| import gradio as gr | |
| from threading import Thread | |
| import time | |
| import anvil.server | |
| from registration import register,get_register,func_reg | |
| from library import get_file,get_files | |
| anvil.server.connect('55MH4EBKM22EP4E6D5T6CVSL-VGO5X4SM6JEXGJVT') | |
| register(get_file) | |
| register(get_files) | |
| # with gr.Blocks() as block: | |
| # textbox = gr.inputs.Textbox(label='Function Register') | |
| # button = gr.Button(value="Show Function Calls") | |
| # button.click(get_register,inputs=None,outputs=[textbox]) | |
| # block.launch() | |
| import json | |
| import ast | |
| def my_inference_function(name): | |
| # print(ast.literal_eval(name)['name']) | |
| return "Input Data: " + name + ", stay tuned for ML models from this API" | |
| gradio_interface = gr.Interface( | |
| fn=my_inference_function, | |
| inputs="text", | |
| outputs="text", | |
| title="REST API with Gradio and Huggingface Spaces", | |
| description='''Inputs should be json of test item e.g., as a dictionary; | |
| output right now is just returning the input; later label will be returned''' | |
| ) | |
| gradio_interface.launch() | |
| # anvil.server.wait_forever() | |