app.py

import gradio as gr
from sentence_transformers import SentenceTransformer

# Load the model
model = SentenceTransformer('sentence-transformers/msmarco-distilbert-dot-v5')

# Function to get the embedding
def embedding(text):
    text_emb = model.encode(text)
    return text_emb

# Define the Streamlit app
gradio_app = gr.Interface(
    embedding,
    inputs=gr.Text(label="TEXT"),
    outputs=gr.Text(label="Embedding"),
    title="Embedding",
)

if __name__ == "__main__":
    gradio_app.launch()