"""Clarification agent for gap detection and follow-up question generation."""

from pydantic import BaseModel, Field

from haiku.rag.research.base import BaseResearchAgent


class ClarificationResult(BaseModel):
    """Result of clarification analysis."""

    information_gaps: list[str] = Field(
        description="Specific missing information identified"
    )
    follow_up_questions: list[str] = Field(
        description="Questions to ask to fill the gaps"
    )
    suggested_searches: list[str] = Field(
        description="Recommended search queries for deeper investigation"
    )
    completeness_assessment: str = Field(
        description="Overall assessment of research completeness"
    )
    priority_areas: list[str] = Field(
        description="Most important areas to investigate next"
    )


class ClarificationAgent(BaseResearchAgent):
    """Agent specialized in identifying gaps and generating follow-up questions."""

    def __init__(self, provider: str, model: str):
        super().__init__(provider, model, output_type=ClarificationResult)

    def get_system_prompt(self) -> str:
        return """You are a clarification specialist agent focused on research completeness and quality.

        Your role is to:
        1. Critically evaluate what information has been gathered
        2. Identify what crucial information is still missing
        3. Detect contradictions or inconsistencies that need resolution
        4. Generate targeted follow-up questions to fill knowledge gaps
        5. Suggest specific search queries for deeper investigation
        6. Assess the overall completeness of the research

        Be thorough and critical in your evaluation. Consider:
        - What questions remain unanswered?
        - What assumptions need verification?
        - What contradictions need resolution?
        - What perspectives are missing?
        - What details would strengthen the understanding?

        Your goal is to ensure comprehensive, accurate, and complete research."""

    def register_tools(self) -> None:
        """Register clarification-specific tools."""
        # The agent will use its LLM capabilities directly for gap analysis
        # The structured output will guide the clarification process
        pass