Update genbiasapp.py

genbiasapp.py

@@ -1,8 +1,6 @@
 import os
 import google.generativeai as genai
 import gradio as gr
-from PIL import Image
-import moviepy.editor as mp
 from google.generativeai.types import HarmBlockThreshold, HarmCategory
 
 # Configure Google API Key and model
@@ -14,8 +12,8 @@ model = genai.GenerativeModel(MODEL_ID)
 example_model = genai.GenerativeModel(
     MODEL_ID,
     system_instruction=[
-     "You are an advocate against gender-based violence.",
-    "Analyze the content for signs of gender discrimination and provide actionable advice."
+        "You are an advocate against gender-based violence.",
+        "Analyze the content for signs of gender discrimination and provide actionable advice."
     ],
 )
 
@@ -36,36 +34,57 @@ safety_settings = {
     HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
 }
 
-# Function to analyze text
+# Function to analyze text with error handling
 def analyze_text(text):
     prompt = f"Analyze this text for any instances of gender-based discrimination and provide tips: {text}"
-    contents=[prompt]
+    contents = [prompt]
     response = example_model.generate_content(
-    contents,
-    generation_config=generation_config,
-    safety_settings=safety_settings,)
+        contents,
+        generation_config=generation_config,
+        safety_settings=safety_settings,
+    )
     return response.text if response else "No response generated."
 
-# Example scenarios
-example_scenarios = [
-    ("During a team meeting, whenever a female colleague tried to express her opinion, she was often interrupted or talked over by male colleagues."),
-    ("The feedback given to female employees often focuses more on their demeanor and less on their actual accomplishments."),
-    ("Male employees are more frequently considered for promotions and challenging projects, even when female employees have similar or superior qualifications."),
-    ("During a hiring panel, female candidates were often asked about their personal life, family plans, and how they would balance home and work."),
-    ("There are significant wage discrepancies between male and female employees who hold the same position and possess comparable experience."),
-    ("Some male colleagues often make inappropriate jokes or comments about female employees' appearances and attire."),
-]
+# Custom CSS for branding and animation
+css = """
+body { font-family: 'Arial', sans-serif; background-color: #f0f0f0; }
+h1 { color: #333; animation: fadeIn 2s; }
+@keyframes fadeIn {
+    from { opacity: 0; }
+    to { opacity: 1; }
+}
+#logo { font-size: 48px; color: #5f4b8b; animation: slideIn 2s; }
+@keyframes slideIn {
+    0% { margin-left: -200px; }
+    100% { margin-left: 0px; }
+}
+.button { background-color: #4CAF50; color: white; padding: 14px 20px; margin: 8px 0; border: none; cursor: pointer; width: 100%; }
+.button:hover { opacity: 0.8; }
+.textbox { width: 100%; padding: 12px 20px; margin: 8px 0; display: inline-block; border: 1px solid #ccc; box-sizing: border-box; }
+"""
+
+example_scenarios= [["aa"], ["b"]]
 
 # Gradio interface setup
-with gr.Blocks() as app:
+with gr.Blocks(css=css) as app:
+    gr.Markdown("<div id='logo'>J<span>ustEva</span></div>")
+    gr.Markdown("<h1 style='text-align: center; color: #5f4b8b;'>Gender Bias Analysis Platform</h1>")
+    gr.Markdown("<p style='text-align: center; font-size: 16px; color: #4a4a4a;'>Powered by AI to advocate against gender-based violence</p>")
     with gr.Tab("Text Analysis"):
-        text_input = gr.Textbox(label="Enter Text", placeholder="Type here...", lines=4)
+        text_input = gr.Textbox(label="Enter Text or Select an Example", placeholder="Type here or select an example...", lines=4)
         analyze_text_btn = gr.Button("Analyze Text")
         text_output = gr.Textbox(label="Analysis Output", lines=6)
+        
+        examples = gr.Examples(
+            examples=example_scenarios,
+            inputs=text_input,
+            outputs=text_output
+        )
+        
         analyze_text_btn.click(
             fn=analyze_text,
             inputs=text_input,
             outputs=text_output
         )
-      
+
 app.launch()