Create app.py

app.py

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+import tensorflow as tf
+import tensorflow_hub as hub
+from tensorflow_text import SentencepieceTokenizer
+import gradio as gr
+import math
+
+model_url = "https://tfhub.dev/google/universal-sentence-encoder-multilingual-large/3"
+model = hub.load(model_url)
+
+def embed_text(text: str) -> dict:
+    embeddings = model(text)
+    return embeddings.numpy().tolist()
+
+embed_text_inter = gr.Interface(
+    fn = embed_text,
+    inputs = "text",
+    outputs = gr.JSON(),
+    title = "Universal Sentence Encoder 3 Large"
+)
+
+def distance(text_1: str, text_2: str) -> float:
+    embeddings_1 = model(text_1)
+    embeddings_2 = model(text_2)
+    dist = math.sqrt(sum((embeddings_1 - embeddings_2)**2))
+    return dist
+
+distance_inter = gr.Interface(
+    fn = distance,
+    inputs = ["text", "text"],
+    outputs = "number",
+    title = "Universal Sentence Encoder 3 Large"
+)
+
+
+iface = gr.TabbedInterface(
+    interface_list=[embed_text_inter, distance_inter],
+    title="Universal Sentence Encoder 3 Large"
+)
+
+iface.launch()