| Name | ollama JSON |
| Version |
0.5.4
JSON |
| download |
| home_page | None |
| Summary | The official Python client for Ollama. |
| upload_time | 2025-09-16 00:25:25 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Ollama Python Library
The Ollama Python library provides the easiest way to integrate Python 3.8+ projects with [Ollama](https://github.com/ollama/ollama).
## Prerequisites
- [Ollama](https://ollama.com/download) should be installed and running
- Pull a model to use with the library: `ollama pull <model>` e.g. `ollama pull gemma3`
- See [Ollama.com](https://ollama.com/search) for more information on the models available.
## Install
```sh
pip install ollama
```
## Usage
```python
from ollama import chat
from ollama import ChatResponse
response: ChatResponse = chat(model='gemma3', messages=[
{
'role': 'user',
'content': 'Why is the sky blue?',
},
])
print(response['message']['content'])
# or access fields directly from the response object
print(response.message.content)
```
See [_types.py](ollama/_types.py) for more information on the response types.
## Streaming responses
Response streaming can be enabled by setting `stream=True`.
```python
from ollama import chat
stream = chat(
model='gemma3',
messages=[{'role': 'user', 'content': 'Why is the sky blue?'}],
stream=True,
)
for chunk in stream:
print(chunk['message']['content'], end='', flush=True)
```
## Custom client
A custom client can be created by instantiating `Client` or `AsyncClient` from `ollama`.
All extra keyword arguments are passed into the [`httpx.Client`](https://www.python-httpx.org/api/#client).
```python
from ollama import Client
client = Client(
host='http://localhost:11434',
headers={'x-some-header': 'some-value'}
)
response = client.chat(model='gemma3', messages=[
{
'role': 'user',
'content': 'Why is the sky blue?',
},
])
```
## Async client
The `AsyncClient` class is used to make asynchronous requests. It can be configured with the same fields as the `Client` class.
```python
import asyncio
from ollama import AsyncClient
async def chat():
message = {'role': 'user', 'content': 'Why is the sky blue?'}
response = await AsyncClient().chat(model='gemma3', messages=[message])
asyncio.run(chat())
```
Setting `stream=True` modifies functions to return a Python asynchronous generator:
```python
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='gemma3', messages=[message], stream=True):
print(part['message']['content'], end='', flush=True)
asyncio.run(chat())
```
## API
The Ollama Python library's API is designed around the [Ollama REST API](https://github.com/ollama/ollama/blob/main/docs/api.md)
### Chat
```python
ollama.chat(model='gemma3', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
```
### Generate
```python
ollama.generate(model='gemma3', prompt='Why is the sky blue?')
```
### List
```python
ollama.list()
```
### Show
```python
ollama.show('gemma3')
```
### Create
```python
ollama.create(model='example', from_='gemma3', system="You are Mario from Super Mario Bros.")
```
### Copy
```python
ollama.copy('gemma3', 'user/gemma3')
```
### Delete
```python
ollama.delete('gemma3')
```
### Pull
```python
ollama.pull('gemma3')
```
### Push
```python
ollama.push('user/gemma3')
```
### Embed
```python
ollama.embed(model='gemma3', input='The sky is blue because of rayleigh scattering')
```
### Embed (batch)
```python
ollama.embed(model='gemma3', input=['The sky is blue because of rayleigh scattering', 'Grass is green because of chlorophyll'])
```
### Ps
```python
ollama.ps()
```
## Errors
Errors are raised if requests return an error status or if an error is detected while streaming.
```python
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)
```
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"description": "# Ollama Python Library\n\nThe Ollama Python library provides the easiest way to integrate Python 3.8+ projects with [Ollama](https://github.com/ollama/ollama).\n\n## Prerequisites\n\n- [Ollama](https://ollama.com/download) should be installed and running\n- Pull a model to use with the library: `ollama pull <model>` e.g. `ollama pull gemma3`\n - See [Ollama.com](https://ollama.com/search) for more information on the models available.\n\n## Install\n\n```sh\npip install ollama\n```\n\n## Usage\n\n```python\nfrom ollama import chat\nfrom ollama import ChatResponse\n\nresponse: ChatResponse = chat(model='gemma3', messages=[\n {\n 'role': 'user',\n 'content': 'Why is the sky blue?',\n },\n])\nprint(response['message']['content'])\n# or access fields directly from the response object\nprint(response.message.content)\n```\n\nSee [_types.py](ollama/_types.py) for more information on the response types.\n\n## Streaming responses\n\nResponse streaming can be enabled by setting `stream=True`.\n\n```python\nfrom ollama import chat\n\nstream = chat(\n model='gemma3',\n messages=[{'role': 'user', 'content': 'Why is the sky blue?'}],\n stream=True,\n)\n\nfor chunk in stream:\n print(chunk['message']['content'], end='', flush=True)\n```\n\n## Custom client\nA custom client can be created by instantiating `Client` or `AsyncClient` from `ollama`.\n\nAll extra keyword arguments are passed into the [`httpx.Client`](https://www.python-httpx.org/api/#client).\n\n```python\nfrom ollama import Client\nclient = Client(\n host='http://localhost:11434',\n headers={'x-some-header': 'some-value'}\n)\nresponse = client.chat(model='gemma3', messages=[\n {\n 'role': 'user',\n 'content': 'Why is the sky blue?',\n },\n])\n```\n\n## Async client\n\nThe `AsyncClient` class is used to make asynchronous requests. It can be configured with the same fields as the `Client` class.\n\n```python\nimport asyncio\nfrom ollama import AsyncClient\n\nasync def chat():\n message = {'role': 'user', 'content': 'Why is the sky blue?'}\n response = await AsyncClient().chat(model='gemma3', messages=[message])\n\nasyncio.run(chat())\n```\n\nSetting `stream=True` modifies functions to return a Python asynchronous generator:\n\n```python\nimport asyncio\nfrom ollama import AsyncClient\n\nasync def chat():\n message = {'role': 'user', 'content': 'Why is the sky blue?'}\n async for part in await AsyncClient().chat(model='gemma3', messages=[message], stream=True):\n print(part['message']['content'], end='', flush=True)\n\nasyncio.run(chat())\n```\n\n## API\n\nThe Ollama Python library's API is designed around the [Ollama REST API](https://github.com/ollama/ollama/blob/main/docs/api.md)\n\n### Chat\n\n```python\nollama.chat(model='gemma3', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])\n```\n\n### Generate\n\n```python\nollama.generate(model='gemma3', prompt='Why is the sky blue?')\n```\n\n### List\n\n```python\nollama.list()\n```\n\n### Show\n\n```python\nollama.show('gemma3')\n```\n\n### Create\n\n```python\nollama.create(model='example', from_='gemma3', system=\"You are Mario from Super Mario Bros.\")\n```\n\n### Copy\n\n```python\nollama.copy('gemma3', 'user/gemma3')\n```\n\n### Delete\n\n```python\nollama.delete('gemma3')\n```\n\n### Pull\n\n```python\nollama.pull('gemma3')\n```\n\n### Push\n\n```python\nollama.push('user/gemma3')\n```\n\n### Embed\n\n```python\nollama.embed(model='gemma3', input='The sky is blue because of rayleigh scattering')\n```\n\n### Embed (batch)\n\n```python\nollama.embed(model='gemma3', input=['The sky is blue because of rayleigh scattering', 'Grass is green because of chlorophyll'])\n```\n\n### Ps\n\n```python\nollama.ps()\n```\n\n\n## Errors\n\nErrors are raised if requests return an error status or if an error is detected while streaming.\n\n```python\nmodel = 'does-not-yet-exist'\n\ntry:\n ollama.chat(model)\nexcept ollama.ResponseError as e:\n print('Error:', e.error)\n if e.status_code == 404:\n ollama.pull(model)\n```\n",
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