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 .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 (before starting Claude): 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 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 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: VideoDBWeekly Installs209Repositoryaffaan-m/everyt…ude-codeGitHub Stars83.1KFirst Seen7 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykWarnInstalled oncodex197cursor164kimi-cli163gemini-cli163github-copilot163opencode163