youtube-transcriber · diff
git:20260318.7f74c63 to git:20260318.d421b1c
61 added, 9 removed. Audit B to B.
---
name: youtube-transcriber
description: Get clean, LLM-ready transcripts from any YouTube video. No timestamps, no clutter — just the text, ready to paste into any AI workflow. Falls back to local Whisper when captions aren't available.
emoji: 📝
---
# YouTube Transcriber
Fetch clean, LLM-ready transcripts from any YouTube video. Uses official YouTube captions when available; falls back to local Whisper transcription when they're not. Output is plain text — no timestamps, no formatting noise — ready to drop straight into any AI prompt or workflow.
## When to Use
Activate when the user wants to:
- Transcribe a YouTube video
- Get the full text of what was said in a video
- Feed a video's content into an LLM (summarize, analyze, Q&A, translate, etc.)
- Extract dialogue, quotes, or research material from a video
- Use shorthand like `t`, `ts`, or `transcribe` followed by a YouTube URL
## Prerequisites
- The YouTube Transcriber service must be running locally:
+ ### Check if the service is running
+ Before making any API calls, check if the service is available:
+
```bash
- # Clone and start the service
+ curl -s http://127.0.0.1:19720/api/health | jq -r '.status'
+ ```
+
+ - If this returns `"healthy"` — you're ready to go, skip to the API section.
+ - If this returns `"unhealthy"` — check `.checks[]` for which component failed.
+ - If this returns connection refused — the service needs to be set up and started (see below).
+
+ ### System dependencies
+
+ The service requires:
+ - **Node.js 18+** and npm
+ - **Python 3.8+**
+ - **yt-dlp** — YouTube audio download
+ - **ffmpeg** — Audio processing
+
+ Install on macOS:
+ ```bash
+ brew install yt-dlp ffmpeg
+ ```
+
+ Install on Ubuntu/Debian:
+ ```bash
+ sudo apt install ffmpeg
+ pip install yt-dlp
+ ```
+
+ ### First-time setup
+
+ ```bash
git clone https://github.com/lifesized/youtube-transcriber.git
cd youtube-transcriber
- npm install
+ npm run setup # Installs all deps, creates Python venv with Whisper, initializes database
+ npm run dev # Starts the service at http://127.0.0.1:19720
+ ```
+
+ `npm run setup` handles everything: Node dependencies, Python virtual environment, Whisper installation, Prisma database initialization, and `.env` configuration. No manual steps needed.
+
+ ### Starting the service (already set up)
+
+ If the service was previously set up but isn't running:
+ ```bash
+ cd youtube-transcriber
npm run dev
- # Now running at http://127.0.0.1:19720
```
+ ### Verify setup
+
+ After starting, confirm everything is working:
+ ```bash
+ curl -s http://127.0.0.1:19720/api/health | jq .
+ ```
+
+ All checks should show `"status": "pass"`. If any show `"fail"`, run `npm run test:setup` for detailed diagnostics.
+
No external MCP servers to clone. No third-party repos to audit. Just a local Next.js service with a clean REST API.
## API
Base URL: `http://127.0.0.1:19720`
### Transcribe a Video
```bash
curl -X POST 'http://127.0.0.1:19720/api/transcripts' \
-H 'Content-Type: application/json' \
-d '{"url": "YOUTUBE_URL"}'
```
**Response:**
```json
{
"id": "abc123",
"title": "Video Title",
"author": "Channel Name",
"videoUrl": "https://youtube.com/watch?v=...",
"transcript": "[{\"text\":\"Hello world\",\"startMs\":0,\"durationMs\":1500}]",
"source": "youtube_captions"
}
```
The `transcript` field is a JSON string. Parse it to get segments with `text`, `startMs`, and `durationMs`.
### Get Clean Text (LLM-Ready)
To extract plain text with no timestamps:
```bash
RESP=$(curl -s -X POST 'http://127.0.0.1:19720/api/transcripts' \
-H 'Content-Type: application/json' \
-d '{"url": "USER_URL"}')
echo "$RESP" | jq -r '.transcript' | python3 -c "
import json, sys
segments = json.load(sys.stdin)
print(' '.join(s['text'] for s in segments))
"
```
This is the primary output format — clean, continuous text ready for any LLM.
### Get Text with Timestamps (optional)
If the user specifically wants timestamps:
```bash
echo "$RESP" | jq -r '.transcript' | python3 -c "
import json, sys
for s in json.load(sys.stdin):
m, sec = s['startMs']//60000, (s['startMs']%60000)//1000
print(f'[{m}:{sec:02d}] {s[\"text\"]}')
"
```
### List Saved Transcripts
```bash
curl 'http://127.0.0.1:19720/api/transcripts'
```
### Search Transcripts
```bash
curl 'http://127.0.0.1:19720/api/transcripts?q=SEARCH_TERM'
```
### Get by ID
```bash
curl 'http://127.0.0.1:19720/api/transcripts/ID'
```
### Delete
```bash
curl -X DELETE 'http://127.0.0.1:19720/api/transcripts/ID'
```
## Recommended Workflow
When a user shares a YouTube URL and wants the transcript:
- 1. POST the URL to `/api/transcripts`
- 2. Parse the response
- 3. Extract clean text (no timestamps) using the snippet above
- 4. Return the clean text directly — it's ready to use
+ 1. Check the service is running: `curl -s http://127.0.0.1:19720/api/health | jq -r '.status'`
+ 2. If not running, inform the user and provide setup instructions from the Prerequisites section
+ 3. POST the URL to `/api/transcripts`
+ 4. Parse the response
+ 5. Extract clean text (no timestamps) using the snippet above
+ 6. Return the clean text directly — it's ready to use
```bash
RESP=$(curl -s -X POST 'http://127.0.0.1:19720/api/transcripts' \
-H 'Content-Type: application/json' \
-d '{"url": "USER_URL"}')
TITLE=$(echo "$RESP" | jq -r '.title')
AUTHOR=$(echo "$RESP" | jq -r '.author')
TEXT=$(echo "$RESP" | jq -r '.transcript' | python3 -c "
import json, sys
segments = json.load(sys.stdin)
print(' '.join(s['text'] for s in segments))
")
echo "📹 $TITLE — $AUTHOR"
echo ""
echo "$TEXT"
```
## Error Handling
| Error | Cause | Fix |
|---|---|---|
- | Connection refused | Service not running | `npm run dev` in the project directory |
+ | Connection refused | Service not running | `cd youtube-transcriber && npm run dev` |
| 400 | Invalid or unsupported URL | Ask user for a valid youtube.com or youtu.be URL |
| 404 | Video not found or unavailable | Inform user the video may be private or deleted |
| 429 | Rate limited | Wait 30–60 seconds and retry |
+ | 503 (health) | Dependency missing | Run `npm run test:setup` for diagnostics |
## Notes
- Submitting the same URL twice returns the cached transcript — no re-transcription
- Videos without captions fall back to local Whisper (may take 1–5 minutes depending on video length and hardware)
- `source` in the response will be `"youtube_captions"` or `"whisper"` — useful for informing the user
- Supported URL formats: `youtube.com/watch?v=`, `youtu.be/`, `youtube.com/shorts/`
- Each user runs their own local instance — transcripts stay on your machine
+ - The web UI is also available at http://127.0.0.1:19720 for browsing transcripts