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| from sentence_transformers import SentenceTransformer, util | |
| import gradio as gr | |
| # Load the SentenceTransformer model for sentence similarity | |
| try: | |
| model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2') | |
| except Exception as e: | |
| print(f"Error loading SentenceTransformer model: {e}") | |
| def match_cv_to_job(cv_text, job_description): | |
| debug_info = "Debug Info:\n" | |
| # Encode the entire CV text | |
| try: | |
| cv_embedding = model.encode(cv_text, convert_to_tensor=True) | |
| debug_info += f"CV Embedding: {cv_embedding}\n" | |
| except Exception as e: | |
| debug_info += f"Error encoding CV text: {e}\n" | |
| return None, debug_info | |
| # Encode the entire job description | |
| try: | |
| job_description_embedding = model.encode(job_description, convert_to_tensor=True) | |
| debug_info += f"Job Description Embedding: {job_description_embedding}\n" | |
| except Exception as e: | |
| debug_info += f"Error encoding job description: {e}\n" | |
| return None, debug_info | |
| # Compute similarity score between the entire CV and the entire job description | |
| try: | |
| similarity_score = util.pytorch_cos_sim(cv_embedding, job_description_embedding).item() | |
| debug_info += f"Overall Similarity Score: {similarity_score}\n" | |
| # Convert similarity score to a percentage for easier interpretation | |
| match_percentage = similarity_score * 100 | |
| debug_info += f"Overall Match Percentage: {match_percentage:.2f}%\n" | |
| except Exception as e: | |
| debug_info += f"Error calculating similarity score: {e}\n" | |
| return None, debug_info | |
| return {"Match Percentage": f"{match_percentage:.2f}%"}, debug_info | |
| # Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# CV and Job Description Matcher with Overall Similarity Score") | |
| # Input fields for CV and job description | |
| cv_text = gr.Textbox(label="CV Text", placeholder="Enter the CV text here", lines=10) | |
| job_description = gr.Textbox(label="Job Description", placeholder="Enter the entire job description text here", lines=10) | |
| # Button and output area | |
| match_button = gr.Button("Calculate Match Percentage") | |
| output = gr.JSON(label="Match Result") | |
| debug_output = gr.Textbox(label="Debug Info", lines=10) # Debug box for detailed output | |
| # Set button click to run the function | |
| match_button.click(fn=match_cv_to_job, inputs=[cv_text, job_description], outputs=[output, debug_output]) | |
| demo.launch() | |