LeMUR

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import assemblyai as aai
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aai.settings.api_key = "<YOUR_API_KEY>"
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transcriber = aai.Transcriber()
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# You can use a local filepath:
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# audio_file = "./example.mp3"
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# Or use a publicly-accessible URL:
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audio_file = (
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    "https://assembly.ai/sports_injuries.mp3"
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)
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transcript = transcriber.transcribe(audio_file)
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prompt = "Provide a brief summary of the transcript."
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result = transcript.lemur.task(
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    prompt, final_model=aai.LemurModel.claude3_5_sonnet
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)
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print(result.response)

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import assemblyai as aai
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aai.settings.api_key = "<YOUR_API_KEY>"
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# Step 1: Transcribe an audio file.
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# audio_file = "./local_file.mp3"
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audio_file = "https://assembly.ai/sports_injuries.mp3"
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transcriber = aai.Transcriber()
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transcript = transcriber.transcribe(audio_file)
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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: Apply LeMUR.
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result = transcript.lemur.task(
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    prompt, final_model=aai.LemurModel.claude3_5_sonnet
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)
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print(result.response)

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import assemblyai as aai
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aai.settings.api_key = "<YOUR_API_KEY>"
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audio_url = "https://assembly.ai/meeting.mp4"
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transcript = aai.Transcriber().transcribe(audio_url)
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questions = [
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    aai.LemurQuestion(
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        question="What are the top level KPIs for engineering?",
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        context="KPI stands for key performance indicator",
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        answer_format="short sentence"),
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    aai.LemurQuestion(
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        question="How many days has it been since the data team has gotten updated metrics?",
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        answer_options=["1", "2", "3", "4", "5", "6", "7", "more than 7"]),
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]
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result = transcript.lemur.question(
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    final_model=aai.LemurModel.claude3_5_sonnet,
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    questions,
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    context="A GitLab meeting to discuss logistics"
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)
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for qa_response in result.response:
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    print(f"Question: {qa_response.question}")
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    print(f"Answer: {qa_response.answer}")

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result = transcript.lemur.task(
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    prompt,
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    final_model=aai.LemurModel.claude3_5_sonnet
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)

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result = transcript.lemur.task(
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    prompt,
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    max_output_size=1000
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)

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result = transcript.lemur.task(
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    prompt,
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    temperature=0.7
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)

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config = aai.TranscriptionConfig(
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  speaker_labels=True,
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)
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transcript = transcriber.transcribe(audio_url, config=config)
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text_with_speaker_labels = ""
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for utt in transcript.utterances:
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    text_with_speaker_labels += f"Speaker {utt.speaker}:\n{utt.text}\n"
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result = aai.Lemur().task(
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    prompt,
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    input_text=text_with_speaker_labels
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)

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transcript_group = transcriber.transcribe_group(
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    [
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        "https://example.org/customer1.mp3",
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        "https://example.org/customer2.mp3",
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        "https://example.org/customer3.mp3",
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    ],
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)
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# Or use existing transcripts:
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# transcript_group = aai.TranscriptGroup.get_by_ids([id1, id2, id3])
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result = transcript_group.lemur.task(
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  prompt="Provide a summary of these customer calls."
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)

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result = transcript.lemur.task(prompt)
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deletion_response = aai.Lemur.purge_request_data(result.request_id)