FastAPI Ollama Server

This project sets up a FastAPI server that interfaces with the Ollama HTTP server to generate text responses based on user prompts. The server supports API key authentication and allows users to interact with various machine learning models via HTTP requests.

Setup

1. Clone the repository:

   git clone <repository_url>
   cd <repository_directory>

2. Install dependencies:

   pip install -r requirements.txt

3. Set your environment variable for the API key:

   export API_KEY_OLLAMA_HTTP_SERVER=<your_api_key>

4. Start the server:

   uvicorn server:app --host 0.0.0.0 --port 8000

   The server will be available at http://localhost:8000.

API Documentation

The server exposes a POST endpoint:

POST /generate

Generates text based on the provided model and prompt.

Request Body:

{
  "model": "mistral",
  "prompt": "Tell me a joke"
}

Headers:

• X-API-Key: Your API key (required)

Responses:

• 200 OK: Successfully generated text.
• 400 Bad Request: If the model is invalid or other input is incorrect.
• 403 Forbidden: If the API key is invalid.
• 500 Internal Server Error: If there is an issue with the Ollama server.

Example Usage

Sending a Request

Using Python's requests library:

import requests
import os

API_KEY = os.environ.get("API_KEY_OLLAMA_HTTP_SERVER")
url = "http://localhost:8000/generate"
headers = {
    "Content-Type": "application/json",
    "X-API-Key": API_KEY
}
data = {
    "model": "mistral",
    "prompt": "Tell me a joke"
}

response = requests.post(url, json=data, headers=headers)

if response.status_code == 200:
    print("Response:", response.json()["response"])
else:
    print("Error:", response.status_code, response.text)

License

This project is licensed under the MIT License - see the LICENSE file for details.