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import gradio as gr
import pandas as pd
from sentence_transformers import SentenceTransformer, util
import torch
# 載入語義搜索模型
model_checkpoint = "sickcell69/cti-semantic-search-minilm"
model = SentenceTransformer(model_checkpoint)
# 載入數據
data_path = 'labeled_cti_data.json'
data = pd.read_json(data_path)
# 載入嵌入文件
embeddings_path = 'corpus_embeddings.pt'
corpus_embeddings = torch.load(embeddings_path, map_location=torch.device('cpu'))
def semantic_search(query):
query_embedding = model.encode(query, convert_to_tensor=True)
search_hits = util.semantic_search(query_embedding, corpus_embeddings, top_k=5)
results = []
for hit in search_hits[0]:
text = " ".join(data.iloc[hit['corpus_id']]['tokens'])
results.append(f"Score: {hit['score']:.4f} - Text: {text}")
return "\n".join(results)
iface = gr.Interface(
fn=semantic_search,
inputs="text",
outputs="text",
title="語義搜索應用",
description="輸入一個查詢,然後模型將返回最相似的結果。"
)
if __name__ == "__main__":
#iface.launch()
iface.launch(share=True) #網頁跑不出來 |