create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from sentence_transformers import SentenceTransformer, util
+
+# Load the pre-trained sentence transformer model
+model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
+
+def inference(text1, text2):
+    # Encode the input sentences into sentence embeddings
+    embeddings1 = model.encode(text1, convert_to_tensor=True)
+    embeddings2 = model.encode(text2, convert_to_tensor=True)
+
+    # Calculate the cosine similarity between the two sentence embeddings
+    similarity_score = util.pytorch_cos_sim(embeddings1, embeddings2).item()
+
+    return round(similarity_score, 2)
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+    """
+    # Sentence Similarity Calculator
+    Start typing below to see the output.
+    """)
+    txt = gr.Textbox(label="Input 1", lines=2)
+    txt_2 = gr.Textbox(label="Input 2")
+    txt_3 = gr.Textbox(value="", label="Output")
+    btn = gr.Button(value="Submit")
+    btn.click(inference, inputs=[txt, txt_2], outputs=[txt_3])
+
+demo.launch()
+