initial app

app.py

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+import gradio as gr
+import tensorflow_text as text  # Registers the ops. (needed for "bert_preprocessor")
+from tensorflow_hub.hf_utils import pull_from_hub
+from sklearn.metrics.pairwise import cosine_similarity
+
+model = pull_from_hub(repo_id="Dimitre/universal-sentence-encoder")
+
+def get_similarity(sentence_a, sentence_b):
+    embed_a = model([sentence_a])
+    embed_b = model([sentence_b])
+    print(embed_a.shape, embed_b.shape)
+    return cosine_similarity(embed_a, embed_b)
+
+iface = gr.Interface(fn=get_similarity, inputs=["text", "text"], outputs="text")
+iface.launch()

requirements.txt

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+sklearn
+tensorflow
+tensorflow_text
+git+https://github.com/dimitreOliveira/hub.git