Update app.py

app.py

@@ -2,11 +2,11 @@ import streamlit as st
 from transformers import pipeline
 from PIL import Image
 
-# Page config
+# Setup
 st.set_page_config(page_title="TinyLLaVA Snapshot Q&A", layout="centered")
-st.title("📸 TinyLLaVA - Snapshot Q&A (Hugging Face Spaces)")
+st.title("📸 TinyLLaVA — Snapshot Q&A (Spaces Safe)")
 
-# Load TinyLLaVA pipeline
+# Load model
 pipe = pipeline(
     task="image-to-text",
     model="bczhou/tiny-llava-v1-hf",
@@ -14,19 +14,27 @@ pipe = pipeline(
     device_map="cpu"
 )
 
-# Always visible camera input
+# 👇 Clear info so the widget tree is stable
+st.markdown("Use your **webcam** OR upload a file:")
+
+# Try webcam first
 image = st.camera_input("📷 Take a snapshot")
 
-# Prompt text input
+# Fallback uploader
+if not image:
+    image = st.file_uploader("📂 Or upload an image", type=["jpg", "png", "jpeg"])
+
+# Prompt
 prompt = st.text_input("💬 Your question:", value="Describe this scene.")
 
-# If both present, run inference
+# Run TinyLLaVA
 if image is not None and prompt:
     img = Image.open(image).convert("RGB")
-    st.image(img, caption="Your Snapshot", use_column_width=True)
+    st.image(img, caption="Your Image", use_column_width=True)
 
     query = f"USER: <image>\n{prompt}\nASSISTANT:"
-    with st.spinner("TinyLLaVA is generating..."):
+
+    with st.spinner("Generating..."):
         result = pipe(query, img)
         answer = result[0]["generated_text"]