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

src/tools/search_postprocessor.py

@@ -1,8 +1,8 @@
 # src/tools/search_postprocessor.py
-import re
 import base64
 import logging
-from typing import List, Dict, Any
+import re
+from typing import Any, Dict, List
 from urllib.parse import urlparse
 
 logger = logging.getLogger(__name__)

src/tools/tavily_search/tavily_search_api_wrapper.py

@@ -11,8 +11,9 @@ from langchain_tavily._utilities import TAVILY_API_URL
 from langchain_tavily.tavily_search import (
     TavilySearchAPIWrapper as OriginalTavilySearchAPIWrapper,
 )
-from src.tools.search_postprocessor import SearchResultPostProcessor
+
 from src.config import load_yaml_config
+from src.tools.search_postprocessor import SearchResultPostProcessor
 
 
 def get_search_config():