DataGlacier · Kaiyfa · May 6, 2025 · May 14, 2025 · Jun 4, 2025 · Jun 4, 2025
diff --git a/.gitignore b/.gitignore
@@ -127,3 +127,4 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+.DS_Store
diff --git a/add.py b/add.py
@@ -0,0 +1,10 @@
+# Get user input for name and favorite sport
+name = input("Adama Sall: ")
+favorite_sport = input("Basketball: ")
+
+# Display the collected information
+print("\nHello,", name + "!")
+print("Your favorite sport is:", favorite_sport)
+
+# Wait for user to press Enter before closing
+input("\nPress Enter to exit...")
diff --git a/flask_ml_app/app.py b/flask_ml_app/app.py
@@ -0,0 +1,19 @@
+from flask import Flask, request, render_template
+import joblib
+import numpy as np
+
+app = Flask(__name__)
+model = joblib.load('model.joblib')
+
+@app.route('/')
+def home():
+    return render_template('index.html')
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    features = [float(x) for x in request.form.values()]
+    prediction = model.predict([features])
+    return f"Predicted class: {prediction[0]}"
+
+if __name__ == '__main__':
+    app.run(debug=True)
diff --git a/flask_ml_app/create_pdf.py b/flask_ml_app/create_pdf.py
@@ -0,0 +1,57 @@
+from reportlab.lib.pagesizes import letter
+from reportlab.pdfgen import canvas
+from reportlab.lib.utils import ImageReader
+import os
+
+def create_pdf():
+    # Setup PDF
+    c = canvas.Canvas("deployment_documentation.pdf", pagesize=letter)
+    width, height = letter
+
+    # Add metadata
+    c.setTitle("Model Deployment Documentation")
+
+    # 1. Header Section
+    c.setFont("Helvetica-Bold", 16)
+    c.drawCentredString(width/2, height-50, "AI Model Deployment Report")
+
+    c.setFont("Helvetica", 12)
+    c.drawString(100, height-80, "Name: Adama")
+    c.drawString(100, height-100, "Batch Code: LISUM45")
+    c.drawString(100, height-120, "Submission Date: 2025-05-28")
+    c.drawString(100, height-140, "Submitted to: DAta Glacier intership week 4")
+
+    # 2. Add screenshots (ensure these files exist)
+    screenshot_dir = "screenshots"
+    screenshots = [
+        ("1_model_training.png", "Step 1: Model Training Output"),
+        ("2_flask_server.png", "Step 2: Flask Server Running"), 
+        ("3_web_interface.png", "Step 3: Web Application"),
+        ("4_prediction.png", "Step 4: Prediction Result")
+    ]
+
+    y_position = height-180
+    for i, (filename, description) in enumerate(screenshots):
+        if os.path.exists(f"{screenshot_dir}/{filename}"):
+            # Add description
+            c.drawString(100, y_position, description)
+            y_position -= 20
+
+            # Add image (scaled to 400px width)
+            img = ImageReader(f"{screenshot_dir}/{filename}")
+            img_width = 400
+            img_height = img._image.size[1] * (img_width/img._image.size[0])
+            c.drawImage(img, 100, y_position-img_height, width=img_width, height=img_height)
+            y_position -= img_height + 40
+
+            # Add new page if needed
+            if y_position < 100 and i < len(screenshots)-1:
+                c.showPage()
+                y_position = height-50
+
+    # Save PDF
+    c.save()
+    print("PDF successfully generated!")
+
+if __name__ == "__main__":
+    create_pdf()
diff --git a/flask_ml_app/deployment_documentation.pdf b/flask_ml_app/deployment_documentation.pdf
diff --git a/flask_ml_app/model.joblib b/flask_ml_app/model.joblib
diff --git a/flask_ml_app/screenshots/1_model_training.png b/flask_ml_app/screenshots/1_model_training.png
diff --git a/flask_ml_app/screenshots/2_flask_server.png b/flask_ml_app/screenshots/2_flask_server.png
diff --git a/flask_ml_app/screenshots/3_web_interface.png b/flask_ml_app/screenshots/3_web_interface.png
diff --git a/flask_ml_app/screenshots/4_prediction.png b/flask_ml_app/screenshots/4_prediction.png
diff --git a/flask_ml_app/templates/index.html b/flask_ml_app/templates/index.html
@@ -0,0 +1,13 @@
+<!DOCTYPE html>
+<html>
+<body>
+  <h2>Iris Classifier</h2>
+  <form action="/predict" method="post">
+    Sepal Length: <input type="text" name="sepal_length"><br>
+    Sepal Width: <input type="text" name="sepal_width"><br>
+    Petal Length: <input type="text" name="petal_length"><br>
+    Petal Width: <input type="text" name="petal_width"><br>
+    <input type="submit" value="Predict">
+  </form>
+</body>
+</html>
diff --git a/flask_ml_app/train.py b/flask_ml_app/train.py
@@ -0,0 +1,15 @@
+from sklearn.datasets import load_iris
+from sklearn.ensemble import RandomForestClassifier
+import joblib
+import pandas as pd
+
+# Step 1: Load toy data
+iris = load_iris()
+X, y = iris.data, iris.target
+
+# Step 2: Train and save model
+model = RandomForestClassifier()
+model.fit(X, y)
+joblib.dump(model, 'model.joblib')
+
+print("Model trained and saved!")
Original file line number	Diff line number	Diff line change
Expand Up		@@ -127,3 +127,4 @@ dmypy.json

		# Pyre type checker
		.pyre/
		.DS_Store