vectorstore

app.py

@@ -34,7 +34,13 @@ login(token=HF_KEY)
 
 class BSIChatbot:
     def __init__(self, model_paths: Dict[str, str], docs_path: str):
-        self.embedding_model = None
+        #self.embedding_model = None
+        self.embedding_model = HuggingFaceEmbeddings(
+            model_name=self.word_and_embed_model_path,
+            multi_process=True,
+            model_kwargs={"device": "cuda"},
+            encode_kwargs={"normalize_embeddings": True},
+        )
         self.llmpipeline = None
         self.llmtokenizer = None
         self.vectorstore = None
@@ -52,12 +58,7 @@ class BSIChatbot:
         raw_knowledge_base = []
 
         # Initialize embedding model
-        self.embedding_model = HuggingFaceEmbeddings(
-            model_name=self.word_and_embed_model_path,
-            multi_process=True,
-            model_kwargs={"device": "cuda"},
-            encode_kwargs={"normalize_embeddings": True},
-        )
+
 
         if rebuild_embeddings:
             # Load documents