import { NextResponse } from "next/server";
import { getProviderDefaultBaseUrl } from "@/lib/ai/provider-defaults";
import { resolveModelRuntimeId } from "@/lib/ai/model-runtime";
import { getAgentAiModelWithProvider } from "@/lib/db/queries";
import { createLogger } from "@/lib/observability/logger";
import { isPascalInternalRequest } from "@/lib/pascal/internal-auth";

export const dynamic = "force-dynamic";
export const maxDuration = 600;
export const runtime = "nodejs";

const logger = createLogger("pascal-model-gateway");
const OPENAI_COMPATIBLE_PROVIDER_TYPES = new Set([
  "alibaba",
  "custom",
  "openai",
  "zhipu",
]);

function upstreamChatUrl(baseUrl: string) {
  const normalized = baseUrl.replace(/\/+$/, "");
  return normalized.endsWith("/chat/completions")
    ? normalized
    : `${normalized}/chat/completions`;
}

function openAiError(message: string, status: number) {
  return NextResponse.json(
    { error: { message, type: "pascal_gateway_error" } },
    { status }
  );
}

export async function GET(request: Request) {
  if (!isPascalInternalRequest(request)) {
    return NextResponse.json({ error: "not_found" }, { status: 404 });
  }

  const configured = await getAgentAiModelWithProvider();
  if (!configured) {
    return NextResponse.json({ configured: false });
  }

  return NextResponse.json({
    configured: true,
    compatible: OPENAI_COMPATIBLE_PROVIDER_TYPES.has(configured.provider.type),
    model: configured.model.displayName || configured.model.modelId,
    provider: configured.provider.name,
    providerType: configured.provider.type,
  });
}

export async function POST(request: Request) {
  if (!isPascalInternalRequest(request)) {
    return NextResponse.json({ error: "not_found" }, { status: 404 });
  }

  let body: Record<string, unknown>;
  try {
    const parsed = await request.json();
    if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) {
      return openAiError("Invalid request body.", 400);
    }
    body = parsed as Record<string, unknown>;
  } catch {
    return openAiError("Invalid JSON body.", 400);
  }

  const configured = await getAgentAiModelWithProvider();
  if (!configured) {
    return openAiError("No enabled Agent text model is configured.", 503);
  }

  const { model, provider } = configured;
  if (!OPENAI_COMPATIBLE_PROVIDER_TYPES.has(provider.type)) {
    return openAiError(
      `The configured Agent provider type '${provider.type}' is not OpenAI-compatible.`,
      503
    );
  }

  const baseUrl =
    provider.baseUrl?.trim() || getProviderDefaultBaseUrl(provider.type) || "";
  const runtimeModelId = resolveModelRuntimeId(model, {
    providerType: provider.type,
  });
  if (!baseUrl || !runtimeModelId || !provider.apiKey) {
    return openAiError("The configured Agent model is incomplete.", 503);
  }

  const startedAt = Date.now();
  try {
    const upstream = await fetch(upstreamChatUrl(baseUrl), {
      method: "POST",
      headers: {
        Authorization: `Bearer ${provider.apiKey}`,
        "Content-Type": "application/json",
      },
      body: JSON.stringify({ ...body, model: runtimeModelId }),
      cache: "no-store",
      signal: request.signal,
    });

    logger.info("upstream completed", {
      elapsedMs: Date.now() - startedAt,
      modelId: model.id,
      providerId: provider.id,
      status: upstream.status,
    });

    const headers = new Headers({
      "Cache-Control": "no-cache, no-transform",
      "Content-Type":
        upstream.headers.get("content-type") || "application/json; charset=utf-8",
      "X-Accel-Buffering": "no",
    });
    return new Response(upstream.body, { status: upstream.status, headers });
  } catch (error) {
    logger.error("upstream failed", {
      elapsedMs: Date.now() - startedAt,
      error: error instanceof Error ? error.message : String(error),
      modelId: model.id,
      providerId: provider.id,
    });
    return openAiError("The configured Agent model is temporarily unavailable.", 502);
  }
}