Upload app and requirements

app.py

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+import gradio as gr
+from PIL import Image
+from smodel.llava_inference import LLaVAHelper
+
+model = LLaVAHelper()
+
+def answer_question(image, question):
+    if image is None or question.strip() == "":
+        return "Please upload an image and enter a question."
+    return model.generate_answer(image, question)
+
+demo = gr.Interface(
+    fn=answer_question,
+    inputs=[
+        gr.Image(type="pil", label="Upload Public Transport Signage"),
+        gr.Textbox(label="Ask a question (e.g., 'When is the next train to London?')")
+    ],
+    outputs=gr.Textbox(label="Answer"),
+    title="UK Public Transport Assistant",
+    description="Upload an image of UK public transport signage (like train timetables or metro maps), and ask a question related to it. Powered by LLaVA-1.5.",
+    examples=[
+        ["assets/example.jpg", "Where is platform 3?"],
+    ]
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+torch
+transformers
+accelerate
+gradio
+llava