Update app.py

app.py

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+from sentence_transformers import SentenceTransformer, util
+import gradio as gr
+
+# Load the model
+model = SentenceTransformer('sartifyllc/AviLaBSE')
+
+# Function to compute similarities
+def compute_similarity(original_sentence, sentences_to_compare):
+    # Encode the original sentence and the sentences to compare
+    embeddings_original = model.encode([original_sentence])
+    embeddings_sentences_to_compare = model.encode(sentences_to_compare)
+
+    # Compute cosine similarities
+    similarities = util.cos_sim(embeddings_original, embeddings_sentences_to_compare)
+
+    # Prepare results
+    results = []
+    for i, sentence in enumerate(sentences_to_compare):
+        results.append((sentence, similarities[0][i].item()))
+
+    return results
+
+# Interface using Gradio
+def sentence_similarity(original_sentence, sentence1, sentence2, sentence3):
+    sentences_to_compare = [sentence1, sentence2, sentence3]
+    results = compute_similarity(original_sentence, sentences_to_compare)
+    return results
+
+iface = gr.Interface(
+    fn=sentence_similarity,
+    inputs=[
+        gr.Textbox(label="Original Sentence"),
+        gr.Textbox(label="Sentence 1"),
+        gr.Textbox(label="Sentence 2"),
+        gr.Textbox(label="Sentence 3")
+    ],
+    outputs=gr.Table(label="Similarity Scores", columns=["Sentence", "Similarity Score"]),
+    title="Sentence Similarity Calculator",
+    description="Enter an original sentence and three sentences to compare their similarity."
+)
+
+iface.launch()