## Supported Embedders

See the list of supported embedders below.

All embedders listed below are supported in the Python implementation. The TypeScript implementation supports: **OpenAI**, **Azure OpenAI**, **AWS Bedrock**, **FastEmbed**, **Google AI**, **Hugging Face**, **Langchain**, **LM Studio**, **Ollama**, **Together**, and **Vertex AI**.

**[OpenAI](https://docs.mem0.ai/components/embedders/models/openai)**  
 **[Azure OpenAI](https://docs.mem0.ai/components/embedders/models/azure_openai)**  
 **[Ollama](https://docs.mem0.ai/components/embedders/models/ollama)**  
 **[Hugging Face](https://docs.mem0.ai/components/embedders/models/huggingface)**  
 **[Google AI](https://docs.mem0.ai/components/embedders/models/google_AI)**  
 **[Vertex AI](https://docs.mem0.ai/components/embedders/models/vertexai)**  
 **[Together](https://docs.mem0.ai/components/embedders/models/together)**  
 **[LM Studio](https://docs.mem0.ai/components/embedders/models/lmstudio)**  
 **[Langchain](https://docs.mem0.ai/components/embedders/models/langchain)**  
 **[AWS Bedrock](https://docs.mem0.ai/components/embedders/models/aws_bedrock)**  
 **[FastEmbed](https://docs.mem0.ai/components/embedders/models/fastembed)**

## 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](https://docs.mem0.ai/components/embedders/config).