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# -*- coding: utf-8 -*- | |
""" | |
Created on Fri Jun 16 23:31:34 2023 | |
@author: Hua | |
""" | |
import gradio as gr | |
from searchEmbeddings import search | |
def searchEMA(inputs): | |
results = search(inputs) | |
outputs = f"(1) {results['Author Full Names'][4]} {results['Article Title'][4]} {results['Publication Year'][4]} \n [Abstract] {results['Abstract'][4]} \n(2) {results['Author Full Names'][3]} {results['Article Title'][3]} {results['Publication Year'][3]} \n [Abstract] {results['Abstract'][3]}" | |
return outputs | |
with gr.Blocks() as demo: | |
gr.Markdown("瑞聚医学数字化设计与制造平台1.0") | |
name = gr.Textbox(label = "Question", placeholder = "What is your problem?") | |
output = gr.Textbox(label = "Recommended solution") | |
greet_btn = gr.Button("Recommened solutions from ramGPT") | |
greet_btn.click(fn=searchEMA, inputs=name, outputs=output, api_name="searchEMA") | |
demo.launch(auth=("admin", "ramGPT")) | |