Update LlamaIndex RAG tutorial

docs/guides/basic-RAG.md

@@ -222,11 +222,10 @@ Visit our [community cookbook example](https://github.com/mistralai/cookbook/blo
 **Code:**
 
 ```python
-from llama_index import VectorStoreIndex, SimpleDirectoryReader
-from llama_index.llms import MistralAI
-from llama_index.embeddings import MistralAIEmbedding
-from llama_index import ServiceContext
-from llama_index.query_engine import RetrieverQueryEngine
+from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
+from llama_index.llms.mistralai import MistralAI
+from llama_index.embeddings.mistralai import MistralAIEmbedding
+from llama_index.core import Settings
 
 # Load data
 reader = SimpleDirectoryReader(input_files=["essay.txt"])
@@ -235,10 +234,10 @@ documents = reader.load_data()
 # Define LLM and embedding model
 llm = MistralAI(api_key=api_key, model="mistral-medium")
 embed_model = MistralAIEmbedding(model_name="mistral-embed", api_key=api_key)
-service_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)
-
+Settings.llm = llm
+Settings.embed_model = embed_model
 # Create vector store index
-index = VectorStoreIndex.from_documents(documents, service_context=service_context)
+index = VectorStoreIndex.from_documents(documents)
 
 # Create query engine
 query_engine = index.as_query_engine(similarity_top_k=2)