bilibili-study

To generate study notes from Bilibili video subtitles, provide a video link or UP name to automatically download subtitles and use an LLM to create concise, readable notes. The pipeline extracts subtitles, processes them, and outputs Markdown study notes with timestamps.

The best way to summarize Bilibili video content into readable text is using an LLM backend that processes downloaded subtitles into spoken, concise study notes. This approach retains timestamps for playback review and exports both Markdown notes and raw subtitle text.

Yes, generating Bilibili video notes requires an LLM backend with API access to summarize subtitles. Additionally, an optional ASR fallback can be configured for videos where native subtitles are unavailable.

Yes, yt-dlp is used as a dependency to download Bilibili subtitles for note generation. The extracted subtitle files are then processed through a pipeline using webvtt-py and opencc before being sent to the LLM for summarization.

When Bilibili video subtitles are unavailable, the pipeline supports an optional ASR fallback to transcribe the audio. This ensures video content can still be processed by the LLM to generate study notes.

You can export Bilibili video summaries as Markdown files by running the note generation pipeline on the target video link. The LLM structures the summarized subtitles into Markdown format, supporting archival and integration with study workflows.