| Name | shasta-python JSON |
| Version |
0.0.2
JSON |
| download |
| home_page | https://krugle.ai/shasta |
| Summary | The official Python client for Krugle Shasta. |
| upload_time | 2024-12-18 14:09:44 |
| maintainer | None |
| docs_url | None |
| author | Jason |
| requires_python | <4.0,>=3.8 |
| license | Apache-2.0 |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Shasta Python Library
The Shasta Python library provides the easiest way to integrate Python 3.8+ projects with [Shasta](https://github.com/krugle2/shasta).
## Prerequisites
- Install Shasta and init with KrugleAI models
## Install
```sh
pip install shasta-python
```
## Usage
```python
from shasta_python import chat
from shasta_python 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](shasta/_types.py) for more information on the response types.
## Streaming responses
Response streaming can be enabled by setting `stream=True`.
```python
from shasta_python 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 `shasta`.
All extra keyword arguments are passed into the [`httpx.Client`](https://www.python-httpx.org/api/#client).
```python
from shasta_python import Client
client = Client(
host='http://localhost:5668',
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 shasta_python 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 shasta_python 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 Shasta Python library's API is designed around the [Shasta REST API](https://github.com/krugle2/shasta/blob/main/docs/api.md)
### Chat
```python
shasta.chat(model='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}])
```
### Generate
```python
shasta.generate(model='llama3.2', prompt='Why is the sky blue?')
```
### List
```python
shasta.list()
```
### Show
```python
shasta.show('llama3.2')
```
### Create
```python
modelfile='''
FROM llama3.2
SYSTEM You are mario from super mario bros.
'''
shasta.create(model='example', modelfile=modelfile)
```
### Copy
```python
shasta.copy('llama3.2', 'user/llama3.2')
```
### Delete
```python
shasta.delete('llama3.2')
```
### Embed
```python
shasta.embed(model='llama3.2', input='The sky is blue because of rayleigh scattering')
```
### Embed (batch)
```python
shasta.embed(model='llama3.2', input=['The sky is blue because of rayleigh scattering', 'Grass is green because of chlorophyll'])
```
### Ps
```python
shasta.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:
shasta.chat(model)
except shasta.ResponseError as e:
print('Error:', e.error)
if e.status_code == 404:
shasta.pull(model)
```
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