace) -> None:
self._provider_configuration = provider_configuration
def values(self) -> list[types.SimpleNamespace]:
return [self._provider_configuration]
@pytest.fixture
def service_with_fake_configurations():
# Build a fake provider schema with minimal fields used by ProviderResponse
fake_provider = types.SimpleNamespace(
provider="langgenius/openai_api_compatible/openai_api_compatible",
label=I18nObject(en_US="OpenAI API Compatible", zh_Hans="OpenAI API Compatible"),
description=None,
icon_small=None,
icon_small_dark=None,
icon_large=None,
background=None,
help=None,
supported_model_types=[ModelType.LLM],
configurate_methods=[ConfigurateMethod.CUSTOMIZABLE_MODEL],
provider_credential_schema=None,
model_credential_schema=None,
)
# Include decrypted credentials to simulate the leak source
custom_model = CustomModelConfiguration(
model="gpt-4o-mini",
model_type=ModelType.LLM,
credentials={"api_key": "sk-plain-text", "endpoint": "https://example.com"},
current_credential_id="cred-1",
current_credential_name="API KEY 1",
available_model_credentials=[],
unadded_to_model_list=False,
)
fake_custom_provider = types.SimpleNamespace(
current_credential_id="cred-1",
current_credential_name="API KEY 1",
available_credentials=[CredentialConfiguration(credential_id="cred-1", credential_name="API KEY 1")],
)
fake_custom_configuration = types.SimpleNamespace(
provider=fake_custom_provider, models=[custom_model], can_added_models=[]
)
fake_system_configuration = types.SimpleNamespace(enabled=False, current_quota_type=None, quota_configurations=[])
fake_provider_configuration = types.SimpleNamespace(
provider=fake_provider,
preferred_provider_type=ProviderType.CUSTOM,
custom_configuration=fake_custom_configuration,
system_configuration=fake_system_configuration,
is_custom_configuration_available=lambda: True,
)
class _FakeProviderManager:
def get_configurations(self, tenant_id: str) -> _FakeConfigurations:
return _FakeConfigurations(fake_provider_configuration)
svc = ModelProviderService()
svc.provider_manager = _FakeProviderManager()
return svc
def test_get_provider_list_strips_credentials(service_with_fake_configurations: ModelProviderService):
providers = service_with_fake_configurations.get_provider_list(tenant_id="tenant-1", model_type=None)
assert len(providers) == 1
custom_models = providers[0].custom_configuration.custom_models
assert custom_models is not None
assert len(custom_models) == 1
# The sanitizer should drop credentials in list response
assert custom_models[0].credentials is None

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