release: v2.0.3 - AI 1-Person Company Engine & Business Intelligence

src/features/company/ceoReporter.ts

@@ -0,0 +1,120 @@
+/**
+ * CEO synthesis pass — runs after all specialists have finished.
+ *
+ * Given the per-agent outputs, this asks the CEO model to produce the final
+ * markdown report (✅ 완료 / 🚀 다음 / 💡 인사이트) that the user actually
+ * reads. The function deliberately doesn't try to *parse* the response —
+ * we trust the prompt to keep the structure and surface the text as-is.
+ *
+ * Failure mode: when the CEO call errors out we still return whatever raw
+ * text we managed to collect (typically empty). The dispatcher then
+ * concatenates the per-agent outputs into a fallback report so the user
+ * never sees a blank screen.
+ */
+import { IAIService } from '../../core/services';
+import { logError } from '../../utils';
+import { getCompanyAgent } from './agents';
+import { applyPromptVars, CEO_REPORT_PROMPT } from './promptAssets';
+import { AgentTurnOutput, CompanyState, CompanyTaskPlan } from './types';
+
+/** Max characters of per-agent output to feed back into the CEO synthesis. */
+const PER_AGENT_REPORT_BUDGET = 2000;
+
+export interface ReportResult {
+    /** Generated markdown. Empty string on hard failure. */
+    report: string;
+    /** True when the LLM call succeeded with non-empty content. */
+    ok: boolean;
+}
+
+/**
+ * Build the user-message payload the CEO sees: the brief, plus each agent's
+ * task + output, lightly trimmed so the planner-model's context window
+ * doesn't blow up on a verbose specialist.
+ */
+function _buildReportUserMessage(
+    plan: CompanyTaskPlan,
+    outputs: AgentTurnOutput[],
+): string {
+    const lines: string[] = [];
+    if (plan.brief) {
+        lines.push('## 이번 작업 브리프');
+        lines.push(plan.brief);
+        lines.push('');
+    }
+    lines.push('## 에이전트별 산출물');
+    if (outputs.length === 0) {
+        lines.push('_(no agent dispatched this turn — produce a brief acknowledgement instead)_');
+    } else {
+        for (const out of outputs) {
+            const def = getCompanyAgent(out.agentId);
+            const head = def ? `### ${def.emoji} ${def.name}` : `### ${out.agentId}`;
+            lines.push('');
+            lines.push(head);
+            lines.push(`**Task:** ${out.task}`);
+            if (out.error) {
+                lines.push(`**Note:** dispatch failed — \`${out.error}\`. 사용 가능한 부분만 인용해서 보고.`);
+            }
+            lines.push('');
+            const body = out.response.length > PER_AGENT_REPORT_BUDGET
+                ? out.response.slice(0, PER_AGENT_REPORT_BUDGET) + '\n…(truncated)'
+                : out.response;
+            lines.push(body);
+        }
+    }
+    return lines.join('\n');
+}
+
+/** Build a fallback report by concatenating agent outputs verbatim. Used when the LLM synthesis fails. */
+export function buildFallbackReport(
+    plan: CompanyTaskPlan,
+    outputs: AgentTurnOutput[],
+): string {
+    const parts: string[] = ['## ✅ 완료된 작업'];
+    if (outputs.length === 0) {
+        parts.push('- _(no agents ran this turn)_');
+    } else {
+        for (const out of outputs) {
+            const def = getCompanyAgent(out.agentId);
+            const head = def ? `**${def.emoji} ${def.name}**` : `**${out.agentId}**`;
+            const firstLine = (out.response.split(/\n/).find((l) => l.trim()) || out.task).trim();
+            parts.push(`- ${head} — ${firstLine.slice(0, 120)}`);
+        }
+    }
+    parts.push('');
+    parts.push('## 🚀 다음 액션');
+    parts.push('_(CEO 합성 실패 — 위 산출물을 직접 확인하세요)_');
+    parts.push('');
+    parts.push('## 💡 인사이트');
+    parts.push(`- 이번 턴은 ${outputs.length}명의 에이전트가 작업했습니다.`);
+    if (plan.brief) parts.push(`- 브리프: ${plan.brief}`);
+    return parts.join('\n');
+}
+
+/** End-to-end synthesis call. Never throws — returns `{ ok: false, … }` on error. */
+export async function runCeoReporter(
+    ai: IAIService,
+    plan: CompanyTaskPlan,
+    outputs: AgentTurnOutput[],
+    state: CompanyState,
+    options: { model?: string; timeoutMs?: number } = {},
+): Promise<ReportResult> {
+    const system = applyPromptVars(CEO_REPORT_PROMPT, { company: state.companyName });
+    const user = _buildReportUserMessage(plan, outputs);
+    try {
+        const result = await ai.chat({
+            system,
+            user,
+            model: options.model,
+            timeoutMs: options.timeoutMs,
+        });
+        const text = (result.content || '').trim();
+        if (!text) {
+            return { report: buildFallbackReport(plan, outputs), ok: false };
+        }
+        return { report: text, ok: true };
+    } catch (e: any) {
+        logError('ceoReporter: AI call failed.', { error: e?.message ?? String(e) });
+        return { report: buildFallbackReport(plan, outputs), ok: false };
+    }
+}