app.py

import torch
import gradio as gr
from PIL import Image
import whisper
from transformers import AutoProcessor, AutoModelForImageTextToText


processor = AutoProcessor.from_pretrained("deepseek-community/Janus-Pro-1B", trust_remote_code=True)
model = AutoModelForImageTextToText.from_pretrained("deepseek-community/Janus-Pro-1B", trust_remote_code=True)


device = "cuda" if torch.cuda.is_available() else "cpu"
model.to(device)

whisper_model = whisper.load_model("base")

def build_instruction(user_text):
    return f"You are a professional AI prompt engineer. Convert the input into a highly detailed AI generation prompt. Include: Subject, Environment, Summary. Input: {user_text}\nReturn only the final prompt."

def text_to_prompt(user_text):
    instruction = build_instruction(user_text)
    inputs = processor(text=instruction, return_tensors="pt").to(device)

    input_len = inputs.input_ids.shape[1]
    
    output = model.generate(**inputs, max_new_tokens=200)
    return processor.decode(output[0][input_len:], skip_special_tokens=True).strip()

def image_text_to_prompt(image_path, user_text):
    if not user_text:
        user_text = "Describe this image in detail."
    
    image = Image.open(image_path).convert("RGB")
    instruction = build_instruction(user_text)
    
    inputs = processor(images=[image], text=instruction, return_tensors="pt").to(device)
    input_len = inputs.input_ids.shape[1]
    
    output = model.generate(**inputs, max_new_tokens=200)
    
    return processor.decode(output[0][input_len:], skip_special_tokens=True).strip()

def audio_to_prompt(audio_path):
    result = whisper_model.transcribe(audio_path)
    return text_to_prompt(result["text"])

def generate_prompt_ui(input_type, text, image, audio):
    try:
        if input_type == "Text":
            return text_to_prompt(text)
        elif input_type == "Image + Text":
            return image_text_to_prompt(image, text)
        elif input_type == "Audio":
            return audio_to_prompt(audio)
    except Exception as e:
        return f"Error: {str(e)}"

# Gradio UI setup
with gr.Blocks() as app:
    gr.Markdown("# 🧠 Janus-Pro Prompt Generator")
    
    input_type = gr.Radio(["Text", "Image + Text", "Audio"], label="Select Input Type", value="Text")
    
    text_input = gr.Textbox(label="Enter your idea")
    image_input = gr.Image(type="filepath", label="Upload Image", visible=False)
    audio_input = gr.Audio(type="filepath", label="Upload Audio", visible=False)
    
    output = gr.Textbox(label="Generated Prompt")
    btn = gr.Button("Generate 🚀")

    def toggle(choice):
        return (
            gr.update(visible=(choice != "Audio")),
            gr.update(visible=(choice == "Image + Text")),
            gr.update(visible=(choice == "Audio"))
        )

    input_type.change(toggle, input_type, [text_input, image_input, audio_input])
    btn.click(generate_prompt_ui, [input_type, text_input, image_input, audio_input], output)

app.launch()