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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.
This is how to call the API from Python:
import requests
response = requests.post("https://gmshroff-gmserver.hf.space/run/predict", json={
"data": [
"\<put some json string here\>",
]}).json()
data = response["data"])
''')
gradio_interface.launch()
# anvil.server.wait_forever()
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