diff --git a/_ml-commons-plugin/conversational-search.md b/_ml-commons-plugin/conversational-search.md
index 92a7f26326..2ddaf02729 100644
--- a/_ml-commons-plugin/conversational-search.md
+++ b/_ml-commons-plugin/conversational-search.md
@@ -353,13 +353,13 @@ GET /<index_name>/_search?search_pipeline=<pipeline_name>
 }
 ```
 
-The RAG search query uses the following request objects under the `generative_qa_paramters` option.
+The RAG search query uses the following request objects under the `generative_qa_parameters` option.
 
 Parameter | Required | Description
 :--- | :--- | :---
 `llm_question` | Yes | The question the LLM must answer. 
 `llm_model` | No | Overrides the original model set in the connection in cases where you want to use a different model (for example, GPT 4 instead of GPT 3.5). This option is required if a default model is not set during pipeline creation.
-`coversation_id` | No | Integrates conversation memory into your RAG pipeline by adding the 10 most recent conversations into the context of the search query to the LLM. 
+`conversation_id` | No | Integrates conversation memory into your RAG pipeline by adding the 10 most recent conversations into the context of the search query to the LLM. 
 
 If your LLM includes a set token limit, set the `size` field in your OpenSearch query to limit the number of documents used in the search response. Otherwise, the RAG pipeline will send every document in the search results to the LLM.