This commit addresses issue #682 by providing clear documentation on how to view complete model output and debug DeerFlow workflows. Changes: - Add new DEBUGGING.md guide with detailed instructions for: - Viewing complete model output - Enabling debug logging - Configuring LangChain verbose logging - Setting up LangSmith tracing - Docker Compose debugging tips - Common troubleshooting scenarios - Update .env.example with: - Clearer comments for DEBUG setting - Documentation for LANGCHAIN_VERBOSE and LANGCHAIN_DEBUG options - Improved LangSmith configuration guidance - Enhance docs/FAQ.md with: - How to view complete model output - How to enable debug logging - How to troubleshoot common issues - Links to the new debugging guide These documentation improvements make it easier for users to: - Debug workflow issues - View LLM prompts and responses - Troubleshoot deployment problems - Monitor performance with LangSmith Fixes #682
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FAQ
Table of Contents
- Where's the name DeerFlow come from?
- Which models does DeerFlow support?
- How do I view complete model output?
- How do I enable debug logging?
- How do I troubleshoot issues?
Where's the name DeerFlow come from?
DeerFlow is short for Deep Exploration and Efficient Research Flow. It is named after the deer, which is a symbol of gentleness and elegance. We hope DeerFlow can bring a gentle and elegant deep research experience to you.
Which models does DeerFlow support?
Please refer to the Configuration Guide for more details.
How do I view complete model output?
If you want to see the complete model output, including system prompts, tool calls, and LLM responses:
-
Enable debug logging by setting
DEBUG=Truein your.envfile -
Enable LangChain verbose logging by adding these to your
.env:LANGCHAIN_VERBOSE=true LANGCHAIN_DEBUG=true -
Use LangSmith tracing for visual debugging (recommended for production):
LANGSMITH_TRACING=true LANGSMITH_API_KEY="your-api-key" LANGSMITH_PROJECT="your-project-name"
For detailed instructions, see the Debugging Guide.
How do I enable debug logging?
To enable debug logging:
- Open your
.envfile - Set
DEBUG=True - Restart your application
For Docker Compose:
docker compose restart
For development:
uv run main.py
You'll now see detailed logs including:
- System prompts sent to LLMs
- Model responses
- Tool execution details
- Workflow state transitions
See the Debugging Guide for more options.
How do I troubleshoot issues?
When encountering issues:
- Check the logs: Enable debug logging as described above
- Review configuration: Ensure your
.envandconf.yamlare correct - Check existing issues: Search GitHub Issues for similar problems
- Enable verbose logging: Use
LANGCHAIN_VERBOSE=truefor detailed output - Use LangSmith: For visual debugging, enable LangSmith tracing
For Docker-specific issues:
# View logs
docker compose logs -f
# Check container status
docker compose ps
# Restart services
docker compose restart
For more detailed troubleshooting steps, see the Debugging Guide.