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import gradio as gr
from sentence_transformers import CrossEncoder
ce = CrossEncoder("cross-encoder/mmarco-mMiniLMv2-L12-H384-v1")
def rerank(query, docs):
texts = [str(d) for d in docs] # просто список строк
pairs = [[query, txt] for txt in texts]
scores = ce.predict(pairs)
rows = [[txt, float(score)] for txt, score in zip(texts, scores)]
return rows
iface = gr.Interface(
fn=rerank,
inputs=[
gr.Textbox(label="Query"),
gr.JSON(label="Docs (JSON array of objects)")
],
outputs=gr.Dataframe(type="array", headers=["doc", "score"]),
api_name="rerank"
)
if __name__ == "__main__":
iface.launch()
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