Ask Questions About Your Audio Transcripts

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import requests
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import time
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# Step 1: Transcribe an audio file.
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base_url = "https://api.assemblyai.com"
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headers = {
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  "authorization": "<YOUR_API_KEY>"
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}
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# You can use a local filepath:
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# with open("./my-audio.mp3", "rb") as f:
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# response = requests.post(base_url + "/v2/upload",
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#                         headers=headers,
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#                         data=f)
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# upload_url = response.json()["upload_url"]
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# Or use a publicly-accessible URL:
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upload_url = "https://assembly.ai/sports_injuries.mp3"
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data = {
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  "audio_url": upload_url
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}
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response = requests.post(base_url + "/v2/transcript", headers=headers, json=data)
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transcript_id = response.json()["id"]
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polling_endpoint = base_url + f"/v2/transcript/{transcript_id}"
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while True:
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  transcript = requests.get(polling_endpoint, headers=headers).json()
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  if transcript["status"] == "completed":
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    break
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  elif transcript["status"] == "error":
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    raise RuntimeError(f"Transcription failed: {transcript['error']}")
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  else:
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    time.sleep(3)
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# Step 2: Define a prompt with your question(s).
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prompt = "What is a runner's knee?"
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# Step 3: Send to LLM Gateway.
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llm_gateway_data = {
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  "model": "claude-sonnet-4-5-20250929",
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  "messages": [
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    {"role": "user", "content": f"{prompt}\n\nTranscript: {transcript['text']}"}
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  ],
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  "max_tokens": 1000
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}
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result = requests.post(
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  "https://llm-gateway.assemblyai.com/v1/chat/completions",
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  headers=headers,
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  json=llm_gateway_data
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)
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print(result.json()["choices"][0]["message"]["content"])

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import requests
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import time
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# Step 1: Transcribe the audio
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base_url = "https://api.assemblyai.com"
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headers = {"authorization": "<YOUR_API_KEY>"}
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audio_url = "https://assembly.ai/meeting.mp4"
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data = {"audio_url": audio_url}
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response = requests.post(base_url + "/v2/transcript", headers=headers, json=data)
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transcript_id = response.json()["id"]
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polling_endpoint = base_url + f"/v2/transcript/{transcript_id}"
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while True:
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    transcript = requests.get(polling_endpoint, headers=headers).json()
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    if transcript["status"] == "completed":
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        break
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    elif transcript["status"] == "error":
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        raise RuntimeError(f"Transcription failed: {transcript['error']}")
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    else:
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        time.sleep(3)
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# Step 2: Create structured Q&A prompt
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questions = [
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    "What are the top level KPIs for engineering? (KPI stands for key performance indicator)",
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    "How many days has it been since the data team has gotten updated metrics? (Choose from: 1, 2, 3, 4, 5, 6, 7, more than 7)"
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]
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prompt = f"""Answer the following questions based on the meeting transcript. Format your response as:
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Q1: [question]
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A1: [answer]
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Q2: [question]
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A2: [answer]
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Questions:
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{". ".join([f"{i+1}. {q}" for i, q in enumerate(questions)])}
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Context: This is a GitLab meeting to discuss logistics."""
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# Step 3: Send to LLM Gateway
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llm_gateway_data = {
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    "model": "claude-sonnet-4-5-20250929",
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    "messages": [
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        {"role": "user", "content": f"{prompt}\n\nTranscript: {transcript['text']}"}
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    ],
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    "max_tokens": 1000
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}
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result = requests.post(
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    "https://llm-gateway.assemblyai.com/v1/chat/completions",
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    headers=headers,
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    json=llm_gateway_data
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)
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print(result.json()["choices"][0]["message"]["content"])