134 lines
6.4 KiB
TypeScript
134 lines
6.4 KiB
TypeScript
import { Agent } from "@strands-agents/sdk";
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import { OpenAIModel } from "@strands-agents/sdk/models/openai";
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import { StrandsAgent } from "@ag-ui/aws-strands";
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import { createStrandsApp } from "@ag-ui/aws-strands/server";
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import { crm } from "./src/crm/store.js";
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import { registerCrmRoutes } from "./src/routes.js";
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import {
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moveStageTool,
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updateDealTool,
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briefDealTool,
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markWonTool,
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} from "./src/tools/deals.js";
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import { logActivityTool } from "./src/tools/activity.js";
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import { searchWebTool, enrichLeadTool } from "./src/tools/enrich.js";
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import { planPipelineTool } from "./src/tools/plan.js";
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import { recommendProductsTool } from "./src/tools/recommend.js";
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import { analyzeTeamTool, repPerformanceTool } from "./src/tools/team.js";
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import { generateWeeklyReportTool } from "./src/tools/report.js";
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const model = new OpenAIModel({
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apiKey: process.env.OPENAI_API_KEY ?? "",
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modelId: "gpt-5.4",
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// Deterministic capture: launch with OPENAI_API_MODE=chat so the agent uses
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// the Chat Completions API, which aimock intercepts with chat-shaped fixtures.
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// Pair with OPENAI_BASE_URL=<aimock>/v1 (the default OpenAI client reads it).
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// Default behavior is unchanged — the Responses API.
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...(process.env.OPENAI_API_MODE === "chat" ? { api: "chat" as const } : {}),
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});
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const SYSTEM_PROMPT = `You are Northstar Copilot, the AI assistant inside Northstar — a CRM for an enterprise computer seller (laptops, workstations, servers, displays, accessories). You help reps and managers work the pipeline, quote hardware, research prospects, and analyze sales. Be concise and action-oriented. Prefer generative-UI cards over long prose; never dump raw tool JSON.
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## Deal references
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Refer to deals by their human name but always pass the deal id (e.g. "d1") to tools.
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## Navigating the workspace
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When the user asks to see/open/go to a page ("show me the pipeline", "open products", "take me to the team page", "go to reports"), call navigate_to({ page }) with one of: dashboard, pipeline, products, accounts, contacts, team, reports, activity. It switches the workspace to that page — confirm in a short phrase; don't describe the page contents.
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## Daily plan / prioritization / "what should I focus on" / "at-risk" requests
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1. Acknowledge in ONE short sentence (e.g. "Let me take a look at your pipeline…").
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2. Call plan_pipeline EXACTLY ONCE. For daily-plan / "what should I focus on" / prioritization, use focus "all" (the default). For "which deals are at risk" / "what needs attention", call plan_pipeline({ focus: "at_risk" }). Do NOT call brief_deal for multiple deals to build a plan.
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3. The result is rendered as a priorities card in the UI. Do NOT restate, list, or summarize the card contents in prose — no re-listing deal names, amounts, risks, or next steps.
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4. End with EXACTLY ONE suggested next step phrased as a question that names a specific deal, account, or contact from the top priority (e.g. "Want me to research Acme, or draft a follow-up to Jordan at TechCorp?"). One question only.
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## Single-deal briefing
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When the user asks about ONE specific deal, call brief_deal for that deal.
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## Research / enrichment
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When the user asks to research or enrich an account, call enrich_lead.
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## Product recommendations / quotes
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When the user wants to quote hardware or asks what to recommend/sell for an account ("recommend laptops for X", "quote a fleet for Y"), call recommend_products({ accountId or name, seats?, useCase? }). The result renders as a quote card — don't restate the line items in prose.
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## Team performance / analytics
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For team-wide questions ("how is the team doing", "team performance", "sales analytics this quarter"), call analyze_team. The result opens on the Team Reports page (Reports → Team Reports) in the workspace; the chat shows a short handoff. Briefly confirm — don't restate the numbers.
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## Individual rep performance
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When the user asks about ONE salesperson ("how is Maya doing", "show me Diego's numbers"), call rep_performance({ name }). Renders as a rep-stats card.
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## Weekly report
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When the user asks to generate/create a weekly (sales) report, call generate_weekly_report. It saves the report and opens it on the Weekly Reports page (Reports → Weekly Reports) in the workspace; the chat shows a short handoff. Briefly confirm — don't restate the figures.
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## Stage moves and deal edits
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After moving stages or editing deals, briefly confirm what changed (one sentence).
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## Follow-up emails
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To send a follow-up: draft the email, then call confirm_followup({ dealId, to, subject, body }).
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If the user approves, call log_activity({ dealId, type: "email", body }) to record it.`;
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const agent = new Agent({
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model,
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systemPrompt: SYSTEM_PROMPT,
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tools: [
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moveStageTool,
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updateDealTool,
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briefDealTool,
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markWonTool,
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logActivityTool,
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searchWebTool,
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enrichLeadTool,
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planPipelineTool,
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recommendProductsTool,
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analyzeTeamTool,
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repPerformanceTool,
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generateWeeklyReportTool,
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],
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});
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await agent.initialize();
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// After any state-mutating tool runs, push the full CRM snapshot to the UI
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// as a STATE_SNAPSHOT. brief_deal/search_web are read-only → no state push.
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const pushState = {
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stateFromResult: () =>
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crm.getStateSnapshot() as unknown as Record<string, unknown>,
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};
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const aguiAgent = new StrandsAgent({
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agent,
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name: "strands_agent",
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config: {
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toolBehaviors: {
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move_stage: pushState,
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update_deal: pushState,
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mark_won: pushState,
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log_activity: pushState,
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enrich_lead: pushState,
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// generate_weekly_report persists a new Report → push so the Reports page updates live.
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generate_weekly_report: pushState,
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// recommend_products / analyze_team / rep_performance are read-only → no push.
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},
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// Inject a compact pipeline summary into every prompt so the agent always
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// sees current state (including UI-initiated edits).
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stateContextBuilder: (_input, prompt) => {
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const { deals } = crm.getStateSnapshot();
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const lines = deals
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.map(
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(d) =>
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`- ${d.id} "${d.name}" — ${d.stage}, $${d.amount}, ${d.probability}%`,
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)
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.join("\n");
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return `${prompt}\n\n[Current pipeline]\n${lines}`;
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},
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},
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});
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const app = await createStrandsApp(aguiAgent, { path: "/" });
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registerCrmRoutes(app);
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const PORT = Number(process.env.PORT) || 8000;
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app.listen(PORT, () => {
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console.log(`Northstar agent listening on http://localhost:${PORT}`);
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});
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