🧩 Embedding models
Overview
Embedchain supports several embedding models from the following providers:
OpenAI
To use OpenAI embedding function, you have to set the OPENAI_API_KEY environment variable. You can obtain the OpenAI API key from the OpenAI Platform.
Once you have obtained the key, you can use it like this:
- OpenAI announced two new embedding models:
text-embedding-3-smallandtext-embedding-3-large. Embedchain supports both these models. Below you can find YAML config for both:
Google AI
To use Google AI embedding function, you have to set the GOOGLE_API_KEY environment variable. You can obtain the Google API key from the Google Maker Suite
For more details regarding the Google AI embedding model, please refer to the Google AI documentation.
Azure OpenAI
To use Azure OpenAI embedding model, you have to set some of the azure openai related environment variables as given in the code block below:
You can find the list of models and deployment name on the Azure OpenAI Platform.
GPT4ALL
GPT4All supports generating high quality embeddings of arbitrary length documents of text using a CPU optimized contrastively trained Sentence Transformer.
Hugging Face
Hugging Face supports generating embeddings of arbitrary length documents of text using Sentence Transformer library. Example of how to generate embeddings using hugging face is given below:
Vertex AI
Embedchain supports Google’s VertexAI embeddings model through a simple interface. You just have to pass the model_name in the config yaml and it would work out of the box.
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