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Dockerfile

@@ -1,21 +1,18 @@
+# Use a minimal base image with Python 3.9 installed
 FROM python:3.9-slim
 
+# Set the working directory inside the container to /app
 WORKDIR /app
 
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    software-properties-common \
-    git \
-    && rm -rf /var/lib/apt/lists/*
-
-COPY requirements.txt ./
-COPY src/ ./src/
+# Copy all files from the current directory on the host to the container's /app directory
+COPY . .
 
+# Install Python dependencies listed in requirements.txt
 RUN pip3 install -r requirements.txt
 
 EXPOSE 8501
 
-HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
+# Define the command to run the Streamlit app on port 8501 and make it accessible externally
+CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0", "--server.enableXsrfProtection=false"]
 
-ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+# NOTE: Disable XSRF protection for easier external access in order to make batch predictions

app.py

@@ -0,0 +1,53 @@
+# ----------------------
+# Streamlit UI (Frontend)
+# ----------------------
+import requests
+import streamlit as st
+
+st.title("Introvert vs Extrovert Predictor")
+
+# Single Prediction Section
+st.subheader("Predict Personality Type for a Single Entry")
+
+# Input fields
+Time_spent_Alone = st.slider("Time Spent Alone (hours per day)", min_value=0, max_value=24, value=5)
+Social_event_attendance = st.slider("Social Event Attendance (events per month)", min_value=0, max_value=30, value=5)
+Going_outside = st.slider("Going Outside Frequency (days per week)", min_value=0, max_value=7, value=3)
+Friends_circle_size = st.slider("Friends Circle Size", min_value=0, max_value=100, value=10)
+Post_frequency = st.slider("Social Media Post Frequency (posts per week)", min_value=0, max_value=50, value=5)
+Stage_fear = st.selectbox("Do you have stage fear?", ["Yes", "No"])
+Drained_after_socializing = st.selectbox("Do you feel drained after socializing?", ["Yes", "No"])
+
+API_BASE = "https://udbhav90-introvert-extrovert-predictor.hf.space"
+
+if st.button("🔍 Predict Personality"):
+    payload = {
+        "Time_spent_Alone": Time_spent_Alone,
+        "Social_event_attendance": Social_event_attendance,
+        "Going_outside": Going_outside,
+        "Friends_circle_size": Friends_circle_size,
+        "Post_frequency": Post_frequency,
+        "Stage_fear": 1 if Stage_fear.lower() == "yes" else 0,
+        "Drained_after_socializing": 1 if Drained_after_socializing.lower() == "yes" else 0
+    }
+
+    res = requests.post(f"{API_BASE}/v1/personality/predict", json=payload)
+
+    if res.status_code == 200:
+        st.success(f" Predicted Personality Type: {res.json()['Personality_Type']}")
+    else:
+        st.error("Failed to get prediction. Check backend logs.")
+
+# Batch Prediction
+st.subheader("Batch CSV Prediction")
+
+batch_file = st.file_uploader("Upload CSV file", type=["csv"])
+
+if batch_file is not None and st.button("Predict Batch"):
+    response = requests.post(f"{API_BASE}/v1/personality/predictbatch", files={"file": batch_file})
+    if response.status_code == 200:
+        result = response.json()
+        st.write("Prediction Results:")
+        st.dataframe(pd.DataFrame(result))
+    else:
+        st.error("Error from backend during batch prediction")

requirements.txt

@@ -1,3 +1,3 @@
-altair
-pandas
-streamlit
+pandas==2.2.2
+requests==2.28.1
+streamlit==1.43.2