docs: add comprehensive debugging guide and improve troubleshooting documentation (#688)

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

docs/FAQ.md

@@ -3,8 +3,10 @@
 ## Table of Contents
 
 - [Where's the name DeerFlow come from?](#wheres-the-name-deerflow-come-from)
-
 - [Which models does DeerFlow support?](#which-models-does-deerflow-support)
+- [How do I view complete model output?](#how-do-i-view-complete-model-output)
+- [How do I enable debug logging?](#how-do-i-enable-debug-logging)
+- [How do I troubleshoot issues?](#how-do-i-troubleshoot-issues)
 
 ## Where's the name DeerFlow come from?
 
@@ -13,3 +15,80 @@ DeerFlow is short for **D**eep **E**xploration and **E**fficient **R**esearch **
 ## Which models does DeerFlow support?
 
 Please refer to the [Configuration Guide](configuration_guide.md) 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:
+
+1. **Enable debug logging** by setting `DEBUG=True` in your `.env` file
+
+2. **Enable LangChain verbose logging** by adding these to your `.env`:
+
+   ```bash
+   LANGCHAIN_VERBOSE=true
+   LANGCHAIN_DEBUG=true
+   ```
+
+3. **Use LangSmith tracing** for visual debugging (recommended for production):
+
+   ```bash
+   LANGSMITH_TRACING=true
+   LANGSMITH_API_KEY="your-api-key"
+   LANGSMITH_PROJECT="your-project-name"
+   ```
+
+For detailed instructions, see the [Debugging Guide](DEBUGGING.md).
+
+## How do I enable debug logging?
+
+To enable debug logging:
+
+1. Open your `.env` file
+2. Set `DEBUG=True`
+3. Restart your application
+
+For Docker Compose:
+
+```bash
+docker compose restart
+```
+
+For development:
+
+```bash
+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](DEBUGGING.md) for more options.
+
+## How do I troubleshoot issues?
+
+When encountering issues:
+
+1. **Check the logs**: Enable debug logging as described above
+2. **Review configuration**: Ensure your `.env` and `conf.yaml` are correct
+3. **Check existing issues**: Search [GitHub Issues](https://github.com/bytedance/deer-flow/issues) for similar problems
+4. **Enable verbose logging**: Use `LANGCHAIN_VERBOSE=true` for detailed output
+5. **Use LangSmith**: For visual debugging, enable LangSmith tracing
+
+For Docker-specific issues:
+
+```bash
+# 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](DEBUGGING.md).