Added examples and changed header

app.py

@@ -10,28 +10,17 @@ glove_vectors = gensim.downloader.load('glove-twitter-25')
 labels = np.load('pca_labels.npy')
 vectors = np.load('pca_vectors.npy')
 
+sentence_examples = ["How did a bear climb up the tree ?", "It is a nice sunny day in India", "I am very excited to learn the concepts of NLP"]
+
 
 with gr.Blocks() as demo:
     gr.Markdown("""
 # ![ai bloq logo https://www.aibloq.com](https://aibloq.com/_next/image?url=%2FLogo.png&w=48&q=75) [Ai Bloq](https://www.aibloq.com)
 # How machines understand natural language
-## This NLP example is a part of Ai Bloq's Blog: **[How do machines understand text via Natural Language Processing (NLP)](https://www.aibloq.com)**
+## This NLP example is a part of Ai Bloq's Blog: **[Natural Language Processing: How Neural Word Embeddings Enable Machines to Understand Text](https://medium.com/@aryan_93507/how-do-machines-understand-text-via-natural-language-processing-nlp-41aeb853ef52)**
 ### For more such content and illustrative explanations visit [Ai Bloq's Resources](https://www.aibloq.com) and explore different machine learning and deep learning concepts
 ## **To create industry level artificially intelligent services and application sign up for a free demo account at [Ai Bloq](https://www.aibloq.com) :- A No-Code data science platform with industry level auto scaling capabilities**
     """)
-    with gr.Tab("Visualize words"):
-        sentence_input_viz = gr.Textbox(label="Enter a sentence")
-        pca_output = gr.Plot()
-
-        generate_pca_button = gr.Button("Visualize words in 3D space")
-    with gr.Tab("View word vectors"):
-        sentence_input = gr.Textbox(label="Enter a sentence")
-        vectors_output = gr.Plot()
-
-        generate_vectors_button = gr.Button("Generate vectors")
-
-    with gr.Accordion("Words not present in the vocabulary"):
-        excl_words_md = gr.Markdown("Enter a sentence and generate vectors first")
 
     def break_words(input_sentence):
 
@@ -48,10 +37,10 @@ with gr.Blocks() as demo:
 
         for word in words:
 
-            if glove_vectors.key_to_index.get(word.strip(), None) == None:
+            if glove_vectors.key_to_index.get(word.strip().lower(), None) == None:
                 excluded_words_state.append(word.strip())
             else:
-                final_words.append(word.strip())
+                final_words.append(word.strip().lower())
 
         if len(final_words) == 0:
             raise gr.Error("No word is present in the vocabulary, please try with another sentence")
@@ -127,6 +116,40 @@ with gr.Blocks() as demo:
 
         return [go.Figure(data=traces), excluded_words_state]
 
+    excl_words_md = None
+
+    with gr.Tab("Visualize words"):
+        sentence_input_viz = gr.Textbox(label="Enter a sentence")
+        pca_output = gr.Plot()
+
+        generate_pca_button = gr.Button("Visualize words in 3D space")
+
+        gr.Markdown("## Sentence Examples")
+        gr.Examples(
+            sentence_examples,
+            sentence_input_viz,
+            [pca_output, excl_words_md],
+            generate_pca_plot,
+            # cache_examples=True,
+        )
+    with gr.Tab("View word vectors"):
+        sentence_input = gr.Textbox(label="Enter a sentence")
+        vectors_output = gr.Plot()
+
+        generate_vectors_button = gr.Button("Generate vectors")
+
+        gr.Markdown("## Sentence Examples")
+        gr.Examples(
+            sentence_examples,
+            sentence_input,
+            [vectors_output, excl_words_md],
+            generate_vectors,
+            # cache_examples=True,
+        )
+
+    with gr.Accordion("Words not present in the vocabulary"):
+        excl_words_md = gr.Markdown("Enter a sentence and generate vectors first")
+    
     generate_vectors_button.click(generate_vectors, inputs=sentence_input, outputs=[vectors_output, excl_words_md])
     generate_pca_button.click(generate_pca_plot, inputs=sentence_input_viz, outputs=[pca_output, excl_words_md])