Create app,py

app,py

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+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline
+
+MODEL_ID = "runwayml/stable-diffusion-v1-5"
+
+pipe = StableDiffusionPipeline.from_pretrained(
+    MODEL_ID,
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
+)
+
+if torch.cuda.is_available():
+    pipe = pipe.to("cuda")
+
+STYLES = {
+    "None": "",
+    "Cinematic": "cinematic lighting, dramatic, ultra detailed",
+    "Anime": "anime style, vibrant colors, sharp lines",
+    "Oil Painting": "oil painting, textured brush strokes",
+    "Cyberpunk": "cyberpunk, neon lights, futuristic",
+    "Fantasy Art": "fantasy art, magical, epic composition"
+}
+
+def generate(prompt, style, steps, guidance):
+    full_prompt = prompt
+    if STYLES[style]:
+        full_prompt = f"{prompt}, {STYLES[style]}"
+
+    image = pipe(
+        prompt=full_prompt,
+        num_inference_steps=steps,
+        guidance_scale=guidance
+    ).images[0]
+
+    return image
+
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple")) as demo:
+    gr.Markdown(
+        """
+        # ✨ Instruct Image
+        Create images from text instructions using AI.
+        """
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            prompt = gr.Textbox(
+                label="Instruction",
+                placeholder="A futuristic city at night with glowing neon lights",
+                lines=3
+            )
+
+            style = gr.Dropdown(
+                choices=list(STYLES.keys()),
+                value="None",
+                label="Style"
+            )
+
+            steps = gr.Slider(15, 50, value=30, step=1, label="Steps")
+            guidance = gr.Slider(1, 15, value=7.5, step=0.5, label="Guidance")
+
+            generate_btn = gr.Button("✨ Generate Image", variant="primary")
+
+        with gr.Column(scale=1):
+            output = gr.Image(label="Result", height=512)
+
+    generate_btn.click(
+        fn=generate,
+        inputs=[prompt, style, steps, guidance],
+        outputs=output
+    )
+
+    gr.Markdow