Update app.py

app.py

@@ -44,7 +44,6 @@ def load_entries(path):
 
 
 def init_models():
-    """Initialize all models and load data"""
     # 1. Load embedding model for semantic search
     embed_model = SentenceTransformer("all-MiniLM-L6-v2", device=cfg.DEVICE)
 
@@ -72,7 +71,6 @@ embed_model, tokenizer, model, entries, vectors = init_models()
 
 
 def search_chunks(query, top_k=cfg.TOP_K, batch_size=512):
-    """Memory-efficient cosine similarity search."""
     import heapq
 
     # Encode query as normalized float32 vector
@@ -144,7 +142,6 @@ QUESTION: {question}
 
 
 def qa_pipeline(question):
-    """Unified pipeline that streams search results first, then LLM answer."""
     results = search_chunks(question)
 
     # Build top results HTML immediately