xlerai 1.12.0

The official Python library for the xler.ai API

XlerAI Python API library

The XlerAI Python library provides convenient access to the XlerAI REST API from any Python 3.7+ application. The library wraps the openai python library, points it at api.xler.ai/v1 for you, and extends their library further with additional functionality.

Documentation

The REST API documentation can be found on docs.xler.ai.

Installation

pip install xlerai

Usage

The full API of this library can be found in api.md.

import os
from xlerai import XlerAI

client = XlerAI(
    # This is the default and can be omitted
    api_key=os.environ.get("OPENAI_API_KEY"),
)

chat_completion = client.chat.completions.create(
    messages=[
        {
            "role": "user",
            "content": "Say this is a test",
        }
    ],
    model="gpt-3.5-turbo",
)

While you can provide an api_key keyword argument, we recommend using python-dotenv to add OPENAI_API_KEY="My API Key" to your .env file so that your API Key is not stored in source control.

Async usage

Simply import AsyncXlerAI instead of XlerAI and use await with each API call:

import os
import asyncio
from xlerai import AsyncXlerAI

client = AsyncXlerAI(
    # This is the default and can be omitted
    api_key=os.environ.get("OPENAI_API_KEY"),
)


async def main() -> None:
    chat_completion = await client.chat.completions.create(
        messages=[
            {
                "role": "user",
                "content": "Say this is a test",
            }
        ],
        model="gpt-3.5-turbo",
    )


asyncio.run(main())

Functionality between the synchronous and asynchronous clients is otherwise identical.

Streaming Responses

We provide support for streaming responses using Server Side Events (SSE).

from xlerai import XlerAI

client = XlerAI()

stream = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Say this is a test"}],
    stream=True,
)
for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")

The async client uses the exact same interface.

from xlerai import AsyncXlerAI

client = AsyncXlerAI()


async def main():
    stream = await client.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": "Say this is a test"}],
        stream=True,
    )
    async for chunk in stream:
        print(chunk.choices[0].delta.content or "", end="")


asyncio.run(main())

Requirements

Python 3.7 or higher.