ollama-embeddings

This repository contains a Dockerfile for running an embeddings model using Ollama on a local server.

Original README below:

---

How to run this:

1. build the Docker image from the Dockerfile:

docker build -t ollama-image

2. run a container from the image (exposes API to the world):

docker run -p 11434:11434 --name ollama-embeddings ollama-image

2.1 run a container from the image, accessible only from the server itself:

docker run -d -p 127.0.0.1:11434:11434 --name ollama-embeddings ollama-image

3. usage example (from within the server):

• curl:

curl http://127.0.0.1:11434/api/embeddings -d '{
  "model": "nomic-embed-text",
  "prompt": "The sky is blue because of Rayleigh scattering"
}'

• python:

import openai

client = openai.OpenAI(
    base_url="http://localhost:11434/v1",
    api_key="ollama",
)

def get_embedding(text: str, model: str = "nomic-embed-text") -> list[float]:
    return client.embeddings.create(input=[text], model=model).data[0].embedding

if __name__ == "__main__":
    text = "The sky is blue because of Rayleigh scattering"
    embedding = get_embedding(text)
    print(embedding)

4. (the simplest) usage example (with FastAPI): 4.1. start a new tmux session:

tmux new -s uvicorn_session

4.2 then run the following command (set a token in the app.py):

uvicorn app:app --reload --host 0.0.0.0 --port 11435

4.3 dettach from the session:

Ctrl + B, then D

4.4 reattach later:

tmux attach -t uvicorn_session