app.py

import os
import gradio as gr
from huggingface_hub import InferenceClient


def respond(
    message,
    history,
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    hf_token = os.getenv("HF_TOKEN")
    client = InferenceClient(
        token=hf_token,
        model="openai/gpt-oss-20b"
    )

    messages = [{"role": "system", "content": system_message}]
    messages.extend(history)
    messages.append({"role": "user", "content": message})

    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        choices = message.choices
        token = ""
        if len(choices) and choices[0].delta.content:
            token = choices[0].delta.content

        response += token
        yield response
# def respond(
#     message,
#     history: list[dict[str, str]],
#     system_message,
#     max_tokens,
#     temperature,
#     top_p,
#     hf_token: gr.OAuthToken,
# ):
#     """
#     For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
#     """
#     client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")

#     messages = [{"role": "system", "content": system_message}]

#     messages.extend(history)

#     messages.append({"role": "user", "content": message})

#     response = ""

#     for message in client.chat_completion(
#         messages,
#         max_tokens=max_tokens,
#         stream=True,
#         temperature=temperature,
#         top_p=top_p,
#     ):
#         choices = message.choices
#         token = ""
#         if len(choices) and choices[0].delta.content:
#             token = choices[0].delta.content

#         response += token
#         yield response


"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
chatbot = gr.ChatInterface(
    respond,
    # type="messages",
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)

# with gr.Blocks() as demo:
#     with gr.Sidebar():
#         gr.LoginButton()
#     chatbot.render()
with gr.Blocks() as demo:
    chatbot.render()

if __name__ == "__main__":
    demo.launch()