Update app.py

app.py

@@ -1,37 +1,100 @@
 import gradio as gr
-from diffusers import StableDiffusionPipeline
-import torch
-
-# Model Load (Free Space friendly)
-model_id = "runwayml/stable-diffusion-v1-5"
-pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
-pipe = pipe.to("cpu")  # Free Space CPU safe
-
-# Function for fast low-res preview + high-res paid option
-def generate_image(prompt, high_res=False):
-    if high_res:
-        # Paid high-res: slower
-        image = pipe(prompt, height=512, width=512).images[0]
-    else:
-        # Free low-res: faster
-        image = pipe(prompt, height=256, width=256).images[0]
-    return image
-
-# Gradio Interface
-iface = gr.Interface(
-    fn=generate_image,
-    inputs=[
-        gr.Textbox(lines=2, placeholder="Type your image description here...", label="Prompt"),
-        gr.Checkbox(label="High-Resolution (Paid Feature)")
-    ],
-    outputs=gr.Image(label="Generated Image"),
-    title="AI Image Generator (Fast Preview)",
-    description="""
-Type any text to get beautiful AI-generated images instantly!
-Free low-res images for fast preview.
-Check High-Resolution for paid download.
-""",
-    allow_flagging="never"
+
+# -------------------------
+# SMART UNDERSTANDING LOGIC
+# -------------------------
+
+def detect_mode(user_text):
+    text = user_text.lower()
+
+    if any(k in text for k in ["upsc", "exam", "notes", "school", "college"]):
+        return "academic"
+    if any(k in text for k in ["instagram", "facebook", "dp", "profile", "post"]):
+        return "social"
+    if any(k in text for k in ["diagram", "flow", "map"]):
+        return "diagram"
+    return "general"
+
+
+def build_prompt(user_text):
+    mode = detect_mode(user_text)
+
+    base_realism = (
+        "highly realistic, photorealistic image, "
+        "natural lighting, real human texture, "
+        "no cartoon, no fantasy, professional quality"
+    )
+
+    if mode == "academic":
+        return (
+            f"{base_realism}, academic textbook style, "
+            f"exam-safe visual, subject based on: {user_text}"
+        )
+
+    if mode == "social":
+        return (
+            f"{base_realism}, premium social media portrait, "
+            f"clean background, instagram facebook ready, "
+            f"based on: {user_text}"
+        )
+
+    if mode == "diagram":
+        return (
+            f"clean academic diagram, simple design, "
+            f"clear labels, NCERT style, topic: {user_text}"
+        )
+
+    return f"{base_realism}, based on: {user_text}"
+
+
+NEGATIVE_PROMPT = (
+    "cartoon, anime, illustration, painting, fantasy, unreal, "
+    "plastic skin, blurry, distorted, watermark, text, logo"
 )
 
-iface.launch()
+# -------------------------
+# IMAGE GENERATION FUNCTION
+# -------------------------
+def generate_image(user_text):
+    final_prompt = build_prompt(user_text)
+
+    # 🔴 यहां अपना MODEL / API call लगाना है
+    # image = model.generate(
+    #     prompt=final_prompt,
+    #     negative_prompt=NEGATIVE_PROMPT
+    # )
+    # return image
+
+    return None  # placeholder (UI test के लिए)
+
+# -------------------------
+# GRADIO UI
+# -------------------------
+with gr.Blocks(title="Smart Text-to-Art AI") as demo:
+    gr.Markdown(
+        """
+        ## 🎓 Smart Text-to-Art AI Generator  
+        बस लिखो, AI खुद समझेगा और realistic image बनाएगा  
+
+        ✔ Student Safe  
+        ✔ Social Media Ready  
+        ✔ No Cartoon / No Fantasy  
+        """
+    )
+
+    user_input = gr.Textbox(
+        label="आप क्या बनवाना चाहते हैं?",
+        placeholder="Example: UPSC ke liye raja ki realistic photo"
+    )
+
+    generate_btn = gr.Button("Generate Image")
+    output = gr.Image(label="Output", type="pil")
+
+    generate_btn.click(
+        fn=generate_image,
+        inputs=user_input,
+        outputs=output
+    )
+
+if __name__ == "__main__":
+    demo.launch()