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app.py.py

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+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")
+model = AutoModelForImageTextToText.from_pretrained("deepseek-community/Janus-Pro-1B")
+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
+
+Make it visually rich and optimized for all existing AI models.
+The Prompt should e detailed prompt about words ranging from 50 to 70.
+
+Input: {user_text}
+
+Return only the final prompt.
+"""
+def text_to_prompt(user_text):
+    instruction = build_instruction(user_text)
+    
+    inputs = processor(
+        text=instruction,
+        return_tensors="pt"
+    ).to(model.device)
+
+    input_len = inputs.input_ids.shape[1]
+    output = model.generate(**inputs, max_new_tokens=150) 
+    generated_tokens = output[0][input_len:]
+
+    return processor.decode(generated_tokens, skip_special_tokens=True)
+
+def image_text_to_prompt(image_path, user_text):
+    image = Image.open(image_path)
+    instruction = build_instruction(user_text)
+
+    inputs = processor(
+        images=image,
+        text=instruction,
+        return_tensors="pt"
+    ).to(model.device)
+
+    input_len = inputs.input_ids.shape[1]
+    output = model.generate(**inputs, max_new_tokens=150)
+    generated_tokens = output[0][input_len:]
+
+    return processor.decode(generated_tokens, skip_special_tokens=True)
+
+def audio_to_prompt(audio_path):
+    result = whisper_model.transcribe(audio_path)
+    text = result["text"]
+    return text_to_prompt(text)
+
+def generate_prompt_ui(input_type, text, image, audio):
+
+    if input_type == "Text":
+        return text_to_prompt(text)
+
+    elif input_type == "Image + Text":
+        if image is None:
+            return "Please upload an image"
+        return image_text_to_prompt(image, text)
+
+    elif input_type == "Audio":
+        if audio is None:
+            return "Please upload audio"
+        return audio_to_prompt(audio)
+
+    return "Invalid input"
+
+with gr.Blocks() as app:
+
+    gr.Markdown("# 🧠 AI Prompt Generator")
+
+    input_type = gr.Radio(
+        ["Text", "Image + Text", "Audio"],
+        label="Select Input Type"
+    )
+
+    text_input = gr.Textbox(label="Enter your idea/prompt")
+
+    image_input = gr.Image(type="filepath", label="Upload Image")
+
+    audio_input = gr.Audio(type="filepath", label="Upload Audio")
+
+    output = gr.Textbox(label="Generated Prompt")
+
+    generate_btn = gr.Button("Generate Prompt 🚀")
+
+    def update_inputs(choice):
+        return (
+            gr.update(visible=(choice == "Text" or choice == "Image + Text")),
+            gr.update(visible=(choice == "Image + Text")),
+            gr.update(visible=(choice == "Audio"))
+        )
+    input_type.change(
+        fn=update_inputs,
+        inputs=input_type,
+        outputs=[text_input, image_input, audio_input]
+    )
+    generate_btn.click(
+        fn=generate_prompt_ui,
+        inputs=[input_type, text_input, image_input, audio_input],
+        outputs=output
+    )
+
+app.launch()