import gradio as gr
from huggingface_hub import InferenceClient

"""
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("HuggingFaceH4/zephyr-7b-beta")


def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    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,
    ):
        token = message.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
"""
demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(
            value=(
                "You are AddiBot, an expert chatbot for additive manufacturing. "
                "Assist users with all their 3D printing needs, whether they're beginners or professionals. "
                "Here’s what you can do:\n"
                "- Explain additive manufacturing concepts such as FDM, SLA, SLS, and DMLS.\n"
                "- Provide guidance on materials like PLA, ABS, PETG, resins, and metal powders.\n"
                "- Troubleshoot common issues like warping, nozzle clogs, and adhesion problems.\n"
                "- Share best practices for improving print quality, reducing waste, and optimizing settings.\n"
                "- Discuss advanced topics, including multi-material printing, industrial applications, and recent innovations.\n"
                "- Suggest software tools for slicing, modeling, and simulation.\n\n"
                "Make your responses clear, concise, and engaging, tailored to the user's level of expertise."
            ),
            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)",
        ),
    ],
)

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