MemOS-MCP

from memos import log from memos.configs.embedder import EmbedderConfigFactory from memos.configs.graph_db import GraphDBConfigFactory from memos.embedders.factory import EmbedderFactory from memos.graph_dbs.factory import GraphStoreFactory from memos.memories.textual.item import TextualMemoryItem from memos.memories.textual.tree_text_memory.retrieve.recall import GraphMemoryRetriever from memos.memories.textual.tree_text_memory.retrieve.retrieval_mid_structs import ParsedTaskGoal logger = log.get_logger(__name__) embedder_config = EmbedderConfigFactory.model_validate( { "backend": "ollama", "config": { "model_name_or_path": "nomic-embed-text:latest", }, } ) embedder = EmbedderFactory.from_config(embedder_config) # Step 1: Prepare a mock ParsedTaskGoal parsed_goal = ParsedTaskGoal( memories=[ "Caroline's participation in the LGBTQ community", "Historical details of her membership", "Specific instances of Caroline's involvement in LGBTQ support groups", "Information about Caroline's activities in LGBTQ spaces", "Accounts of Caroline's role in promoting LGBTQ+ inclusivity", ], keys=["Family hiking experiences", "LGBTQ support group"], goal_type="retrieval", tags=["LGBTQ", "support group"], ) # Step 2: Initialize graph store graph_config = GraphDBConfigFactory( backend="neo4j", config={ "uri": "bolt://localhost:7687", "user": "neo4j", "password": "12345678", "db_name": "caroline", "auto_create": True, }, ) graph_store = GraphStoreFactory.from_config(graph_config) # Step 6: Create embedding for query query = "When did Caroline go to the LGBTQ support group?" query_embedding = embedder.embed([query])[0] # Step 7: Init memory retriever retriever = GraphMemoryRetriever(graph_store=graph_store, embedder=embedder) # Step 8: Run hybrid retrieval retrieved_items: list[TextualMemoryItem] = retriever.retrieve( query=query, parsed_goal=parsed_goal, top_k=10, memory_scope="LongTermMemory", query_embedding=[query_embedding], ) # Step 9: Print retrieved memory items print("\n=== Retrieved Memory Items ===") for item in retrieved_items: print(f"ID: {item.id}") print(f"Memory: {item.memory}")