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Victor Dibia
7a45929807
* DevUI: Add OpenAI Responses API proxy support with enhanced UI features This commit adds support for proxying requests to OpenAI's Responses API, allowing DevUI to route conversations to OpenAI models when configured to enable testing. Backend changes: - Add OpenAI proxy executor with conversation routing logic - Enhance event mapper to support OpenAI Responses API format - Extend server endpoints to handle OpenAI proxy mode - Update models with OpenAI-specific response types - Remove emojis from logging and CLI output for cleaner text Frontend changes: - Add settings modal with OpenAI proxy configuration UI - Enhance agent and workflow views with improved state management - Add new UI components (separator, switch) for settings - Update debug panel with better event filtering - Improve message renderers for OpenAI content types - Update types and API client for OpenAI integration * update ui, settings modal and workflow input form, add register cleanup hooks. * add workflow HIL support, user mode, other fixes * feat(devui): add human-in-the-loop (HIL) support with dynamic response schemas Implement HIL workflow support allowing workflows to pause for user input with dynamically generated JSON schemas based on response handler type hints. Key Features: - Automatic response schema extraction from @response_handler decorators - Dynamic form generation in UI based on Pydantic/dataclass response types - Checkpoint-based conversation storage for HIL requests/responses - Resume workflow execution after user provides HIL response Backend Changes: - Add extract_response_type_from_executor() to introspect response handlers - Enrich RequestInfoEvent with response_schema via _enrich_request_info_event_with_response_schema() - Map RequestInfoEvent to response.input.requested OpenAI event format - Store HIL responses in conversation history and restore checkpoints Frontend Changes: - Add HILInputModal component with SchemaFormRenderer for dynamic forms - Support Pydantic BaseModel and dataclass response types - Render enum fields as dropdowns, strings as text/textarea, numbers, booleans, arrays, objects - Display original request context alongside response form Testing: - Add tests for checkpoint storage (test_checkpoints.py) - Add schema generation tests for all input types (test_schema_generation.py) - Validate end-to-end HIL flow with spam workflow sample This enables workflows to seamlessly pause execution and request structured user input with type-safe, validated forms generated automatically from response type annotations. * improve HIL support, improve workflow execution view * ui updates * ui updates * improve HIL for workflows, add auth and view modes * update workflow * security improvements , ui fixes * fix mypy error * update loading spinner in ui * DevUI: Serialize workflow input as string to maintain conformance with OpenAI Responses format * Phase 1: Add /meta endpoint and fix workflow event naming for .NET DevUI compatibility * additional fixes for .NET DevUI workflow visualization item ID tracking **Problem:** .NET DevUI was generating different item IDs for ExecutorInvokedEvent and ExecutorCompletedEvent, causing only the first executor to highlight in the workflow graph. Long executor names and error messages also broke UI layout. **Changes:** - Add ExecutorActionItemResource to match Python DevUI implementation - Track item IDs per executor using dictionary in AgentRunResponseUpdateExtensions - Reuse same item ID across invoked/completed/failed events for proper pairing - Add truncateText() utility to workflow-utils.ts - Truncate executor names to 35 chars in execution timeline - Truncate error messages to 150 chars in workflow graph nodes ** Details:** - ExecutorActionItemResource registered with JSON source generation context - Dictionary cleaned up after executor completion/failure to prevent memory leaks - Frontend item tracking by unique item.id supports multiple executor runs - All changes follow existing codebase patterns and conventions Tested with review-workflow showing correct executor highlighting and state transitions for sequential and concurrent executors. * format fixes, remove cors tests * remove unecessary attributes --------- Co-authored-by: Mark Wallace <127216156+markwallace-microsoft@users.noreply.github.com> Co-authored-by: Reuben Bond <reuben.bond@gmail.com>
7a45929807
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2025-11-10 18:56:31 +00:00
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DevUI Frontend
Build Instructions
cd frontend
yarn install
# Create .env.local with backend URL
echo 'VITE_API_BASE_URL=http://localhost:8000' > .env.local
# Create .env.production (empty for relative URLs)
echo '' > .env.production
# Development
yarn dev
# Build (copies to backend)
yarn build
Expanding the ESLint configuration
If you are developing a production application, we recommend updating the configuration to enable type-aware lint rules:
export default tseslint.config([
globalIgnores(['dist']),
{
files: ['**/*.{ts,tsx}'],
extends: [
// Other configs...
// Remove tseslint.configs.recommended and replace with this
...tseslint.configs.recommendedTypeChecked,
// Alternatively, use this for stricter rules
...tseslint.configs.strictTypeChecked,
// Optionally, add this for stylistic rules
...tseslint.configs.stylisticTypeChecked,
// Other configs...
],
languageOptions: {
parserOptions: {
project: ['./tsconfig.node.json', './tsconfig.app.json'],
tsconfigRootDir: import.meta.dirname,
},
// other options...
},
},
])
You can also install eslint-plugin-react-x and eslint-plugin-react-dom for React-specific lint rules:
// eslint.config.js
import reactX from 'eslint-plugin-react-x'
import reactDom from 'eslint-plugin-react-dom'
export default tseslint.config([
globalIgnores(['dist']),
{
files: ['**/*.{ts,tsx}'],
extends: [
// Other configs...
// Enable lint rules for React
reactX.configs['recommended-typescript'],
// Enable lint rules for React DOM
reactDom.configs.recommended,
],
languageOptions: {
parserOptions: {
project: ['./tsconfig.node.json', './tsconfig.app.json'],
tsconfigRootDir: import.meta.dirname,
},
// other options...
},
},
])