Chatbot

Spinning up a Chatbot is the equivalent of Hello World in the LLM space. Here's an example.

The following is an example code for a chatbot demo with gradio using our Python Client. Since our APIs are compliant with the OpenAI API template, this will be a very short example.

Installation:

Just gradio and our client:

pip install gradio hyperbee

demo.py:

from hyperbee import HyperBee
import gradio as gr
import os
 
 
client = HyperBee(
    api_key=os.environ["HYPERBEE_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="hyperchat", 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

Integration Retrieval Bot