Create 2_Emotion_Recognition.py

pages/2_Emotion_Recognition.py

@@ -0,0 +1,59 @@
+import streamlit as st
+from PIL import Image
+import tempfile
+from deepface import DeepFace
+from openai import OpenAI
+
+# Initialize OpenAI
+client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
+
+st.title("📸 Shaafee - Emotion Recognition")
+
+st.write(
+    "Upload your selfie — I’ll detect your emotion and suggest a Qur'anic Ayah for you."
+)
+
+# Upload file
+uploaded_file = st.file_uploader("Choose a selfie image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    img = Image.open(uploaded_file).convert("RGB")
+    st.image(img, caption="Your Uploaded Selfie", use_container_width=True)
+
+    # Save temporarily
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp_file:
+        img.save(tmp_file.name)
+        image_path = tmp_file.name
+
+    # Analyze with DeepFace
+    with st.spinner("Analyzing your emotion..."):
+        result = DeepFace.analyze(img_path=image_path, actions=["emotion"], enforce_detection=False)
+
+    dominant_emotion = result[0]["dominant_emotion"] if isinstance(result, list) else result["dominant_emotion"]
+    dominant_emotion = dominant_emotion.lower()
+
+    st.success(f"😊 Detected Emotion: *{dominant_emotion.capitalize()}*")
+
+    # Ask OpenAI for Ayah for this emotion
+    prompt = f"""
+    Suggest a Qur'anic Ayah in Arabic for someone feeling '{dominant_emotion}'.
+    Include:
+    1) The Ayah in Arabic
+    2) Its English translation
+    3) A short, simple tafsir.
+    Be gentle and authentic.
+    """
+
+    try:
+        response = client.chat.completions.create(
+            model="gpt-4o-mini",
+            messages=[{"role": "user", "content": prompt}]
+        )
+
+        output = response.choices[0].message.content
+
+        st.subheader("🕋 Qur'anic Guidance")
+        st.write(output)
+
+    except Exception as e:
+        st.error(f"❌ API Error: {e}")