Ross ROSS = Recommend OSS · open-source software intelligence for agents

wendy7756/AI-Video-Transcriber

Transcribe and summarize videos and podcasts using AI. Open-source, multi-platform, and supports multiple languages. observed · 2026-08-28

github.com/wendy7756/AI-Video-Transcriber · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

62/100

  • Activity 99
  • Release rhythm 35
  • Longevity 26

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 370
  • days_rel: n/a
  • days_push: 10
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

3215 stars · 409 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

An open-source AI tool that transcribes, summarizes, and archives videos and podcasts from 30+ platforms (YouTube, TikTok, Bilibili, etc.) or local files. It uses a subtitle-first architecture with Faster-Whisper as fallback, plus LLM-based text optimization and multi-language summaries via any OpenAI-compatible API.

Use cases

  • transcribe youtube videos to text
  • summarize podcasts with ai
  • convert tiktok videos to transcripts
  • transcribe local audio and video files
  • generate summaries in multiple languages
  • get transcripts without downloading audio
  • self-host a video transcription service

When to choose

  • you need transcripts from many video/podcast platforms via URL
  • you want subtitle extraction first for speed with Whisper fallback
  • you prefer bringing your own OpenAI-compatible API key or local LLM
  • you want a self-hosted, multi-language transcription and summarization pipeline

When to avoid

  • you need a fully managed hosted service with daily briefs and knowledge base features
  • you have no access to any OpenAI-compatible LLM API
  • you need real-time live captioning rather than batch transcription
  • you require speaker diarization or word-level timestamps

Facets

application · maturity active

speech-recognition nlp llm-inference video-processing audio-processing http-server artificial-intelligence speech-processing media developer-tools self-hosted python self-hosted cross-platform whisper yt-dlp transcription summarization podcasts youtube fastapi openai-compatible subtitles ffmpeg natural-language-processing video audio web-server docker

5 sources

Member repositories

RepositoryRoleHealth v2
wendy7756/AI-Video-Transcribermain62

For agents

markdown · JSON · MCP: product_card(name="wendy7756/AI-Video-Transcriber")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem