mirror of
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132 lines
4.8 KiB
TypeScript
132 lines
4.8 KiB
TypeScript
// reply_bot.ts
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import { Agent, Runner, hostedMcpTool, withTrace } from "@openai/agents";
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console.log("✅ Reply bot starting...");
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const allowedMcpTools = [
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"search",
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"reply_to_post",
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"reply_to_comment",
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"recent_posts",
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"get_post",
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"list_unread_messages",
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"mark_notifications_read",
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];
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console.log("🛠️ Configured Hosted MCP tools:", allowedMcpTools.join(", "));
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// ---- MCP 工具（Hosted MCP） ----
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// 关键点：requireApproval 设为 "never"，避免卡在人工批准。
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const mcp = hostedMcpTool({
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serverLabel: "openisle_mcp",
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serverUrl: "https://www.open-isle.com/mcp",
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allowedTools: allowedMcpTools,
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requireApproval: "never",
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});
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type WorkflowInput = { input_as_text: string };
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// 从环境变量读取你的站点鉴权令牌（可选）
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const OPENISLE_TOKEN = process.env.OPENISLE_TOKEN ?? "";
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console.log(
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OPENISLE_TOKEN
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? "🔑 OPENISLE_TOKEN detected in environment."
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: "🔓 OPENISLE_TOKEN not set; agent will request it if required."
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);
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// ---- 定义 Agent ----
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const openisleBot = new Agent({
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name: "OpenIsle Bot",
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instructions: [
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"You are a helpful and cute assistant for https://www.open-isle.com. Please use plenty of kawaii kaomoji (颜表情), such as (๑˃ᴗ˂)ﻭ, (•̀ω•́)✧, (｡•ᴗ-)_♡, (⁎⁍̴̛ᴗ⁍̴̛⁎), etc., in your replies to create a friendly, adorable vibe.",
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"Finish tasks end-to-end before replying. If multiple MCP tools are needed, call them sequentially until the task is truly done.",
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"When presenting the result, reply in Chinese with a concise, cute summary filled with kaomoji and include any important URLs or IDs.",
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OPENISLE_TOKEN
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? `If tools require auth, use this token exactly where the tool schema expects it: ${OPENISLE_TOKEN}`
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: "If a tool requires auth, ask me to provide OPENISLE_TOKEN via env.",
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"After finishing replies, call mark_notifications_read with all processed notification IDs to keep the inbox clean.",
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].join("\n"),
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tools: [mcp],
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model: "gpt-4o",
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modelSettings: {
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temperature: 0.7,
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topP: 1,
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maxTokens: 2048,
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toolChoice: "auto",
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store: true,
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},
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});
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// ---- 入口函数：跑到拿到 finalOutput 为止，然后输出并退出 ----
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export const runWorkflow = async (workflow: WorkflowInput) => {
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// 强烈建议在外部（shell）设置 OPENAI_API_KEY
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if (!process.env.OPENAI_API_KEY) {
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throw new Error("Missing OPENAI_API_KEY");
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}
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const runner = new Runner({
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workflowName: "OpenIsle Bot",
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traceMetadata: {
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__trace_source__: "agent-builder",
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workflow_id: "wf_69003cbd47e08190928745d3c806c0b50d1a01cfae052be8",
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},
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// 如需完全禁用上报可加：tracingDisabled: true
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});
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return await withTrace("OpenIsle Bot run", async () => {
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const preview = workflow.input_as_text.trim();
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console.log(
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"📝 Received workflow input (preview):",
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preview.length > 200 ? `${preview.slice(0, 200)}…` : preview
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);
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// Runner.run 会自动循环执行：LLM → 工具 → 直至 finalOutput
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console.log("🚦 Starting agent run with maxTurns=16...");
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const result = await runner.run(openisleBot, workflow.input_as_text, {
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maxTurns: 16, // 允许更复杂任务多轮调用 MCP
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// stream: true // 如需边跑边看事件可打开，然后消费流事件
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});
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console.log("📬 Agent run completed. Result keys:", Object.keys(result));
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if (!result.finalOutput) {
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// 若没产出最终结果，通常是启用了人工批准/工具失败/达到 maxTurns
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throw new Error("Agent result is undefined (no final output).");
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}
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const openisleBotResult = { output_text: String(result.finalOutput) };
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console.log(
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"🤖 Agent result (length=%d):\n%s",
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openisleBotResult.output_text.length,
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openisleBotResult.output_text
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);
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return openisleBotResult;
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});
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};
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// ---- CLI 运行（示范）----
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if (require.main === module) {
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(async () => {
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try {
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const query = `
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【AUTO】无需确认，自动处理所有未读的提及与评论：
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1）调用 list_unread_messages；
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2）依次处理每条“提及/评论”：如需上下文则使用 get_post 获取，生成简明中文回复；如有 commentId 则用 reply_to_comment，否则用 reply_to_post；
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3）跳过关注和系统事件；
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4）保证幂等性：如该贴最后一条是你自己发的回复，则跳过；
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5）调用 mark_notifications_read，传入本次已处理的通知 ID 清理已读；
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6）最多只处理最新10条；结束时仅输出简要摘要（包含URL或ID）。
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`;
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console.log("🔍 Running workflow...");
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await runWorkflow({ input_as_text: query });
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process.exit(0);
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} catch (err: any) {
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console.error("❌ Agent failed:", err?.stack || err);
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process.exit(1);
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}
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})();
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}
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