This project provides an implementation of API clients for fetching embeddings from various LLM providers.

Currently supported APIs:

• OpenAI
• Cohere
• Google Vertex
• VoyageAI
• Ollama
• AWS Bedrock

You can find sample programs that demonstrate how to use the client packages to fetch the embeddings in cmd directory of this project.

Finally, the document package provides an implementation of simple document text splitters, heavily inspired by the popular Langchain framework. It's essentially a Go rewrite of character and recursive character text splitters from the Langchain framework with minor modifications, but more or less identical results.

Here's a list of the env vars for each supported client

• OPENAI_API_KEY: Open AI API token

• COHERE_API_KEY: Cohere API token

• VERTEXAI_TOKEN: Google Vertex AI API token (can be fetch by gcloud auth print-access-token once you've authenticated)
• VERTEXAI_MODEL_ID: Embeddings model (at the moment only textembedding-gecko@00 or multimodalembedding@001 are available)
• GOOGLE_PROJECT_ID: Google Project ID
• VOYAGE_API_KEY: VoyageAI API key

• VOYAGE_API_KEY: Voyage AI API key

• AWS_REGION: AWS region

Usual AWS env vars as read by the AWS SDKs i.e. AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, etc.

The project provides a simple nix flake tha leverages gomod2nix for consistent Go environments and builds.

To get started just run

nix develop

And you'll be dropped into development shell.

In addition, each command is exposed as a nix app so you can run them as follows:

nix run ".#vertexai" -- -help

NOTE: gomod2nix vendors dependencies into nix store so every time you add a new dependency you must run gomod2nix generate that updates gomod2nix.toml

Yes please!