retoor ef149e48fb feat: implement dataset loading and management with CRUD operations
Add core dataset functionality including creation, listing, retrieval, and deletion
of datasets. Introduce Dataset model with fields for name, description, and metadata,
along with a dedicated service layer for business logic and a RESTful API controller
exposing endpoints under /api/datasets. Include validation for required fields and
error handling for duplicate names and missing datasets.
2024-12-09 17:49:50 +00:00

Yura LLM Client for Katya server

Part of project with as target replacing the native ollama protocol. This protocol supports streaming and is usable trough https and it is possible to directly attach a web client to the backend.

Install

pip install -e .

Build

make build

Command line usage

yura ws://[host]:[port]/[path]/

Python

import asyncio

from yura.client import AsyncClient


async def communicate():
    client = AsyncClient("ws://[host]:[port]/[path]/")
    async for response in client.chat("Your prompt"):
        print(response)


asyncio.run(communicate())
S
Description
Async client for the katya AI server
Readme
334 KiB
Languages
Python 96.9%
Makefile 3.1%