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File size: 1,302 Bytes
9c3f77f 573c7b4 9c3f77f 573c7b4 9c3f77f 573c7b4 f9bbfe7 f1d11f4 573c7b4 9c3f77f 573c7b4 f1d11f4 813f2a4 86b65b5 59c76b8 b88350d d0750e7 9c3f77f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | import gradio as gr
import requests
import json
import pprint
import pandas as pd
def sar_alert(MESSAGE, API_KEY):
url = "https://9byf8l4qzk.execute-api.eu-west-2.amazonaws.com/dev/sar-alert-container"
payload = json.dumps({"message": MESSAGE})
headers = {
'Content-Type': 'application/json',
'x-api-key': API_KEY
}
response = requests.request("POST", url, headers=headers, data=payload)
output_data = json.loads(response.text)
#
pprint.pprint(output_data)
df_response = pd.json_normalize(output_data)
print(df_response,df_response.columns)
df_response = df_response[['output.SAR_requested', 'output.explanation']]
return df_response, str(output_data)
iface = gr.Interface(
fn=sar_alert,
inputs=[
"text",
"text"],
outputs=[
gr.outputs.Dataframe(headers=['SAR_Requested', 'Explanation'], type='pandas', label="Output"),
gr.outputs.Textbox(label="Raw Output")
],
# examples=[
# ["Customer is asking about his data, and he is concerned about GDPR because he heard about it in the news.", "Private Key"],
# ["Hey Kate, save $50 when you spend $150 or more. Today only! Click here to see our new products (link).", "Private Key"],
# ]
)
iface.launch() |