Update RAG.py

RAG.py

@@ -37,12 +37,19 @@ def load_models_llm():
                       "max_length": 100}  # Faster inference
     )
     return llm
-
-
+    
 def create_database(embedding, documents):
-    vector_store = Chroma.from_documents(documents, embedding=embedding)
+    # Use a local Chroma client (no server needed)
+    client = chromadb.Client()
+
+    # Create vector store from documents
+    vector_store = Chroma.from_documents(documents, embedding=embedding, client=client)
     return vector_store
 
+# def create_database(embedding, documents):
+#     vector_store = Chroma.from_documents(documents, embedding=embedding)
+#     return vector_store
+
 # retriever = create_database().as_retriever()