Create app.py

app.py

@@ -0,0 +1,22 @@
+import gradio as gr
+from sentence_transformers import SentenceTransformer
+
+# Load the pre-trained model
+model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
+
+def get_embeddings(sentences):
+    # Get embeddings for the input sentences
+    embeddings = model.encode(sentences)
+    return embeddings.tolist()
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=get_embeddings,  # Function to call
+    inputs=gr.Textbox(lines=2, placeholder="Enter sentences here, one per line"),  # Input component
+    outputs=gr.JSON(),  # Output component
+    title="Sentence Embeddings",  # Interface title
+    description="Enter sentences to get their embeddings."  # Description
+)
+
+# Launch the interface
+interface.launch()