Update app.py

app.py

@@ -5,16 +5,20 @@ import re
 # ✅ Load Hugging Face summarization/chat model
 summarizer = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1")
 
-# ✅ Highlight matching keywords
+# ✅ Highlight matching and find missing keywords
 from sklearn.feature_extraction.text import ENGLISH_STOP_WORDS
 
-def highlight_keywords(resume_text, job_desc):
+def compare_keywords(resume_text, job_desc):
     resume_words = set(re.findall(r"\b\w{3,}\b", resume_text.lower())) - ENGLISH_STOP_WORDS
     job_words = set(re.findall(r"\b\w{3,}\b", job_desc.lower())) - ENGLISH_STOP_WORDS
     matched = resume_words & job_words
+    missing = job_words - resume_words
+    return matched, missing
+
+def highlight_keywords(resume_text, matched):
     highlighted = resume_text
     for word in sorted(matched, key=len, reverse=True):
-        highlighted = re.sub(rf"\\b({re.escape(word)})\\b", r"**\1**", highlighted, flags=re.IGNORECASE)
+        highlighted = re.sub(rf"\b({re.escape(word)})\b", r"**\1**", highlighted, flags=re.IGNORECASE)
     return highlighted
 
 # 🔍 Prompt for dynamic section classification and feedback
@@ -48,8 +52,9 @@ def analyze_resume(job_desc, resume_text, analyze_with_jd):
         response = summarizer(user_prompt, max_new_tokens=768, do_sample=True, temperature=0.7)[0]['generated_text']
         cleaned = re.sub(rf".*?{re.escape(resume_text)}", "", response, flags=re.DOTALL).strip()
         if analyze_with_jd and job_desc:
-            highlighted_resume = highlight_keywords(resume_text, job_desc)
-            return f"### 🔍 Resume with Highlighted Matches\n\n{highlighted_resume}\n\n---\n{cleaned}"
+            matched, missing = compare_keywords(resume_text, job_desc)
+            highlighted_resume = highlight_keywords(resume_text, matched)
+            return f"### 🔍 Resume with Highlighted Matches\n\n{highlighted_resume}\n\n---\n**✅ Matched Keywords:** {', '.join(sorted(matched)) or 'None'}\n\n**❌ Missing Keywords from Resume:** {', '.join(sorted(missing)) or 'None'}\n\n---\n{cleaned}"
         return cleaned
     except Exception as e:
         return f"❌ Error: {str(e)}"