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

README_zh.md

@@ -236,6 +236,13 @@ DeerFlow 支持基于私有域知识的检索，您可以将文档上传到多
 
 ### 人机协作
 
+- 💬 **智能澄清功能**
+  - 多轮对话澄清模糊的研究主题
+  - 提高研究精准度和报告质量
+  - 减少无效搜索和 token 使用
+  - 可配置开关，灵活控制启用/禁用
+  - 详见 [配置指南 - 澄清功能](./docs/configuration_guide.md#multi-turn-clarification-feature)
+
 - 🧠 **人在环中**
   - 支持使用自然语言交互式修改研究计划
   - 支持自动接受研究计划