videodb
affaan-m/ecc
Ingest, index, search, and edit video and audio with real-time desktop capture and live stream monitoring.
What is videodb?
VideoDB provides end-to-end video and audio processing: ingest from files, URLs, RTSP feeds, or live desktop capture; build searchable visual and semantic indexes with timestamps; and perform timeline edits (subtitles, overlays, transcoding, dubbing). Use it for video understanding, live monitoring, media asset generation, and automated event alerts.
- Ingest video from local files, URLs, RTSP/live feeds, or desktop screen/audio capture
- Extract frames and build visual, semantic, and temporal indexes for searchable moments
- Search video by spoken words, visual content, or keywords with exact timestamps and auto-clip generation
- Transcode and normalize codec, bitrate, fps, resolution, and aspect ratio
- Edit timelines: add subtitles, text/image overlays, branding, audio, dubbing, and translations
- Generate real-time alerts and events from live streams or desktop sessions
How to install videodb
npx skills add null --skill videodb- Python 3.7+
- pip install videodb[capture] python-dotenv (or videodb without capture on Linux)
- Free API key from console.videodb.io (50 free uploads, no credit card required)
- VIDEO_DB_API_KEY environment variable or .env file in project directory
How to use videodb
- 1.Install the SDK: pip install 'videodb[capture]' python-dotenv
- 2.Set VIDEO_DB_API_KEY via export or .env file in your project
- 3.Load environment and connect: from dotenv import load_dotenv; load_dotenv(); import videodb; conn = videodb.connect()
- 4.Upload media: coll = conn.get_collection(); video = coll.upload(url='...') or coll.upload(file_path='...')
- 5.Index and search: video.index_spoken_words(); results = video.search('query'); stream_url = results.compile()
- 6.Edit timelines: from videodb.timeline import Timeline; timeline = Timeline(conn); timeline.add_inline(...); stream_url = timeline.generate_stream()
Use cases
- Search for specific moments in long videos by keyword or visual description, then auto-generate clips
- Capture and monitor desktop sessions with live alerts on spoken content or screen activity
- Ingest YouTube or external video URLs and normalize them for consistent playback and processing
- Reframe videos for social media platforms (vertical, horizontal, square) with smart cropping
- Build searchable archives of recorded meetings or streams with transcripts and indexed scenes
- Video analysts and researchers needing searchable video archives
- Content creators editing and repurposing video for multiple platforms
- Security and monitoring teams tracking live RTSP feeds with event detection
- Developers building video-aware applications with timeline composition
- Teams automating video workflows: transcoding, subtitling, and asset generation
videodb FAQ
Visit console.videodb.io and sign up for free. You get 50 free uploads with no credit card required.
Yes. Call video.index_spoken_words(force=True) to index spoken content, then use video.search('query') to find moments by keyword.
The search() method raises InvalidRequestError with 'No results found'. Always wrap searches in try/except and treat that error as an empty result set.
Yes. Use the desktop capture feature to record screen, mic, and system audio, then run real-time alerts on spoken content and visual events.
Use video.reframe(target='vertical', mode=ReframeMode.smart) for short segments. For full-length videos, provide a callback_url for async processing since reframing can take several minutes.
Full instructions (SKILL.md)
Source of truth, from affaan-m/ecc.
name: videodb description: See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture. metadata: origin: ECC allowed-tools: Read Grep Glob Bash(python:*) argument-hint: "[task description]"
VideoDB Skill
Perception + memory + actions for video, live streams, and desktop sessions.
When to use
Desktop Perception
- Start/stop a desktop session capturing screen, mic, and system audio
- Stream live context and store episodic session memory
- Run real-time alerts/triggers on what's spoken and what's happening on screen
- Produce session summaries, a searchable timeline, and playable evidence links
Video ingest + stream
- Ingest a file or URL and return a playable web stream link
- Transcode/normalize: codec, bitrate, fps, resolution, aspect ratio
Index + search (timestamps + evidence)
- Build visual, spoken, and keyword indexes
- Search and return exact moments with timestamps and playable evidence
- Auto-create clips from search results
Timeline editing + generation
- Subtitles: generate, translate, burn-in
- Overlays: text/image/branding, motion captions
- Audio: background music, voiceover, dubbing
- Programmatic composition and exports via timeline operations
Live streams (RTSP) + monitoring
- Connect RTSP/live feeds
- Run real-time visual and spoken understanding and emit events/alerts for monitoring workflows
How it works
Common inputs
- Local file path, public URL, or RTSP URL
- Desktop capture request: start / stop / summarize session
- Desired operations: get context for understanding, transcode spec, index spec, search query, clip ranges, timeline edits, alert rules
Common outputs
- Stream URL
- Search results with timestamps and evidence links
- Generated assets: subtitles, audio, images, clips
- Event/alert payloads for live streams
- Desktop session summaries and memory entries
Running Python code
Before running any VideoDB code, change to the project directory and load environment variables:
from dotenv import load_dotenv
load_dotenv(".env")
import videodb
conn = videodb.connect()
This reads VIDEO_DB_API_KEY from:
- Environment (if already exported)
- Project's
.envfile in current directory
If the key is missing, videodb.connect() raises AuthenticationError automatically.
Do NOT write a script file when a short inline command works.
When writing inline Python (python -c "..."), always use properly formatted code — use semicolons to separate statements and keep it readable. For anything longer than ~3 statements, use a heredoc instead:
python << 'EOF'
from dotenv import load_dotenv
load_dotenv(".env")
import videodb
conn = videodb.connect()
coll = conn.get_collection()
print(f"Videos: {len(coll.get_videos())}")
EOF
Setup
When the user asks to "setup videodb" or similar:
1. Install SDK
pip install "videodb[capture]" python-dotenv
If videodb[capture] fails on Linux, install without the capture extra:
pip install videodb python-dotenv
2. Configure API key
The user must set VIDEO_DB_API_KEY using either method:
- Export in terminal (before starting Claude):
export VIDEO_DB_API_KEY=your-key - Project
.envfile: SaveVIDEO_DB_API_KEY=your-keyin the project's.envfile
Get a free API key at console.videodb.io (50 free uploads, no credit card).
Do NOT read, write, or handle the API key yourself. Always let the user set it.
Quick Reference
Upload media
# URL
video = coll.upload(url="https://example.com/video.mp4")
# YouTube
video = coll.upload(url="https://www.youtube.com/watch?v=VIDEO_ID")
# Local file
video = coll.upload(file_path="/path/to/video.mp4")
Transcript + subtitle
# force=True skips the error if the video is already indexed
video.index_spoken_words(force=True)
text = video.get_transcript_text()
stream_url = video.add_subtitle()
Search inside videos
from videodb.exceptions import InvalidRequestError
video.index_spoken_words(force=True)
# search() raises InvalidRequestError when no results are found.
# Always wrap in try/except and treat "No results found" as empty.
try:
results = video.search("product demo")
shots = results.get_shots()
stream_url = results.compile()
except InvalidRequestError as e:
if "No results found" in str(e):
shots = []
else:
raise
Scene search
import re
from videodb import SearchType, IndexType, SceneExtractionType
from videodb.exceptions import InvalidRequestError
# index_scenes() has no force parameter — it raises an error if a scene
# index already exists. Extract the existing index ID from the error.
try:
scene_index_id = video.index_scenes(
extraction_type=SceneExtractionType.shot_based,
prompt="Describe the visual content in this scene.",
)
except Exception as e:
match = re.search(r"id\s+([a-f0-9]+)", str(e))
if match:
scene_index_id = match.group(1)
else:
raise
# Use score_threshold to filter low-relevance noise (recommended: 0.3+)
try:
results = video.search(
query="person writing on a whiteboard",
search_type=SearchType.semantic,
index_type=IndexType.scene,
scene_index_id=scene_index_id,
score_threshold=0.3,
)
shots = results.get_shots()
stream_url = results.compile()
except InvalidRequestError as e:
if "No results found" in str(e):
shots = []
else:
raise
Timeline editing
Important: Always validate timestamps before building a timeline:
startmust be >= 0 (negative values are silently accepted but produce broken output)startmust be <endendmust be <=video.length
from videodb.timeline import Timeline
from videodb.asset import VideoAsset, TextAsset, TextStyle
timeline = Timeline(conn)
timeline.add_inline(VideoAsset(asset_id=video.id, start=10, end=30))
timeline.add_overlay(0, TextAsset(text="The End", duration=3, style=TextStyle(fontsize=36)))
stream_url = timeline.generate_stream()
Transcode video (resolution / quality change)
from videodb import TranscodeMode, VideoConfig, AudioConfig
# Change resolution, quality, or aspect ratio server-side
job_id = conn.transcode(
source="https://example.com/video.mp4",
callback_url="https://example.com/webhook",
mode=TranscodeMode.economy,
video_config=VideoConfig(resolution=720, quality=23, aspect_ratio="16:9"),
audio_config=AudioConfig(mute=False),
)
Reframe aspect ratio (for social platforms)
Warning: reframe() is a slow server-side operation. For long videos it can take
several minutes and may time out. Best practices:
- Always limit to a short segment using
start/endwhen possible - For full-length videos, use
callback_urlfor async processing - Trim the video on a
Timelinefirst, then reframe the shorter result
from videodb import ReframeMode
# Always prefer reframing a short segment:
reframed = video.reframe(start=0, end=60, target="vertical", mode=ReframeMode.smart)
# Async reframe for full-length videos (returns None, result via webhook):
video.reframe(target="vertical", callback_url="https://example.com/webhook")
# Presets: "vertical" (9:16), "square" (1:1), "landscape" (16:9)
reframed = video.reframe(start=0, end=60, target="square")
# Custom dimensions
reframed = video.reframe(start=0, end=60, target={"width": 1280, "height": 720})
Generative media
image = coll.generate_image(
prompt="a sunset over mountains",
aspect_ratio="16:9",
)
Error handling
from videodb.exceptions import AuthenticationError, InvalidRequestError
try:
conn = videodb.connect()
except AuthenticationError:
print("Check your VIDEO_DB_API_KEY")
try:
video = coll.upload(url="https://example.com/video.mp4")
except InvalidRequestError as e:
print(f"Upload failed: {e}")
Common pitfalls
| Scenario | Error message | Solution |
|---|---|---|
| Indexing an already-indexed video | Spoken word index for video already exists | Use video.index_spoken_words(force=True) to skip if already indexed |
| Scene index already exists | Scene index with id XXXX already exists | Extract the existing scene_index_id from the error with re.search(r"id\s+([a-f0-9]+)", str(e)) |
| Search finds no matches | InvalidRequestError: No results found | Catch the exception and treat as empty results (shots = []) |
| Reframe times out | Blocks indefinitely on long videos | Use start/end to limit segment, or pass callback_url for async |
| Negative timestamps on Timeline | Silently produces broken stream | Always validate start >= 0 before creating VideoAsset |
generate_video() / create_collection() fails | Operation not allowed or maximum limit | Plan-gated features — inform the user about plan limits |
Examples
Canonical prompts
- "Start desktop capture and alert when a password field appears."
- "Record my session and produce an actionable summary when it ends."
- "Ingest this file and return a playable stream link."
- "Index this folder and find every scene with people, return timestamps."
- "Generate subtitles, burn them in, and add light background music."
- "Connect this RTSP URL and alert when a person enters the zone."
Screen Recording (Desktop Capture)
Use ws_listener.py to capture WebSocket events during recording sessions. Desktop capture supports macOS only.
Quick Start
- Choose state dir:
STATE_DIR="${VIDEODB_EVENTS_DIR:-$HOME/.local/state/videodb}" - Start listener:
VIDEODB_EVENTS_DIR="$STATE_DIR" python scripts/ws_listener.py --clear "$STATE_DIR" & - Get WebSocket ID:
cat "$STATE_DIR/videodb_ws_id" - Run capture code (see reference/capture.md for the full workflow)
- Events written to:
$STATE_DIR/videodb_events.jsonl
Use --clear whenever you start a fresh capture run so stale transcript and visual events do not leak into the new session.
Query Events
import json
import os
import time
from pathlib import Path
events_dir = Path(os.environ.get("VIDEODB_EVENTS_DIR", Path.home() / ".local" / "state" / "videodb"))
events_file = events_dir / "videodb_events.jsonl"
events = []
if events_file.exists():
with events_file.open(encoding="utf-8") as handle:
for line in handle:
try:
events.append(json.loads(line))
except json.JSONDecodeError:
continue
transcripts = [e["data"]["text"] for e in events if e.get("channel") == "transcript"]
cutoff = time.time() - 300
recent_visual = [
e for e in events
if e.get("channel") == "visual_index" and e["unix_ts"] > cutoff
]
Additional docs
Reference documentation is in the reference/ directory adjacent to this SKILL.md file. Use the Glob tool to locate it if needed.
- reference/api-reference.md - Complete VideoDB Python SDK API reference
- reference/search.md - In-depth guide to video search (spoken word and scene-based)
- reference/editor.md - Timeline editing, assets, and composition
- reference/streaming.md - HLS streaming and instant playback
- reference/generative.md - AI-powered media generation (images, video, audio)
- reference/rtstream.md - Live stream ingestion workflow (RTSP/RTMP)
- reference/rtstream-reference.md - RTStream SDK methods and AI pipelines
- reference/capture.md - Desktop capture workflow
- reference/capture-reference.md - Capture SDK and WebSocket events
- reference/use-cases.md - Common video processing patterns and examples
Do not use ffmpeg, moviepy, or local encoding tools when VideoDB supports the operation. The following are all handled server-side by VideoDB — trimming, combining clips, overlaying audio or music, adding subtitles, text/image overlays, transcoding, resolution changes, aspect-ratio conversion, resizing for platform requirements, transcription, and media generation. Only fall back to local tools for operations listed under Limitations in reference/editor.md (transitions, speed changes, crop/zoom, colour grading, volume mixing).
When to use what
| Problem | VideoDB solution |
|---|---|
| Platform rejects video aspect ratio or resolution | video.reframe() or conn.transcode() with VideoConfig |
| Need to resize video for Twitter/Instagram/TikTok | video.reframe(target="vertical") or target="square" |
| Need to change resolution (e.g. 1080p → 720p) | conn.transcode() with VideoConfig(resolution=720) |
| Need to overlay audio/music on video | AudioAsset on a Timeline |
| Need to add subtitles | video.add_subtitle() or CaptionAsset |
| Need to combine/trim clips | VideoAsset on a Timeline |
| Need to generate voiceover, music, or SFX | coll.generate_voice(), generate_music(), generate_sound_effect() |
Provenance
Reference material for this skill is vendored locally under skills/videodb/reference/.
Use the local copies above instead of following external repository links at runtime.
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