A fork of the official Python client for Ollama for Home Assistant.
Project description
NOTE: This is a fork of the official Ollama Python library with loosened dependencies in order to make it compatible with Home Assistant.
Ollama Python Library
The Ollama Python library provides the easiest way to integrate Python 3.8+ projects with Ollama.
Install
pip install ollama
Usage
import ollama
response = ollama.chat(model='llama2', messages=[
{
'role': 'user',
'content': 'Why is the sky blue?',
},
])
print(response['message']['content'])
Streaming responses
Response streaming can be enabled by setting stream=True
, modifying function calls to return a Python generator where each part is an object in the stream.
import ollama
stream = ollama.chat(
model='llama2',
messages=[{'role': 'user', 'content': 'Why is the sky blue?'}],
stream=True,
)
for chunk in stream:
print(chunk['message']['content'], end='', flush=True)
API
The Ollama Python library's API is designed around the Ollama REST API
Chat
ollama.chat(model='llama2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
Generate
ollama.generate(model='llama2', prompt='Why is the sky blue?')
List
ollama.list()
Show
ollama.show('llama2')
Create
modelfile='''
FROM llama2
SYSTEM You are mario from super mario bros.
'''
ollama.create(model='example', modelfile=modelfile)
Copy
ollama.copy('llama2', 'user/llama2')
Delete
ollama.delete('llama2')
Pull
ollama.pull('llama2')
Push
ollama.push('user/llama2')
Embeddings
ollama.embeddings(model='llama2', prompt='They sky is blue because of rayleigh scattering')
Custom client
A custom client can be created with the following fields:
host
: The Ollama host to connect totimeout
: The timeout for requests
from ollama import Client
client = Client(host='http://localhost:11434')
response = client.chat(model='llama2', messages=[
{
'role': 'user',
'content': 'Why is the sky blue?',
},
])
Async 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())
Setting stream=True
modifies functions 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())
Errors
Errors are raised if requests return an error status or if an error is detected while streaming.
model = 'does-not-yet-exist'
try:
ollama.chat(model)
except ollama.ResponseError as e:
print('Error:', e.error)
if e.status_code == 404:
ollama.pull(model)
Project details
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