started youtube transcription with ai

_integrations/youtube-summarizer/youtube.py

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+import yt_dlp
+import os
+import io
+import time
+from dotenv import load_dotenv
+from langchain_community.document_loaders.blob_loaders.youtube_audio import (
+    YoutubeAudioLoader,
+)
+from langchain_community.document_loaders.generic import GenericLoader
+from langchain_community.document_loaders.parsers import (
+    OpenAIWhisperParser,
+)
+from pydub import AudioSegment
+
+import openai
+
+load_dotenv()
+
+URLS = ['https://www.youtube.com/watch?v=LQRuaP2VFfA']
+
+ydl_opts = {
+    'format': 'm4a/bestaudio/best',
+    # ℹ️ See help(yt_dlp.postprocessor) for a list of available Postprocessors and their arguments
+    'postprocessors': [{  # Extract audio using ffmpeg
+        'key': 'FFmpegExtractAudio',
+        'preferredcodec': 'm4a',
+    }]
+}
+
+with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+    ydl.download(URLS)
+
+client = openai.OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+# openai.api_key = os.getenv("OPENAI_API_KEY")
+
+# Audio file from disk
+audio = AudioSegment.from_file("./test.m4a")
+
+# Define the duration of each chunk in minutes
+# Need to meet 25MB size limit for Whisper API
+chunk_duration = 20
+chunk_duration_ms = chunk_duration * 60 * 1000
+
+# Split the audio into chunk_duration_ms chunks
+for split_number, i in enumerate(range(0, len(audio), chunk_duration_ms)):
+    # Audio chunk
+    chunk = audio[i: i + chunk_duration_ms]
+    # Skip chunks that are too short to transcribe
+    # if chunk.duration_seconds <= self.chunk_duration_threshold:
+    #     continue
+    file_obj = io.BytesIO(chunk.export(format="mp3").read())
+    # if blob.source is not None:
+    #     file_obj.name = blob.source + f"_part_{split_number}.mp3"
+    # else:
+    file_obj.name = f"part_{split_number}.mp3"
+
+    # Transcribe
+    print(f"Transcribing part {split_number + 1}!")  # noqa: T201
+    attempts = 0
+    while attempts < 3:
+        try:
+            transcript = client.audio.transcriptions.create(
+                model="whisper-1", file=file_obj
+            )
+            break
+        except Exception as e:
+            attempts += 1
+            print(f"Attempt {attempts} failed. Exception: {str(e)}")  # noqa: T201
+            time.sleep(5)
+    else:
+        print("Failed to transcribe after 3 attempts.")  # noqa: T201
+        continue
+
+    print(transcript.text)