环境安装
mem0ai[graph] 安装
uv pip install "mem0ai[graph]"
docker 启动neo4j数据库
docker run \
-p 7474:7474 -p 7687:7687 \
-e NEO4J_AUTH=neo4j/password \
neo4j:5
模型配置
from dotenv import load_dotenv
import os
from openai import AsyncOpenAI
from agents import OpenAIChatCompletionsModel, set_tracing_disabled,Agent,Runner
load_dotenv()
QWEN_API_KEY = os.getenv("QWEN_API_KEY")
QWEN_BASE_URL = os.getenv("QWEN_BASE_URL")
QWEN_MODEL_NAME = os.getenv("QWEN_MODEL_NAME")
client = AsyncOpenAI(base_url=QWEN_BASE_URL, api_key=QWEN_API_KEY)
set_tracing_disabled(disabled=True)
qwen_model = OpenAIChatCompletionsModel(model=QWEN_MODEL_NAME, openai_client=client)
Memory配置
from mem0 import Memory
config = {
"embedder": {
"provider": "openai",
"config": {
"model": "text-embedding-v2",
"embedding_dims": 1536,
"api_key": QWEN_API_KEY,
"openai_base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1"
}
},
"graph_store": {
"provider": "neo4j",
"config": {
"url": "bolt://localhost:7687",
"username": "neo4j",
"password": "password",
},
},
"llm": {
"provider":"openai",
"config":{
"model": "qwen-plus",
"api_key": QWEN_API_KEY,
"openai_base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1"
},
},
}
memory = Memory.from_config(config_dict=config)
测试
import asyncio
async def chat_with_memories(message: str, user_id: str = "default_user") -> str:
# Retrieve relevant memories
relevant_memories = memory.search(query=message, user_id=user_id, limit=3)
memories_str = "\n".join(f"- {entry['memory']}" for entry in relevant_memories["results"])
# Generate Assistant response
system_prompt = f"You are a helpful AI. Answer the question based on query and memories.\nUser Memories:\n{memories_str}"
messages = [{"role": "system", "content": system_prompt}, {"role": "user", "content": message}]
agent = Agent(
name="Assistant",
instructions=system_prompt,
model=OpenAIChatCompletionsModel(model=QWEN_MODEL_NAME, openai_client=client)
)
assistant_response = await Runner.run(agent, message)
# Create new memories from the conversation
messages.append({"role": "assistant", "content": assistant_response.final_output})
memory.add(messages, user_id=user_id)
return assistant_response.final_output
async def run_example_conversations():
# Example 1: Simple greeting
print("=== Example 1: Simple Greeting ===")
response1 = await chat_with_memories("Hello, how are you? My name is Bob")
print(f"User: Hello, how are you?")
print(f"AI: {response1}\n")
# Example 2: Follow-up question
print("=== Example 2: Follow-up Question ===")
response2 = await chat_with_memories("What's my name?")
print(f"User: What's my name?")
print(f"AI: {response2}\n")
await run_example_conversations()
=== Example 1: Simple Greeting ===
User: Hello, how are you?
AI: Hello, Bob! I'm just a virtual assistant, so I don't have feelings, but I'm here and ready to help you with whatever you need. How can I assist you today?
=== Example 2: Follow-up Question ===
User: What's my name?
AI: Your name is Bob.