from huggingface_hub import InferenceClient
import gradio as gr

class MixtralChatInterface:
    def __init__(self, model_name):
        self.client = InferenceClient(model_name)
        self.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",
            )
        ]
        self.examples=[
            ["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, ],
            ["Can you write a short story about a time-traveling detective who solves historical mysteries?", 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,],
            ["I have chicken, rice, and bell peppers in my kitchen. Can you suggest an easy recipe I can make with these ingredients?", 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,],
        ]

    def format_prompt(self, 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(self, 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)

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

        formatted_prompt = self.format_prompt(f"{system_prompt}, {prompt}", history)
        stream = self.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
        return output

    def launch(self):
        gr.ChatInterface(
            fn=self.generate,
            chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
            additional_inputs=self.additional_inputs,
            title="Mixtral 46.7B",
            examples=self.examples,
            concurrency_limit=20,
        ).launch(show_api=False)

# Usage
if __name__ == "__main__":
    model_name = "mistralai/Mixtral-8x7B-Instruct-v0.1"
    chat_interface = MixtralChatInterface(model_name)
    chat_interface.launch()