app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import time
import random

# Load the model and tokenizer
model_id = "microsoft/phi-2"  # Change to your desired model
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

# --- Functions ---

def get_response(input_text, temperature, top_p, top_k, max_length):
    inputs = tokenizer(input_text, return_tensors="pt")
    outputs = model.generate(
        input_ids=inputs["input_ids"],
        attention_mask=inputs["attention_mask"],
        max_length=max_length,
        temperature=temperature,
        top_p=top_p,
        top_k=top_k,
    )
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response

def analyze_text(text):
    num_tokens = len(tokenizer.tokenize(text))
    return {
        "Number of characters": len(text),
        "Number of words": len(text.split()),
        "Number of tokens": num_tokens,
    }

# --- Interface ---

css = """
.gradio-container {
  background-color: #000000; /* Black background */
  font-family: 'Roboto', sans-serif;
}

.gradio-interface {
  background-color: rgba(0, 0, 0, 0.8); /* Dark translucent background */
  border: 3px solid #00FF00; /* Green border */
  padding: 20px;
  box-shadow: 0 0 10px rgba(0, 255, 0, 0.5); /* Green shadow */
}

.gradio-button {
  background-color: #00FF00; /* Green button */
  color: white;
  border: none;
  padding: 10px 20px;
  font-size: 16px;
  cursor: pointer;
}

.gradio-button:hover {
  background-color: #00CC00; /* Darker green on hover */
}

.gradio-textbox {
  background-color: #111111; /* Dark gray background */
  color: #00FF00; /* Green text */
  border: 1px solid #00FF00; /* Green border */
  padding: 10px;
  margin-bottom: 10px;
}

.gradio-text-area {
  background-color: #111111; /* Dark gray background */
  color: #00FF00; /* Green text */
  border: 1px solid #00FF00; /* Green border */
  padding: 10px;
}

.gradio-slider {
  background-color: #111111; /* Dark gray background */
  color: #00FF00; /* Green text */
}

.gradio-slider .slider-bar {
  background-color: #00FF00; /* Green slider bar */
}

.gradio-slider .slider-thumb {
  background-color: #00FF00; /* Green slider thumb */
}

.gradio-label {
  color: #00FF00; /* Green labels */
}

h1, h2 {
  color: #00FF00; /* Green headings */
  text-align: center;
}

.analysis-container {
  margin-top: 20px;
  padding: 10px;
  border: 1px solid #00FF00;
}
"""

iface = gr.Interface(
    fn=get_response,
    inputs=[
        gr.Textbox(label="Your message:", lines=5, placeholder="Ask me anything...", show_label=True,
                   style={'background-color': '#111111', 'color': '#00FF00', 'border': '1px solid #00FF00'}),
        gr.Slider(label="Temperature", minimum=0.1, maximum=1.0, step=0.1, value=0.7),
        gr.Slider(label="Top p", minimum=0.1, maximum=1.0, step=0.1, value=0.9),
        gr.Slider(label="Top k", minimum=1, maximum=100, step=1, value=50),
        gr.Slider(label="Max length", minimum=10, maximum=1000, step=10, value=250),
    ],
    outputs=[
        gr.TextArea(label="AI Response:", lines=10,
                    style={'background-color': '#111111', 'color': '#00FF00', 'border': '1px solid #00FF00'}),
        gr.HTML(elem_id="analysis", style={'color': '#00FF00'}),
    ],
    title="NVIDIA AI Chat",
    description="Engage in a conversation with our advanced AI model. Customize the response using various parameters.",
    theme="default",
    css=css,
    layout="vertical",
    allow_flagging="never",
)

# --- Dynamic Background ---

def update_background():
    while True:
        r = random.randint(0, 255)
        g = 255  # Keep the green component constant
        b = random.randint(0, 255)
        iface.root.style.background_color = f"rgb({r}, {g}, {b})"
        time.sleep(1)

# Start a separate thread to update the background color
gr.Interface.update(update_background, inputs=[], outputs=[], live=True)

# --- Analysis Logic ---

def update_analysis(response):
    analysis = analyze_text(response)
    analysis_str = f"<div class='analysis-container'>Number of characters: {analysis['Number of characters']}<br>" \
                  f"Number of words: {analysis['Number of words']}<br>" \
                  f"Number of tokens: {analysis['Number of tokens']}</div>"
    iface.update(analysis=analysis_str, live=True)

iface.outputs[0].postprocess = update_analysis

iface.launch(debug=True)