Overview

Mem0 offers support for various embedding models, allowing users to choose the one that best suits their needs.

Supported Embedders

See the list of supported embedders below.

<Note> The following embedders are supported in the Python implementation. The TypeScript implementation currently only supports OpenAI. </Note> <CardGroup cols={4}> <Card title="OpenAI" href="/components/embedders/models/openai"></Card> <Card title="Azure OpenAI" href="/components/embedders/models/azure_openai"></Card> <Card title="Ollama" href="/components/embedders/models/ollama"></Card> <Card title="Hugging Face" href="/components/embedders/models/huggingface"></Card> <Card title="Google AI" href="/components/embedders/models/google_AI"></Card> <Card title="Vertex AI" href="/components/embedders/models/vertexai"></Card> <Card title="Together" href="/components/embedders/models/together"></Card> <Card title="LM Studio" href="/components/embedders/models/lmstudio"></Card> <Card title="Langchain" href="/components/embedders/models/langchain"></Card> <Card title="AWS Bedrock" href="/components/embedders/models/aws_bedrock"></Card> </CardGroup>

Usage

To utilize an embedding model, 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 embedding model.

For a comprehensive list of available parameters for embedding model configuration, please refer to Config.