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| import requests | |
| from youtube_transcript_api import YouTubeTranscriptApi | |
| import json | |
| import os | |
| headers = { | |
| "Authorization": f"Bearer {os.environ['HF_Token']}" | |
| } # NOTE: put this somewhere else | |
| def retrieve_transcript(vid_id): | |
| try: | |
| transcript = YouTubeTranscriptApi.get_transcript(vid_id) | |
| return transcript | |
| except Exception as e: | |
| return None | |
| def split_transcript(transcript, chunk_size=40): | |
| sentences = [] | |
| for i in range(0, len(transcript), chunk_size): | |
| to_add = [x["text"] for x in transcript[i : i + chunk_size]] | |
| sentences.append(" ".join(to_add)) | |
| return sentences | |
| def query_punctuation(splits): | |
| payload = {"inputs": splits} | |
| API_URL = "https://api-inference.huggingface.co/models/oliverguhr/fullstop-punctuation-multilang-large" | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.json() | |
| def parse_output(output, comb): | |
| total = [] | |
| # loop over the response from the huggingface api | |
| for i, o in enumerate(output): | |
| added = 0 | |
| tt = comb[i] | |
| for elem in o: | |
| # Loop over the output chunks and add the . and ? | |
| if elem["entity_group"] not in ["0", ",", ""]: | |
| split = elem["end"] + added | |
| tt = tt[:split] + elem["entity_group"] + tt[split:] | |
| added += 1 | |
| total.append(tt) | |
| return " ".join(total) | |
| def punctuate(video_id): | |
| transcript = retrieve_transcript(video_id) | |
| splits = split_transcript( | |
| transcript | |
| ) # Get the transcript from the YoutubeTranscriptApi | |
| resp = query_punctuation(splits) # Get the response from the Inference API | |
| punctuated_transcript = parse_output(resp, splits) | |
| return punctuated_transcript | |