SivaMallikarjun/Robust-Approval-System

1import gradio as gr2import json3import random4 5# Sample ML Model Simulation6def ml_model_evaluate(application_text):7    # Simulating ML-based approval (Adjust as per real model)8    keywords = ["experience", "Python", "ML", "AI", "certification"]9    score = sum(1 for word in keywords if word.lower() in application_text.lower())10    return score >= 3  # Approve if at least 3 keywords match11 12# Job Application Processing Function13def process_application(user_id, application_text):14    # Check if the user exists (simulated with JSON storage)15    try:16        with open("applications.json", "r") as file:17            applications = json.load(file)18    except FileNotFoundError:19        applications = {}20 21    if str(user_id) in applications:22        return f"⚠️ You have already applied. Please wait for approval."23 24    # ML Model Decision25    approved = ml_model_evaluate(application_text)26 27    if approved:28        applications[str(user_id)] = "Approved"29        with open("applications.json", "w") as file:30            json.dump(applications, file)31        return f"✅ Application Approved! You are eligible for job postings."32    else:33        return f"❌ Application Rejected. Improve details and resubmit."34 35# Gradio UI36iface = gr.Interface(37    fn=process_application,38    inputs=["text", "text"],39    outputs="text",40    title="AI Job Application Approval System",41    description="Submit your job application. If everything is correct, it will be approved automatically!",42    examples=[["2345", "I have experience in AI, Python, and ML."]],43)44 45if __name__ == "__main__":46    iface.launch()47