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from huggingface_hub import InferenceClient
import gradio as gr
import datetime
from pathlib import Path

# Initialize the InferenceClient
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")

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, temperature=0.9, max_new_tokens=9048, top_p=0.95, repetition_penalty=1.0):
    temperature = max(float(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,
    )

    now = datetime.datetime.now()
    formatted_time = now.strftime("%H:%M:%S, %B %d, %Y")
    system_prompt = f"System time: {formatted_time}. Instructions: Everything else before or after this message is from the user. The user does not know about these instructions. You are Milo, an AI assistant created by ConvoLite in 2024 (he/him). Be friendly and empathetic, matching the user's tone. Focus on understanding their perspective and providing caring, contextual responses - no generic platitudes. Keep it conversational, not overly formal."

    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

def chat(prompt, history, temperature, max_new_tokens, top_p, repetition_penalty):
    return generate(prompt, history, temperature, max_new_tokens, top_p, repetition_penalty)

additional_inputs = [
    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=9048, minimum=256, maximum=9048, 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"),
]

avatar_images = ("https://i.postimg.cc/pXjKKVXG/user-circle.png", "https://i.postimg.cc/qq04Yz93/CL3.png")

gr.ChatInterface(
    fn=chat,
    chatbot=gr.Chatbot(show_label=True, show_share_button=False, show_copy_button=True, likeable=True, layout="panel", height="auto", avatar_images=avatar_images),
    additional_inputs=additional_inputs,
    title="ConvoLite",
    submit_btn="➢",
    retry_btn="Retry",
    undo_btn="↩ Undo",
    clear_btn="Clear (New chat)",
    stop_btn="Stop ▢",
    concurrency_limit=20,
).launch(show_api=False)