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from typing import Dict | |
from pathlib import Path | |
import pandas as pd | |
from io import StringIO | |
import gradio as gr | |
# def predict(text: str) -> Dict: | |
# return {"alive": 0.9, "death": 0.1} | |
# example_list = [[1.0, 1.0, 0.0], [1.0, 0.0, 0.0], [0.0, 0.0, 0.0]] | |
# # Create title, description and article strings | |
# title = "This is title." | |
# description = "This is description." | |
# article = "This is article." | |
# default_csv = "Phase,Activity,Start date,End date\n\"Mapping the Field\",\"Literature review\",2024-01-01,2024-01-31" | |
# def process_csv_text(temp_file): | |
# if isinstance(temp_file, str): | |
# print("1") | |
# df = pd.read_csv(temp_file, header = "infer", sep = ",", encoding = "utf-8") | |
# else: | |
# print("2") | |
# df = pd.read_csv(temp_file.name) | |
# print("***") | |
# print(df) | |
# print("***") | |
# return df | |
# with gr.Blocks() as demo: | |
# upload_button = gr.UploadButton(label="Upload Timetable", file_types = ['.csv'], file_count = "single") | |
# table = gr.Dataframe(headers=["Phase", "Activity", "Start date", "End date"], type="pandas", col_count=4) | |
# upload_button.upload(fn=process_csv_text, inputs=upload_button, outputs=table, api_name="upload_csv") | |
# demo.launch(debug=True) | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
with gr.Column(): | |
patient_upload_btn = gr.UploadButton(label="Upload A Patient", | |
file_types = ['.csv'], | |
file_count = "single") | |
with gr.Row(): | |
# patient_1_input_btn = gr.Button("Patient 1") | |
# patient_1_download_btn = gr.DownloadButton("Download 1") | |
with gr.Column(min_width=100): | |
patient_1_input_btn = gr.Button("Patient 1") | |
patient_1_download_btn = gr.DownloadButton("Download 1") | |
with gr.Column(min_width=100): | |
patient_2_input_btn = gr.Button("Patient 2") | |
patient_2_download_btn = gr.DownloadButton("Download 2") | |
with gr.Column(min_width=100): | |
patient_3_input_btn = gr.Button("Patient 3") | |
patient_3_download_btn = gr.DownloadButton("Download 3") | |
with gr.Column(): | |
btn1 = gr.Button("Will Display Output") | |
demo.launch(debug=True) | |