fix typos

15-rag-and-vector-databases/README.md

@@ -123,7 +123,7 @@ An example of embedded text using OpenAI's `text-embedding-ada-002` model is:
 
 ## Retrieval and Vector Search
 
-When a user asks a question, the retriever transforms it into a vector using the query encoder, it then searches the through our document search index for relevant vectors in the document that are related to the input. Once done, it converts both the input vector and document vectors into text and passes it through the LLM.
+When a user asks a question, the retriever transforms it into a vector using the query encoder, it then searches through our document search index for relevant vectors in the document that are related to the input. Once done, it converts both the input vector and document vectors into text and passes it through the LLM.
 
 ### Retrieval
 
@@ -207,7 +207,7 @@ def chatbot(user_input):
 
     # create a message object
     messages=[
-        {"role": "system", "content": "You are an AI assiatant that helps with AI questions."},
+        {"role": "system", "content": "You are an AI assistant that helps with AI questions."},
         {"role": "user", "content": history[-1]}
     ]