Create app.py

app.py

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+import gradio as gr
+from sentence_transformers import SentenceTransformer
+
+model_Q = SentenceTransformer('flax-sentence-embeddings/multi-QA_v1-mpnet-asymmetric-Q')
+
+def getVectors(sentences):
+            vectors = []
+            splitSentences = sentences.split('/*/')
+            for sentence in sentences:
+                        vectors.append(model_Q.encode(sentence))
+            return vectors
+            
+interface = gr.Interface(fn = getVectors,
+inputs = "text",
+outputs = ['text'],
+title = 'get vectors',
+description = 'get vectors for search')
+
+interface.launch(inline = False)