async def fetch_similar_memories(search_text: str):
        """
Search memories from vector database if conversation requires additional context.

Args:
- search_text : The string to embed and do vector similarity search
        """
        
        search_vector = (await generate_embeddings([search_text]))[0]
        memories = await search_memories(search_vector, 
                                         user_id=user_id)
        memories_str = [
            f"id={m_.id}\ntext={m_.text}\ncreated_at={m_.date}"
            for m_ in memories
        ]
        return {
            "memories": memories_str
        }