diff --git a/README.md b/README.md
index 8f434be..a10fc5b 100644
--- a/README.md
+++ b/README.md
@@ -18,7 +18,6 @@
    - [Step 4: Faiss Vector Store](#step-4-faiss-vector-store)
    - [Step 5: Ollama Chat Model](#step-5-ollama-chat-model)
    - [Step 6: Buffer Memory](#step-6-buffer-memory)
-   - [Step 7: Conversational Retrieval QA Chain](#step-7-conversational-retrieval-qa-chain)
 7. [Upsert Documents](#upsert-documents)
 8. [Using Cloud LLM APIs (Optional)](#using-cloud-llm-apis-optional)
 9. [Deploy Chatbot to Users](#deploy-chatbot-to-users)
@@ -279,21 +278,6 @@ Connect the **BufferMemory** output to the **Memory** input of the QA Chain.
 
 ---
 
-### Step 7: Conversational Retrieval QA Chain
-
-Search for **"Conversational Retrieval QA Chain"** and drag it onto the canvas.
-
-Connect:
-- **ChatOllama** → **Chat Model**
-- **Faiss Retriever** → **Vector Store Retriever**
-- **BufferMemory** → **Memory**
-
-Leave **Input Moderation** and **Return Source Documents** as optional based on your needs.
-
-**Save the flow** using the save button (top right).
-
----
-
 ## Upsert Documents
 
 Before the chatbot can answer questions, you must index your documents into the vector store.