peepshow.dev ·
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@tom_taylor
peepshow
video → frames → LLM. Any LLM CLI. Any storage backend. Zero glue code.
Turn a video — or an animated GIF, APNG, or WebP — into a timeline of still frames plus an extracted audio track and its transcript, so an LLM can "watch" and "listen" to what's inside.
Static images (JPG, PNG, static WebP) are already handled natively by most LLMs — drag, drop, done. peepshow only steps in for things that have multiple frames across time: videos and animated images, which today's LLMs can't consume directly.
Same drag-and-drop UX as images. Drop a .mp4 / .mov / .gif into the Claude Code prompt and a UserPromptSubmit hook auto-invokes /peepshow:slides <path> behind the scenes — Claude extracts frames, reads them, and answers. No slash command, no Bash call, no copy-paste. Works with natural-language prompts too ("what's in ~/Desktop/bug.mov?") and with every other CLI entry point (explicit /peepshow:slides, shell peepshow ..., pipes into --sink).
Pluggable sink backends — write your own, or use the built-ins. Every run can fan out to downstream systems via --sink <name> or --sink-cmd <shell>. A sink is any executable that reads a JSON payload on stdin — write one in bash, Node, Python, Go, whatever. The full video + tags + frames + audio + extraction payload (same as --emit json) flows to each sink, so they receive the full context, not just the frame paths. 95 sinks ship built-in across SQL (SQLite · Postgres · MongoDB), vector + AI memory (Chroma · Qdrant · Pinecone · pgvector · Weaviate · Milvus · MemPalace · Zep · Mem0 · Letta), object + file storage (S3-compatible · GCS · Firebase Storage · Azure Blob · Supabase · Dropbox · Google Drive · Box · OpenAI Files), chat (Slack · Discord · MS Teams · Telegram · WhatsApp · iMessage · Mattermost · Rocket.Chat · Zulip · Matrix), issue trackers (Linear · Height · GitHub Issues · Jira · Asana · ClickUp · Shortcut · Trello), whiteboards (Miro · Figma), wiki/notes (Notion · Obsidian · Logseq · Outline · Confluence · Apple Notes · Bear), product analytics (PostHog · Plausible · Mixpanel/Amplitude/Segment), observability (Sentry · Datadog · New Relic · Honeycomb · PagerDuty · Opsgenie · Grafana Oncall), and workflow glue (Webhook · GraphQL · IDE · Aider · Continue · Cody · Raycast · Pipedream · Zapier · Shortcuts · Apple Reminders · Things 3). Browse docs/sinks/ or use the use-case finder. Full spec: docs/PLUGINS.md.
Audio is extracted too, not just frames. When the input has an audio track (MP4 / MOV / WebM / MKV), peepshow runs a second ffmpeg pass that emits a compact mono 16 kHz AAC track next to the frames and probes loudness peak + silence ratio. Animated GIF, APNG, and animated WebP inputs skip this cleanly — they can't carry audio at the format level. The extracted audio.m4a + its analysis fields land in the JSON payload alongside video + frames, so any downstream sink sees the full picture. Opt out with --no-audio.
Audio transcription
When audio is extracted, peepshow can also transcribe it. If whisper.cpp is on your PATH, transcription auto-enables with the base.en model — no flag, no API key, nothing leaves the machine. The model file downloads to ~/.peepshow/whisper-models/ggml-<model>.bin on first use (override with PEEPSHOW_WHISPER_MODEL_DIR). Skip entirely with --no-transcribe or PEEPSHOW_TRANSCRIBE=off.
Prefer a cloud provider? Pick one in a single flag and set the matching API key — peepshow uploads the extracted audio.m4a and stores the result back on the same payload:
