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import gradio as gr | |
import requests | |
import os | |
API_URL1 = "/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Fcardiffnlp%2Ftwitter-roberta-base-sentiment%26quot%3B%3C%2Fspan%3E%3C!-- HTML_TAG_END --> | |
API_URL2 = "/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Ffacebook%2Fconvnext-xlarge-384-22k-1k%26quot%3B%3C%2Fspan%3E%3C!-- HTML_TAG_END --> | |
API_URL3 = "/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Fmicrosoft%2Ftrocr-base-handwritten%26quot%3B%3C%2Fspan%3E%3C!-- HTML_TAG_END --> | |
bt = os.environ['HACKAITHONBEARERTOKEN'] | |
headers = {"Authorization": bt } | |
def query(mood, select_model, filepath): | |
print (select_model); | |
print (filepath); | |
if (select_model=="Sentiment"): | |
response = requests.post(API_URL1, headers=headers, json=mood) | |
elif (select_model=="WhatIsThat"): | |
data = open(filepath, 'rb' ).read() | |
response = requests.post(API_URL2, headers=headers, data=data) | |
else: | |
data = open(filepath, 'rb' ).read() | |
response = requests.post(API_URL3, headers=headers, data=data) | |
return str(response.json()) | |
def greet(mood,select_model,image): | |
output = query({"inputs":mood}, select_model, image) | |
print (str(output)) | |
return str(output) | |
iface = gr.Interface( | |
fn=greet, inputs=["text", gr.Radio(choices=["Sentiment", "WhatIsThat", "HandWriting"],value="Sentiment"),gr.Image(type="filepath")], outputs="text") | |
iface.launch() | |