from huggingface_hub import InferenceClient
from typing import List
import gradio as gr

model_llm_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
# model_toxicity_id = "unitary/toxic-bert"
model_toxicity_id = "unitary/unbiased-toxic-roberta"
client = InferenceClient(model_llm_id)
client_toxicity = InferenceClient(model_toxicity_id)


def format_prompt(message, history):
    prompt = "<s>"
    for user_prompt, bot_response in history:
        prompt += f"[INST] {user_prompt} [/INST]"
        prompt += f" {bot_response}</s> "
    prompt += f"[INST] {message} [/INST]"
    return prompt


def generate(prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, ):
    temperature = float(temperature)
    if temperature < 1e-2:
        temperature = 1e-2
    top_p = float(top_p)

    start_toxic = "[Toxic Classification] "

    generate_kwargs = dict(
        temperature=temperature,
        max_new_tokens=max_new_tokens,
        top_p=top_p,
        repetition_penalty=repetition_penalty,
        do_sample=True,
        seed=42,
    )

    response: List = client_toxicity.text_classification(prompt)
    toxicity_level = [f'{d["label"]}:{round(d["score"], 4)}' for d in response]

    if start_toxic in history:
        s_idx = history.find(start_toxic)
        history = history[:s_idx]

    formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True,
                                    return_full_text=False)
    output = ""

    for response in stream:
        output += response.token.text
        yield output

    output += ' \n \n'
    output += start_toxic + " | ".join(toxicity_level)
    yield output

    return output


examples = [
    ["Wat zijn klompen?", None,
     None, None, None, None, ],
    [
    "I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?",
    None, None, None, None, None, ],
    [
        "I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?",
        None, None, None, None, None, ],
    [
        "Kapadokya'yı bu kadar ünlü yapan şeyin ne olduğunu kısaca açıklayın",
        None, None, None, None, None, ],
    ["Can you explain how the QuickSort algorithm works and provide a Python implementation?", None, None, None,
     None, None, ],
    [
        "What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?",
        None, None, None, None, None, ],
]

additional_inputs = [
    gr.Textbox(
        label="System Prompt",
        max_lines=1,
        interactive=True,
    ),
    gr.Slider(
        label="Temperature",
        value=0.9,
        minimum=0.0,
        maximum=1.0,
        step=0.05,
        interactive=True,
        info="Higher values produce more diverse outputs",
    ),
    gr.Slider(
        label="Max new tokens",
        value=256,
        minimum=0,
        maximum=1048,
        step=64,
        interactive=True,
        info="The maximum numbers of new tokens",
    ),
    gr.Slider(
        label="Top-p (nucleus sampling)",
        value=0.90,
        minimum=0.0,
        maximum=1,
        step=0.05,
        interactive=True,
        info="Higher values sample more low-probability tokens",
    ),
    gr.Slider(
        label="Repetition penalty",
        value=1.2,
        minimum=1.0,
        maximum=2.0,
        step=0.05,
        interactive=True,
        info="Penalize repeated tokens",
    )
]

demo = gr.ChatInterface(
    fn=generate,
    chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True,
                       layout="panel"),
    additional_inputs=additional_inputs,
    title="Mixtral 46.7B",
    description="Mixtral with Toxic comment classification",
    examples=examples,
    concurrency_limit=20,
)

demo.launch(show_api=False)