Delete app.py

app.py

@@ -1,99 +0,0 @@
-import os
-import google.generativeai as genai
-import gradio as gr
-from google.generativeai.types import HarmBlockThreshold, HarmCategory
-
-# Configure Google API Key and model
-GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
-genai.configure(api_key=GOOGLE_API_KEY)
-MODEL_ID = "gemini-1.5-pro-002"
-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."
-    ],
-)
-
-# Set model parameters
-generation_config = genai.GenerationConfig(
-    temperature=0.9,
-    top_p=1.0,
-    top_k=32,
-    candidate_count=1,
-    max_output_tokens=8192,
-)
-
-# Safety and instruction settings
-safety_settings = {
-    HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
-    HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
-    HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
-    HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
-}
-
-# 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]
-    response = example_model.generate_content(
-        contents,
-        generation_config=generation_config,
-        safety_settings=safety_settings,
-    )
-    return response.text if response else "No response generated."
-
-# 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 for gender discrimination analysis
-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."
-]
-
-# Gradio interface setup
-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 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()