videodb
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.
Maintained By: VideoDB