README.md

---
title: TutorialMaker
emoji: 💻
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 6.19.0
python_version: '3.13'
app_file: app.py
pinned: false
license: mit
short_description: Make Tutorials from YouTube Videos
---

# YouTube → Tutorial Post Generator

Give a **topic** and your **Hugging Face token**, and this Space builds a downloadable
**`.docx` tutorial** (text + AI-captioned screenshots) from the single best YouTube video
on that topic.

## Pipeline

1. **Search** — top 5 videos via the [`adarshajay/youtube-search`](https://huggingface.co/spaces/adarshajay/youtube-search) Space.
2. **Sentiment rank** — fetch top comments per video with `yt-dlp` and score them with the
   BERT classifier [`OmarMedhat7/youtube-sentiment-analysis-model`](https://huggingface.co/OmarMedhat7/youtube-sentiment-analysis-model);
   the video with the highest positive share wins.
3. **Download** the winner with `yt-dlp` and extract audio with `ffmpeg`.
4. **Transcribe** locally with `faster-whisper` (segment timestamps).
5. **Candidate frames** are extracted densely from the video, then the **video is
   auto-deleted** — only small JPEGs and the transcript remain.
6. **Tutorial text** — `deepseek-ai/DeepSeek-V3` (HF Inference Providers, billed to your
   token) turns the transcript into an **answer-engine-optimized** post: an answer-first
   paragraph, H2 step headings, an FAQ, a meta description, a URL slug, and a
   last-updated/source citation. Optional **primary/secondary keyword** placement (primary
   ~3× + in title/slug/meta/intro/H2; each secondary once).
7. **Screenshot selection** — a weighted indicator blends each step's LLM-suggested
   timestamp with Whisper's actual speech timing.
8. **Captions** — a vision model (default `Qwen/Qwen2.5-VL-72B-Instruct`, billed to your
   token) captions each screenshot.
9. **Assemble** the `.docx` for download.

## Notes

- **Your HF token is used only for the LLM and vision-model calls** and is billed to your
  account. Create a fine-grained token with *"Make calls to Inference Providers"* at
  <https://huggingface.co/settings/tokens>.
- **Free CPU tier:** Whisper runs on CPU, so transcription is slow — keep videos short
  (default cap ~20 min).
- **YouTube usually blocks the Space's datacenter IP.** Each visitor can supply their own
  access in the **"YouTube access — cookies / proxy"** panel (used only for that run, then
  deleted):
  - **Cookies:** a `youtube.com` cookies.txt (Netscape format, raw or base64) exported
    from a **throwaway** Google account.
  - **Proxy:** a **residential** proxy URL. **Free *datacenter* proxies (e.g. Webshare's
    free tier) usually do *not* bypass YouTube's block** and have tight bandwidth caps.
  - An operator can set shared defaults via the `YT_COOKIES` / `YT_PROXY` Space secrets.
  - A hosted Space **cannot** open or read a visitor's browser — auth must be supplied
    explicitly.

## PO token guide (free, no proxy)

YouTube increasingly requires a **Proof-of-Origin (PO) token** to serve video from
datacenter IPs. A matching **PO token + visitor data** pair can get the Space past the
"Sign in to confirm you're not a bot" wall **without any proxy** — and it's free. It's
fiddly to extract by hand and the tokens expire (hours), so re-do this when downloads
start failing.

Paste the values into the app's **"YouTube access — cookies / proxy"** panel:
**PO token** field and **Visitor data** field.

### Easiest: the PO Token Grabber extension (one click)

This repo ships a tiny Chrome/Edge extension in [`extension/`](extension/) that reads the
PO token + visitor data for you. Grab it with the **⬇️ Download the PO Token Grabber
extension (.zip)** button in the app's *YouTube access* panel (or from
[`extension/`](extension/)), unzip it, and load it unpacked (`chrome://extensions` →
Developer mode → Load unpacked). Open a YouTube video and press play, then click the
extension **while on the YouTube tab** to capture the values. Open this Space in another
tab and hit **⤵ Fill the Space tab** to inject them straight into the fields below (or use
the Copy buttons and paste). See
[`extension/README.md`](extension/README.md). (It's unpublished/sideloaded and may need
updates when YouTube changes; the manual steps below always work as a fallback.)

### Get them manually (web client, ~2 min)

1. Open a fresh **Incognito** window and go to <https://www.youtube.com> (a throwaway
   logged-in account is fine; if you log in, also export that session's cookies).
2. Open **DevTools → Network** (F12), then **play any video**.
3. **Visitor data:** filter Network for `v1/player`, open the request to
   `youtubei/v1/player`, and in the **Request payload** copy
   `context.client.visitorData` (a string ending in `%3D%3D`). Paste it into the
   **Visitor data** field.
4. **PO token (gvs):** filter Network for `googlevideo.com`, open a `videoplayback`
   request, and copy the value of its **`pot`** query parameter. In the **PO token**
   field enter it prefixed with the client + context:

   ```
   web.gvs+<pot-value>
   ```

   You can supply more than one, comma-separated, e.g.
   `web.gvs+<gvs-pot>, web.player+<player-pot>` (the player PO token comes from the
   `v1/player` request's response, field `...poToken`).
5. Run the Space. When a PO token is present it automatically uses the **web** player
   client so the token applies.

**Tips**
- The PO token is bound to the **visitor data** (and cookies) it was made with — always
  submit them together, from the same session.
- Prefer using the **same Incognito session** for cookies + visitor data + PO token.
- Tokens are short-lived; refresh when you next get blocked.

### Automated / operator option

yt-dlp can auto-generate PO tokens via the
[`bgutil-ytdlp-pot-provider`](https://github.com/Brainicism/bgutil-ytdlp-pot-provider)
plugin, but that needs a small provider server running alongside yt-dlp — not bundled in
this hosted Space. A self-hosting operator can run it and set shared defaults via the
`YT_POT` / `YT_VISITOR_DATA` Space secrets.

See the authoritative, up-to-date method in the
[yt-dlp PO Token Guide](https://github.com/yt-dlp/yt-dlp/wiki/PO-Token-Guide).

## Local run

```bash
pip install -r requirements.txt   # needs ffmpeg on PATH
python app.py
```