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Ollama

LiteLLM supports all models from Ollama

Open In Colab

Pre-requisites​

Ensure you have your ollama server running

Example usage​

from litellm import completion

response = completion(
    model="ollama/llama2", 
    messages=[{ "content": "respond in 20 words. who are you?","role": "user"}], 
    api_base="http://localhost:11434"
)
print(response)

Example usage - Streaming​

from litellm import completion

response = completion(
    model="ollama/llama2", 
    messages=[{ "content": "respond in 20 words. who are you?","role": "user"}], 
    api_base="http://localhost:11434",
    stream=True
)
print(response)
for chunk in response:
    print(chunk['choices'][0]['delta'])

Example usage - Streaming + Acompletion​

Ensure you have async_generator installed for using ollama acompletion with streaming

pip install async_generator
async def async_ollama():
    response = await litellm.acompletion(
        model="ollama/llama2", 
        messages=[{ "content": "what's the weather" ,"role": "user"}], 
        api_base="http://localhost:11434", 
        stream=True
    )
    async for chunk in response:
        print(chunk)

# call async_ollama
import asyncio
asyncio.run(async_ollama())

Ollama Models​

Ollama supported models: https://github.com/jmorganca/ollama

Model NameFunction Call
Mistralcompletion(model='ollama/mistral', messages, api_base="http://localhost:11434", stream=True)
Llama2 7Bcompletion(model='ollama/llama2', messages, api_base="http://localhost:11434", stream=True)
Llama2 13Bcompletion(model='ollama/llama2:13b', messages, api_base="http://localhost:11434", stream=True)
Llama2 70Bcompletion(model='ollama/llama2:70b', messages, api_base="http://localhost:11434", stream=True)
Llama2 Uncensoredcompletion(model='ollama/llama2-uncensored', messages, api_base="http://localhost:11434", stream=True)
Code Llamacompletion(model='ollama/codellama', messages, api_base="http://localhost:11434", stream=True)
Llama2 Uncensoredcompletion(model='ollama/llama2-uncensored', messages, api_base="http://localhost:11434", stream=True)
Orca Minicompletion(model='ollama/orca-mini', messages, api_base="http://localhost:11434", stream=True)
Vicunacompletion(model='ollama/vicuna', messages, api_base="http://localhost:11434", stream=True)
Nous-Hermescompletion(model='ollama/nous-hermes', messages, api_base="http://localhost:11434", stream=True)
Nous-Hermes 13Bcompletion(model='ollama/nous-hermes:13b', messages, api_base="http://localhost:11434", stream=True)
Wizard Vicuna Uncensoredcompletion(model='ollama/wizard-vicuna', messages, api_base="http://localhost:11434", stream=True)

LiteLLM/Ollama Docker Image​

For Ollama LiteLLM Provides a Docker Image for an OpenAI API compatible server for local LLMs - llama2, mistral, codellama

Chat on WhatsApp Chat on Discord

An OpenAI API compatible server for local LLMs - llama2, mistral, codellama​

Quick Start:​

Docker Hub: https://hub.docker.com/repository/docker/litellm/ollama/general

docker pull litellm/ollama
docker run --name ollama litellm/ollama

Test the server container​

On the docker container run the test.py file using python3 test.py

Making a request to this server​

import openai

api_base = f"http://0.0.0.0:8000" # base url for server

openai.api_base = api_base
openai.api_key = "temp-key"
print(openai.api_base)


print(f'LiteLLM: response from proxy with streaming')
response = openai.ChatCompletion.create(
    model="ollama/llama2", 
    messages = [
        {
            "role": "user",
            "content": "this is a test request, acknowledge that you got it"
        }
    ],
    stream=True
)

for chunk in response:
    print(f'LiteLLM: streaming response from proxy {chunk}')

Responses from this server​

{
  "object": "chat.completion",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": " Hello! I acknowledge receipt of your test request. Please let me know if there's anything else I can assist you with.",
        "role": "assistant",
        "logprobs": null
      }
    }
  ],
  "id": "chatcmpl-403d5a85-2631-4233-92cb-01e6dffc3c39",
  "created": 1696992706.619709,
  "model": "ollama/llama2",
  "usage": {
    "prompt_tokens": 18,
    "completion_tokens": 25,
    "total_tokens": 43
  }
}

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