This project automates the process of analyzing content from YouTube channels. It involves fetching video URLs from a YouTube channel, downloading them as MP3 files, transcribing the audio using OpenAI's Whisper, cleaning the data through several mini-programs, and finally analyzing the content with the Assistant API.

• Python 3.x
• OpenAI API key
• Google API client
• Internet connection

pip install -r requirements.txt

• video_URL_fetcher.py: Fetches video URLs from a specified YouTube channel.
• video_as_mp3_downloader.py: Downloads videos as MP3 files.
• video_transcriber.ipynb: Transcribes the audio from the MP3 files using OpenAI's Whisper.
• util_data_cleaner.py: Cleans the transcribed data.
• util_mergetxt.py: Merges text files.
• util_tokencounter.py: Counts tokens in the text.
• util_charcounter.py: Counts characters in the text.
• assistant_podcast_intel.ipynb and assistant_demo1.ipynb: Analyze the content using the Assistant API.

• Set up your API keys and environment variables.
• Run video_URL_fetcher.py to fetch video URLs.
• Use video_as_mp3_downloader.py to download videos as MP3.
• Transcribe the audio files with video_transcriber.ipynb.
• Clean the data using util_data_cleaner.py.
• Merge, count tokens, and characters using the respective utility scripts.
• Analyze the content using the Jupyter notebooks.

• OpenAI for Whisper and Assistant APIs
• YouTube API