app.py

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
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,
}







# Prompt the model to generate content

# Function to analyze text
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."

# Gradio interface setup
with gr.Blocks() as app:
    with gr.Tab("Text Analysis"):
        text_input = gr.Textbox(label="Enter Text", placeholder="Type here...", lines=4)
        analyze_text_btn = gr.Button("Analyze Text")
        text_output = gr.Textbox(label="Analysis Output", lines=6)
        analyze_text_btn.click(
            fn=analyze_text,
            inputs=text_input,
            outputs=text_output
        )
    
 
 
app.launch()