videodb

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

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "videodb" with this command: npx skills add video-db/skills/video-db-skills-videodb

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

  1. Video ingest + stream
  • Ingest a file or URL and return a playable web stream link

  • Transcode/normalize: codec, bitrate, fps, resolution, aspect ratio

  1. 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

  1. 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

  1. 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:

  • Environment (if already exported)

  • 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

  1. 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

Important: Always validate timestamps before building a timeline:

  • start must be >= 0 (negative values are silently accepted but produce broken output)

  • start must be < end

  • end must 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 /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

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

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

Screen Recording (Desktop Capture)

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

Quick Start

  • Start listener: python scripts/ws_listener.py &

  • Get WebSocket ID: cat /tmp/videodb_ws_id

  • Run capture code (see reference/capture.md for full workflow)

  • 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

  • scripts/ws_listener.py - WebSocket event listener (dumps to JSONL)

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, 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()

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

nano-banana-2

Nano Banana 2 - Gemini 3.1 Flash Image Preview

Repository Source
General

qwen-image-2

Qwen-Image - Alibaba Image Generation

Repository Source
15340.8K
inferen-sh
General

p-video

Pruna P-Video Generation

Repository Source
15340.8K
inferen-sh