feat: Add intelligent clarification feature in coordinate step for research queries (#613)

* 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

docs/configuration_guide.md

@@ -288,4 +288,47 @@ MILVUS_EMBEDDING_PROVIDER=openai
 MILVUS_EMBEDDING_BASE_URL=
 MILVUS_EMBEDDING_MODEL=
 MILVUS_EMBEDDING_API_KEY=
-```
+```
+
+---
+
+## Multi-Turn Clarification (Optional)
+
+An optional feature that helps clarify vague research questions through conversation. **Disabled by default.**
+
+### Enable via Command Line
+
+```bash
+# Enable clarification for vague questions
+uv run main.py "Research AI" --enable-clarification
+
+# Set custom maximum clarification rounds
+uv run main.py "Research AI" --enable-clarification --max-clarification-rounds 3
+
+# Interactive mode with clarification
+uv run main.py --interactive --enable-clarification --max-clarification-rounds 3
+```
+
+### Enable via API
+
+```json
+{
+  "messages": [{"role": "user", "content": "Research AI"}],
+  "enable_clarification": true,
+  "max_clarification_rounds": 3
+}
+```
+
+### Enable via UI Settings
+
+1. Open DeerFlow web interface
+2. Navigate to **Settings** → **General** tab
+3. Find **"Enable Clarification"** toggle
+4. Turn it **ON** to enable multi-turn clarification. Clarification is **disabled** by default. You need to manually enable it through any of the above methods. When clarification is enabled, you'll see **"Max Clarification Rounds"** field appear below the toggle
+6. Set the maximum number of clarification rounds (default: 3, minimum: 1)
+7. Click **Save** to apply changes
+
+**When enabled**, the Coordinator will ask up to the specified number of clarifying questions for vague topics before starting research, improving report relevance and depth. The `max_clarification_rounds` parameter controls how many rounds of clarification are allowed.
+
+
+**Note**: The `max_clarification_rounds` parameter only takes effect when `enable_clarification` is set to `true`. If clarification is disabled, this parameter is ignored.