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# backend_files/app.py
import joblib
import pandas as pd
from flask import Flask, request, jsonify
# Initialize Flask app
app = Flask("ExtraaLearn Lead Conversion Predictor")
# Load the trained lead-conversion model
model = joblib.load("my_model_v1_0.joblib")
@app.get("/")
def home():
return (
"Welcome to the ExtraaLearn Lead Conversion Prediction API - "
"Use POST /v1/lead for single prediction or POST /v1/leadbatch to upload CSV."
)
@app.post("/v1/lead")
def predict_lead():
"""
Expects JSON body with the lead features only.
"""
try:
lead_json = request.get_json(force=True)
except Exception as e:
return jsonify({"error": "Invalid or missing JSON body", "details": str(e)}), 400
# Features used during model training
expected_features = [
"age", "current_occupation", "first_interaction", "profile_completed",
"website_visits", "time_spent_on_website", "page_views_per_visit",
"last_activity", "EmailActivity", "PhoneActivity", "WebsiteActivity",
"print_media_type1", "print_media_type2", "digital_media",
"educational_channels", "referral"
]
# Build sample
sample = {f: lead_json.get(f, None) for f in expected_features}
input_df = pd.DataFrame([sample])
try:
raw_pred = model.predict(input_df)[0] # returns 0 or 1
label = "Converted" if raw_pred == 1 else "Not Converted"
return jsonify({"Prediction": label})
except Exception as e:
return jsonify({
"error": "Model prediction failed.",
"details": str(e),
"sample_input": sample
}), 500
@app.post("/v1/leadbatch")
def predict_lead_batch():
"""
Expects a 'file' in form-data (CSV).
CSV must contain only model features.
"""
if "file" not in request.files:
return jsonify({"error": "No file uploaded. Please attach a CSV with key 'file'."}), 400
file = request.files["file"]
if file.filename == "":
return jsonify({"error": "Empty filename. Please upload a valid CSV file."}), 400
try:
df = pd.read_csv(file)
except Exception as e:
return jsonify({"error": "Failed to read CSV file.", "details": str(e)}), 400
try:
raw_preds = model.predict(df).tolist()
results = ["Converted" if int(pred) == 1 else "Not Converted" for pred in raw_preds]
return jsonify({"Predictions": results})
except Exception as e:
return jsonify({
"error": "Batch prediction failed.",
"details": str(e)
}), 500
if __name__ == "__main__":
app.run(debug=True, host="0.0.0.0", port=5000)
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