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import gradio as gr
import subprocess
'''
import gradio as gr
def greet(name):
return "Hello " + name + "!"
demo = gr.Interface(fn=greet, inputs="text", outputs="text")
demo.launch()
'''
def greet(name1, name2):
# Storing each input in a variable, you can process or save them as you like
str1 = name1 ## openai
str2 = "213e22ba-4c3b-402b-bd36-6e9d4e86b1b5" #bioportal
str3 = "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" # huggingface
str4 = name2
with open('abstractsave.txt', 'w') as f:
f.write(name4)
# def run_command(command):
# result = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
# output_string = result.stdout
# error_string = result.stderr
# return output_string, error_string
###### output_string1, error_string1= run_command("pip install optogpt")
# output_string1, error_string1 = run_command("curl -sSL https://install.python-poetry.org | python3 -")
# output_string2, error_string2= run_command(f"poetry run runoak set-apikey -e openai {str1}")
# run_command(f"poetry run runoak set-apikey -e bioportal {str2}")
# run_command(f"poetry run runoak set-apikey -e hfhub-key {str3}")
# output = run_command(f"ontogpt extract -t gocam.GoCamAnnotations -i ./abstract.txt")
# output = run_command(f"cancerontogpt extract -t cancer.CancerAnnotations -i ./abstractsave.txt")"""
# output_string1, error_string1=run_command("poetry")# ontogpt")
# return location
# For the purpose of this example, I'm just returning the values concatenated
# return f"Inputs received: {str1} \n, {str2}, {str3}, {str4}, '--------------', '--------------', {output_string1},{error_string1},{output_string2},{error_string2},{output}"
# # return location
# For the purpose of this example, I'm just returning the values concatenated
return f"{str4}"
# Define 5 text input boxes with labels
input_boxes = [
gr.inputs.Textbox(label="openai api key"),
gr.inputs.Textbox(label="Input data"),
]
iface = gr.Interface(fn=greet, inputs=input_boxes, outputs="text")
iface.launch()
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