Update app.py

app.py

@@ -7,52 +7,54 @@ def load_model(model_name):
     return SentenceTransformer(model_name)
 
 # Function to compute similarity and classify relationship
-def predict(original_sentence_input, *sentences_to_compare):
+def predict(model_name_display, original_sentence_input, sentence_1=None, sentence_2=None, sentence_3=None):
     model_name = "sartifyllc/African-Cross-Lingua-Embeddings-Model"
     model = load_model(model_name)
     result = {
         "Model Name": model_name,
         "Original Sentence": original_sentence_input,
-        "Sentences to Compare": sentences_to_compare,
+        "Sentences to Compare": {
+            "Sentence 1": sentence_1,
+            "Sentence 2": sentence_2,
+            "Sentence 3": sentence_3
+        },
         "Similarity Scores": {}
     }
     
-    if original_sentence_input and sentences_to_compare:
-        sentences = [original_sentence_input] + list(sentences_to_compare)
-        embeddings = model.encode(sentences)
-        original_embedding = embeddings[0]
-
-        for i, sentence in enumerate(sentences_to_compare, start=1):
-            similarity_score = util.pytorch_cos_sim(original_embedding, embeddings[i]).item()
-            result["Similarity Scores"][f"Sentence {i}"] = similarity_score
+    if not sentence_1 or not sentence_2 or not sentence_3:
+        return "Please provide a minimum of three sentences for comparison.", {}
+    if not original_sentence_input:
+        return "Please provide the original sentence.", {}
+    
+    sentences = [original_sentence_input, sentence_1, sentence_2, sentence_3]
+    embeddings = model.encode(sentences)
+    similarities = util.cos_sim(embeddings[0], embeddings[1:])
+    similarity_scores = {
+        "Sentence 1": float(similarities[0, 0]),
+        "Sentence 2": float(similarities[0, 1]),
+        "Sentence 3": float(similarities[0, 2])
+    }
+    result["Similarity Scores"] = similarity_scores
     
     return result
 
-# Define inputs and outputs for Gradio interface
 model_name_display = gr.Markdown(value="**Model Name**: sartifyllc/African-Cross-Lingua-Embeddings-Model")
 original_sentence_input = gr.Textbox(lines=2, placeholder="Enter the original sentence here...", label="Original Sentence")
 
-# Initial sentence comparison inputs
-sentence_to_compare_inputs = [
-    gr.Textbox(lines=2, placeholder="Enter the sentence you want to compare...", label="Sentence to Compare 1"),
-    gr.Textbox(lines=2, placeholder="Enter the sentence you want to compare...", label="Sentence to Compare 2"),
-    gr.Textbox(lines=2, placeholder="Enter the sentence you want to compare...", label="Sentence to Compare 3")
-]
+sentence_1 = gr.Textbox(lines=2, placeholder="Enter the first sentence here...", label="Sentence 1")
+sentence_2 = gr.Textbox(lines=2, placeholder="Enter the second sentence here...", label="Sentence 2")
+sentence_3 = gr.Textbox(lines=2, placeholder="Enter the third sentence here...", label="Sentence 3")
 
+inputs = [model_name_display, original_sentence_input, sentence_1, sentence_2, sentence_3]
 outputs = gr.JSON(label="Detailed Similarity Scores")
 
-def create_interface():
-    inputs_dynamic = [model_name_display, original_sentence_input, sentence_to_compare_inputs]
-    return gr.Interface(
-        fn=predict,
-        title="African Cross-Lingua Embeddings Model's Demo",
-        description="Compute the semantic similarity across various sentences among any African Languages using African-Cross-Lingua-Embeddings-Model.",
-        inputs=inputs_dynamic,
-        outputs=outputs,
-        live=False,
-        allow_flagging="never"
-    )
-
-# Create and launch the initial interface
-interface = create_interface()
-interface.launch(debug=True, share=True)
+# Create Gradio interface
+gr.Interface(
+    fn=predict,
+    title="African Cross-Lingua Embeddings Model's Demo",
+    description="Compute the semantic similarity across various sentences among any African Languages using African-Cross-Lingua-Embeddings-Model.",
+    inputs=inputs,  
+    outputs=outputs,
+    cache_examples=False,
+    article="Author: Innocent Charles. Model from Hugging Face Hub (sartify.com): [sartifyllc/African-Cross-Lingua-Embeddings-Model](https://huggingface.co/sartifyllc/African-Cross-Lingua-Embeddings-Model)",
+).launch(debug=True, share=True)