@cognite/copilot-core

This is the core library for the Copilot. It contains the UI for the chatbot, and acts as a thin wrapper above the Chains from @cognite/llm-hub.

Getting started

1. Install the library

yarn add @cognite/copilot-core
# if your in `fusion` repo already, you can skip this,
# '@fusion/copilot-core' is already avaialble to you

2. import the Copilot component from the library and mount it. It expects a valid sdk (CogniteClient).

import { Copilot } from '@cognite/copilot-core';
// or
// import { Copilot } from '@fusion/copilot-core'

// somewhere in your app
<Copilot sdk={sdk}>{/* children */}</Copilot>;

You can mount the copilot anywhere in your app, but we recommend the root. With this wrapper, useCopilotContext will be available to you anywhere in your app. You can use this to customize the copilot chat interface, such as (or "for example"/"e.g."):

• availability of the button / UI
• how "messages" (responses from AI and user) behave
• which features are available to run in the UI
• run a specific feature

We call these features "Flows", more on this in next section.

Flows

Flows are features you can run to help a user do a task end to end. They are wrapped around a Chain from @cognite/llm-hub usually, but they can be anything.

For example, we have PythonAppBuilderFlow which is a flow that helps a user build a python app. This flow is a wrapper around the PythonAppBuilderChain from @cognite/llm-hub. In the Flow, we add the ability for apps to pass in the current code, and also decide how the response should be rendered as a UI for the user.

Create a flow

A Flow is defined as the following:

import { CogniteClient } from '@cognite/sdk';

import { Flow, CopilotBotTextResponse } from '@cognite/copilot-core'; // or '@fusion/copilot-core' from within the fusion repo

type Input = { prompt: string; sdk: CogniteClient }; // must at least have SDK

type Output = CopilotBotTextResponse; // must be one of CopilotBotResponse

export class MyAwesomeFlow extends Flow<Input, Output> {
  label = 'Inquire about CDF';
  description = 'Answer questions about CDF';

  // must be implemented
  // takes the input, does magic, and gives a Response
  run: Flow<Input, Output>['run'] = async ({ prompt, sdk }) => {
    // some magic...
    // here you should also run Chains from @cognite/llm-hub

    return {
      type: 'text',
      content: 'some new content',
    };
  };
  // implement chatRun to allow for it to run from Copilot
  chatRun: Flow<Input, Output>['chatRun'] = async (sendMessage, sendStatus) => {
    // loop through required Inputs that hasnt been completed yet
    if (this.fields?.prompt === undefined) {
      // return only valid "UserAction" (those supported by the chatbot)
      return {
        text: 'What would like you like to know about CDF?',
        type: 'text',
        onNext: ({ content }) => {
          this.fields.prompt = content;
        },
      };
    }
    // update status
    sendStatus({ status: 'Finding answer...' });
    // send a Response to the copilot coming back by the default run
    // and send to the user as a Message
    sendMessage(await this.run(this.fields as Input));
    // reset the state after a response is finished
    this.fields.prompt = undefined;

    // return undefined to stop the chatbot from asking for more input
    return undefined;
  };
}

Running a flow

After declaring the flow, there are 2 ways to run the flow.

1. Run it directly from the app

const { runFlow } = useCopilotContext();

const flow = useMemo(() => new MyAwesomeFlow({ sdk }), [sdk]);

const response = await runFlow(flow, { prompt: 'What is CDF' });

// if you want to have the response in the chatbot with a message indicating some context, you can do

const response = await runFlow(flow, { prompt: 'What is CDF' }, true, { type: 'text', content: 'Running this now', source: 'user' });

2. Enable it from the chat bot

const { registerFlow } = useCopilotContext();

const flow = useMemo(() => new MyAwesomeFlow({ sdk }), [sdk]);

useEffect(() => {
  const unregister = await registerFlow({
    flow,
  });

  // dont forget to unregister the flow
  return () => unregister();
}, []);

Async input

Sometimes you need to pass in additional input to the flow that needs to be passed in at time of request (i.e. the current code when user runs the Flow).

const unregister = await registerFlow({
  flow,
  input: {
    somethingFromTheApp: () => someRef.current.value,
  },
});

Additional message actions (buttons)

Sometimes the message from Copilot (Responses from Flows) needs additional actions for users to be able to interact with. For example, the PythonAppBuilderFlow has a "Use code" button that allows users to use the code.

const unregister = await registerFlow({
  flow,
  undefined,
  messageActions: {
    text: (message) => [
      {
        content: 'Use code',
        onClick: () => {
          // do something with message.content
        },
      },
    ],
  },
});

Copilot core additional states

AI states

1. loadingStatus - the current loading status of the copilot

UI states

1. messages - all the current messages
2. createNewChat - creates a new chat
3. showChatButton/setShowChatButton - the current visibility of the chat button

Diagram of how it works

Explaining more of how it works, here's some diagrams

Missing styles, monaco editor, and web workers

monaco

Make sure to create a file like the following

/* eslint-disable import/no-webpack-loader-syntax */

/**  This is the built in way how to load the web workers using webpack is with worker-loader */
import { loader } from '@monaco-editor/react';
import * as monaco from 'monaco-editor';
/**  This is the built in way how to load the web workers using webpack is with worker-loader */
import { Environment as MonacoEditorEnvironment } from 'monaco-editor';
import MonacoEditorWorker from 'worker-loader?esModule=true&inline=fallback!monaco-editor/esm/vs/editor/editor.worker?worker';

// point here so the context can be used
declare const self: any;

(self as any).MonacoEnvironment = {
  getWorker(_: string, _label: string) {
    // otherwise, load the default web worker from monaco
    return new MonacoEditorWorker();
  },
} as MonacoEditorEnvironment;

loader.config({ monaco });

styles

Additionally, make sure to load in the styles!

import 'highlight.js/styles/dracula.css';
import 'monaco-editor/dev/vs/editor/editor.main.css';
import 'react-resizable/css/styles.css';
import '@cognite/cogs.js/dist/cogs.css';
import '@cognite/cogs.js-v10/dist/cogs.css';

Local dev

In fusion monorepo if you want to use this library in any subapp, just load it in via @fusion/copilot-core. Then any updates are picked up immediately from the app you are running local dev mode or build.

We have also a thin wrapper for the homepage's copilot, which is in apps/copilot. For that to develop locally read the README there.

To host build the library by itself, you can just run yarn nx build copilot-core --with-deps --watch. The --watch will allow NX to watch for changes and rebuild the library.

For debugging add --skip-nx-cache if you want to make sure it is always building, and not loading from cache.

The output of the library will be at dist/libs/@fusion/copilot-core (NOT dist/libs/copilot-core). This is good to know as you can run yarn link from the library, and then yarn link @cognite/copilot-core from the app you want to use it in. This will allow you to use the locally built library from the app. To see how yarn link works, check here.

working along with a local @cognite/llm-hub

There's a special caveat to just the normal yarn link method, as the `@cognite/sdk`` will cause issues, thus

• in fusion
  • cd node_modules/@cognite/sdk
  • yarn link (set up SDK linking)
  • go back to root (cd ../../../)
• in llm-hub
  • yarn link @cognite/sdk (link up to @cognite/sdk from fusion)
  • yarn build --watch
  • yarn link (set up llm-hub linking)
• in fusion
  • yarn link @cognite/llm-hub (link up to @cognite/llm-hub from cognite-llm-hub)

Voila!

Issues locally built library linking

Copilot is built in fusion, which is linked and imported from other apps (link from fusion, used in app), in these cases you may see errors for common libraries, like error: react hooks invalid or core-js not found.

In these cases, the app you are running takes priority, and fusion side needs to respect the packages of your app. You then would link @cognite/sdk and monaco-editor and react the opposite way - from your app to fusion. To do this, go to node_modules/<package> like node_modules/@cognite/sdk and run yarn link from the other repo (the app you are running copilot in), then in the fusion side (from the root folder /fusion NOT /fusion/lib/copilot-core), do yarn link <package>.

yarn nx build copilot-core --watch again

Note:

Intel chips There is a potential issue with core-js, in which case, install core-js in the root of this repo / in the libs/copilot-core.

Running unit tests

Run yarn nx test copilot-core to execute the unit tests via Jest.

Running storybook

Run yarn nx storybook copilot-core