embedding / app.py
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Create app.py
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import gradio as gr
from sentence_transformers import SentenceTransformer
# Load the embedding model
model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
def embed_text(text):
embedding = model.encode(text).tolist()
return embedding
iface = gr.Interface(
fn=embed_text,
inputs=gr.Textbox(lines=5, label="Enter patient text"),
outputs="json",
title="Clinical Text Embedding API"
)
iface.launch()