import os from "node:os";
import { parseArgs } from "node:util";
import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
import { type ModelMessage, streamText } from "ai";

import StreamRenderer from "./src/render";

const { values: args, positionals } = parseArgs({
  args: Bun.argv,
  options: {
    model: {
      type: "string",
    },
    new: {
      type: "boolean",
    },
  },
  strict: true,
  allowPositionals: true,
});

const home = os.homedir();
const convoFile = Bun.file(`${home}/.aicl_convo.json`);

async function main() {
  const provider = createOpenAICompatible({
    name: "llama.cpp",
    apiKey: "local",
    baseURL: "http://127.0.0.1:8080/v1",
    includeUsage: true, // Include usage information in streaming responses
  });

  const messages: ModelMessage[] = [];

  if (!args.new) {
    try {
      const convo = await convoFile.json();
      messages.push(...convo);
    } catch {}
  }

  const prompt = positionals[2] ?? "Introduce yourself.";
  messages.push({ role: "user", content: prompt });

  const { fullStream, textStream, text, totalUsage } = streamText({
    model: provider(args.model ?? "qwen3.5-35b-a3b"),
    messages,
  });

  const start = Date.now();

  const streamRender = new StreamRenderer().renderStream(fullStream);

  const [width] = process.stdout.getWindowSize();
  const glow = Bun.spawn({
    cmd: ["glow", "-w", `${width}`, "-"],
    stdin: textStream,
    stdout: "inherit",
  });

  await streamRender;

  const stop = Date.now();

  await glow.exited;

  messages.push({ role: "assistant", content: await text });
  await convoFile.write(JSON.stringify(messages));

  const { inputTokens, outputTokens } = await totalUsage;
  const context = (inputTokens ?? 0) / 1000;
  const output = (outputTokens ?? 0) / 1000;
  const time = (stop - start) / 1000;
  process.stderr.write(
    `\u001b[2mContext: ${context.toFixed(1)}k, Output: ${output.toFixed(1)}k, Time: ${time.toFixed(2)}s\u001b[22m\n`,
  );
}

await main();