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| import gradio as gr | |
| import requests | |
| import os | |
| API_URL1 = "https://api-inference.huggingface.co/models/cardiffnlp/twitter-roberta-base-sentiment" | |
| API_URL2 = "https://api-inference.huggingface.co/models/facebook/convnext-xlarge-384-22k-1k" | |
| API_URL3 = "https://api-inference.huggingface.co/models/microsoft/trocr-base-handwritten" | |
| bt = os.environ['RobertaSecret'] | |
| 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() | |