changes

src/app/api/compliance/m7/ai/playbook/route.ts

@@ -0,0 +1,169 @@
+import { z } from "zod";
+import { NextResponse } from "next/server";
+import { requireAdminApiUser } from "@/lib/auth/admin";
+import { callOpenAiJsonSchema } from "@/lib/ai/openai";
+import { storeAiSuggestionFromEnvelope } from "@/lib/ai/suggestions";
+import { getM7DatasetForUser } from "@/lib/compliance/server";
+import type { M7Dataset } from "@/lib/compliance/types";
+
+const M7_PROMPT_VERSION = "m7_playbook_v1";
+
+const M7PlaybookSchema = z.object({
+  predictedIncidents: z
+    .array(
+      z.object({
+        title: z.string().min(8).max(220),
+        likelihood: z.enum(["alta", "media", "baja"]),
+        impact: z.enum(["alto", "medio", "bajo"]),
+        timeHorizon: z.string().min(4).max(80),
+      }),
+    )
+    .max(12),
+  priorityOrder: z.array(z.string().min(8).max(220)).max(12),
+  preventiveActions: z
+    .array(
+      z.object({
+        action: z.string().min(8).max(400),
+        ownerSuggestion: z.string().min(3).max(120),
+        targetDate: z.string().min(4).max(40),
+      }),
+    )
+    .max(20),
+  escalationAdvice: z.array(z.string().min(8).max(420)).max(8),
+  confidence: z.enum(["low", "medium", "high"]),
+});
+
+const M7PlaybookJsonSchema = {
+  type: "object",
+  additionalProperties: false,
+  required: ["predictedIncidents", "priorityOrder", "preventiveActions", "escalationAdvice", "confidence"],
+  properties: {
+    predictedIncidents: {
+      type: "array",
+      items: {
+        type: "object",
+        additionalProperties: false,
+        required: ["title", "likelihood", "impact", "timeHorizon"],
+        properties: {
+          title: { type: "string" },
+          likelihood: { type: "string", enum: ["alta", "media", "baja"] },
+          impact: { type: "string", enum: ["alto", "medio", "bajo"] },
+          timeHorizon: { type: "string" },
+        },
+      },
+    },
+    priorityOrder: {
+      type: "array",
+      items: { type: "string" },
+    },
+    preventiveActions: {
+      type: "array",
+      items: {
+        type: "object",
+        additionalProperties: false,
+        required: ["action", "ownerSuggestion", "targetDate"],
+        properties: {
+          action: { type: "string" },
+          ownerSuggestion: { type: "string" },
+          targetDate: { type: "string" },
+        },
+      },
+    },
+    escalationAdvice: {
+      type: "array",
+      items: { type: "string" },
+    },
+    confidence: { type: "string", enum: ["low", "medium", "high"] },
+  },
+} as const;
+
+function parseDataset(value: unknown): M7Dataset | null {
+  if (!value || typeof value !== "object" || Array.isArray(value)) {
+    return null;
+  }
+
+  return value as M7Dataset;
+}
+
+export async function POST(request: Request) {
+  const user = await requireAdminApiUser();
+
+  if (!user) {
+    return NextResponse.json({ error: "Unauthorized" }, { status: 401 });
+  }
+
+  const body = (await request.json().catch(() => ({}))) as Record<string, unknown>;
+  const providedDataset = parseDataset(body.dataset);
+  const dataset = providedDataset ?? (await getM7DatasetForUser(user.id));
+
+  const condensedDataset = {
+    generatedAt: dataset.generatedAt,
+    kpis: dataset.kpis,
+    m3States: dataset.m3States,
+    deadlines: dataset.tabs.plazos.slice(0, 25),
+    alerts: dataset.tabs.alertas.slice(0, 40),
+    checklist: dataset.tabs.checklist.slice(0, 25),
+  };
+
+  const systemPrompt = [
+    "Eres un especialista en cumplimiento para contratacion publica en Mexico.",
+    "Construye un playbook preventivo con enfoque operativo para los proximos 30 dias.",
+    "No cambies severidades ni estados existentes: solo sugiere acciones.",
+    "Responde solo JSON valido en espanol.",
+  ].join(" ");
+
+  const userPrompt = [
+    "Dataset actual de M7:",
+    JSON.stringify(condensedDataset),
+    "",
+    "Genera:",
+    "- predictedIncidents: incidentes probables (sin inventar datos externos).",
+    "- priorityOrder: orden de atencion recomendado.",
+    "- preventiveActions: acciones con ownerSuggestion y targetDate.",
+    "- escalationAdvice: criterios breves para escalar a legal/direccion.",
+  ].join("\n");
+
+  const envelope = await callOpenAiJsonSchema({
+    promptVersion: M7_PROMPT_VERSION,
+    systemPrompt,
+    userPrompt,
+    outputSchema: M7PlaybookSchema,
+    schemaName: "m7_playbook",
+    jsonSchema: M7PlaybookJsonSchema as unknown as Record<string, unknown>,
+    model: process.env.OPENAI_M7_MODEL?.trim() || undefined,
+  });
+
+  const payload =
+    envelope.data ??
+    ({
+      predictedIncidents: [],
+      priorityOrder: [],
+      preventiveActions: [],
+      escalationAdvice: [],
+      confidence: envelope.confidence ?? "low",
+    } satisfies z.infer<typeof M7PlaybookSchema>);
+
+  const persisted = await storeAiSuggestionFromEnvelope({
+    userId: user.id,
+    moduleKey: "M7",
+    featureKey: "compliance_playbook",
+    subjectType: "m7_dataset",
+    subjectId: dataset.generatedAt,
+    inputForHash: condensedDataset,
+    envelope,
+    responsePayload: payload,
+  });
+
+  return NextResponse.json({
+    ok: true,
+    ...payload,
+    suggestionId: persisted.suggestionId,
+    meta: {
+      engine: envelope.engine,
+      model: envelope.model,
+      usage: envelope.usage,
+      warnings: envelope.warnings,
+      confidence: envelope.confidence,
+    },
+  });
+}