from typing import List, Dict, Any
from sqlmodel import select
# Assuming MemoryRecord is accessible or passed, simulating direct pgvector call

class RAGTool:
    def __init__(self, async_session_maker):
        self.async_session_maker = async_session_maker

    async def get_embedding(self, query: str) -> List[float]:
        # Simulated embedding logic; in reality, this would call an embedding API
        return [0.1] * 1536

    async def retrieve(self, query: str, limit: int = 5) -> List[Dict[str, Any]]:
        embedding = await self.get_embedding(query)
        # We simulate the retrieve_memory call logic from MemoryRAG here
        # Normally you would inject MemoryRAG or a repository, doing a simplistic return here
        return [{"query": query, "simulated_results": f"Found results for {query} with vector {embedding[:2]}..."}]