Update knowledge_base.py

knowledge_base.py

@@ -6,7 +6,8 @@ from langchain.vectorstores import Chroma
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.docstore.document import Document
 
-CHROMA_DIR = "chroma"
+CHROMA_DIR = os.path.abspath("chroma")
+print("📂 Loading vectorstore from:", CHROMA_DIR)
 MODEL_NAME = "sentence-transformers/all-MiniLM-L6-v2"
 
 # Set this to your actual file on HF
@@ -49,4 +50,15 @@ def create_vectorstore(chunks):
 
 def load_vectorstore():
     embeddings = HuggingFaceEmbeddings(model_name=MODEL_NAME)
-    return Chroma(persist_directory=CHROMA_DIR, embedding_function=embeddings)
+    db = Chroma(persist_directory=CHROMA_DIR, embedding_function=embeddings)
+    
+    try:
+        sample = db.get()["documents"][:5]
+        print("✅ Sample documents from vectorstore:")
+        for i, s in enumerate(sample):
+            print(f"[{i+1}] {s[:100]}...")  # print first 100 chars
+    except Exception as e:
+        print(f"❌ Error loading documents: {e}")
+    
+    return db
+