feat: showcase thinking steps #98
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| import { OpenAI } from 'openai'; | ||
| import { rollDice, rollDiceDefinition } from './tools/dice.js'; | ||
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| // OpenAI LLM client | ||
| const openai = new OpenAI({ | ||
| apiKey: process.env.OPENAI_API_KEY, | ||
| }); | ||
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| /** | ||
| * Stream an LLM response to prompts with an example dice rolling function | ||
| * | ||
| * @param {import("@slack/web-api").ChatStreamer} streamer - Slack chat stream | ||
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| * @param {Array} prompts - OpenAI ResponseInputParam messages | ||
| * | ||
| * @see {@link https://docs.slack.dev/tools/bolt-js/web#sending-streaming-messages} | ||
| * @see {@link https://platform.openai.com/docs/guides/text} | ||
| * @see {@link https://platform.openai.com/docs/guides/streaming-responses} | ||
| * @see {@link https://platform.openai.com/docs/guides/function-calling} | ||
| */ | ||
| export async function callLLM(streamer, prompts) { | ||
| const toolCalls = []; | ||
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| const response = await openai.responses.create({ | ||
| model: 'gpt-4o-mini', | ||
| input: prompts, | ||
| tools: [rollDiceDefinition], | ||
| tool_choice: 'auto', | ||
| stream: true, | ||
| }); | ||
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| for await (const event of response) { | ||
| // Stream markdown text from the LLM response as it arrives | ||
| if (event.type === 'response.output_text.delta' && event.delta) { | ||
| await streamer.append({ | ||
| markdown_text: event.delta, | ||
| }); | ||
| } | ||
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| // Save function calls for later computation and a new task is shown | ||
| if (event.type === 'response.output_item.done') { | ||
| if (event.item.type === 'function_call') { | ||
| toolCalls.push(event.item); | ||
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| if (event.item.name === 'roll_dice') { | ||
| const args = JSON.parse(event.item.arguments); | ||
| await streamer.append({ | ||
| chunks: [ | ||
| { | ||
| type: 'task_update', | ||
| id: event.item.call_id, | ||
| title: `Rolling a ${args.count}d${args.sides}...`, | ||
| status: 'in_progress', | ||
| }, | ||
| ], | ||
| }); | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| // Perform tool calls and marks tasks as completed | ||
| if (toolCalls.length > 0) { | ||
| for (const call of toolCalls) { | ||
| if (call.name === 'roll_dice') { | ||
| const args = JSON.parse(call.arguments); | ||
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| prompts.push({ | ||
| id: call.id, | ||
| call_id: call.call_id, | ||
| type: 'function_call', | ||
| name: 'roll_dice', | ||
| arguments: call.arguments, | ||
| }); | ||
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| const result = rollDice(args); | ||
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| prompts.push({ | ||
| type: 'function_call_output', | ||
| call_id: call.call_id, | ||
| output: JSON.stringify(result), | ||
| }); | ||
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| if (result.error != null) { | ||
| await streamer.append({ | ||
| chunks: [ | ||
| { | ||
| type: 'task_update', | ||
| id: call.call_id, | ||
| title: result.error, | ||
| status: 'error', | ||
| }, | ||
| ], | ||
| }); | ||
| } else { | ||
| await streamer.append({ | ||
| chunks: [ | ||
| { | ||
| type: 'task_update', | ||
| id: call.call_id, | ||
| title: result.description, | ||
| status: 'complete', | ||
| }, | ||
| ], | ||
| }); | ||
| } | ||
| } | ||
| } | ||
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| // complete the llm response after making tool calls | ||
| await callLLM(streamer, prompts); | ||
| } | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,64 @@ | ||
| /** | ||
| * Roll one or more dice with a specified number of sides. | ||
| * | ||
| * @param {Object} options - The roll options | ||
| * @param {number} [options.sides=6] - The number of sides on the die | ||
| * @param {number} [options.count=1] - The number of dice to roll | ||
| * @returns {Object} The roll results with rolls array, total, and description | ||
| */ | ||
| export function rollDice({ sides = 6, count = 1 } = {}) { | ||
| if (sides < 2) { | ||
| return { | ||
| error: 'A die must have at least 2 sides', | ||
| rolls: [], | ||
| total: 0, | ||
| }; | ||
| } | ||
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| if (count < 1) { | ||
| return { | ||
| error: 'Must roll at least 1 die', | ||
| rolls: [], | ||
| total: 0, | ||
| }; | ||
| } | ||
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| const rolls = Array.from({ length: count }, () => Math.floor(Math.random() * sides) + 1); | ||
| const total = rolls.reduce((sum, roll) => sum + roll, 0); | ||
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| return { | ||
| rolls, | ||
| total, | ||
| description: `Rolled a ${count}d${sides} to total ${total}`, | ||
| }; | ||
| } | ||
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| /** | ||
| * Tool definition for OpenAI API | ||
| * | ||
| * @type {import('openai/resources/responses/responses').Tool} | ||
| * @see {@link https://platform.openai.com/docs/guides/function-calling} | ||
| */ | ||
| export const rollDiceDefinition = { | ||
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| type: 'function', | ||
| name: 'roll_dice', | ||
| description: | ||
| 'Roll one or more dice with a specified number of sides. Use this when the user wants to roll dice or generate random numbers within a range.', | ||
| parameters: { | ||
| type: 'object', | ||
| properties: { | ||
| sides: { | ||
| type: 'integer', | ||
| description: 'The number of sides on the die (e.g., 6 for a standard die, 20 for a d20)', | ||
| default: 6, | ||
| }, | ||
| count: { | ||
| type: 'integer', | ||
| description: 'The number of dice to roll', | ||
| default: 1, | ||
| }, | ||
| }, | ||
| required: ['sides', 'count'], | ||
| }, | ||
| strict: false, | ||
| }; | ||
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note - still deciding how to restructure README.md to make setup easier. I think the most obvious point of confusion is deciding whether to use CLI or terminal to setup, i think a toggle like
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@srtaalej Thanks for calling this out! 📚 ✨ I agree it's a confusing and hope we can encourage the CLI most-
IIRC @lukegalbraithrussell had thoughts on related changes as well and we should match such in slack-samples/bolt-python-assistant-template#42 too!