showcase/shell-docs/src/content/docs/integrations/deepagents/generative-ui/tool-rendering.mdx
<IframeSwitcher id="backend-tools-example" exampleUrl="https://feature-viewer.copilotkit.ai/langgraph/feature/backend_tool_rendering?sidebar=false&chatDefaultOpen=false" codeUrl="https://feature-viewer.copilotkit.ai/langgraph/feature/backend_tool_rendering?view=code&sidebar=false&codeLayout=tabs" exampleLabel="Demo" codeLabel="Code" height="700px" />
<Callout> This example demonstrates the [implementation](#implementation) section applied in the <a href="https://feature-viewer.copilotkit.ai/langgraph/feature/agentic_chat" target="_blank">CopilotKit feature viewer</a>. </Callout>Tools are a way for the LLM to call predefined, typically, deterministic functions. CopilotKit allows you to render these tools in the UI as a custom component, which we call Generative UI.
Rendering tools in the UI is useful when you want to provide the user with feedback about what your agent is doing, specifically when your agent is calling tools. CopilotKit allows you to fully customize how these tools are rendered in the chat.
<Tabs groupId="agent_language" items={['Python', 'TypeScript']} persist> <Tab value="Python"> ```python title="agent.py" from deepagents import create_deep_agent from langchain.tools import tool
# [!code highlight:6]
@tool
def get_weather(location: str):
"""
Get the weather for a given location.
"""
return f"The weather for {location} is 70 degrees."
agent = create_deep_agent(
model="openai:gpt-4o",
tools=[get_weather], # [!code highlight]
system_prompt="You are a helpful assistant.",
)
```
</Tab>
<Tab value="TypeScript">
```ts title="agent.ts"
import { createDeepAgent } from "deepagents";
import { tool } from "langchain";
import { z } from "zod";
// [!code highlight:12]
const getWeather = tool(
(args) => {
return `The weather for ${args.location} is 70 degrees.`;
},
{
name: "get_weather",
description: "Get the weather for a given location.",
schema: z.object({
location: z.string().describe("The location to get weather for"),
}),
}
);
export const agent = createDeepAgent({
model: "openai:gpt-4o",
tools: [getWeather], // [!code highlight]
systemPrompt: "You are a helpful assistant.",
});
```
</Tab>
import { useRenderTool } from "@copilotkit/react-core/v2"; // [!code highlight]
import { z } from "zod";
// ...
const weatherParams = z.object({
location: z.string().describe("The location to get weather for"),
});
const YourMainContent = () => {
// ...
// [!code highlight:14]
useRenderTool({
name: "get_weather",
parameters: weatherParams,
render: ({ status, parameters }) => {
return (
<p className="text-gray-500 mt-2">
{status !== "complete" && "Calling weather API..."}
{status === "complete" && `Called the weather API for ${parameters.location}.`}
</p>
);
},
});
// ...
}
Try asking the agent to get the weather for a location. You should see the custom UI component that we added render the tool call and display the arguments that were passed to the tool.
</Step> </Steps>