ollama-vertex-ai v0.2.0

ollama-vertex-ai

REST API proxy to Vertex AI with the interface of ollama. HTTP server for accessing Vertex AI via the REST API interface of ollama.

Synopsis

Get embeddings for a text:

❯ curl localhost:22434/api/embeddings -d '{
  "model": "textembedding-gecko@003",
  "prompt": "Half-orc is the best race for a barbarian."
}'

{ "embedding": [0.05424513295292854, -0.023687424138188362, ...] }

Setup

Make sure that you have installed Bun 1.1.17 or newer.

1. Download a JSON file with your Google account key from Google Project Console and save it to the current directory under the name google-account.json.
2. Optionally create a file model-defaults.json in the current directory to change the default model parameters.
3. Run the server:

❯ bunx ollama-vertex-ai

Listening on http://localhost:22434 ...

Configuring

The following properties from google-account.json are used:

{
  "project_id": "...",
  "private_key_id": "...",
  "private_key": "-----BEGIN PRIVATE KEY-----\n...\n-----END PRIVATE KEY-----\n",
  "client_email": "...",
  "scope": "https://www.googleapis.com/auth/cloud-platform", // optional, can be missing
  "auth_uri": "https://www.googleapis.com/oauth2/v4/token"   // optional, can be missing
}

Set the environment variable PORT to override the default port 22434.

Set the environment variable DEBUG to one or more strings separated by commas to customise logging on stderr. The default value is ovai when run on the command line and ovai:srv inside the Docker container.

Docker

For example, run a container for testing purposes with verbose logging, deleted on exit, exposing the port 22434:

docker run --rm -it -p 22434:22434 -e DEBUG=ovai,ovai:* \
  -v ${PWD}/google-account.json:/usr/src/app/google-account.json \
  ghcr.io/prantlf/ollama-vertex-ai

For example, run a container named ollama-vertex-ai in the background with custom defaults, exposing the port 22434:

docker run --rm -dt -p 22434:22434 --name ollama-vertex-ai \
  -v ${PWD}/google-account.json:/usr/src/app/google-account.json \
  -v ${PWD}/model-defaults.json:/usr/src/app/model-defaults.json \
  ghcr.io/prantlf/ollama-vertex-ai

And the same task as above, only using Docker Compose (place docker-compose.yml to the current directory) to make it easier:

docker-compose up -d

Building

Make sure that you have installed Bun 1.1.17 or newer.

git clone https://github.com/prantlf/ollama-vertex-ai.git
cd ollama-vertex-ai
bun i -y
bun run build
bun run test
bum start

Executing bum start will require the google-account.json file in the current directory.

API

See the original REST API documentation for details about the interface.

Embeddings

Creates a vector from the specified prompt. See the available embedding models.

❯ curl localhost:22434/api/embeddings -d '{
  "model": "textembedding-gecko@003",
  "prompt": "Half-orc is the best race for a barbarian."
}'

{ "embedding": [0.05424513295292854, -0.023687424138188362, ...] }

The returned vector of floats has 768 dimensions.

Text

Generates a text using the specified prompt. See the available bison text models and gemini chat models.

❯ curl localhost:22434/api/generate -d '{
  "model": "gemini-1.5-pro-preview-0409",
  "prompt": "Describe guilds from Dungeons and Dragons.",
  "stream": false
}'

{
  "model": "gemini-1.5-pro-preview-0409",
  "created_at": "2024-05-10T14:10:54.885Z",
  "response": {
    "role": "assistant",
    "content": "Guilds serve as organizations that bring together individuals with ..."
  },
  "done": true,
  "total_duration": 13884049373,
  "load_duration": 0,
  "prompt_eval_count": 7,
  "prompt_eval_duration: 3471012343,
  "eval_count: 557,
  "eval_duration: 10413037030
}

The property stream has to be always set to false, because the streaming mode isn't supported. The property options is optional with the following defaults:

"options": {
  "num_predict": 8192,
  "temperature": 1,
  "top_p": 0.95,
  "top_k": 40
}

Chat

Replies to a chat with the specified message history. See the available bison chat models and gemini chat models.

❯ curl localhost:22434/api/chat -d '{
  "model": "gemini-1.0-pro",
  "messages": [
    {
      "role": "system",
      "content": "You are an expert on Dungeons and Dragons."
    },
    {
      "role": "user",
      "content": "What race is the best for a barbarian?"
    }
  ],
  "stream": false
}'

{
  "model": "gemini-1.0-pro",
  "created_at": "2024-05-06T23:32:05.219Z",
  "message": {
    "role": "assistant",
    "content": "Half-Orcs are a strong and resilient race, making them ideal for barbarians. ..."
  },
  "done": true,
  "total_duration": 2325524053,
  "load_duration": 0,
  "prompt_eval_count": 9,
  "prompt_eval_duration: 581381013,
  "eval_count: 292,
  "eval_duration: 1744143040
}

The property stream has to be always set to false, because the streaming mode isn't supported. The property options is optional with the following defaults:

"options": {
  "num_predict": 8192,
  "temperature": 1,
  "top_p": 0.95,
  "top_k": 40
}

Ping

Checks that the server is running.

❯ curl -f localhost:22434/api/ping -X HEAD

Shutdown

Gracefully shuts down the HTTP server and exits the process.

❯ curl localhost:22434/api/shutdown -X POST

Contributing

In lieu of a formal styleguide, take care to maintain the existing coding style. Lint and test your code.

License

Copyright (C) 2024 Ferdinand Prantl

Licensed under the MIT License.