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2510cc61de
* 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
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
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# SPDX-License-Identifier: MIT
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from langgraph.graph import MessagesState
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from src.prompts.planner_model import Plan
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from src.rag import Resource
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class State(MessagesState):
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"""State for the agent system, extends MessagesState with next field."""
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# Runtime Variables
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locale: str = "en-US"
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research_topic: str = ""
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observations: list[str] = []
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resources: list[Resource] = []
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plan_iterations: int = 0
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current_plan: Plan | str = None
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final_report: str = ""
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auto_accepted_plan: bool = False
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enable_background_investigation: bool = True
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background_investigation_results: str = None
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# Clarification state tracking (disabled by default)
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enable_clarification: bool = (
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False # Enable/disable clarification feature (default: False)
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)
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clarification_rounds: int = 0
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clarification_history: list[str] = []
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is_clarification_complete: bool = False
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clarified_question: str = ""
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max_clarification_rounds: int = (
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3 # Default: 3 rounds (only used when enable_clarification=True)
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)
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# Workflow control
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goto: str = "planner" # Default next node
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