Update app.py

app.py

@@ -2,10 +2,13 @@
 import gradio as gr
 import requests
 import os
+import io
 
 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"
+API_URL4 = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
+
 
 bt = os.environ['HACKAITHONBEARERTOKEN']
 headers = {"Authorization": bt }
@@ -21,16 +24,32 @@ def query(mood, select_model, filepath):
     elif (select_model=="WhatIsThat"):
         data = open(filepath, 'rb' ).read()
         response = requests.post(API_URL2, headers=headers, data=data)
-    else:
+    elif (select_model=="HandWriting"):
         data = open(filepath, 'rb' ).read()
         response = requests.post(API_URL3, headers=headers, data=data)
-    return str(response.json())
+    else:
+        response = requests.post(API_URL4, headers=headers, json=mood) 
+        
+    if (select_model=="Sentiment"):
+        return str(response.json())
+    elif (select_model=="WhatIsThat"):
+        return str(response.json())    
+    elif (select_model=="HandWriting"):
+        return str(response.json())
+    else:
+        return response.content 
 
+        
 def greet(mood,select_model,image):
     output = query({"inputs":mood}, select_model, image)
-    print (str(output))
-    return str(output)
+    
+    if (select_model=="Text2Image"):
+     from PIL import Image
+        image = Image.open(io.BytesIO(output))   
+    else:
+        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")
+  fn=greet, inputs=["text", gr.Radio(choices=["Sentiment", "WhatIsThat", "HandWriting","Text2Image"],value="Sentiment"),gr.Image(type="filepath")], outputs="text","image")
 iface.launch()