| Name | ollama JSON |
| Version |
0.1.9
JSON |
| download |
| home_page | https://ollama.ai |
| Summary | The official Python client for Ollama. |
| upload_time | 2024-04-26 00:13:33 |
| 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/jmorganca/ollama).
## Install
```sh
pip install ollama
```
## Usage
```python
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.
```python
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](https://github.com/jmorganca/ollama/blob/main/docs/api.md)
### Chat
```python
ollama.chat(model='llama2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
```
### Generate
```python
ollama.generate(model='llama2', prompt='Why is the sky blue?')
```
### List
```python
ollama.list()
```
### Show
```python
ollama.show('llama2')
```
### Create
```python
modelfile='''
FROM llama2
SYSTEM You are mario from super mario bros.
'''
ollama.create(model='example', modelfile=modelfile)
```
### Copy
```python
ollama.copy('llama2', 'user/llama2')
```
### Delete
```python
ollama.delete('llama2')
```
### Pull
```python
ollama.pull('llama2')
```
### Push
```python
ollama.push('user/llama2')
```
### Embeddings
```python
ollama.embeddings(model='llama2', prompt='The 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 to
- `timeout`: The timeout for requests
```python
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
```python
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:
```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='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.
```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/jmorganca/ollama).\n\n## Install\n\n```sh\npip install ollama\n```\n\n## Usage\n\n```python\nimport ollama\nresponse = ollama.chat(model='llama2', messages=[\n {\n 'role': 'user',\n 'content': 'Why is the sky blue?',\n },\n])\nprint(response['message']['content'])\n```\n\n## Streaming responses\n\nResponse 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.\n\n```python\nimport ollama\n\nstream = ollama.chat(\n model='llama2',\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## API\n\nThe Ollama Python library's API is designed around the [Ollama REST API](https://github.com/jmorganca/ollama/blob/main/docs/api.md)\n\n### Chat\n\n```python\nollama.chat(model='llama2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])\n```\n\n### Generate\n\n```python\nollama.generate(model='llama2', prompt='Why is the sky blue?')\n```\n\n### List\n\n```python\nollama.list()\n```\n\n### Show\n\n```python\nollama.show('llama2')\n```\n\n### Create\n\n```python\nmodelfile='''\nFROM llama2\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('llama2', 'user/llama2')\n```\n\n### Delete\n\n```python\nollama.delete('llama2')\n```\n\n### Pull\n\n```python\nollama.pull('llama2')\n```\n\n### Push\n\n```python\nollama.push('user/llama2')\n```\n\n### Embeddings\n\n```python\nollama.embeddings(model='llama2', prompt='The sky is blue because of rayleigh scattering')\n```\n\n## Custom client\n\nA custom client can be created with the following fields:\n\n- `host`: The Ollama host to connect to\n- `timeout`: The timeout for requests\n\n```python\nfrom ollama import Client\nclient = Client(host='http://localhost:11434')\nresponse = client.chat(model='llama2', messages=[\n {\n 'role': 'user',\n 'content': 'Why is the sky blue?',\n },\n])\n```\n\n## Async client\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='llama2', 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='llama2', messages=[message], stream=True):\n print(part['message']['content'], end='', flush=True)\n\nasyncio.run(chat())\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",
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