* feat: add citation support in research report block and markdown
- Enhanced ResearchReportBlock to fetch citations based on researchId and pass them to the Markdown component.
- Introduced CitationLink component to display citation metadata on hover for links in markdown.
- Implemented CitationCard and CitationList components for displaying citation details and lists.
- Updated Markdown component to handle citation links and inline citations.
- Created HoverCard component for displaying citation information in a tooltip-like manner.
- Modified store to manage citations, including setting and retrieving citations for ongoing research.
- Added CitationsEvent type to handle citations in chat events and updated Message type to include citations.
* fix(log): Enable the logging level when enabling the DEBUG environment variable (#793)
* fix(frontend): render all tool calls in the frontend #796 (#797)
* build(deps): bump jspdf from 3.0.4 to 4.0.0 in /web (#798)
Bumps [jspdf](https://github.com/parallax/jsPDF) from 3.0.4 to 4.0.0.
- [Release notes](https://github.com/parallax/jsPDF/releases)
- [Changelog](https://github.com/parallax/jsPDF/blob/master/RELEASE.md)
- [Commits](https://github.com/parallax/jsPDF/compare/v3.0.4...v4.0.0)
---
updated-dependencies:
- dependency-name: jspdf
dependency-version: 4.0.0
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* fix(frontend):added the display of the 'analyst' message #800 (#801)
* fix: migrate from deprecated create_react_agent to langchain.agents.create_agent (#802)
* fix: migrate from deprecated create_react_agent to langchain.agents.create_agent
Fixes#799
- Replace deprecated langgraph.prebuilt.create_react_agent with
langchain.agents.create_agent (LangGraph 1.0 migration)
- Add DynamicPromptMiddleware to handle dynamic prompt templates
(replaces the 'prompt' callable parameter)
- Add PreModelHookMiddleware to handle pre-model hooks
(replaces the 'pre_model_hook' parameter)
- Update AgentState import from langchain.agents in template.py
- Update tests to use the new API
* fix:update the code with review comments
* fix: Add runtime parameter to compress_messages method(#803)
* fix: Add runtime parameter to compress_messages method(#803)
The compress_messages method was being called by PreModelHookMiddleware
with both state and runtime parameters, but only accepted state parameter.
This caused a TypeError when the middleware executed the pre_model_hook.
Added optional runtime parameter to compress_messages signature to match
the expected interface while maintaining backward compatibility.
* Update the code with the review comments
* fix: Refactor citation handling and add comprehensive tests for citation features
* refactor: Clean up imports and formatting across citation modules
* fix: Add monkeypatch to clear AGENT_RECURSION_LIMIT in recursion limit tests
* feat: Enhance citation link handling in Markdown component
* fix: Exclude citations from finish reason handling in mergeMessage function
* fix(nodes): update message handling
* fix(citations): improve citation extraction and handling in event processing
* feat(citations): enhance citation extraction and handling with improved merging and normalization
* fix(reporter): update citation formatting instructions for clarity and consistency
* fix(reporter): prioritize using Markdown tables for data presentation and comparison
---------
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: LoftyComet <1277173875@qq。>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* fix(config): Add support for MCP server configuration parameters
* refact: rename the sse_readtimeout to sse_read_timeout
* update the code with review comments
* update the MCP document for the latest change
This pull request adds support for custom HTTP headers to the MCP server configuration and ensures that these headers are properly validated and included when adding new MCP servers. The changes are primarily focused on extending the schema and data handling for MCP server metadata.
When NEXT_PUBLIC_API_URL is not explicitly configured, the frontend now
automatically detects the API URL based on the current page's hostname.
This allows accessing DeerFlow from other machines without rebuilding
the frontend.
- Add getBaseURL() helper with runtime window.location detection
- Use same protocol and hostname with default port 8000
- Preserve explicit NEXT_PUBLIC_API_URL configuration when set
- Fallback to localhost:8000 for SSR scenarios
* feat(eval): add report quality evaluation module
Addresses issue #773 - How to evaluate generated report quality objectively.
This module provides two evaluation approaches:
1. Automated metrics (no LLM required):
- Citation count and source diversity
- Word count compliance per report style
- Section structure validation
- Image inclusion tracking
2. LLM-as-Judge evaluation:
- Factual accuracy scoring
- Completeness assessment
- Coherence evaluation
- Relevance and citation quality checks
The combined evaluator provides a final score (1-10) and letter grade (A+ to F).
Files added:
- src/eval/__init__.py
- src/eval/metrics.py
- src/eval/llm_judge.py
- src/eval/evaluator.py
- tests/unit/eval/test_metrics.py
- tests/unit/eval/test_evaluator.py
* feat(eval): integrate report evaluation with web UI
This commit adds the web UI integration for the evaluation module:
Backend:
- Add EvaluateReportRequest/Response models in src/server/eval_request.py
- Add /api/report/evaluate endpoint to src/server/app.py
Frontend:
- Add evaluateReport API function in web/src/core/api/evaluate.ts
- Create EvaluationDialog component with grade badge, metrics display,
and optional LLM deep evaluation
- Add evaluation button (graduation cap icon) to research-block.tsx toolbar
- Add i18n translations for English and Chinese
The evaluation UI allows users to:
1. View quick metrics-only evaluation (instant)
2. Optionally run deep LLM-based evaluation for detailed analysis
3. See grade (A+ to F), score (1-10), and metric breakdown
* feat(eval): improve evaluation reliability and add LLM judge tests
- Extract MAX_REPORT_LENGTH constant in llm_judge.py for maintainability
- Add comprehensive unit tests for LLMJudge class (parse_response,
calculate_weighted_score, evaluate with mocked LLM)
- Pass reportStyle prop to EvaluationDialog for accurate evaluation criteria
- Add researchQueries store map to reliably associate queries with research
- Add getResearchQuery helper to retrieve query by researchId
- Remove unused imports in test_metrics.py
* fix(eval): use resolveServiceURL for evaluate API endpoint
The evaluateReport function was using a relative URL '/api/report/evaluate'
which sent requests to the Next.js server instead of the FastAPI backend.
Changed to use resolveServiceURL() consistent with other API functions.
* fix: improve type accuracy and React hooks in evaluation components
- Fix get_word_count_target return type from Optional[Dict] to Dict since it always returns a value via default fallback
- Fix useEffect dependency issue in EvaluationDialog using useRef to prevent unwanted re-evaluations
- Add aria-label to GradeBadge for screen reader accessibility
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>
Fixes#598
* fix: parsed json with extra tokens issue
* Added unit test for json.ts
* fix the json unit test running issue
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update the code with code review suggestion
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Willem Jiang <143703838+willem-bd@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
---------
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
---------
Co-authored-by: Henry Li <henry1943@163.com>
LoftyComet
Willem Jiang
Jiahe Wu
Qiyuan Jiao
jimmyuconn1982
HagonChan
Anoyer-lzh
CHANGXUBO
suntp
JeffJiang
Abeautifulsnow
johnny0120
DanielWalnut
Lan
Aeolusw
Henry Li
Li Xin