diff --git a/README.md b/README.md
index 9f40b24..01632a5 100644
--- a/README.md
+++ b/README.md
@@ -7,7 +7,7 @@ We provide 2 starter kits:
 1. Uses `LangChain`
 2. Uses OpenAI's `Swarm` framework
 
-Both agents are equipped with Coinbase's [AgentKit](https://github.com/coinbase/cdp-agentkit) for making on-chain transactions as well as a Twitter toolbox for read and write access to X.
+Both agents use OpenGradient's verifiable inference and on-chain ML tools for AI-powered workflows.
 
 ## Documentation
 
diff --git a/langchain-starter/README.md b/langchain-starter/README.md
index 8df817c..caae143 100644
--- a/langchain-starter/README.md
+++ b/langchain-starter/README.md
@@ -20,7 +20,7 @@ The agent is equipped by the following tools:
 
 1. Dependencies are defined in `requirements.txt`, run `pip install -r requirements.txt` to install all dependencies. We recommend using virtualenv.
 2. You'll need an OpenGradient token in order to run inferences. You can use the `opengradient` CLI to create it, read more on our [official docs](https://docs.opengradient.ai/developers/sdk/#credentials-setup).
-3. Make a copy of the `.env.sh.template` file in the root folder and rename to `.env.sh`. Fill in with your OpenGradient token as well as Twitter API keys.
+3. Make a copy of the `.env.sh.template` file in the root folder and rename to `.env.sh`. Fill in with your OpenGradient token.
 
 Note: If you run into git permission denied error messages, please generate a Github SSH key.
 ```
diff --git a/langchain-starter/agent.py b/langchain-starter/agent.py
index ecdc87f..cc8141d 100644
--- a/langchain-starter/agent.py
+++ b/langchain-starter/agent.py
@@ -22,6 +22,6 @@ def create_agent_executor():
     agent_executor = create_react_agent(
         model=llm, 
         tools=create_agent_toolkit(),
-        messages_modifier=AGENT_SYSTEM_PROMPT)
+        state_modifier=AGENT_SYSTEM_PROMPT)
 
     return agent_executor
\ No newline at end of file
diff --git a/langchain-starter/tools.py b/langchain-starter/tools.py
index 1ac3724..5097680 100644
--- a/langchain-starter/tools.py
+++ b/langchain-starter/tools.py
@@ -3,7 +3,7 @@
 from langchain_community.tools import WikipediaQueryRun
 from langchain_community.utilities import WikipediaAPIWrapper
 from langchain_core.tools import BaseTool
-from opengradient.mltools import create_og_model_tool, ToolType
+from opengradient.alphasense import create_run_model_tool, ToolType
 
 # Define the tools the agent can use
 def create_agent_toolkit() -> List[BaseTool]:
@@ -13,12 +13,12 @@ def create_agent_toolkit() -> List[BaseTool]:
     tools.append(wikipedia)
 
     # Add Spot Forecast model
-    tools.append(create_og_model_tool(
+    tools.append(create_run_model_tool(
         tool_type=ToolType.LANGCHAIN,
         model_cid="QmY1RjD3s4XPbSeKi5TqMwbxegumenZ49t2q7TrK7Xdga4",
         tool_name="SuiSpotForecast",
-        input_getter=lambda: {"open_high_low_close": fetch_sui_price_candles()},
-        output_formatter=lambda out: f"The predicted price change is: {out['destandardized_prediction'][0] * 100}%",
+        model_input_provider=lambda: {"open_high_low_close": fetch_sui_price_candles()},
+        model_output_formatter=lambda out: f"The predicted price change is: {out['destandardized_prediction'][0] * 100}%",
         tool_description="Runs an ML model to forecast the price of SUI 30 minutes from now. Requires no input."
     ))