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Documentation Index

Fetch the complete documentation index at: https://docs.mem0.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Camel AI integration

Connect Camel’s agent framework to Mem0 so every agent can persist and recall conversation context across sessions with minimal setup.
Prerequisites
  • Mem0: MEM0_API_KEY (or self-hosted endpoint), pip install mem0ai
  • Camel AI: pip install camel-ai (requires Python 3.9+)
  • Optional: OpenAI API key if you run LLM-backed agents
Camel provides a Python SDK today. A TypeScript path is not available yet.

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Configure credentials

1

Export your API key

export MEM0_API_KEY="sk-..."
2

(Self-host) Point to your Mem0 API

export MEM0_BASE_URL="https://your-mem0-domain"
Mem0Storage reads MEM0_API_KEY automatically. Pass api_key explicitly only when you need to override the environment.

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Wire Mem0 into a Camel agent

1

Create a Mem0-backed memory store

import os
from camel.storages import Mem0Storage

mem0_store = Mem0Storage(
    api_key=os.environ.get("MEM0_API_KEY"),
    agent_id="travel_agent",
    user_id="alice",
    metadata={"source": "camel-demo"},
)
2

Attach it to Camel memory

from camel.memories import ChatHistoryMemory, ScoreBasedContextCreator
from camel.utils import OpenAITokenCounter
from camel.types import ModelType

memory = ChatHistoryMemory(
    context_creator=ScoreBasedContextCreator(
        token_counter=OpenAITokenCounter(ModelType.GPT_4O_MINI),
        token_limit=1024,
    ),
    storage=mem0_store,
    agent_id="travel_agent",
)
3

Let your agent read and write Mem0

from camel.agents import ChatAgent
from camel.messages import BaseMessage

agent = ChatAgent(
    system_message=BaseMessage.make_assistant_message(
        role_name="Agent",
        content="You are a helpful travel assistant. Reuse stored memories."
    )
)

agent.memory = memory

response = agent.step(
    BaseMessage.make_user_message(
        role_name="User",
        content="I prefer boutique hotels in Paris."
    )
)

print(response.msgs[0].content)
Run python camel_mem0_demo.py (or the snippet above in a REPL). You should see the agent respond and the memory persisted to Mem0. Re-running with a new prompt should include the stored preference.

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Verify the integration

  • Mem0 dashboard shows new memories under agent_id=travel_agent and user_id=alice.
  • mem0_store.load() returns the records you just wrote.
  • Camel agent replies reference prior user preferences on subsequent runs.

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Troubleshooting

  • Missing MEM0_API_KEY — set export MEM0_API_KEY="sk-..." or pass api_key into Mem0Storage.
  • No memories returned — ensure agent_id/user_id in your query match what you used when writing.
  • Network errors to Mem0 — if self-hosting, set MEM0_BASE_URL to your deployment URL.

Memory types in Mem0

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