This fix addresses the issue where math formulas become corrupted or
incorrectly displayed after editing the generated report in the editor.
**Root Cause:**
The issue occurred due to incompatibility between markdown processing
in the display component and the Tiptap editor:
1. Display component used \[\] and \(\) LaTeX delimiters
2. Tiptap Mathematics extension expects $ and 70868 delimiters
3. tiptap-markdown didn't have built-in math node serialization
4. Math syntax was lost/corrupted during editor save operations
**Solution Implemented:**
1. Created MathematicsWithMarkdown extension that adds markdown
serialization support to Tiptap's Mathematics nodes
2. Added math delimiter normalization functions:
- normalizeMathForEditor(): Converts LaTeX delimiters to $/70868
- normalizeMathForDisplay(): Standardizes all delimiters to 70868
3. Updated Markdown component to use new normalization
4. Updated ReportEditor to normalize content before loading
**Changes:**
- web/src/components/editor/math-serializer.ts (new)
- web/src/components/editor/extensions.tsx
- web/src/components/editor/index.tsx
- web/src/components/deer-flow/markdown.tsx
- web/src/core/utils/markdown.ts
- web/tests/markdown-math-editor.test.ts (new)
- web/tests/markdown-katex.test.ts
**Testing:**
- Added 15 comprehensive tests for math normalization round-trip
- All tests passing (math editor + existing katex tests)
- Verified TypeScript compilation and linting
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Bug Fix
This PR fixes the issue where max_clarification_rounds parameter was not being passed from the frontend to the backend, causing a TypeError: '<' not supported between instances of 'int' and 'NoneType' error.
Technical Details
The issue was that the frontend was not passing the max_clarification_rounds parameter to the backend API, causing the backend to receive None values and fail during comparison operations. This fix ensures the parameter is properly typed and passed through the entire request chain.
* fix: support local models by making thought field optional in Plan model
- Make thought field optional in Plan model to fix Pydantic validation errors with local models
- Add Ollama configuration example to conf.yaml.example
- Update documentation to include local model support
- Improve planner prompt with better JSON format requirements
Fixes local model integration issues where models like qwen3:14b would fail
due to missing thought field in JSON output.
* feat: Add intelligent clarification feature for research queries
- Add multi-turn clarification process to refine vague research questions
- Implement three-dimension clarification standard (Tech/App, Focus, Scope)
- Add clarification state management in coordinator node
- Update coordinator prompt with detailed clarification guidelines
- Add UI settings to enable/disable clarification feature (disabled by default)
- Update workflow to handle clarification rounds recursively
- Add comprehensive test coverage for clarification functionality
- Update documentation with clarification feature usage guide
Key components:
- src/graph/nodes.py: Core clarification logic and state management
- src/prompts/coordinator.md: Detailed clarification guidelines
- src/workflow.py: Recursive clarification handling
- web/: UI settings integration
- tests/: Comprehensive test coverage
- docs/: Updated configuration guide
* fix: Improve clarification conversation continuity
- Add comprehensive conversation history to clarification context
- Include previous exchanges summary in system messages
- Add explicit guidelines for continuing rounds in coordinator prompt
- Prevent LLM from starting new topics during clarification
- Ensure topic continuity across clarification rounds
Fixes issue where LLM would restart clarification instead of building upon previous exchanges.
* fix: Add conversation history to clarification context
* fix: resolve clarification feature message to planer, prompt, test issues
- Optimize coordinator.md prompt template for better clarification flow
- Simplify final message sent to planner after clarification
- Fix API key assertion issues in test_search.py
* fix: Add configurable max_clarification_rounds and comprehensive tests
- Add max_clarification_rounds parameter for external configuration
- Add comprehensive test cases for clarification feature in test_app.py
- Fixes issues found during interactive mode testing where:
- Recursive call failed due to missing initial_state parameter
- Clarification exited prematurely at max rounds
- Incorrect logging of max rounds reached
* Move clarification tests to test_nodes.py and add max_clarification_rounds to zh.json
- Make thought field optional in Plan model to fix Pydantic validation errors with local models
- Add Ollama configuration example to conf.yaml.example
- Update documentation to include local model support
- Improve planner prompt with better JSON format requirements
Fixes local model integration issues where models like qwen3:14b would fail
due to missing thought field in JSON output.
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat:Add context compress
* feat: Add unit test
* feat: add unit test for context manager
* feat: add postprocessor param && code format
* feat: add configuration guide
* fix: fix the configuration_guide
* fix: fix the unit test
* fix: fix the default value
* feat: add test and log for context_manager
* add searx/searxng support
* nit
* Fix indentation in search.py for readability
* Clean up imports in search.py
Removed unused imports from search.py
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat:support config tavily search results
* feat: support config tavily search results
* feat: update the default value of include_images
* fix: fix the test
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* Debug deerflow server, web with vscode
Signed-off-by: shjy <asdf_0403@qq.com>
* removed the duplicated setting of .vscode
---------
Signed-off-by: shjy <asdf_0403@qq.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: add Google AI Studio API support with platform-based detection
* chore: update configuration_guide.md
* fix the uv.lock formate error
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: Implement MilvusRetriever with embedding model and resource management
* chore: Update configuration and loader files for consistency
* chore: Clean up test_milvus.py for improved readability and organization
* feat: Add tests for DashscopeEmbeddings query and document embedding methods
* feat: Add tests for embedding model initialization and example file loading in MilvusProvider
* chore: Remove unused imports and clean up test_milvus.py for better readability
* chore: Clean up test_milvus.py for improved readability and organization
* chore: Clean up test_milvus.py for improved readability and organization
* fix: replace print statements with logging in recursion limit function
* Implement feature X to enhance user experience and optimize performance
* refactor: clean up unused imports and comments in AboutTab component
* Implement feature X to enhance user experience and fix bug Y in module Z
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* docs: add deployment note for Linux servers
- allow external connections by changing the host to 0.0.0.0.
- security warning to remind users to secure their environment before exposing the service.
* docs: add deployment note for Linux servers
- allow external connections by changing the host to 0.0.0.0.
- security warning to remind users to secure their environment before exposing the service.
* fix: using mongomock for the checkpoint test
* Add postgres mock setting to the unit test
* Added utils file of postgres_mock_utils
* fixed the runtime loading error of deerflow server
* fix: correct typo in MongoDB connection string within .env.example
- Changes 'ongodb' to 'mongodb' in LANGGRAPH_CHECKPOINT_DB_URL example.
- This ensures the example configuration is valid and can be used directly.
* Update LANGGRAPH_CHECKPOINT_DB_URL in .env.example
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix: using commit hash as the action version
* fix: using commit hash as the action version
---------
Co-authored-by: Willem Jiang <143703838+willem-bd@users.noreply.github.com>
* feat: Enhance chat streaming and tool call processing
- Added support for MongoDB checkpointer in the chat streaming workflow.
- Introduced functions to process tool call chunks and sanitize arguments.
- Improved event message creation with additional metadata.
- Enhanced error handling for JSON serialization in event messages.
- Updated the frontend to convert escaped characters in tool call arguments.
- Refactored the workflow input preparation and initial message processing.
- Added new dependencies for MongoDB integration and tool argument sanitization.
* fix: Update MongoDB checkpointer configuration to use LANGGRAPH_CHECKPOINT_DB_URL
* feat: Add support for Postgres checkpointing and update README with database recommendations
* feat: Implement checkpoint saver functionality and update MongoDB connection handling
* refactor: Improve code formatting and readability in app.py and json_utils.py
* refactor: Clean up commented code and improve formatting in server.py
* refactor: Remove unused imports and improve code organization in app.py
* refactor: Improve code organization and remove unnecessary comments in app.py
* chore: use langgraph-checkpoint-postgres==2.0.21 to avoid the JSON convert issue in the latest version, implement chat stream persistant with Postgres
* feat: add MongoDB and PostgreSQL support for LangGraph checkpointing, enhance environment variable handling
* fix: update comments for clarity on Windows event loop policy
* chore: remove empty code changes in MongoDB and PostgreSQL checkpoint tests
* chore: clean up unused imports and code in checkpoint-related files
* chore: remove empty code changes in test_checkpoint.py
* chore: remove empty code changes in test_checkpoint.py
* chore: remove empty code changes in test_checkpoint.py
* test: update status code assertions in MCP endpoint tests to allow for 403 responses
* test: update MCP endpoint tests to assert specific status codes and enable MCP server configuration
* chore: remove unnecessary environment variables from unittest workflow
* fix: invert condition for MCP server configuration check to raise 403 when disabled
* chore: remove pymongo from test dependencies in uv.lock
* chore: optimize the _get_agent_name method
* test: enhance ChatStreamManager tests for PostgreSQL and MongoDB initialization
* test: add persistence tests for ChatStreamManager with PostgreSQL and MongoDB
* test: add unit tests for ChatStreamManager initialization with PostgreSQL and MongoDB
* test: enhance persistence tests for ChatStreamManager with PostgreSQL and MongoDB to verify message aggregation
* test: add unit tests for ChatStreamManager with PostgreSQL and MongoDB
* test: add unit tests for ChatStreamManager initialization with PostgreSQL and MongoDB
* test: add unit tests for ChatStreamManager initialization with PostgreSQL and MongoDB
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix: update README and configuration guide for new model support and reasoning capabilities
* fix: format code for consistency in agent and node files
* fix: update test cases for environment variable handling in llm configuration
* fix: refactor message chunk conversion functions for improved clarity and maintainability
* refactor: remove enable_thinking parameter from LLM configuration functions
* chore: update agent-LLM mapping for consistency
* chore: update LLM configuration handling for improved clarity
* test: add unit tests for Dashscope message chunk conversion and LLM configuration
* test: add unit tests for message chunk conversion in Dashscope
* test: add unit tests for message chunk conversion in Dashscope
* chore: remove unused imports from test_dashscope.py
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
