Components as Tools
Let your agent render rich React components directly in the chat by calling them as tools.
"""Agent backing the Tool-Based Generative UI demo.
The frontend registers `render_bar_chart` and `render_pie_chart` tools via
`useComponent`. The ADKAgent middleware injects those tools into the model
request at runtime so the agent can call them.
"""
from __future__ import annotations
from google.adk.agents import LlmAgent
from ag_ui_adk import AGUIToolset
from agents.shared_chat import get_model, stop_on_terminal_text
_INSTRUCTION = (
"You are a data visualization assistant.\n\n"
"When the user asks for a chart, call `render_bar_chart` or "
"`render_pie_chart` with a concise title, short description, and a "
"`data` array of `{label, value}` items. Pick bar for comparisons over "
"a small set of categories; pick pie for composition / share-of-whole.\n\n"
"If the user names a chart subject but does NOT supply concrete numbers "
'(e.g. "show me a pie chart of website traffic by source"), do NOT '
"ask them for data. Invent plausible illustrative sample values "
"yourself, call the appropriate `render_*` tool immediately, and "
"briefly note in the follow-up that the values are illustrative "
"samples. Always render the chart on the first turn -- never reply "
"with a clarifying question asking for the data.\n\n"
"Keep chat responses brief -- let the chart do the talking."
)
gen_ui_tool_based_agent = LlmAgent(
name="GenUiToolBasedAgent",
model=get_model(),
instruction=_INSTRUCTION,
tools=[AGUIToolset()],
after_model_callback=stop_on_terminal_text,
)
What is this?#
Tool-based Generative UI is the simplest form of Generative UI: you register
a React component with useComponent, and CopilotKit exposes it to the
agent as a tool. When the agent calls the tool, CopilotKit renders your
component inline in the chat, passing the tool's arguments straight through
as typed props.
Unlike tool rendering, which wraps a real backend tool in a custom UI, tool-based GenUI is the component. There is no handler, no user interaction, no server-side execution. The agent decides when to show it, populates the data, and CopilotKit paints it.
When should I use this?#
Use useComponent when you want to:
- Display rich UI (cards, charts, tables, dashboards) inline in the chat
- Show structured data the agent has derived from its reasoning
- Render previews, status indicators, or visual summaries
- Let the agent present information beyond plain text
For components that need user interaction, see Human-in-the-loop. For operational transparency around a real backend tool, see Tool rendering.
How it works in code#
Install the ADK + AG-UI bridge
pip install ag-ui-adkAdd AGUIToolset() to your agent
AGUIToolset() exposes CopilotKit's frontend tools to the model.
Add it to your LlmAgent's tools= list. Use an ADK-supported model
available to your project.
The callback below preserves the Gemini termination safeguard: it stops on
final text with a STOP finish reason, while leaving partial responses and
pending tool calls alone. It is defined here in full, not imported from
ag-ui-adk or a showcase-only module.
from ag_ui_adk import AGUIToolset
from google.adk.agents import LlmAgent
from google.adk.agents.callback_context import CallbackContext
from google.adk.models.llm_response import LlmResponse
def stop_on_terminal_text(
callback_context: CallbackContext, llm_response: LlmResponse
) -> None:
content = llm_response.content
if llm_response.partial or not content or content.role != "model":
return
finish_reason = llm_response.finish_reason
if getattr(finish_reason, "name", finish_reason) != "STOP":
return
parts = content.parts or []
if not any(part.text for part in parts) or any(part.function_call for part in parts):
return
# ADK's invocation context is private; tolerate SDK changes.
invocation = getattr(callback_context, "_invocation_context", None)
if invocation is not None:
try:
invocation.end_invocation = True
except AttributeError:
pass
agent = LlmAgent(
name="assistant",
model="gemini-3.1-flash-lite",
instruction="Help the user and call the available frontend tools when appropriate.",
tools=[AGUIToolset()],
after_model_callback=stop_on_terminal_text,
)Import the React hook and Zod in the component that registers the tool. This also applies to the built-in agent, which needs no backend tool-registration step.
import { useComponent } from "@copilotkit/react-core/v2";
import { z } from "zod";useComponent takes a name, a Zod schema for its props, and the component
to render. The runtime registers it as a frontend tool so the agent can
discover it, and Zod validates the LLM's arguments before they reach your
component.
useComponent({ name: "render_bar_chart", description: "Display a bar chart with labeled numeric values.", parameters: barChartPropsSchema, render: BarChart, });The component itself is ordinary React: it reads only its props and can stream in as the agent fills the payload. The example above uses Recharts for the bar chart; it doesn't know anything about CopilotKit.
The name you pass to useComponent is what the agent sees as the tool
name. Make it a verb like render_bar_chart or show_weather so the LLM
reliably picks it when the user asks for that visualization.