Create utils/cv_processor.py

utils/cv_processor.py

@@ -0,0 +1,57 @@
+from PyPDF2 import PdfReader
+from docx import Document
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+import re
+import numpy as np
+import os
+
+class CVProcessor:
+    def __init__(self):
+        self.model = SentenceTransformer('all-MiniLM-L6-v2')
+        self.job_reqs = self._load_job_requirements()
+    
+    def extract_text(self, file_path):
+        if file_path.endswith('.pdf'):
+            reader = PdfReader(file_path)
+            return " ".join([page.extract_text() for page in reader.pages])
+        elif file_path.endswith('.docx'):
+            doc = Document(file_path)
+            return " ".join([para.text for para in doc.paragraphs])
+    
+    def evaluate(self, cv_path, job_role):
+        cv_text = self.extract_text(cv_path)
+        reqs = self.job_reqs[job_role]
+        
+        # Semantic similarity
+        cv_embed = self.model.encode(cv_text)
+        req_embed = self.model.encode(reqs["required_skills"])
+        similarity = cosine_similarity([cv_embed], [req_embed])[0][0]
+        
+        # Experience check
+        exp_matches = re.findall(r"(\d+)\s+years?", cv_text.lower())
+        total_exp = sum(int(m) for m in exp_matches) if exp_matches else 0
+        
+        is_qualified = (similarity > 0.4 and 
+                       total_exp >= reqs["min_experience"])
+        
+        return {
+            "is_qualified": is_qualified,
+            "cv_summary": {
+                "text": cv_text[:2000] + "..." if len(cv_text) > 2000 else cv_text,
+                "experience": total_exp,
+                "skills_match": float(similarity)
+            }
+        }
+    
+    def _load_job_requirements(self):
+        return {
+            "Software Engineer": {
+                "min_experience": 2,
+                "required_skills": "programming, algorithms, software development, testing, debugging"
+            },
+            "Data Scientist": {
+                "min_experience": 3,
+                "required_skills": "machine learning, statistics, python, data analysis, SQL"
+            }
+        }