refactor(insights): share workbook export and ai defaults

packages/api/src/__tests__/insights-procedure-support.test.ts

@@ -1,3 +1,4 @@
+import { DEFAULT_OPENAI_MODEL } from "@capakraken/shared";
 import { TRPCError } from "@trpc/server";
 import { beforeEach, describe, expect, it, vi } from "vitest";
 
@@ -14,7 +15,7 @@ vi.mock("../ai-client.js", async (importOriginal) => {
         },
       },
     })),
-    isAiConfigured: vi.fn().mockReturnValue(true),
+    isAiConfigured: vi.fn((settings: unknown) => settings != null),
     loggedAiCall: vi.fn(async (_provider, _model, _promptLength, fn) => fn()),
     parseAiError: vi.fn((error: unknown) => error instanceof Error ? error.message : String(error)),
   };
@@ -99,7 +100,7 @@ describe("insights procedure support", () => {
             findUnique: vi.fn().mockResolvedValue({
               id: "singleton",
               aiProvider: "openai",
-              azureOpenAiDeployment: "gpt-4o-mini",
+              azureOpenAiDeployment: DEFAULT_OPENAI_MODEL,
               aiMaxCompletionTokens: 220,
               aiTemperature: 0.4,
             }),
@@ -109,15 +110,15 @@ describe("insights procedure support", () => {
       );
 
       expect(isAiConfigured).toHaveBeenCalledWith(
-        expect.objectContaining({ azureOpenAiDeployment: "gpt-4o-mini" }),
+        expect.objectContaining({ azureOpenAiDeployment: DEFAULT_OPENAI_MODEL }),
       );
       expect(createAiClient).toHaveBeenCalledWith(
-        expect.objectContaining({ azureOpenAiDeployment: "gpt-4o-mini" }),
+        expect.objectContaining({ azureOpenAiDeployment: DEFAULT_OPENAI_MODEL }),
       );
       expect(loggedAiCall).toHaveBeenCalledOnce();
       expect(aiCompletionCreate).toHaveBeenCalledWith(
         expect.objectContaining({
-          model: "gpt-4o-mini",
+          model: DEFAULT_OPENAI_MODEL,
           max_completion_tokens: 220,
           temperature: 0.4,
           messages: expect.arrayContaining([
@@ -148,6 +149,83 @@ describe("insights procedure support", () => {
     }
   });
 
+  it("fails when AI settings are missing", async () => {
+    await expect(
+      generateProjectNarrative(
+        createContext({
+          project: {
+            findUnique: vi.fn().mockResolvedValue({
+              id: "project_1",
+              name: "Apollo",
+              shortCode: "APO",
+              status: "ACTIVE",
+              startDate: new Date("2026-03-03T00:00:00.000Z"),
+              endDate: new Date("2026-04-30T00:00:00.000Z"),
+              budgetCents: 200_000_00,
+              dynamicFields: null,
+              demandRequirements: [],
+              assignments: [],
+            }),
+            update: vi.fn(),
+          },
+          systemSettings: {
+            findUnique: vi.fn().mockResolvedValue(null),
+          },
+        }),
+        { projectId: "project_1" },
+      ),
+    ).rejects.toEqual(
+      expect.objectContaining<Partial<TRPCError>>({
+        code: "PRECONDITION_FAILED",
+        message: "AI is not configured. Please set credentials in Admin → Settings.",
+      }),
+    );
+
+    expect(createAiClient).not.toHaveBeenCalled();
+    expect(loggedAiCall).not.toHaveBeenCalled();
+  });
+
+  it("fails when AI configuration is incomplete", async () => {
+    vi.mocked(isAiConfigured).mockReturnValue(false);
+
+    await expect(
+      generateProjectNarrative(
+        createContext({
+          project: {
+            findUnique: vi.fn().mockResolvedValue({
+              id: "project_1",
+              name: "Apollo",
+              shortCode: "APO",
+              status: "ACTIVE",
+              startDate: new Date("2026-03-03T00:00:00.000Z"),
+              endDate: new Date("2026-04-30T00:00:00.000Z"),
+              budgetCents: 200_000_00,
+              dynamicFields: null,
+              demandRequirements: [],
+              assignments: [],
+            }),
+            update: vi.fn(),
+          },
+          systemSettings: {
+            findUnique: vi.fn().mockResolvedValue({
+              id: "singleton",
+              aiProvider: "openai",
+              azureOpenAiDeployment: null,
+            }),
+          },
+        }),
+        { projectId: "project_1" },
+      ),
+    ).rejects.toEqual(
+      expect.objectContaining<Partial<TRPCError>>({
+        code: "PRECONDITION_FAILED",
+        message: "AI is not configured. Please set credentials in Admin → Settings.",
+      }),
+    );
+    expect(createAiClient).not.toHaveBeenCalled();
+    expect(aiCompletionCreate).not.toHaveBeenCalled();
+  });
+
   it("returns the cached narrative for a project", async () => {
     const result = await getCachedNarrative(
       createContext({

packages/api/src/router/insights-procedure-support.ts

@@ -1,4 +1,9 @@
+import { DEFAULT_OPENAI_MODEL } from "@capakraken/shared";
 import { TRPCError } from "@trpc/server";
+import type {
+  ChatCompletion,
+  ChatCompletionCreateParamsNonStreaming,
+} from "openai/resources/chat/completions/completions";
 import { z } from "zod";
 import { createAiClient, isAiConfigured, loggedAiCall, parseAiError } from "../ai-client.js";
 import type { TRPCContext } from "../trpc.js";
@@ -73,13 +78,15 @@ export async function generateProjectNarrative(
     throw new TRPCError({ code: "NOT_FOUND", message: "Project not found" });
   }
 
-  if (!isAiConfigured(settings)) {
+  if (!settings || !isAiConfigured(settings)) {
     throw new TRPCError({
       code: "PRECONDITION_FAILED",
       message: "AI is not configured. Please set credentials in Admin → Settings.",
     });
   }
 
+  const configuredSettings = settings;
+
   const now = new Date();
   const totalDays = countBusinessDays(project.startDate, project.endDate);
   const elapsedDays = countBusinessDays(
@@ -125,27 +132,30 @@ export async function generateProjectNarrative(
 
 ${dataContext}`;
 
-  const client = createAiClient(settings);
-  const model = settings.azureOpenAiDeployment;
-  const maxTokens = settings.aiMaxCompletionTokens ?? 300;
-  const temperature = settings.aiTemperature ?? 1;
-  const provider = settings.aiProvider ?? "openai";
+  const client = createAiClient(configuredSettings);
+  const model = configuredSettings.azureOpenAiDeployment ?? DEFAULT_OPENAI_MODEL;
+  const maxTokens = configuredSettings.aiMaxCompletionTokens ?? 300;
+  const temperature = configuredSettings.aiTemperature ?? 1;
+  const provider = configuredSettings.aiProvider ?? "openai";
 
   let narrative = "";
   try {
-    const completion = await loggedAiCall(provider, model, prompt.length, () =>
-      client.chat.completions.create({
-        messages: [
-          {
-            role: "system",
-            content: "You are a project management analyst providing brief executive summaries. Be factual and action-oriented.",
-          },
-          { role: "user", content: prompt },
-        ],
-        max_completion_tokens: maxTokens,
-        model,
-        ...(temperature !== 1 ? { temperature } : {}),
-      }),
+    const completionRequest: ChatCompletionCreateParamsNonStreaming = {
+      messages: [
+        {
+          role: "system",
+          content: "You are a project management analyst providing brief executive summaries. Be factual and action-oriented.",
+        },
+        { role: "user", content: prompt },
+      ],
+      max_completion_tokens: maxTokens,
+      model,
+      stream: false,
+      ...(temperature !== 1 ? { temperature } : {}),
+    };
+
+    const completion = await loggedAiCall<ChatCompletion>(provider, model, prompt.length, () =>
+      client.chat.completions.create(completionRequest),
     );
     narrative = completion.choices[0]?.message?.content?.trim() ?? "";
   } catch (error) {