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build_index.py

@@ -1,11 +1,11 @@
 import os
-from llama_index.core import SimpleDirectoryReader, VectorStoreIndex, StorageContext
-from llama_index.core import Settings
+from llama_index.core import SimpleDirectoryReader, VectorStoreIndex, StorageContext, Settings
 from llama_index.embeddings.fastembed import FastEmbedEmbedding
 
 
 
-# --- 1. Load Data ---
+# ----- 1) Load Data -----
+
 files_to_index = [
     "./Lebenslauf_SuhasKamuni.pdf",
     "./about_me.txt",
@@ -21,7 +21,8 @@ except FileNotFoundError:
 
 
 
-# --- 2. Configure Embedding Model ---
+# ----- 2) Configure Embedding Model -----
+
 try:
     embed_model = FastEmbedEmbedding(model_name="BAAI/bge-small-en-v1.5")
     Settings.embed_model = embed_model
@@ -32,8 +33,9 @@ except Exception as e:
 
 
 
-# --- 3. Build and Store Index ---
+# ----- 3) Build and Store Index -----
+
 index = VectorStoreIndex.from_documents(documents, show_progress=True)
 index.storage_context.persist(persist_dir="./index_storage")
 
-print("\n✅ Portfolio index built successfully in ./index_storage")
+print("\n✅ Portfolio index built.")