| Name | ollama JSON |
| Version |
0.4.4
JSON |
| download |
| home_page | https://ollama.com |
| Summary | The official Python client for Ollama. |
| upload_time | 2024-12-08 03:39:17 |
| maintainer | None |
| docs_url | None |
| author | Ollama |
| requires_python | <4.0,>=3.8 |
| license | MIT |
| 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 llama3.2`
- 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='llama3.2', 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='llama3.2',
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='llama3.2', 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='llama3.2', 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='llama3.2', 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='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
```
### Generate
```python
ollama.generate(model='llama3.2', prompt='Why is the sky blue?')
```
### List
```python
ollama.list()
```
### Show
```python
ollama.show('llama3.2')
```
### Create
```python
modelfile='''
FROM llama3.2
SYSTEM You are mario from super mario bros.
'''
ollama.create(model='example', modelfile=modelfile)
```
### Copy
```python
ollama.copy('llama3.2', 'user/llama3.2')
```
### Delete
```python
ollama.delete('llama3.2')
```
### Pull
```python
ollama.pull('llama3.2')
```
### Push
```python
ollama.push('user/llama3.2')
```
### Embed
```python
ollama.embed(model='llama3.2', input='The sky is blue because of rayleigh scattering')
```
### Embed (batch)
```python
ollama.embed(model='llama3.2', 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)
```
Raw data
{
"_id": null,
"home_page": "https://ollama.com",
"name": "ollama",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.8",
"maintainer_email": null,
"keywords": null,
"author": "Ollama",
"author_email": "hello@ollama.com",
"download_url": "https://files.pythonhosted.org/packages/d8/55/af1d77457cbd4b0de93a6a0c4367de327c057ecfdd4efd19a428516b56d4/ollama-0.4.4.tar.gz",
"platform": null,
"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 llama3.2`\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='llama3.2', 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='llama3.2',\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='llama3.2', 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='llama3.2', 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='llama3.2', 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='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])\n```\n\n### Generate\n\n```python\nollama.generate(model='llama3.2', prompt='Why is the sky blue?')\n```\n\n### List\n\n```python\nollama.list()\n```\n\n### Show\n\n```python\nollama.show('llama3.2')\n```\n\n### Create\n\n```python\nmodelfile='''\nFROM llama3.2\nSYSTEM You are mario from super mario bros.\n'''\n\nollama.create(model='example', modelfile=modelfile)\n```\n\n### Copy\n\n```python\nollama.copy('llama3.2', 'user/llama3.2')\n```\n\n### Delete\n\n```python\nollama.delete('llama3.2')\n```\n\n### Pull\n\n```python\nollama.pull('llama3.2')\n```\n\n### Push\n\n```python\nollama.push('user/llama3.2')\n```\n\n### Embed\n\n```python\nollama.embed(model='llama3.2', input='The sky is blue because of rayleigh scattering')\n```\n\n### Embed (batch)\n\n```python\nollama.embed(model='llama3.2', 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\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "The official Python client for Ollama.",
"version": "0.4.4",
"project_urls": {
"Homepage": "https://ollama.com",
"Repository": "https://github.com/ollama/ollama-python"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "d301815774a30d0047d464add27e2824a5b1d02ea4ad021c83590cd753e5f511",
"md5": "224069e34638d613043fd1fb924a6bb4",
"sha256": "0f466e845e2205a1cbf5a2fef4640027b90beaa3b06c574426d8b6b17fd6e139"
},
"downloads": -1,
"filename": "ollama-0.4.4-py3-none-any.whl",
"has_sig": false,
"md5_digest": "224069e34638d613043fd1fb924a6bb4",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4.0,>=3.8",
"size": 13155,
"upload_time": "2024-12-08T03:39:14",
"upload_time_iso_8601": "2024-12-08T03:39:14.969028Z",
"url": "https://files.pythonhosted.org/packages/d3/01/815774a30d0047d464add27e2824a5b1d02ea4ad021c83590cd753e5f511/ollama-0.4.4-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "d855af1d77457cbd4b0de93a6a0c4367de327c057ecfdd4efd19a428516b56d4",
"md5": "7f218225f9a75f33ae03801a89616e73",
"sha256": "e1db064273c739babc2dde9ea84029c4a43415354741b6c50939ddd3dd0f7ffb"
},
"downloads": -1,
"filename": "ollama-0.4.4.tar.gz",
"has_sig": false,
"md5_digest": "7f218225f9a75f33ae03801a89616e73",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4.0,>=3.8",
"size": 13065,
"upload_time": "2024-12-08T03:39:17",
"upload_time_iso_8601": "2024-12-08T03:39:17.219285Z",
"url": "https://files.pythonhosted.org/packages/d8/55/af1d77457cbd4b0de93a6a0c4367de327c057ecfdd4efd19a428516b56d4/ollama-0.4.4.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-12-08 03:39:17",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "ollama",
"github_project": "ollama-python",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "ollama"
}
