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videodb

video-db
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Métadesign

À propos

La compétence videodb permet aux développeurs d'ingérer, d'analyser et de manipuler programmatiquement des vidéos/audios à partir de fichiers, d'URL ou de sources en direct. Elle offre des capacités d'indexation de contenu, de recherche de moments spécifiques, de réalisation de montages et de génération d'alertes en temps réel. Utilisez-la pour créer des applications nécessitant un traitement vidéo automatisé, une surveillance de flux en direct, ou une capture et analyse de sessions bureau.

Installation rapide

Claude Code

Recommandé
Principal
npx skills add video-db/skills -a claude-code
Commande PluginAlternatif
/plugin add https://github.com/video-db/skills
Git CloneAlternatif
git clone https://github.com/video-db/skills.git ~/.claude/skills/videodb

Copiez et collez cette commande dans Claude Code pour installer cette compétence

Documentation

VideoDB Skill

Perception + memory + actions for video, live streams, and desktop sessions.

Use this skill when you need to:

1) 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

2) Video ingest + stream

  • Ingest a file or URL and return a playable web stream link
  • Transcode/normalize: codec, bitrate, fps, resolution, aspect ratio

3) 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

4) 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

5) Live streams (RTSP) + monitoring

  • Connect RTSP/live feeds
  • Run real-time visual and spoken understanding and emit events/alerts for monitoring workflows

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 — make it playable: https://console.videodb.io/player?url={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

Canonical prompts (examples)

  • “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.”

Running Python code

CRITICAL: Always cd to the user's project directory before running Python code. This ensures load_dotenv(".env") finds the correct .env file.

from dotenv import load_dotenv
load_dotenv(".env")

import videodb
conn = videodb.connect()

This reads VIDEO_DB_API_KEY from:

  1. Environment (if already exported)
  2. Project's .env file 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 (recommended): export VIDEO_DB_API_KEY=your-key
  • Project .env file: Save VIDEO_DB_API_KEY=your-key in the project's .env file

Get a free API key at https://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

Use the Editor API to compose videos, images, audio, and text. See reference/editor.md for full workflow.

from videodb.editor import Timeline, Track, Clip, VideoAsset, ImageAsset, AudioAsset, Fit

timeline = Timeline(conn)
timeline.resolution = "1280x720"

video_track = Track()
video_track.add_clip(0, Clip(asset=VideoAsset(id=video.id, start=10), duration=20))

audio_track = Track()
audio_track.add_clip(0, Clip(asset=AudioAsset(id=music.id, volume=0.2), duration=20))

timeline.add_track(video_track)
timeline.add_track(audio_track)
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/end when possible
  • For full-length videos, use callback_url for async processing
  • Trim the video on a Timeline first, 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

ScenarioError messageSolution
Indexing an already-indexed videoSpoken word index for video already existsUse video.index_spoken_words(force=True) to skip if already indexed
Scene index already existsScene index with id XXXX already existsExtract the existing scene_index_id from the error with re.search(r"id\s+([a-f0-9]+)", str(e))
Search finds no matchesInvalidRequestError: No results foundCatch the exception and treat as empty results (shots = [])
Reframe times outBlocks indefinitely on long videosUse start/end to limit segment, or pass callback_url for async
Negative timestamps on TimelineSilently produces broken streamAlways validate start >= 0 before creating VideoAsset
generate_video() / create_collection() failsOperation not allowed or maximum limitPlan-gated features — inform the user about plan limits

Additional docs

Reference documentation is in the reference/ directory adjacent to this SKILL.md file. Use the Glob tool to locate it if needed.

Screen Recording (Desktop Capture)

Use ws_listener.py to capture WebSocket events during recording sessions. Desktop capture supports macOS only.

Quick Start

  1. Start listener: python scripts/ws_listener.py --cwd=<PROJECT_ROOT> &
  2. Get WebSocket ID: cat /tmp/videodb_ws_id
  3. Run capture code (see reference/capture.md for full workflow)
  4. Events written to: /tmp/videodb_events.jsonl

Query Events

import json
events = [json.loads(l) for l in open("/tmp/videodb_events.jsonl")]

# Get all transcripts
transcripts = [e["data"]["text"] for e in events if e.get("channel") == "transcript"]

# Get visual descriptions from last 5 minutes
import time
cutoff = time.time() - 300
recent_visual = [e for e in events 
                 if e.get("channel") == "visual_index" and e["unix_ts"] > cutoff]

Utility Scripts

For complete capture workflow, see reference/capture.md.

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, volume control, fade transitions, and media generation. Only fall back to local tools for operations listed under Limitations in reference/editor.md (speed changes, crop/zoom, colour grading, keyframe animation).

When to use what

ProblemVideoDB solution
Platform rejects video aspect ratio or resolutionvideo.reframe() or conn.transcode() with VideoConfig
Need to resize video for Twitter/Instagram/TikTokvideo.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 videoAudioAsset on an Editor Timeline with volume control
Need to add subtitlesvideo.add_subtitle() or CaptionAsset on Editor Timeline
Need to combine/trim clipsVideoAsset on an Editor Timeline
Need to compose images with voiceoverImageAsset + AudioAsset on separate Editor tracks
Need to generate voiceover, music, or SFXcoll.generate_voice(), generate_music(), generate_sound_effect()

Dépôt GitHub

video-db/skills
Chemin: python
0
aiampclaudeclaude-codecodexmultimodal-ai

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