videodb – skill Thiết kế & UI cho agent AI
Nhận diện, lập chỉ mục và chỉnh sửa video và âm thanh. Nhập file/URL/luồng trực tiếp, xây dựng chỉ mục hình ảnh/giọng nói, tìm kiếm theo timestamp, chỉnh sửa timeline, thêm overlay/phụ đề, tạo media và thiết lập cảnh báo thời gian thực.
Cài skill videodb bằng một lệnh
Chọn công cụ bạn đang dùng, copy lệnh và dán vào terminal. Skill sẽ nằm trong thư mục skills của công cụ đó và sẵn sàng dùng ở phiên làm việc tiếp theo.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/videodb-9ec0c.tgz | tar xz -C ~/.claude/skills
Gọi trong Claude Code: /videodb – rồi mô tả công việc bạn muốn làm.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/videodb-9ec0c.tgz | tar xz -C ~/.codex/skills
Gọi trong Codex: $videodb – rồi mô tả công việc bạn muốn làm.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/videodb-9ec0c.tgz | tar xz -C ~/.hermes/skills
Gọi trong Hermes Agent: /videodb – rồi mô tả công việc bạn muốn làm.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/videodb-9ec0c.tgz | tar xz -C ~/.deepcode/skills
Gọi trong DeepSeek: /videodb – rồi mô tả công việc bạn muốn làm.
Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
VideoDB Skill
Perception + memory + actions for video, live streams, and desktop sessions.
Use this skill when you need to:
When to Use
- You need video or audio perception, indexing, search, or timeline editing from files, URLs, desktop sessions, or live streams.
- The task involves timestamps, searchable evidence, subtitles, clips, overlays, or real-time monitoring alerts.
- You want one workflow that combines ingestion, understanding, retrieval, and media actions.
Authorization, privacy and SDK version
Confirm the exact collection, media sources, processing scope and cost limit before cloud ingestion/indexing/generation. Desktop or meeting recording requires explicit authorization for each screen/microphone/system-audio source and participant consent as applicable. Select the minimum channels; never enable recording storage by default, capture passwords, or start hidden/background monitoring. Stop on request immediately. Treat stream URLs, client tokens, event files and transcripts as sensitive; do not publish them or log credentials. Webhook destinations need authorization and verified authentication/signatures, replay protection and idempotency. Generated text or confidence scores are not verified evidence.
The bundled references describe legacy SDK patterns. Check the installed version before using them: newer VideoDB SDKs provide v2 understand/index/retrieve; v1 search is exposed as legacy_search. Do not automatically migrate existing projects or install latest to make an old example work. Use an isolated environment with reviewed compatible versions.
The listener does not start or stop recording. Give it a dedicated private directory (mode 0700), explicit time/byte limits, and keep its PID tied to the process you launched. Do not blindly kill a reused PID. Reconnection can change the WebSocket ID; reconnect pipelines through the documented API or stop rather than silently losing events. Export waits need a timeout and failure state. Deletion and making collections public require the user’s specific authorization.
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
- 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
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:
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())}")
EOFSetup
When the user asks to "setup videodb" or similar:
1. Install SDK
python -m pip install "videodb[capture]==<reviewed-compatible-version>" python-dotenvIf videodb[capture] fails on Linux, install without the capture extra:
python -m pip install "videodb==<reviewed-compatible-version>" python-dotenv2. 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
Configure a key at https://console.videodb.io; verify current account limits and pricing before any paid operation.
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:
raiseScene 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. Inspect a documented index listing; do not parse arbitrary errors.
try:
scene_index_id = video.index_scenes(
extraction_type=SceneExtractionType.shot_based,
prompt="Describe the visual content in this scene.",
)
except Exception:
# Inspect documented index listings; never infer an index ID from arbitrary errors.
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:
raiseTimeline 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=A… (nội dung đầy đủ có trong gói tải về)
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