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64 lines
3.7 KiB
Plaintext
64 lines
3.7 KiB
Plaintext
---
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title: Overview
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description: "Overview of all supported LLM providers in Mem0, including OpenAI, Anthropic, Groq, Ollama, and more."
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---
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Mem0 includes built-in support for various popular large language models. Memory can utilize the LLM provided by the user, ensuring efficient use for specific needs.
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## Usage
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To use an LLM, you must provide a configuration to customize its usage. If no configuration is supplied, a default configuration will be applied, and `OpenAI` will be used as the LLM.
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For a comprehensive list of available parameters for llm configuration, please refer to [Config](./config).
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## Supported LLMs
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See the list of supported LLMs below.
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<Note>
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All LLMs are supported in Python. The following LLMs are also supported in TypeScript: **OpenAI**, **Anthropic**, **AWS Bedrock**, **Groq**, **Azure OpenAI**, **DeepSeek**, **Google AI**, **Langchain**, **LM Studio**, **Mistral AI**, and **Ollama**.
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</Note>
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<CardGroup cols={4}>
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<Card title="OpenAI" icon="/images/provider-icons/openai.svg" href="/components/llms/models/openai" />
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<Card title="Ollama" icon="/images/provider-icons/ollama.svg" href="/components/llms/models/ollama" />
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<Card title="Azure OpenAI" icon="/images/provider-icons/azure-color.svg" href="/components/llms/models/azure_openai" />
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<Card title="Anthropic" icon="/images/provider-icons/anthropic.svg" href="/components/llms/models/anthropic" />
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<Card title="Together" icon="/images/provider-icons/together-color.svg" href="/components/llms/models/together" />
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<Card title="Groq" icon="/images/provider-icons/groq.svg" href="/components/llms/models/groq" />
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<Card title="Litellm" icon="shuffle" href="/components/llms/models/litellm" />
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<Card title="Mistral AI" icon="/images/provider-icons/mistral-color.svg" href="/components/llms/models/mistral_AI" />
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<Card title="Google AI" icon="/images/provider-icons/google-color.svg" href="/components/llms/models/google_AI" />
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<Card title="AWS bedrock" icon="/images/provider-icons/bedrock-color.svg" href="/components/llms/models/aws_bedrock" />
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<Card title="DeepSeek" icon="/images/provider-icons/deepseek-color.svg" href="/components/llms/models/deepseek" />
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<Card title="MiniMax" icon="/images/provider-icons/minimax-color.svg" href="/components/llms/models/minimax" />
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<Card title="xAI" icon="/images/provider-icons/xai.svg" href="/components/llms/models/xAI" />
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<Card title="Sarvam AI" icon="/images/provider-icons/sarvam.svg" href="/components/llms/models/sarvam" />
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<Card title="LM Studio" icon="/images/provider-icons/lmstudio.svg" href="/components/llms/models/lmstudio" />
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<Card title="Langchain" icon="/images/provider-icons/langchain-color.svg" href="/components/llms/models/langchain" />
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</CardGroup>
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## Structured vs Unstructured Outputs
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Mem0 supports two types of OpenAI LLM formats, each with its own strengths and use cases:
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### Structured Outputs
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Structured outputs are LLMs that align with OpenAI's structured outputs model:
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- **Optimized for:** Returning structured responses (e.g., JSON objects)
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- **Benefits:** Precise, easily parseable data
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- **Ideal for:** Data extraction, form filling, API responses
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- **Learn more:** [OpenAI Structured Outputs Guide](https://platform.openai.com/docs/guides/structured-outputs/introduction)
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### Unstructured Outputs
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Unstructured outputs correspond to OpenAI's standard, free-form text model:
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- **Flexibility:** Returns open-ended, natural language responses
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- **Customization:** Use the `response_format` parameter to guide output
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- **Trade-off:** Less efficient than structured outputs for specific data needs
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- **Best for:** Creative writing, explanations, general conversation
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Choose the format that best suits your application's requirements for optimal performance and usability.
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