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Dockerfile

@@ -1,20 +1,30 @@
-FROM python:3.13.5-slim
+FROM python:3.9-slim
 
 WORKDIR /app
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
 
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    git \
-    && rm -rf /var/lib/apt/lists/*
+# Install OS deps (optional but good for SSL/timezones)
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ca-certificates curl && \
+    rm -rf /var/lib/apt/lists/*
 
-COPY requirements.txt ./
-COPY src/ ./src/
+# Copy app
+COPY . /app
 
-RUN pip3 install -r requirements.txt
+# Copy and install Python deps
+# COPY requirements.txt /app/requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
 
-EXPOSE 8501
 
-HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
 
-ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+# Hugging Face expects 7860
+EXPOSE 7860
+
+# Streamlit default settings suitable for Spaces
+ENV STREAMLIT_SERVER_PORT=7860
+ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
+ENV STREAMLIT_BROWSER_GATHER_USAGE_STATS=false
+
+# Run
+CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0"]

app.py

@@ -0,0 +1,49 @@
+import streamlit as st
+import requests
+
+# Backend URL (update this with your deployed backend URL)
+BACKEND_URL = "https://rajendrakumarpachaiappan-extraa-learn-backend.hf.space/predict"
+
+st.set_page_config(page_title="ExtraaLearn Lead Prediction", layout="centered")
+
+st.title("ExtraaLearn - Lead Conversion Prediction")
+st.write("Fill the form below to predict whether a lead is likely to convert.")
+
+# Collect user input
+current_occupation = st.selectbox("Current Occupation", ["Student", "Working Professional", "Other"])
+first_interaction = st.selectbox("First Interaction", ["Website", "Mobile App", "Other"])
+profile_completed = st.selectbox("Profile Completed", ["Yes", "No"])
+last_activity = st.selectbox("Last Activity", ["Email Opened", "Page Visited", "Form Submitted", "Other"])
+print_media_type1 = st.radio("Print Media Type 1", ["Yes", "No"])
+print_media_type2 = st.radio("Print Media Type 2", ["Yes", "No"])
+digital_media = st.radio("Digital Media", ["Yes", "No"])
+educational_channels = st.radio("Educational Channels", ["Yes", "No"])
+referral = st.radio("Referral", ["Yes", "No"])
+
+# Submit button
+if st.button("Predict Lead Conversion"):
+    payload = {
+        "current_occupation": current_occupation,
+        "first_interaction": first_interaction,
+        "profile_completed": profile_completed,
+        "last_activity": last_activity,
+        "print_media_type1": print_media_type1,
+        "print_media_type2": print_media_type2,
+        "digital_media": digital_media,
+        "educational_channels": educational_channels,
+        "referral": referral
+    }
+
+    try:
+        response = requests.post(BACKEND_URL, json=payload)
+        if response.status_code == 200:
+            result = response.json()
+            prediction = result.get("prediction")
+            if prediction == 1:
+                st.success("This lead is **likely to convert!**")
+            else:
+                st.error("This lead is **not likely to convert.**")
+        else:
+            st.error(f"Error: {response.text}")
+    except Exception as e:
+        st.error(f"Request failed: {str(e)}")

extraa_learn_project.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e3d73d72aae8deaf826eac03287444ad286e091625841015311eb65714e397a9
+size 3314409

requirements.txt

@@ -1,3 +1,3 @@
-altair
-pandas
-streamlit
+
+streamlit
+requests