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,
    }

def update_analysis(response):
    analysis = analyze_text(response)
    analysis_str = f"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']}"
    return analysis_str

# --- Interface ---

with gr.Blocks() as iface:
    gr.Markdown(
        """
        # Hajax Chat
        """
    )

    input_text = gr.Textbox(
        label="Your message:", lines=5, placeholder="Ask me anything...", show_label=True
    )
    temperature = gr.Slider(label="Temperature", minimum=0.1, maximum=1.0, step=0.1, value=0.7)
    top_p = gr.Slider(label="Top p", minimum=0.1, maximum=1.0, step=0.1, value=0.9)
    top_k = gr.Slider(label="Top k", minimum=1, maximum=100, step=1, value=50)
    max_length = gr.Slider(label="Max length", minimum=10, maximum=1000, step=10, value=250)
    submit_button = gr.Button(value="Submit")
    response = gr.TextArea(label="Response:", lines=10)
    analysis_html = gr.HTML(elem_id="analysis")

    submit_button.click(fn=get_response, inputs=[input_text, temperature, top_p, top_k, max_length], outputs=[response])
    response.change(fn=update_analysis, inputs=[response], outputs=[analysis_html])

    # --- Dynamic Background ---

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

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

iface.launch(debug=True)