Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Pretrained vision-to-text model
+captioner = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
+
+def generate_caption(image):
+    result = captioner(image)[0]['generated_text']
+    return result
+
+# Gradio UI
+demo = gr.Interface(
+    fn=generate_caption,
+    inputs=gr.Image(type="filepath"),
+    outputs=gr.Textbox(label="Generated Caption"),
+    title="Mini Image Captioner",
+    description="Upload an image and get a natural language caption (Vision + LLM)"
+)
+
+if __name__ == "__main__":
+    demo.launch()