Spaces:
Runtime error
Runtime error
| import spacy | |
| from spacy.cli import download | |
| import nltk | |
| import os | |
| import gradio as gr | |
| import torch | |
| from sentence_transformers import SentenceTransformer | |
| import PyPDF2 | |
| # Ensure NLTK 'punkt' tokenizer is downloaded | |
| try: | |
| nltk.data.find('tokenizers/punkt') | |
| except LookupError: | |
| print("Downloading NLTK 'punkt' tokenizer...") | |
| nltk.download('punkt') | |
| # Ensure spaCy 'en_core_web_sm' model is downloaded | |
| try: | |
| nlp = spacy.load("en_core_web_sm") | |
| except OSError: | |
| print("Downloading spaCy 'en_core_web_sm' model...") | |
| download("en_core_web_sm") | |
| nlp = spacy.load("en_core_web_sm") | |
| # Load Sentence Transformer model | |
| embedding_model = SentenceTransformer('all-MiniLM-L6-v2') | |
| # Check for GPU availability | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| print(f"Running on: {device}") | |
| # Function to extract text from PDF | |
| def extract_text_from_pdf(file_path): | |
| try: | |
| with open(file_path, 'rb') as file: | |
| reader = PyPDF2.PdfReader(file) | |
| text = ''.join(page.extract_text() for page in reader.pages) | |
| return text | |
| except Exception as e: | |
| print(f"Error extracting PDF text: {e}") | |
| return "" | |
| # Placeholder function for CV skill analysis | |
| def analyze_cv_skills(cv_text): | |
| # Implement skill analysis and career recommendations | |
| return "Skill analysis and recommendations coming soon!" | |
| # Function to process CV and provide recommendations | |
| def cv_skill_assessment(cv_file): | |
| try: | |
| cv_text = extract_text_from_pdf(cv_file.name) | |
| if not cv_text.strip(): | |
| with open(cv_file.name, 'r', encoding='utf-8') as f: | |
| cv_text = f.read() | |
| assessment = analyze_cv_skills(cv_text) | |
| return assessment | |
| except Exception as e: | |
| return f"Error processing CV: {str(e)}" | |
| # Create Gradio Interface | |
| def launch_cv_skill_assessment_app(): | |
| demo = gr.Interface( | |
| fn=cv_skill_assessment, | |
| inputs=gr.File(label="Upload Your CV (PDF/Text)", type="file"), | |
| outputs=gr.Markdown(label="Career Recommendation Report"), | |
| title="🚀 CV Skills Assessment AI", | |
| description=""" | |
| Discover your ideal career path based on your CV! | |
| - Upload your CV (PDF or Text file) | |
| - AI analyzes your skills and experience | |
| - Receive personalized career recommendations | |
| """, | |
| ) | |
| demo.launch(server_name="0.0.0.0", server_port=7860, share=True) | |
| # Run the application | |
| if __name__ == "__main__": | |
| launch_cv_skill_assessment_app() | |