Slack Agent 示例

cd my-slack-agent

npm install agents openai

touch .env

SLACK_CLIENT_ID="your-slack-client-id"
SLACK_CLIENT_SECRET="your-slack-client-secret"
SLACK_SIGNING_SECRET="your-slack-signing-secret"
OPENAI_API_KEY="your-openai-api-key"
OPENAI_BASE_URL="https://gateway.ai.cloudflare.com/v1/YOUR_ACCOUNT_ID/YOUR_GATEWAY/openai"

import { env } from "cloudflare:workers";
import { SlackAgent } from "./slack";
import { OpenAI } from "openai";

const openai = new OpenAI({
	apiKey: env.OPENAI_API_KEY,
	baseURL: env.OPENAI_BASE_URL,
});

type SlackMsg = {
	user?: string;
	text?: string;
	ts: string;
	thread_ts?: string;
	subtype?: string;
	bot_id?: string;
};

function normalizeForLLM(msgs: SlackMsg[], selfUserId: string) {
	return msgs.map((m) => {
		const role = m.user && m.user !== selfUserId ? "user" : "assistant";
		const text = (m.text ?? "").replace(/<@([A-Z0-9]+)>/g, "@$1");
		return { role, content: text };
	});
}

export class MyAgent extends SlackAgent {
	async generateAIReply(conversation: SlackMsg[]) {
		const selfId = await this.ensureAppUserId();
		const messages = normalizeForLLM(conversation, selfId);

		const system = `You are a helpful AI assistant in Slack.
Be brief, specific, and actionable. If you're unsure, ask a single clarifying question.`;

		const input = [{ role: "system", content: system }, ...messages];

		const response = await openai.chat.completions.create({
			model: "gpt-4o-mini",
			messages: input,
		});

		const msg = response.choices[0].message.content;
		if (!msg) throw new Error("No message from AI");

		return msg;
	}

	async onSlackEvent(event: { type: string } & Record<string, unknown>) {
		// Ignore bot messages and subtypes (edits, joins, etc.)
		if (event.bot_id || event.subtype) return;

		// Handle direct messages
		if (event.type === "message") {
			const e = event as unknown as SlackMsg & { channel: string };
			const isDM = (e.channel || "").startsWith("D");
			const mentioned = (e.text || "").includes(
				`<@${await this.ensureAppUserId()}>`,
			);

			if (!isDM && !mentioned) return;

			const conversation = await this.fetchConversation(e.channel);
			const content = await this.generateAIReply(conversation);
			await this.sendMessage(content, { channel: e.channel });
			return;
		}

		// Handle @mentions in channels
		if (event.type === "app_mention") {
			const e = event as unknown as SlackMsg & {
				channel: string;
				text?: string;
			};
			const thread = await this.fetchThread(e.channel, e.thread_ts || e.ts);
			const content = await this.generateAIReply(thread);
			await this.sendMessage(content, {
				channel: e.channel,
				thread_ts: e.thread_ts || e.ts,
			});
			return;
		}
	}
}

export default MyAgent.listen({
	clientId: env.SLACK_CLIENT_ID,
	clientSecret: env.SLACK_CLIENT_SECRET,
	slackSigningSecret: env.SLACK_SIGNING_SECRET,
	scopes: [
		"chat:write",
		"chat:write.public",
		"channels:history",
		"app_mentions:read",
		"im:write",
		"im:history",
	],
});

npm run dev

npx cloudflared tunnel --url http://localhost:8787

npx wrangler secret put SLACK_CLIENT_ID
npx wrangler secret put SLACK_CLIENT_SECRET
npx wrangler secret put SLACK_SIGNING_SECRET
npx wrangler secret put OPENAI_API_KEY
npx wrangler secret put OPENAI_BASE_URL

npx wrangler deploy

https://my-slack-agent.your-account.workers.dev

const response = await openai.chat.completions.create({
	model: "gpt-4o", // 或其他 model
	messages: input,
});

async storeMessage(channel: string, message: SlackMsg) {
  const history = await this.ctx.storage.kv.get(`history:${channel}`) || [];
  history.push(message);
  await this.ctx.storage.kv.put(`history:${channel}`, history);
}

async onSlackEvent(event: { type: string } & Record<string, unknown>) {
  if (event.type === "message") {
    const e = event as unknown as SlackMsg & { channel: string };

    if (e.text?.includes("help")) {
      await this.sendMessage("Here's how I can help...", {
        channel: e.channel
      });
      return;
    }
  }

  // ... rest of your event handling
}

import { Ai } from "@cloudflare/ai";

export class MyAgent extends SlackAgent {
	async generateAIReply(conversation: SlackMsg[]) {
		const ai = new Ai(this.ctx.env.AI);
		const response = await ai.run("@cf/meta/llama-3-8b-instruct", {
			messages: normalizeForLLM(conversation, await this.ensureAppUserId()),
		});
		return response.response;
	}
}