Update utils.py

utils.py

@@ -1,32 +1,42 @@
 import json
 from transformers import pipeline
+from rapidfuzz import fuzz
 
-# Load local course data
+# Load course data
 def load_courses():
     with open("data/courses.json") as f:
         return json.load(f)
 
-# Use LLM to recommend best course
+# Recommend course using fuzzy matching and LLM summarization
 def recommend_course(user_input, courses):
-    relevant = [c for c in courses if user_input.lower() in c["category"].lower() or user_input.lower() in c["title"].lower()]
-    
+    user_input = user_input.lower()
+    relevant = []
+    for course in courses:
+        text_to_match = " ".join([
+            course.get("title", ""),
+            course.get("category", ""),
+            " ".join(course.get("keywords", []))
+        ]).lower()
+        score = fuzz.partial_ratio(user_input, text_to_match)
+        if score > 60:
+            relevant.append((course, score))
+
     if not relevant:
-        return "No relevant courses found."
+        return "⚠️ No relevant courses found. Try a simpler topic like 'Python' or 'AI'."
 
-    sorted_courses = sorted(relevant, key=lambda x: x["rating"], reverse=True)
+    # Sort by rating, then relevance
+    relevant = sorted(relevant, key=lambda x: (x[0]["rating"], x[1]), reverse=True)
 
-    # Optional: Use LLM to summarize reviews
     summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
-    summaries = []
-    for course in sorted_courses[:3]:
-        review_text = " ".join(course["reviews"])
-        summary = summarizer(review_text, max_length=60, min_length=10, do_sample=False)[0]["summary_text"]
-        summaries.append((course, summary))
 
     result = ""
-    for course, summary in summaries:
-        result += f"**{course['title']}** ({course['platform']})\n"
+    for course, _ in relevant[:3]:
+        reviews = " ".join(course["reviews"])
+        summary = summarizer(reviews, max_length=60, min_length=10, do_sample=False)[0]["summary_text"]
+
+        result += f"### {course['title']} ({course['platform']})\n"
         result += f"⭐ Rating: {course['rating']}\n"
-        result += f"📝 Summary of reviews: {summary}\n\n"
-    
+        result += f"📂 Category: {course['category']}\n"
+        result += f"💬 Summary of Reviews: {summary}\n\n"
+
     return result