import { LLM_CONFIG } from "../config/llm.js";

/**
 * Pings the local llama.cpp server to ensure it's up, running, and has a model loaded.
 * If the server is offline or still loading, it terminates the pipeline gracefully.
 * Skipped entirely when using a cloud provider.
 */
export async function checkLlmServer(
  url = "http://127.0.0.1:8080/health",
): Promise<void> {
  if (LLM_CONFIG.provider !== "local") {
    console.log("🌐 Using cloud provider — skipping local health check.");
    return;
  }

  try {
    const response = await fetch(url);

    // llama.cpp returns a 503 status if the server is up but the model weights are still loading
    if (response.status === 503) {
      throw new Error(
        "Local AI engine is starting up, but the model is still loading into memory. " +
          "Please wait a minute for the weights to load, then run the pipeline again.",
      );
    }

    // Parse the JSON health response (expected: { status: "ok" })
    const data = (await response.json()) as { status?: string };

    if (response.ok && data.status === "ok") {
      console.log("🟢 Local AI engine is connected and ready for inference!");
      return;
    }

    // Catch-all for unexpected active server responses
    throw new Error(
      `Unknown response from local AI engine health check (Status: ${response.status}).`,
    );
  } catch (error: unknown) {
    if (error instanceof Error && error.message.includes("Local AI engine")) {
      throw error; // Re-throw our own errors
    }
    throw new Error(
      `Could not connect to the local AI engine at ${url}. ` +
        "Make sure your './llama-server' command is actively running in another terminal tab.",
      { cause: error },
    );
  }
}