---
title: LangChain
---

Mem0 supports LangChain as a provider to access a wide range of LLM models. LangChain is a framework for developing applications powered by language models, making it easy to integrate various LLM providers through a consistent interface.

For a complete list of available chat models supported by LangChain, refer to the [LangChain Chat Models documentation](https://python.langchain.com/docs/integrations/chat).

## Usage

<CodeGroup>
```python Python
import os
from mem0 import Memory

# Set necessary environment variables for your chosen LangChain provider
# For example, if using OpenAI through LangChain:
os.environ["OPENAI_API_KEY"] = "your-api-key"

config = {
    "llm": {
        "provider": "langchain",
        "config": {
            "langchain_provider": "OpenAI",
            "model": "gpt-4o",
            "temperature": 0.2,
            "max_tokens": 2000,
        }
    }
}

m = Memory.from_config(config)
messages = [
    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
    {"role": "assistant", "content": "How about a thriller movies? They can be quite engaging."},
    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
]
m.add(messages, user_id="alice", metadata={"category": "movies"})
```
</CodeGroup>

## Supported LangChain Providers

LangChain supports a wide range of LLM providers, including:

- OpenAI (`ChatOpenAI`)
- Anthropic (`ChatAnthropic`)
- Google (`ChatGoogleGenerativeAI`, `ChatGooglePalm`)
- Mistral (`ChatMistralAI`)
- Ollama (`ChatOllama`)
- Azure OpenAI (`AzureChatOpenAI`)
- HuggingFace (`HuggingFaceChatEndpoint`)
- And many more

You can specify any supported provider in the `langchain_provider` parameter. For a complete and up-to-date list of available providers, refer to the [LangChain Chat Models documentation](https://python.langchain.com/docs/integrations/chat).

## Provider-Specific Configuration

When using LangChain as a provider, you'll need to:

1. Set the appropriate environment variables for your chosen LLM provider
2. Specify the LangChain provider class name in the `langchain_provider` parameter
3. Include any additional configuration parameters required by the specific provider

<Note>
  Make sure to install the necessary LangChain packages and any provider-specific dependencies.
</Note>

## Config

All available parameters for the `langchain` config are present in [Master List of All Params in Config](../config).