Integrate Atlas Agent Chat

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

Agent external ID: $ARGUMENTS

Dependencies

The atlas-agent library files (copied in Step 2) require these npm packages:

Package	Version
@sinclair/typebox	^0.33.0
ajv	^8.17.1
ajv-formats	^2.1.1

@cognite/sdk is assumed to already be present in Flows apps.

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Your job

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

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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

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Step 2 — Copy the atlas-agent source files

The atlas-agent library lives in the code/ directory next to this skill file. Read and copy the following files into src/atlas-agent/ inside the app:

• code/types.ts
• code/validation.ts
• code/client.ts
• code/session.ts
• code/react.ts

The Python-related files (python.ts, pyodide.ts, pyodide-react.ts, pyodide-runtime.ts) are only needed if the agent uses Python tools. The setup-python-tools skill copies those.

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Step 3 — Install dependencies

Install the required peer packages (see Dependencies above) using the app's package manager:

• pnpm → pnpm add @sinclair/typebox@^0.33.0 ajv@^8.17.1 ajv-formats@^2.1.1
• npm → npm install @sinclair/typebox@^0.33.0 ajv@^8.17.1 ajv-formats@^2.1.1
• yarn → yarn add @sinclair/typebox@^0.33.0 ajv@^8.17.1 ajv-formats@^2.1.1

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Step 4 — Build the chat component

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

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

Key hook API

import { useAtlasChat } from "./atlas-agent/react";
import type { ChatMessage } from "./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} />
))}

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Step 5 — 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 copies the Python-related source files from @skills/integrate-atlas-chat/code, 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.

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Done

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