Added Large Word2Vec and updated project

.gitignore

@@ -139,4 +139,7 @@ dmypy.json
 .idea
 
 # Media Dirs
-media/
+media/
+
+# Large Word2Vect]
+model/model-word2vec-300d.txt

analyzer/models.py

@@ -91,6 +91,6 @@ def prediction(self):
         data = np.reshape(data, (1, 100, 300))
 
         with graph.as_default():
-            model = load_model("model/LSTM-CNN-MODEL.h5")  # load model
+            model = load_model("model/LSTM-CNN-Model.h5")  # load model
             print(model.predict(np.array(data)))
             return model.predict(np.array(data))

analyzer/templates/analyzer/home.html

@@ -57,7 +57,7 @@
         </div>
     </div>
 
-    <div class="app-content">
+    <div class="app-content" id="container">
         <div class="app-sidebar">
             <a href="" class="app-sidebar-link active">
                 <svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="feather feather-home">
@@ -133,7 +133,6 @@
             <div class="project-boxes jsGridView">
                 {% if documents %}
                 {% for document in documents %}
-<!--                        <li><a href="{{ document.docfile.url }}">{{ document.docfile.name }}</a></li>-->
                 <div class="project-box-wrapper">
                     <div class="project-box" style="background-color: #a0e989;">
                         <div class="project-box-header" style="margin: 0;">
@@ -185,25 +184,40 @@
     function processData(link) {
         jQuery.get(link, function(data) {
             let Text = data;
-            console.log(Text)
+            console.log(Text);
+
+            let newDiv = document.createElement("div");
+            newDiv.className = "alert alert-success";
+            newDiv.role = "alert";
+            newDiv.innerHTML = "<button type=\"button\" class=\"close\" data-dismiss=\"alert\" aria-label=\"Close\"><span aria-hidden=\"true\">&times;</span></button>\n" +
+                "Wait a minute... Model analyze your text";
+
+            $("#container").before(newDiv);
 
             $.ajax({
                 headers: { "X-CSRFToken": getCookie("csrftoken") },
                 type: "POST",
                 url: '/predict/',
                 data: {Text: Text},
-                success: function (data) {
-                    console.log(data);
-                    window.location.href = "{% url 'prediction' %}";
+
+                success: function() {
+                    window.location = "{% url 'prediction' %}";
                 },
 
-                error: function (xhr, status) {
-                    console.log(xhr);
-                    window.location.href = "{% url 'prediction' %}";
+                error: function () {
+                    let newDiv = document.createElement("div");
+                    newDiv.className = "alert alert-danger";
+                    newDiv.role = "alert";
+                    newDiv.innerHTML = "<button type=\"button\" class=\"close\" data-dismiss=\"alert\" aria-label=\"Close\"><span aria-hidden=\"true\">&times;</span></button>\n" +
+                        "An error occurred while trying to predict the result...";
+
+                    $("#container").before(newDiv);
                 }
             });
         });
     }
     </script>
+<script src="https://cdn.jsdelivr.net/npm/popper.js@1.16.1/dist/umd/popper.min.js" integrity="sha384-9/reFTGAW83EW2RDu2S0VKaIzap3H66lZH81PoYlFhbGU+6BZp6G7niu735Sk7lN" crossorigin="anonymous"></script>
+<script src="https://cdn.jsdelivr.net/npm/bootstrap@4.6.0/dist/js/bootstrap.min.js" integrity="sha384-+YQ4JLhjyBLPDQt//I+STsc9iw4uQqACwlvpslubQzn4u2UU2UFM80nGisd026JF" crossorigin="anonymous"></script>
 </body>
 </html>

analyzer/urls.py

@@ -1,5 +1,7 @@
 from django.urls import path
 from django.contrib.auth.decorators import login_required
+from django.views.generic import TemplateView
+
 from . import views
 from .views import upload
 

analyzer/views.py

@@ -38,14 +38,20 @@ def upload(request):
     return render(request, 'analyzer/upload.html', context)
 
 
+VALID = []
+
+
 def prediction(request):
     text = request.POST.get('Text', False)
-    sent = Sentence(str(text))
-    predict = sent.prediction()
 
-    print(str(text))
+    if text != False:
+        sent = Sentence(str(text))
+        predict = sent.prediction()
+        VALID.append(predict)
+    else:
+        predict = VALID[-1]
 
     print("Prediction is :", float(predict))
-    context = {'prediction':  round(float(predict), 2) * 100, 'sent': sent}
+    context = {'prediction':  round(float(predict), 2) * 100, 'sent': str(text)}
 
-    return render(request, 'analyzer/predict.html', context)
+    return render(request, 'analyzer/predict.html', context)