Method retrieve

src/agent/context.py:1058–1115

Retrieve similar agents using FAISS similarity search. Args: query: Query string to search for k: Number of results to return (default: 4) Returns: List of dictionaries containing agent information with similarity scores

(self, query: str, k: int = 4)

        return contract_text
    
    async def retrieve(self, query: str, k: int = 4) -> List[Dict[str, Any]]:
        """Retrieve similar agents using FAISS similarity search.
        
        Args:
            query: Query string to search for
            k: Number of results to return (default: 4)
            
        Returns:
            List of dictionaries containing agent information with similarity scores
        """
        if self._faiss_service is None:
            logger.warning("| ⚠️ FAISS service not initialized, cannot retrieve agents")
            return []
        
        try:
            from src.environment.faiss.types import FaissSearchRequest
            
            request = FaissSearchRequest(
                query=query,
                k=k,
                fetch_k=k * 5  # Fetch more candidates before filtering
            )
            
            result = await self._faiss_service.search_similar(request)
            
            if not result.success:
                logger.warning(f"| ⚠️ FAISS search failed: {result.message}")
                return []
            
            # Extract documents and scores from result
            documents = []
            if result.extra and "documents" in result.extra:
                docs = result.extra["documents"]
                scores = result.extra.get("scores", [])
                
                for doc, score in zip(docs, scores):
                    # Extract agent name from metadata
                    metadata = doc.get("metadata", {}) if isinstance(doc, dict) else {}
                    agent_name = metadata.get("name", "")
                    
                    # Get agent config if available
                    agent_config = None
                    if agent_name and agent_name in self._agent_configs:
                        agent_config = self._agent_configs[agent_name]
                    
                    documents.append({
                        "name": agent_name,
                        "description": metadata.get("description", ""),
                        "score": float(score),
                        "content": doc.get("page_content", "") if isinstance(doc, dict) else str(doc),
                        "config": agent_config.model_dump() if agent_config else None
                    })
            
            return documents
            
        except Exception as e:
            logger.error(f"| ❌ Error retrieving agents: {e}")
            return []