| import gradio as gr | |
| from transformers import pipeline | |
| def predict_ats_score(job_description, resume): | |
| model = pipeline("text-classification", model="AventIQ-AI/multinomialnb-ats-score-predictor") | |
| input_text = f"Job Description: {job_description}\nResume: {resume}" | |
| result = model(input_text) | |
| return result[0]['label'], round(result[0]['score'] * 100, 2) | |
| custom_css = """ | |
| body { background: #1e1e2f; font-family: Arial, sans-serif; color: #ffffff; } | |
| .gradio-container { max-width: 700px; margin: auto; padding: 20px; border-radius: 10px; background: #2a2a3c; box-shadow: 0px 4px 15px rgba(0,0,0,0.2); } | |
| .gr-button { background-color: #ff6b6b; color: white; font-size: 16px; border-radius: 8px; padding: 10px 20px; border: none; cursor: pointer; transition: all 0.3s ease; } | |
| .gr-button:hover { background-color: #ff4757; } | |
| .gr-textbox { background: #3a3a4a; color: white; border-radius: 8px; border: 1px solid #555; padding: 10px; font-size: 14px; } | |
| """ | |
| iface = gr.Interface( | |
| fn=predict_ats_score, | |
| inputs=[ | |
| gr.Textbox(label="Job Description", lines=5, placeholder="Enter the job description here...", elem_classes="gr-textbox"), | |
| gr.Textbox(label="Resume", lines=5, placeholder="Enter the resume here...", elem_classes="gr-textbox") | |
| ], | |
| outputs=[ | |
| gr.Textbox(label="Predicted Score", interactive=False, elem_classes="gr-textbox"), | |
| gr.Textbox(label="Confidence Score (%)", interactive=False, elem_classes="gr-textbox") | |
| ], | |
| title="🚀 ATS Score Predictor", | |
| description="🔍 Enter a job description and a resume to predict the ATS score. This will help determine how well a resume matches a job description.", | |
| theme="compact", | |
| css=custom_css | |
| ) | |
| iface.launch() | |