Integrate Atlas Agent Chat

Add a streaming Atlas Agent chat UI to this Dune app.

Agent external ID: $ARGUMENTS

Your job

Complete these steps in order. Read each file before modifying it.

Step 1 — Understand the app

Read these files before touching anything:

package.json — detect package manager (packageManager field or lock file) and existing deps
src/App.tsx (or equivalent entry component) — understand current structure

Step 2 — Install dependencies

Install the package and its required peer deps using the app's package manager:

pnpm → pnpm add "github:cognitedata/dune-industrial-components#semver:*" @sinclair/typebox ajv ajv-formats
npm → npm install "github:cognitedata/dune-industrial-components#semver:*" @sinclair/typebox ajv ajv-formats
yarn → yarn add "github:cognitedata/dune-industrial-components#semver:*" @sinclair/typebox ajv ajv-formats

Step 3 — Build the chat component

Replace (or create) the main App.tsx with a full chat UI. The component must:

Import useAtlasChat and ChatMessage from @cognite/dune-industrial-components/atlas-agent/react
Get the SDK via useDune() from @cognite/dune
Pass null while loading — client: isLoading ? null : sdk
Show streaming text in real time using msg.isStreaming with a blinking cursor
Show tool call events — when progress.startsWith("Executing:"), render it distinctly (e.g. a ⚙ icon + monospace tool name) so tool calls are clearly visible
Show tool calls — each assistant message.toolCalls (after streaming completes) should appear as expandable cards beneath the message
Abort button — show a "Stop" button while isStreaming, wired to abort()
Reset button — "New chat" button wired to reset()
Auto-scroll — scroll to bottom on new messages and progress updates
Auto-resize textarea — expand up to ~120px, submit on Enter, newline on Shift+Enter

Key hook API

import { useAtlasChat } from "@cognite/dune-industrial-components/atlas-agent/react";
import type { ChatMessage } from "@cognite/dune-industrial-components/atlas-agent/react";

const { messages, send, isStreaming, progress, error, reset, abort } = useAtlasChat({
  client: isLoading ? null : sdk,   // null-safe — hook waits for a real client
  agentExternalId: "...",
  tools?: AtlasTool[],              // optional client-side tools
});

// messages[n].role          — "user" | "assistant"
// messages[n].text          — full text (streams chunk-by-chunk via isStreaming)
// messages[n].isStreaming   — true while this message is being written
// messages[n].toolCalls     — ToolCall[] once response is complete (client + server-side, in call order)
// progress                  — e.g. "Agent thinking" or "Executing: get_timeseries"
// isStreaming               — true for the entire duration of a response

Tool call display pattern

// During streaming — show as a distinct "tool call" bubble above the message
{isStreaming && progress?.startsWith("Executing:") && (
  <div>⚙ {progress}</div>
)}

// After response — show tool calls on the assistant message
{msg.toolCalls?.map((tc, i) => (
  <ToolResult key={i} name={tc.name} output={tc.output} details={tc.details} />
))}

Step 4 — Python tools (optional)

If the agent has Python tools (type runPythonCode in its CDF config), run the setup-python-tools skill to add Pyodide-based client-side execution:

/setup-python-tools $ARGUMENTS

That skill installs pyodide, sets up usePyodideRuntime, and wires the runtime into useAtlasChat via pythonRuntime. The library fetches Python tool code from the agent config automatically — no PythonToolConfig entries needed.

You don't need this if the agent only uses built-in or regular client tools.

Done

Start the app and you should see a streaming chat UI connected to Atlas Agent $ARGUMENTS.

integrate-atlas-chat