feat: Add download pickle button

dekwahdimas · Sep 12, 2024 · b9771df · b9771df
1 parent 4d0c08b
commit b9771df
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Showing 4 changed files with 27 additions and 10 deletions.
diff --git a/web_app/scripts/modeling_evaluation.py b/web_app/scripts/modeling_evaluation.py
@@ -21,7 +21,7 @@ def svm_pipeline(X_train, X_test, y_train, y_test):
     cr_svm = classification_report(y_test, y_pred_svm, target_names=['negative', 'neutral', 'positive'])
     cm_svm = confusion_matrix(y_test, y_pred_svm)
 
-    return cr_svm, cm_svm
+    return svm_pipeline, cr_svm, cm_svm
 
 
 # K-Nearest Neighbor pipeline
@@ -37,7 +37,7 @@ def knn_pipeline(X_train, X_test, y_train, y_test):
     cr_knn = classification_report(y_test, y_pred_knn, target_names=['negative', 'neutral', 'positive'])
     cm_knn = confusion_matrix(y_test, y_pred_knn)
 
-    return cr_knn, cm_knn
+    return knn_pipeline, cr_knn, cm_knn
 
 
 # Naive Bayes pipeline
@@ -53,7 +53,7 @@ def nb_pipeline(X_train, X_test, y_train, y_test):
     cr_nb = classification_report(y_test, y_pred_nb, target_names=['negative', 'neutral', 'positive'])
     cm_nb = confusion_matrix(y_test, y_pred_nb)
 
-    return cr_nb, cm_nb
+    return nb_pipeline, cr_nb, cm_nb
 
 
 def modeling_and_evaluation(filepath, chosen_model):
@@ -64,14 +64,14 @@ def modeling_and_evaluation(filepath, chosen_model):
 
     X = df["content"]
     y = df["hard_label"]
-
+    
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
 
     if chosen_model == 'svm':
-        cr, cm = svm_pipeline(X_train, X_test, y_train, y_test)
+        pipeline, cr, cm = svm_pipeline(X_train, X_test, y_train, y_test)
     elif chosen_model == 'knn':
-        cr, cm = knn_pipeline(X_train, X_test, y_train, y_test)
+        pipeline, cr, cm = knn_pipeline(X_train, X_test, y_train, y_test)
     elif chosen_model == 'nb':
-        cr, cm = nb_pipeline(X_train, X_test, y_train, y_test)
+        pipeline, cr, cm = nb_pipeline(X_train, X_test, y_train, y_test)
 
-    return cr, cm
+    return pipeline, cr, cm
diff --git a/web_app/templates/base.html b/web_app/templates/base.html
@@ -4,9 +4,10 @@
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>Google Play Store Sentiment Analysis</title>
-
+    
     <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css">
     <link rel="stylesheet" href="https://cdn.datatables.net/2.1.5/css/dataTables.bootstrap5.css">
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
 </head>
 <body>
     <!-- Start navbar -->

diff --git a/web_app/templates/features/modeling-evaluation.html b/web_app/templates/features/modeling-evaluation.html
@@ -48,6 +48,14 @@ <h5 class="m-0 font-weight-bold text-center">{{ context['feature_title'] }}</h5>
 </form>
 
 {% if context["classification_report"] %}
+<!-- Start button download pickle -->
+<div style="text-align: right;">
+    <a href="{{ url_for('views.download_model') }}" class="btn btn-primary">
+        <i class="fa fa-download"></i> Download Pickle</a>
+</div>
+<!-- End button download pickle -->
+<br>
+
 <div class="row">
     <div class="col">
         <div class="card shadow md-4">

diff --git a/web_app/views.py b/web_app/views.py
@@ -1,8 +1,10 @@
 import os
 from datetime import datetime
+import joblib
 
 from flask import Blueprint, request, current_app, render_template, redirect, send_from_directory, url_for
 from werkzeug.utils import secure_filename
+from werkzeug.security import safe_join
 import pytz
 
 from .scripts.scraping_reviews import scrape_reviews
@@ -103,7 +105,10 @@ def modeling_evaluation():
     if request.method == 'POST':
         filepath = upload_file()
         chosen_model = request.form['chosen_model']
-        cr, cm = modeling_and_evaluation(filepath, chosen_model)
+        pipeline, cr, cm = modeling_and_evaluation(filepath, chosen_model)
+        joblib.dump(pipeline, os.path.join(current_app.config['UPLOAD_FOLDER'], 'model_pipeline.pkl'))
+        # safe_path = safe_join(os.path.join(current_app.config['UPLOAD_FOLDER'], 'pickle'))
+        # joblib.dump(pipeline, safe_path, 'model_pipeline.pkl')
 
         context = {
             'feature_title': feature_title,
@@ -115,6 +120,9 @@ def modeling_evaluation():
 
     return render_template("features/modeling-evaluation.html", context={'feature_title': feature_title})
 
+@views.route('/download_model')
+def download_model():
+    return send_from_directory(current_app.config['UPLOAD_FOLDER'], 'model_pipeline.pkl')
 
 @views.route('/prediction')
 def prediction():