Extract message content from direct_response tool call args
and display it as the message content when tool call completes.
Note: This is a workaround. The message is not streamed because
direct_response uses tool calling mechanism where args are JSON,
not natural language text that can be streamed directly.
* fix(web): handle incomplete JSON in MCP tool call arguments (#528)
When using stream_mode=["messages", "updates"] with MCP tools, tool call
arguments arrive in chunks that may be incomplete JSON (missing closing
braces). This caused JSON.parse() to throw errors in the frontend.
Changes:
- Add safeParseToolArgs() function using best-effort-json-parser to
gracefully handle incomplete JSON from streaming
- Replace direct JSON.parse() with safe parser in mergeMessage()
- Add comprehensive tests for tool call argument parsing scenarios
* Address the code review comments
* fix: make SSE buffer size configurable to prevent overflow during multi-round searches (Issue #664)
- Add NEXT_PUBLIC_MAX_STREAM_BUFFER_SIZE environment variable for frontend SSE stream buffer
- Default to 1MB for backward compatibility, users can increase to 5-10MB for large searches
- Enhance error message with actual buffer sizes and guidance on configuration
- Add validation schema in env.js with positive integer requirement
- Document configuration in .env.example with clear examples and use cases
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
- Add unescape for \{ and \} characters in unescapeMarkdownSpecialChars()
- These are commonly used in LaTeX commands like \mathcal{F}
- Add test cases for Fourier transform notation and mixed escape scenarios
- All 118 tests pass including 4 new edge case tests for issue #608
* fix: improve config loading resilience for non-localhost access (#510)
- Add DEFAULT_CONFIG fallback to always return valid config even if fetch fails
- Implement retry logic with exponential backoff (max 2 retries) to handle transient failures
- Add 5-second fetch timeout to prevent hanging on unreachable backends
- Improve error logging with clear messages about config fetch status
- Always return DeerFlowConfig (never null) to prevent UI rendering issues
- Add safety checks in input-box component to verify reasoning models before access
- Improve type safety: verify array length before accessing array indices
- Add comprehensive documentation in .env.example with examples for different deployment scenarios
- Document NEXT_PUBLIC_API_URL variable behavior and fallback mechanism
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* fix: add nullish coalescing to prevent TypeScript error in input-box
- Add ?? operator to handle potential undefined value when accessing reasoning[0]
- Fixes TS2322 error: Type 'string | undefined' is not assignable to type 'string | number | Date'
---------
Co-authored-by: Willem Jiang <143703838+willem-bd@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* fix: resolve issue #588 - react key warnings from duplicate message IDs + establish jest testing framework
* Update the makefile and workflow with the js test
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
When editing reports, tiptap-markdown escapes special characters (*, _, [, ])
which corrupts LaTeX formulas. This fix:
1. Adds unescapeLatexInMath() function to reverse markdown escaping within
math delimiters ($...$ and 94410...94410)
2. Applies the unescape function in the editor's onChange callback to clean
the markdown before storing it
3. Adds comprehensive tests covering edge cases and round-trip scenarios
The fix ensures formulas like $(f * g)[n]$ remain unescaped when editing,
preventing display errors after save/reload.
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
* 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
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Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: implment backend for adjust report style
* feat: add web part
* fix test cases
* fix: fix typing
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Co-authored-by: Henry Li <henry1943@163.com>
