Create app.py

app.py

@@ -0,0 +1,51 @@
+import gradio as gr
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+
+model = SentenceTransformer("sentence-t5-base")
+
+
+def inference(
+        base_text: str = "",
+        compare_text: str = "",
+        exponent: int = 1,
+        progress=gr.Progress(),
+):
+    progress(0, "Computing embeddings...")
+    base_embedding = model.encode(base_text)
+    compare_embedding = model.encode(compare_text)
+
+    progress(0.5, "Computing similarity score...")
+    cos_sim = cosine_similarity([base_embedding], [compare_embedding])
+    score = cos_sim.item() ** exponent
+    score = float(f"{score:.5f}")
+
+    sim_type = "Cosine Similarity" if exponent == 1 else f"Sharpened Cosine Similarity (Exp: {exponent})"
+
+    return sim_type, score
+
+
+if __name__ == '__main__':
+    demo = gr.Interface(
+        fn=inference,
+        title="Sentence Similarity",
+        description="Calculate Sharpened Confine Similarity between two sentences by sentence-t5-base.",
+        inputs=[
+            gr.Textbox(label="Base Sentence", placeholder="The sentence to compare against.", value="Improve this text:"),
+            gr.Textbox(label="Compare Sentence", placeholder="The sentence to compare.", value="Improve the text:"),
+            gr.Radio(label="Exponent", choices=[1, 2, 3], value=3),
+        ],
+        outputs=[
+            gr.Label(label="Type"),
+            gr.Label(label="Similarity Score"),
+        ],
+        examples=[
+            ["Improve this text:", "Improve the text:", 3],
+            ["Puppies are young pet dogs that are both playful and cuddly.",
+             "Young, playful, and cuddly pet dogs are known as puppies.", 3],
+            ["James loved to play piano, a habit inherited from his father.",
+             "The piano was quite heavy, making it hard for James to carry.", 3],
+        ],
+        cache_examples=True,
+    )
+    demo.launch()