"""
Summarizer Agent Module
========================
Agent responsible for summarizing documents and content.
"""

from dataclasses import dataclass, field
from typing import Any
from .base import BaseAgent


@dataclass
class SummarizerAgent(BaseAgent):
    """
    Agent that summarizes documents and content.
    
    Takes a list of documents/text and produces a concise summary.
    """
    role: str = "summarizer"
    tools: list[str] = field(default_factory=lambda: ["text_analysis", "summarization"])
    
    async def run(self, input: dict[str, Any]) -> dict[str, Any]:
        """
        Summarize the provided documents.
        
        Args:
            input: Dictionary with 'documents' key containing list of documents to summarize
            
        Returns:
            Dictionary with summary
        """
        documents = input.get("documents", [])
        self.log(f"Summarizing {len(documents)} documents")
        
        summary = self._generate_summary(documents)
        
        return {
            "agent": "summarizer",
            "summary": summary,
            "document_count": len(documents)
        }
    
    def _generate_summary(self, documents: list[dict | str]) -> str:
        """
        Generate a summary from the provided documents.
        
        Args:
            documents: List of documents (can be dicts with 'snippet'/'text' or strings)
            
        Returns:
            Summary string
        """
        if not documents:
            return "No documents provided for summarization."
        
        # Extract text content from documents
        texts = []
        for doc in documents:
            if isinstance(doc, dict):
                # Try common text fields
                text = doc.get("snippet") or doc.get("text") or doc.get("content") or ""
                if doc.get("title"):
                    text = f"{doc['title']}: {text}"
                texts.append(text)
            elif isinstance(doc, str):
                texts.append(doc)
        
        # Generate summary (simplified - in production, use LLM)
        combined = " ".join(texts)
        
        # Create a simulated intelligent summary
        if len(combined) > 200:
            key_sentences = combined[:200] + "..."
        else:
            key_sentences = combined
            
        summary = (
            f"Summary of {len(documents)} documents: "
            f"{key_sentences} "
            f"[Analysis based on {len(combined)} characters of source text]"
        )
        
        return summary