def process_transcribe()

in source/consumer/lambda_handler.py [0:0]


def process_transcribe(asset, workflow, results, type):
    metadata = json.loads(results)

    transcript = metadata["results"]["transcripts"][0]
    transcript["workflow"] = workflow
    transcript_time = metadata["results"]["items"]

    index_name = type+"transcript"
    es = connect_es(es_endpoint)
    index_document(es, asset, index_name, transcript)

    transcribe_items = []

    for item in transcript_time:
        content = item["alternatives"][0]["content"]
        confidence = normalize_confidence(item["alternatives"][0]["confidence"])
        if "start_time" in item and "end_time" in item:
            start_time = convert_to_milliseconds(item["start_time"])
            end_time = convert_to_milliseconds(item["end_time"])
            item["start_time"] = start_time
            item["end_time"] = end_time

        del item["alternatives"]

        item["confidence"] = confidence
        item["content"] = content
        item["workflow"] = workflow

        transcribe_items.append(item)

    bulk_index(es, asset, index_name, transcribe_items)