Update app.py

app.py

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+import os
+from typing import List, Tuple
+import torch
+import gradio as gr
+from PIL import Image
+from transformers import AutoProcessor, AutoModelForVision2Seq
+
+# ---------- Config ----------
+MODEL_NAME = os.getenv("MODEL_NAME", "Qwen/Qwen2-VL-2B-Instruct")  # Smaller CPU-friendly model
+MAX_NEW_TOKENS = int(os.getenv("MAX_NEW_TOKENS", "512"))
+
+DISCLAIMER = (
+    "⚠️ **Disclaimer:** This tool provides general information and is **not** a substitute for "
+    "official emergency guidance. In an emergency, follow directions from local authorities."
+)
+
+# ---------- Load model ----------
+device = "cuda" if torch.cuda.is_available() else "cpu"
+dtype = torch.float16 if device == "cuda" else torch.float32
+
+print(f"Loading model: {MODEL_NAME} on {device} ({dtype})")
+
+processor = AutoProcessor.from_pretrained(MODEL_NAME)
+model = AutoModelForVision2Seq.from_pretrained(
+    MODEL_NAME,
+    torch_dtype=dtype
+).to(device)
+
+# ---------- Core logic ----------
+DEFAULT_QUESTION = (
+    "Identify the type of natural disaster in this image and give immediate and long-term "
+    "precautionary / preparedness measures, with a short disclaimer."
+)
+
+def analyze(image: Image.Image, question: str, history: List[Tuple[str, str]]):
+    if image is None:
+        return history, "❌ Please upload an image first."
+    if not question.strip():
+        question = DEFAULT_QUESTION
+
+    # Prepare input for Qwen2-VL
+    inputs = processor(images=image, text=question, return_tensors="pt").to(device)
+    output_ids = model.generate(**inputs, max_new_tokens=MAX_NEW_TOKENS)
+    answer = processor.decode(output_ids[0], skip_special_tokens=True)
+
+    answer = answer.strip() + "\n\n" + DISCLAIMER
+    history.append((question, answer))
+    return history, ""
+
+def clear():
+    return [], ""
+
+# ---------- Gradio UI ----------
+with gr.Blocks(title="Disaster Precaution Chatbot (Qwen2-VL + Gradio)") as demo:
+    gr.Markdown("# 🌪️ Disaster Precaution Chatbot")
+    gr.Markdown(
+        "Upload an image that shows a natural disaster (or its aftermath) and ask for "
+        "precautionary / preparedness measures."
+    )
+    gr.Markdown(DISCLAIMER)
+
+    state = gr.State([])
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            img_input = gr.Image(type="pil", label="Upload disaster image")
+            txt_input = gr.Textbox(
+                label="Your question (optional)",
+                placeholder="e.g., What should I do to prepare for this?"
+            )
+            analyze_btn = gr.Button("Analyze Image", variant="primary")
+            clear_btn = gr.Button("Clear Chat", variant="secondary")
+
+        with gr.Column(scale=1):
+            chatbot = gr.Chatbot(label="Chatbot", height=480, show_copy_button=True)
+
+    analyze_btn.click(
+        fn=analyze,
+        inputs=[img_input, txt_input, state],
+        outputs=[chatbot, txt_input]
+    )
+
+    clear_btn.click(fn=clear, inputs=[], outputs=[chatbot, txt_input])
+
+if __name__ == "__main__":
+    demo.launch()