Examples

Chat Demo

This is a example code for chat demo with gradio.

Install necessary packages: pip install gradio git+https://github.com/HyperbeeAI/hive-python

demo.py file:

from hyperbee import Hive
import gradio as gr
import os


client = Hive(
    api_key=os.environ["HIVE_API_KEY"],
)


def predict(message, history):
    history_openai_format = []
    for human, assistant in history:
        history_openai_format.append({"role": "user", "content": human})
        history_openai_format.append({"role": "assistant", "content": assistant})
    history_openai_format.append({"role": "user", "content": message})

    response = client.chat.completions.create(
        model="hive", messages=history_openai_format, temperature=0.4, stream=True
    )

    partial_message = ""
    for chunk in response:
        if chunk.choices[0].delta.content is not None:
            partial_message = partial_message + chunk.choices[0].delta.content
            yield partial_message

gr.ChatInterface(predict).launch(server_name="0.0.0.0", server_port=8080, share=True)

Run the demo.py file and open the browser with the link provided in the terminal.

python demo.py

Usage

import os
from hyperbee import Hive

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

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

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

Async usage

Simply import AsyncHive instead of Hive and use await with each API call:

import os
import asyncio
from hyperbee import AsyncHive

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


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


asyncio.run(main())

Functionality between the synchronous and asynchronous clients is otherwise identical.