Update app.py

app.py

@@ -1,47 +1,111 @@
 # app.py
-
 import gradio as gr
-from transformers import pipeline, MarianMTModel, MarianTokenizer
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 from diffusers import StableDiffusionPipeline
 import torch
-import os
+import re
 
-# Get Hugging Face token from environment (in Hugging Face Spaces this is auto-populated from secrets)
-hf_token = os.getenv("HUGGINGFACE_TOKEN")
+# Initialize models (load once at startup)
+# Translation pipeline (Tamil to English)
+translator = pipeline(
+    "translation", 
+    model="Helsinki-NLP/opus-mt-ta-en",
+    device=0 if torch.cuda.is_available() else -1
+)
 
-# Load Translation Pipeline: Tamil → English using MarianMT
-translation_model_name = "Helsinki-NLP/opus-mt-ta-en"
-translator = pipeline("translation", model=translation_model_name)
+# Text generation pipeline (English creative content)
+text_generator = pipeline(
+    "text-generation", 
+    model="gpt2-medium",
+    device=0 if torch.cuda.is_available() else -1
+)
 
-# Load Stable Diffusion Pipeline: English → Image
-device = "cuda" if torch.cuda.is_available() else "cpu"
+# Image generation pipeline (English text to image)
+if torch.cuda.is_available():
+    image_pipe = StableDiffusionPipeline.from_pretrained(
+        "runwayml/stable-diffusion-v1-5",
+        torch_dtype=torch.float16,
+        revision="fp16"
+    ).to("cuda")
+else:
+    image_pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
 
-image_pipe = StableDiffusionPipeline.from_pretrained(
-    "CompVis/stable-diffusion-v1-4",
-    use_auth_token=hf_token,
-    torch_dtype=torch.float16 if device == "cuda" else torch.float32
-).to(device)
+# Clean and format generated text
+def clean_text(text):
+    """Remove special characters and truncate to complete sentences"""
+    cleaned = re.split(r'(?<=[.!?])\s+', text)[0]  # Take first complete sentence
+    return re.sub(r'[^a-zA-Z0-9,.!?\'"\- ]+', '', cleaned).strip()
 
-# Core function
-def translate_and_generate(tamil_text):
-    # Step 1: Translate Tamil to English
-    english_output = translator(tamil_text)[0]['translation_text']
+def process_content(tamil_input, creativity_level):
+    """Main processing pipeline: Translate → Generate Image → Create Text"""
+    outputs = {}
+    error = ""
     
-    # Step 2: Generate Image from English Text
-    image = image_pipe(english_output).images[0]
+    try:
+        # Translate Tamil to English
+        translation = translator(tamil_input)
+        english_text = translation[0]['translation_text']
+        outputs["translation"] = english_text
+        
+        # Generate image from translated text
+        image = image_pipe(
+            english_text, 
+            guidance_scale=creativity_level
+        ).images[0]
+        outputs["image"] = image
+        
+        # Generate creative text from translation
+        creative_output = text_generator(
+            f"Create creative content about: {english_text}",
+            max_length=150,
+            temperature=creativity_level/10,
+            num_return_sequences=1
+        )
+        outputs["creative_text"] = clean_text(creative_output[0]['generated_text'])
+        
+    except Exception as e:
+        error = f"⚠️ Error: {str(e)}"
     
-    return english_output, image
+    return outputs, error
 
 # Gradio UI
-iface = gr.Interface(
-    fn=translate_and_generate,
-    inputs=gr.Textbox(lines=2, label="Enter Tamil Text"),
-    outputs=[
-        gr.Textbox(label="Translated English Text"),
-        gr.Image(label="Generated Image")
-    ],
-    title="Tamil-to-Image Generator 🌸",
-    description="Enter Tamil text. It will be translated to English and visualized using Stable Diffusion."
-)
+with gr.Blocks(theme=gr.themes.Soft()) as app:
+    gr.Markdown("# 🌐 Tamil Creative Content Generator")
+    gr.Markdown("Enter Tamil text → Get English translation + AI-generated image + creative English text")
+    
+    with gr.Row():
+        with gr.Column():
+            tamil_input = gr.Textbox(
+                label="தமிழ் உள்ளீடு (Tamil Input)", 
+                placeholder="உங்கள் உரையை இங்கே உள்ளிடவும்...",
+                lines=3
+            )
+            creativity = gr.Slider(
+                label="Creativity Level", 
+                minimum=1, maximum=10, value=7, step=1
+            )
+            submit_btn = gr.Button("Generate Content")
+            
+        with gr.Column():
+            translation_box = gr.Textbox(label="English Translation")
+            creative_output = gr.Textbox(label="Creative English Content")
+            image_output = gr.Image(label="Generated Image")
+            error_output = gr.Textbox(label="System Messages", visible=True)
+    
+    examples = gr.Examples(
+        examples=[
+            ["ஒரு மலையின் மீது உள்ள அழகிய கோட்டை", 8],
+            ["விண்மீன்கள் நிறைந்த இரவு வா��த்தில் பறக்கும் யானை", 9],
+            ["தாவரங்கள் வளரும் புதிரான கோளம்", 10]
+        ],
+        inputs=[tamil_input, creativity]
+    )
+    
+    submit_btn.click(
+        fn=process_content,
+        inputs=[tamil_input, creativity],
+        outputs=[{"translation": translation_box, "creative_text": creative_output, "image": image_output}, error_output]
+    )
 
-iface.launch()
+if __name__ == "__main__":
+    app.launch(share=True)