Adjusted app.py file

app.py

@@ -3,44 +3,39 @@ import json
 import gradio as gr
 import google.generativeai as genai
 
-GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
+GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
 genai.configure(api_key=GOOGLE_API_KEY)
 
 # Set up the model
 generation_config = {
-  "temperature": 0.9,
-  "top_p": 1,
-  "top_k": 1,
-  "max_output_tokens": 2048,
+    "temperature": 0.9,
+    "top_p": 1,
+    "top_k": 1,
+    "max_output_tokens": 2048,
 }
 
 safety_settings = [
-  {
-    "category": "HARM_CATEGORY_HARASSMENT",
-    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-  },
-  {
-    "category": "HARM_CATEGORY_HATE_SPEECH",
-    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-  },
-  {
-    "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
-    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-  },
-  {
-    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
-    "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-  }
+    {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
+    {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
+    {
+        "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+        "threshold": "BLOCK_MEDIUM_AND_ABOVE",
+    },
+    {
+        "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+        "threshold": "BLOCK_MEDIUM_AND_ABOVE",
+    },
 ]
 
 model = genai.GenerativeModel(
     model_name="gemini-pro",
     generation_config=generation_config,
-    safety_settings=safety_settings
+    safety_settings=safety_settings,
 )
 
 task_description = " You are an SMS (Short Message Service) reader who reads every message that the short message service centre receives and you need to classify each message among the following categories: {}<div>Let the output be a softmax function output giving the probability of message belonging to each category.</div><div>The sum of the probabilities should be 1</div><div>The output must be in JSON format</div>"
 
+
 def classify_msg(categories, message):
     prompt_parts = [
         task_description.format(categories),
@@ -51,18 +46,20 @@ def classify_msg(categories, message):
     response = model.generate_content(prompt_parts)
 
     json_response = json.loads(
-        response.text[response.text.find('{'):response.text.rfind('}') + 1]
+        response.text[response.text.find("{") : response.text.rfind("}") + 1]
     )
 
     return gr.Label(json_response)
 
+
 def clear_inputs_and_outputs():
     return [None, None, None]
 
+
 with gr.Blocks() as demo:
     gr.Markdown(
         """
-        <center><h1>Multi-language Text Classifier using Gemini Pro</h1></center> \
+        # Multi-language Text Classifier using Gemini Pro \
         This space demos SMS and text in general classification using Gemini Pro<br> \
 For the categories, enter a list of words separated by commas<br><br>
         """
@@ -70,7 +67,10 @@ For the categories, enter a list of words separated by commas<br><br>
     with gr.Row():
         with gr.Column():
             with gr.Row():
-                categories = gr.Textbox(label="Categories", placeholder="Input the list of categories as comma separated words")
+                categories = gr.Textbox(
+                    label="Categories",
+                    placeholder="Input the list of categories as comma separated words",
+                )
             with gr.Row():
                 message = gr.Textbox(label="Message", placeholder="Enter Message")
             with gr.Row():
@@ -92,10 +92,10 @@ For the categories, enter a list of words separated by commas<br><br>
 
     gr.Examples(
         examples=[
-            ['Normal, Promotional, Urgent', 'Will you be passing by?'],
-            ['Spam, Ham', 'Plus de 300 % de perte de poids pendant le régime.'],
-            ['Χαρούμενος, Δυστυχισμένος', 'Η εξυπηρέτηση σας ήταν απαίσια'],
-            ['مهم، أقل أهمية ', 'خبر عاجل']
+            ["Normal, Promotional, Urgent", "Will you be passing by?"],
+            ["Spam, Ham", "Plus de 300 % de perte de poids pendant le régime."],
+            ["Χαρούμενος, Δυστυχισμένος", "Η εξυπηρέτηση σας ήταν απαίσια"],
+            ["مهم، أقل أهمية ", "خبر عاجل"],
         ],
         inputs=[categories, message],
         outputs=lbl_output,
@@ -103,4 +103,4 @@ For the categories, enter a list of words separated by commas<br><br>
         cache_examples=True,
     )
 
-demo.launch()
+demo.launch(debug=True, share=True)