LangGraph: Force-Calling a Tool

Summary

This video demonstrates a simple modification to a chat agent executive, where the system is set to always call a tool first before any other action. The setup involves creating tools, a tool executor, and binding them to a model. A new node, called 'first agent,' is introduced to ensure the tool is called initially. The graph is updated with a forced flow, ensuring that the tool is called first, leading to faster results. The video provides a clear walkthrough of the changes and shows how this modification avoids unnecessary language model calls.

Takeaways

• 😀 Watch the 'Chat Agent Executive' video for full context before starting the modification process.
• 😀 The goal is to modify the chat agent to always call a tool first before performing other actions.
• 😀 The core setup remains the same, including creating tools, a tool executor column, and a model.
• 😀 You need to bind tools to the model and define the agent's state as part of the setup.
• 😀 An additional node, called the 'first model node,' is introduced to trigger the tool call first.
• 😀 The first model node should return a message instructing the agent to call a specific tool (e.g., 'tavil search results').
• 😀 The first model node uses the 'query' input from the most recent message content to pass into the tool.
• 😀 The graph is modified to set 'first agent' as the new entry point, ensuring it's always called first.
• 😀 The graph includes conditional nodes for 'agent to action' or 'end', similar to the previous structure.
• 😀 A new node from 'first agent' to 'action' ensures the tool is called first before the agent proceeds to action.
• 😀 The modification results in faster tool responses since it bypasses language model calls initially, using the tool directly.

Q & A

What is the main modification being made to the chat agent executive in this video?

The main modification is ensuring that a tool is always called first before any language model call is made, which is a change in the agent's execution flow.

What should viewers do before watching this video for better context?

Viewers are advised to watch the previous chat agent executive video, as this video builds upon the notebook from that earlier video.

What is the purpose of creating a new 'first model node' in this modification?

The 'first model node' is created to be the first entry point in the system, which will trigger the call of a specific tool, such as the 'tavil search results Json tool,' before anything else.

How does the modified graph differ from the previous version?

The modified graph introduces a new entry point called 'first agent,' making it the first node to be called in the execution flow, in contrast to the previous setup where the agent node was called first.

What tool is specifically being called in the modified system?

The specific tool being called is the 'tavil search results Json tool,' which is passed the query from the most recent message in the system.

How does the system handle language model calls in the modified version?

In the modified version, the language model call is skipped initially, with the system first executing the tool call. The language model is only invoked later in the process after the tool has been called.

What is the reason for forcing the system to always call the tool first?

The goal of forcing the tool to be called first is to ensure that the tool's results are used as inputs for the subsequent steps in the agent's process, optimizing the flow and potentially reducing unnecessary language model calls.

How does the tool execution affect the speed of response?

The tool execution speeds up the response because it bypasses the need for an initial language model call and instead directly uses the inputs passed to the tool, resulting in a faster result.

What does the graph modification add in terms of flow after the first agent node?

After the first agent node, a new node directs the flow to always call the action node, ensuring that the tool call happens first, followed by the rest of the action execution.

What is the role of the conditional node in the new graph structure?

The conditional node ensures that after the first agent node executes, the flow continues to either call an action or end, preserving the flexibility of the previous graph structure while ensuring the tool is called first.