refactor(api): simplify AI event route with extracted utilities and env-based model

Replace inline JSON extraction with the shared json-utils module,
extract chat response content parsing into a dedicated helper, make
the AI model configurable via AI_MODEL env var, and improve error
messages for production safety.

src/app/api/ai-event/route.ts

@@ -1,10 +1,11 @@
+import { headers } from "next/headers";
 import { NextResponse } from "next/server";
 import { auth } from "@/auth";
-import { headers } from "next/headers";
+import { extractJsonFromText } from "@/lib/json-utils";
 import { openRouterClient } from "@/lib/openrouter-client";
 import { AiEventRequestSchema, AiEventResponseSchema } from "@/lib/types";
 
-const MODEL = "openai/gpt-5.4-mini";
+const MODEL = process.env.AI_MODEL ?? "openai/gpt-5.4-mini";
 
 const buildSystemPrompt = () => `
 You are an assistant that converts natural language and images into an ARRAY of calendar events.
@@ -42,7 +43,26 @@ const callTextOnly = async (systemPrompt: string, prompt: string) => {
 	});
 
 	const rawResponse = await result.getText();
-	return { rawResponse, startTime: performance.now() };
+	return { rawResponse };
+};
+
+/** Extract the text content from an OpenRouter chat.send response. */
+const extractContentFromChatResponse = (response: unknown): string => {
+	if (
+		typeof response === "object" &&
+		response !== null &&
+		"choices" in response
+	) {
+		const choices = (
+			response as {
+				choices: Array<{ message: { content: string | unknown } }>;
+			}
+		).choices;
+		const content = choices?.[0]?.message?.content;
+		if (typeof content === "string") return content;
+		if (content) return JSON.stringify(content);
+	}
+	throw new Error("Unexpected response format from AI chat API");
 };
 
 const callMultimodal = async (
@@ -70,8 +90,6 @@ const callMultimodal = async (
 		},
 	];
 
-	const startTime = performance.now();
-
 	const response = await openRouterClient.chat.send({
 		chatRequest: {
 			model: MODEL,
@@ -79,32 +97,8 @@ const callMultimodal = async (
 		},
 	});
 
-	const rawResponse =
+	const rawResponse = extractContentFromChatResponse(response);
-		typeof response === "object" &&
+	return { rawResponse };
-		"choices" in response &&
-		response.choices?.[0]?.message
-			? typeof response.choices[0].message.content === "string"
-				? response.choices[0].message.content
-				: JSON.stringify(response.choices[0].message.content)
-			: JSON.stringify(response);
-
-	return { rawResponse, startTime };
-};
-
-const extractJsonFromText = (text: string): unknown => {
-	try {
-		return JSON.parse(text);
-	} catch {
-		const codeBlockMatch = text.match(/```(?:json)?\s*([\s\S]*?)```/);
-		if (codeBlockMatch) {
-			return JSON.parse(codeBlockMatch[1].trim());
-		}
-		const arrayMatch = text.match(/\[[\s\S]*\]/);
-		if (arrayMatch) {
-			return JSON.parse(arrayMatch[0]);
-		}
-		throw new Error(`No JSON found in response: ${text.slice(0, 200)}`);
-	}
 };
 
 export async function POST(request: Request) {
@@ -133,25 +127,19 @@ export async function POST(request: Request) {
 	}
 
 	const { prompt, imageBase64 } = parsedInput.data;
-	const inputMode = imageBase64 ? "multimodal" : "text";
 	const systemPrompt = buildSystemPrompt();
-	let rawResponse: string | undefined;
 
 	try {
-		const result =
+		const result = imageBase64
-			inputMode === "multimodal"
+			? await callMultimodal(systemPrompt, prompt, imageBase64)
-				? await callMultimodal(systemPrompt, prompt, imageBase64!)
+			: await callTextOnly(systemPrompt, prompt ?? "");
-				: await callTextOnly(systemPrompt, prompt!);
 
-		rawResponse = result.rawResponse;
+		const rawJson = extractJsonFromText(result.rawResponse);
-
-		const rawJson = extractJsonFromText(rawResponse);
 		const validated = AiEventResponseSchema.safeParse(rawJson);
 
 		if (!validated.success) {
 			console.error("AI response validation failed:", {
 				issues: validated.error.flatten().fieldErrors,
-				rawResponse,
 			});
 
 			return NextResponse.json(
@@ -167,10 +155,7 @@ export async function POST(request: Request) {
 	} catch (error) {
 		console.error("AI Event Creation Error:", error);
 		return NextResponse.json(
-			{
+			{ error: "Failed to process AI response. Please try again." },
-				error: "Failed to parse AI output",
-				raw: error instanceof Error ? error.message : String(error),
-			},
 			{ status: 500 },
 		);
 	}