app.py

from huggingface_hub import InferenceClient
import gradio as gr
import datetime
import re

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

# Define the system prompt templates
system_prompt_templates = {
    r"\btime\b|\bhour\b|\bclock\b": "server log: ~This message was sent at {formatted_time}.~",
    r"\bdate\b|\bcalendar\b": "server log: ~Today's date is {formatted_date}.~",
    

def format_prompt(message, history, system_prompt):
    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=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,
    )

    # Get current time and date
    now = datetime.datetime.now()
    formatted_time = now.strftime("%H.%M.%S, %B, %Y")
    formatted_date = now.strftime("%B %d, %Y")

    # Check for keywords in the user's input and update the system prompt accordingly
    for keyword, template in system_prompt_templates.items():
        if re.search(keyword, prompt, re.IGNORECASE):
            system_prompt = template.format(formatted_time=formatted_time, formatted_date=formatted_date)
            break

    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

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=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")
]

def check_keywords(text):
    for keyword, _ in system_prompt_templates.items():
        if re.search(keyword, text, re.IGNORECASE):
            return True
    return False

chatbot = gr.Chatbot(show_label=True, show_share_button=False, show_copy_button=True, likeable=True, layout="panel")
with gr.Blocks():
    with gr.Row():
        with gr.Column(scale=3):
            user_input = gr.Textbox(label="Your message", placeholder="Type your message here...")
        with gr.Column(scale=1):
            submit_button = gr.Button("Send")

    with gr.Row():
        chatbot_output = chatbot

    submit_button.click(
        fn=generate,
        inputs=[user_input, chatbot, gr.Textbox(label="System Prompt", max_lines=1, interactive=True)],
        outputs=chatbot_output,
        every=200,
        _js="check_keywords"
    )

gr.Blocks().launch(show_api=False)