ollama-python/README.md

Ollama Python Library

The Ollama Python library provides the easiest way to integrate your Python 3 project with Ollama.

Getting Started

Requires Python 3.8 or higher.

pip install ollama

A global default client is provided for convenience and can be used in the same way as the synchronous client.

import ollama
response = ollama.chat(model='llama2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])

import ollama
message = {'role': 'user', 'content': 'Why is the sky blue?'}
for part in ollama.chat(model='llama2', messages=[message], stream=True):
  print(part['message']['content'], end='', flush=True)

Using the Synchronous Client

from ollama import Client
message = {'role': 'user', 'content': 'Why is the sky blue?'}
response = Client().chat(model='llama2', messages=[message])

Response streaming can be enabled by setting stream=True. This modifies the function to return a Python generator where each part is an object in the stream.

from ollama import Client
message = {'role': 'user', 'content': 'Why is the sky blue?'}
for part in Client().chat(model='llama2', messages=[message], stream=True):
  print(part['message']['content'], end='', flush=True)

Using the Asynchronous Client

import asyncio
from ollama import AsyncClient

async def chat():
  message = {'role': 'user', 'content': 'Why is the sky blue?'}
  response = await AsyncClient().chat(model='llama2', messages=[message])

asyncio.run(chat())

Similar to the synchronous client, setting stream=True modifies the function to return a Python asynchronous generator.

import asyncio
from ollama import AsyncClient

async def chat():
  message = {'role': 'user', 'content': 'Why is the sky blue?'}
  async for part in await AsyncClient().chat(model='llama2', messages=[message], stream=True):
    print(part['message']['content'], end='', flush=True)

asyncio.run(chat())