from sentence_transformers import SentenceTransformer
import gradio as gr

# Load a clinical sentence transformer
model = SentenceTransformer("pritamdeka/BioBERT-mnli-snli-scinli-scitail-mednli-stsb")

def embed_text(text):
    embedding = model.encode(text, convert_to_numpy=True, normalize_embeddings=True).tolist()
    return embedding

iface = gr.Interface(
    fn=embed_text,
    inputs=gr.Textbox(lines=5, label="Enter clinical text"),
    outputs="json",
    title="High-Accuracy Clinical Embeddings",
    description="BioBERT fine-tuned for semantic similarity (STSB, MedNLI)"
)

iface.launch()