# 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.

## Configure credentials

1. Export your API key

```bash
export MEM0_API_KEY="sk-..."
```

2. (Self-host) Point to your Mem0 API

```bash
export MEM0_BASE_URL="https://your-mem0-domain"
```

3. Install Camel with Mem0 dependency

```bash
pip install "camel-ai>=0.2.0" mem0ai
```

4. (Optional) Add your model credentials

```bash
export OPENAI_API_KEY="sk-openai..."
```

Mem0Storage reads `MEM0_API_KEY` automatically. Pass `api_key` explicitly only when you need to override the environment.

## Wire Mem0 into a Camel agent

1. Create a Mem0-backed memory store

```python
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

```python
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

```python
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.

## 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.

## 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.