Update app.py

app.py

@@ -18,11 +18,11 @@ def calculate_similarities(sentence1, sentence2):
     tfidf_matrix = tfidf_vectorizer.fit_transform([sentence1, sentence2])
     tfidf_score = cosine_similarity(tfidf_matrix[0:1], tfidf_matrix[1:2])[0][0]
     
-    # Return two separate values instead of a dictionary
     return float(wordllama_score), float(tfidf_score)
 
-# Extended examples with more diverse sentences
+# Examples combining original and new homophone-based examples
 examples = [
+    # Original examples
     ["I went to the car", "I went to the pawn shop"],
     ["The cat is on the roof", "A dog is in the yard"],
     ["She loves playing tennis", "She enjoys sports"],
@@ -32,23 +32,72 @@ examples = [
     ["Python is a programming language", "Java is used for coding"],
     ["The movie was entertaining", "I enjoyed watching the film"],
     ["Climate change affects our planet", "Global warming is a serious issue"],
-    ["Students study in the library", "People read books in the library"]
+    ["Students study in the library", "People read books in the library"],
+    
+    # New examples with similar words but different meanings
+    ["The executive board met this morning", "I was so bored during the meeting"],
+    ["Don't waste your time on this", "The dress fits perfectly at the waist"],
+    ["The principal called a meeting", "It's a matter of principle"],
+    ["The weather is beautiful today", "I don't know whether to go or stay"],
+    ["I need a piece of the cake", "The world needs peace"],
+    ["The bass was swimming in the lake", "Turn up the bass in the speaker"],
+    ["The fair is in town this weekend", "That decision wasn't fair at all"],
+    ["I need to address this letter", "What's your new address?"],
+    ["The bank of the river is muddy", "I need to go to the bank for money"],
+    ["Can you bear this weight?", "I saw a bear in the woods"]
 ]
 
 # Define Gradio interface with updated layout
-with gr.Blocks() as iface:
-    gr.Markdown("# Text Similarity Comparison")
-    gr.Markdown("Compare sentences using both WordLlama and TF-IDF similarity metrics")
+with gr.Blocks(theme=gr.themes.Soft()) as iface:
+    gr.Markdown("# Advanced Text Similarity Comparison")
+    gr.Markdown("""
+    Compare sentences using both WordLlama and TF-IDF similarity metrics.
+    This tool includes examples of similar words with different meanings to demonstrate semantic understanding.
+    """)
     
     with gr.Row():
-        sentence1 = gr.Textbox(lines=2, placeholder="Enter first sentence...", label="First Sentence")
-        sentence2 = gr.Textbox(lines=2, placeholder="Enter second sentence...", label="Second Sentence")
+        with gr.Column():
+            sentence1 = gr.Textbox(
+                lines=2,
+                placeholder="Enter first sentence...",
+                label="First Sentence",
+                info="Type or select from examples below"
+            )
+        with gr.Column():
+            sentence2 = gr.Textbox(
+                lines=2,
+                placeholder="Enter second sentence...",
+                label="Second Sentence",
+                info="Type or select from examples below"
+            )
     
-    button = gr.Button("Calculate Similarities")
+    button = gr.Button("Calculate Similarities", variant="primary")
     
     with gr.Row():
-        wordllama_output = gr.Number(label="WordLlama Similarity")
-        tfidf_output = gr.Number(label="TF-IDF Similarity")
+        wordllama_output = gr.Number(
+            label="WordLlama Similarity",
+            info="Contextual similarity score (0-1)",
+            value=0.0
+        )
+        tfidf_output = gr.Number(
+            label="TF-IDF Similarity",
+            info="Term frequency-based similarity score (0-1)",
+            value=0.0
+        )
+    
+    gr.Markdown("""
+    ### Understanding the Scores
+    - **WordLlama Similarity**: Measures semantic similarity considering context and meaning
+    - **TF-IDF Similarity**: Measures similarity based on word frequency and importance
+    """)
+    
+    gr.Markdown("### Example Sentence Pairs")
+    gr.Markdown("""
+    The examples include:
+    - Regular sentence pairs
+    - Sentences with similar words but different meanings (homophones)
+    - Contextually related sentences
+    """)
     
     button.click(
         calculate_similarities,
@@ -56,10 +105,11 @@ with gr.Blocks() as iface:
         outputs=[wordllama_output, tfidf_output]
     )
     
-    gr.Markdown("### Example Sentence Pairs")
     gr.Examples(
         examples=examples,
-        inputs=[sentence1, sentence2]
+        inputs=[sentence1, sentence2],
+        label="Click on any example to load it"
     )
 
+# Launch the interface
 iface.launch(share=True)