diff --git a/examples/langchain_react_agent.py b/examples/langchain_react_agent.py
index 7d372ca..c52a72d 100644
--- a/examples/langchain_react_agent.py
+++ b/examples/langchain_react_agent.py
@@ -1,13 +1,10 @@
 """
 Basic LangChain agent using OpenGradient.
-
 Creates a simple ReAct agent with a tool, powered by an OpenGradient LLM.
-
 Usage:
     export OG_PRIVATE_KEY="your_private_key"
     python examples/langchain_react_agent.py
 """
-
 import os
 
 from langchain_core.tools import tool
@@ -17,20 +14,17 @@
 
 private_key = os.environ["OG_PRIVATE_KEY"]
 
-# Ensure sufficient OPG allowance for Permit2 spending
 llm_client = og.LLM(private_key=private_key)
 llm_client.ensure_opg_approval(min_allowance=5)
 
-# Create the OpenGradient LangChain adapter
 llm = og.agents.langchain_adapter(
-    private_key=private_key,
+    client=llm_client,
     model_cid=og.TEE_LLM.GPT_4_1_2025_04_14,
     max_tokens=300,
     x402_settlement_mode=og.x402SettlementMode.INDIVIDUAL_FULL,
 )
 
 
-# Define a simple tool
 @tool
 def get_balance(account: str) -> str:
     """Returns the balance for a given account name."""
@@ -38,10 +32,7 @@ def get_balance(account: str) -> str:
     return balances.get(account, "Account not found")
 
 
-# Create a ReAct agent with the tool
 agent = create_react_agent(llm, [get_balance])
 
-# Run the agent
 result = agent.invoke({"messages": [("user", "What is the balance of my 'treasury' account?")]})
-
 print(result["messages"][-1].content)