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app.py

@@ -3,20 +3,34 @@ import gradio as gr
 import requests
 import os
 
-API_URL = "https://api-inference.huggingface.co/models/cardiffnlp/twitter-roberta-base-sentiment"
+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['HACKAITHONBEARERTOKEN']
+bt = os.environ['RobertaSecret']
 headers = {"Authorization": bt }
 
-def query(data):
-    response = requests.post(API_URL, headers=headers, json=data)
-    return "V2"+str(response.json())
+def query(mood, select_model, filepath):
 
-def greet(howareyoufeeling):
-    output = query({"inputs":howareyoufeeling})
+    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"], outputs="text",  allow_flagging="never")
+  fn=greet, inputs=["text", gr.Radio(choices=["Sentiment", "WhatIsThat", "HandWriting"],value="Sentiment"),gr.Image(type="filepath")], outputs="text")
 iface.launch()