Auto Chapters

const baseUrl = "https://api.assemblyai.com";

const headers = {
  authorization: "<YOUR_API_KEY>",
  "content-type": "application/json",
};

// Step 1: Transcribe your audio file
const audioUrl = "https://assembly.ai/wildfires.mp3";

const data = {
  audio_url: audioUrl,
  speech_models: ["universal-3-pro", "universal-2"],
  language_detection: true,
};

const response = await fetch(`${baseUrl}/v2/transcript`, {
  method: "POST",
  headers,
  body: JSON.stringify(data),
});

const { id: transcriptId } = await response.json();
const pollingEndpoint = `${baseUrl}/v2/transcript/${transcriptId}`;

let transcriptionResult;
while (true) {
  const pollingResponse = await fetch(pollingEndpoint, { headers });
  transcriptionResult = await pollingResponse.json();

  if (transcriptionResult.status === "completed") {
    break;
  } else if (transcriptionResult.status === "error") {
    throw new Error(`Transcription failed: ${transcriptionResult.error}`);
  } else {
    await new Promise((resolve) => setTimeout(resolve, 3000));
  }
}

// Step 2: Get paragraphs from the transcript
const paragraphsResponse = await fetch(`${pollingEndpoint}/paragraphs`, {
  headers,
});
const { paragraphs } = await paragraphsResponse.json();

// Step 3: Combine paragraphs into groups for chapter summaries
const step = 2; // Adjust to control chapter length
const combinedParagraphs = [];

for (let i = 0; i < paragraphs.length; i += step) {
  const group = paragraphs.slice(i, i + step);
  combinedParagraphs.push({
    text: group.map((p) => p.text).join(" "),
    start: group[0].start,
    end: group[group.length - 1].end,
  });
}

// Step 4: Generate chapter summaries with LLM Gateway
for (const chapter of combinedParagraphs) {
  const llmGatewayData = {
    model: "claude-sonnet-4-6",
    messages: [
      {
        role: "user",
        content: `Provide a brief one-paragraph summary, a one-line gist, and a headline for this section of a transcript.\n\nText: ${chapter.text}`,
      },
    ],
    max_tokens: 500,
  };

  const result = await fetch(
    "https://llm-gateway.assemblyai.com/v1/chat/completions",
    {
      method: "POST",
      headers,
      body: JSON.stringify(llmGatewayData),
    }
  );

  const resultData = await result.json();
  console.log(
    `${chapter.start}-${chapter.end}: ${resultData.choices[0].message.content}\n`
  );
}