Extract Transcript Quotes with LLM Gateway

const API_KEY = "YOUR_API_KEY";

const headers = {
  "authorization": API_KEY,
  "Content-Type": "application/json"
};

// Transcribe the audio file
console.log("Submitting audio for transcription...");
let res = await fetch(
  "https://api.assemblyai.com/v2/transcript",
  {
    method: "POST",
    headers,
    body: JSON.stringify({
      audio_url: "https://assembly.ai/wildfires.mp3",
      speaker_labels: true,
      language_detection: true
    })
  }
);
if (!res.ok) throw new Error(`Error: ${res.status}`);
const transcriptResponse = await res.json();
const transcriptId = transcriptResponse.id;

// Poll for transcription completion
let transcriptResult;
while (true) {
  res = await fetch(
    `https://api.assemblyai.com/v2/transcript/${transcriptId}`,
    { headers }
  );
  if (!res.ok) throw new Error(`Error: ${res.status}`);
  transcriptResult = await res.json();

  if (transcriptResult.status === "completed") {
    break;
  } else if (transcriptResult.status === "error") {
    throw new Error(`Transcription failed: ${transcriptResult.error}`);
  }

  await new Promise(resolve => setTimeout(resolve, 3000));
}

// Extract utterances with timestamps
const utterancesData = transcriptResult.utterances.map(u => ({
  text: u.text,
  start: u.start,
  end: u.end,
  speaker: u.speaker
}));

// Create prompt with timestamped utterances
const prompt = `You are analyzing a transcript with timestamped utterances. Each utterance includes the text content, speaker label, and start/end timestamps in milliseconds.

Here is the transcript data:
${JSON.stringify(utterancesData, null, 2)}

Task: Identify the 3-5 most engaging, impactful, or quotable utterances from this transcript.

Return your response as a JSON array with the following structure:
{
  "quotes": [
    {
      "text": "exact quote text",
      "start": start_timestamp_in_milliseconds,
      "end": end_timestamp_in_milliseconds,
      "speaker": "speaker_label",
      "reason": "brief explanation of why this quote is engaging"
    }
  ]
}

Return ONLY valid JSON, no additional text.`;

// Use LLM Gateway to extract quotes
console.log("Submitting transcript to LLM Gateway for quote extraction...");
res = await fetch(
  "https://llm-gateway.assemblyai.com/v1/chat/completions",
  {
    method: "POST",
    headers,
    body: JSON.stringify({
      model: "claude-sonnet-4-6",
      messages: [
        { role: "user", content: prompt }
      ]
    })
  }
);
if (!res.ok) throw new Error(`Error: ${res.status}`);
const result = await res.json();

const quotesJson = JSON.parse(result.choices[0].message.content.replace(/^```json\n?/, '').replace(/```$/, '').trim());
console.log(JSON.stringify(quotesJson, null, 2));

const API_KEY = "YOUR_API_KEY";

const headers = {
  "authorization": API_KEY,
  "Content-Type": "application/json"
};

// Transcribe the audio file
console.log("Submitting audio for transcription...");
let res = await fetch(
  "https://api.assemblyai.com/v2/transcript",
  {
    method: "POST",
    headers,
    body: JSON.stringify({
      audio_url: "https://assembly.ai/wildfires.mp3",
      speaker_labels: true,
      language_detection: true
    })
  }
);
if (!res.ok) throw new Error(`Error: ${res.status}`);
const transcriptResponse = await res.json();
const transcriptId = transcriptResponse.id;

// Poll for transcription completion
let transcriptResult;
while (true) {
  res = await fetch(
    `https://api.assemblyai.com/v2/transcript/${transcriptId}`,
    { headers }
  );
  if (!res.ok) throw new Error(`Error: ${res.status}`);
  transcriptResult = await res.json();

  if (transcriptResult.status === "completed") {
    break;
  } else if (transcriptResult.status === "error") {
    throw new Error(`Transcription failed: ${transcriptResult.error}`);
  }

  await new Promise(resolve => setTimeout(resolve, 3000));
}

const utterancesData = transcriptResult.utterances.map(u => ({
  text: u.text,
  start: u.start,
  end: u.end,
  speaker: u.speaker
}));

// Create prompt with timestamped utterances
const prompt = `You are analyzing a transcript with timestamped utterances. Each utterance includes the text content, speaker label, and start/end timestamps in milliseconds.

Here is the transcript data:
${JSON.stringify(utterancesData, null, 2)}

Task: Identify the 3-5 most engaging, impactful, or quotable utterances from this transcript.

Return your response as a JSON array with the following structure:
{
  "quotes": [
    {
      "text": "exact quote text",
      "start": start_timestamp_in_milliseconds,
      "end": end_timestamp_in_milliseconds,
      "speaker": "speaker_label",
      "reason": "brief explanation of why this quote is engaging"
    }
  ]
}

Return ONLY valid JSON, no additional text.`;

// Use LLM Gateway to extract quotes
console.log("Submitting transcript to LLM Gateway for quote extraction...");
let res = await fetch(
  "https://llm-gateway.assemblyai.com/v1/chat/completions",
  {
    method: "POST",
    headers,
    body: JSON.stringify({
      model: "claude-sonnet-4-6",
      messages: [
        { role: "user", content: prompt }
      ]
    })
  }
);
if (!res.ok) throw new Error(`Error: ${res.status}`);
const result = await res.json();

const quotesJson = JSON.parse(result.choices[0].message.content.replace(/^```json\n?/, '').replace(/```$/, '').trim());
console.log(JSON.stringify(quotesJson, null, 2));