Update app.py

app.py

@@ -1,15 +1,48 @@
 import streamlit as st
+import requests
 
-# Page setup
-st.set_page_config(page_title="Hello World App", page_icon="👋", layout="centered")
+# ✅ Page setup
+st.set_page_config(page_title="IMDB Sentiment Analyzer 🎬", page_icon="🎬", layout="centered")
 
-# Simple UI
-st.title("👋 Hello, Hugging Face + Streamlit!")
-st.write("If you see this message, your Space is working correctly 🚀")
+# Hugging Face model API
+API_URL = "https://api-inference.huggingface.co/models/ibrahim313/my-imdb-sentiment-analyzer"
 
-name = st.text_input("What's your name?")
-if st.button("Say Hello"):
-    if name.strip():
-        st.success(f"Hello, {name}! 🎉")
+# Auth headers if private model
+headers = {}
+if "HF_TOKEN" in st.secrets:
+    headers = {"Authorization": f"Bearer {st.secrets['HF_TOKEN']}"}
+
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
+
+# --- UI ---
+st.title("🎬 IMDB Sentiment Analyzer")
+st.markdown("### Predict whether a movie review is **Positive 😀** or **Negative 😞**")
+
+# Pre-filled example
+default_text = "I really loved this movie, the acting was fantastic and the story was emotional."
+user_input = st.text_area("✍️ Enter your review below:", value=default_text, height=150)
+
+if st.button("🔍 Analyze Sentiment"):
+    if user_input.strip() == "":
+        st.warning("⚠️ Please enter some text")
     else:
-        st.warning("Please enter your name above 👆")
+        result = query({"inputs": user_input})
+
+        if isinstance(result, list) and len(result) > 0 and isinstance(result[0], list):
+            label = result[0][0]["label"]
+            score = result[0][0]["score"]
+
+            # Emoji for label
+            emoji = "😀" if "pos" in label.lower() else "😞"
+
+            st.markdown(f"### {emoji} Prediction: **{label}**")
+            st.progress(min(max(score, 0.0), 1.0))  # Clamp between 0-1
+            st.caption(f"Confidence: {score:.2%}")
+        else:
+            st.error(f"⚠️ Error from model: {result}")
+
+# Footer
+st.markdown("---")
+st.caption("Built with ❤️ using Streamlit + Hugging Face")