reelsaw

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Self-hosted, AI-powered long-form → short-form video clipper. Paste a YouTube link or upload a video; Reelsaw transcribes it, asks an LLM for the most clippable moments, then renders vertical 9:16 clips with word-highlight captions and a hook overlay. A hosted service at app.reelsaw.com runs the same code (Free, then $12 / $29 / $59 a month, metered in source minutes).

Pure TypeScript. Any AI vendor via the AI SDK. One-step deploy with Docker Compose.

<p align="center"> <img src="docs/assets/pipeline.gif" alt="Animated walkthrough of the pipeline: a video is ingested, transcribed in parallel chunks, refined by three jobs, its best moments are ranked pairwise, and five vertical clips are rendered; a worker restarts mid-render and resumes from its last checkpoint" width="920"> </p> <p align="center"> _{One video through the five queues: ingest → transcribe → refine ×3 → pick moments → render. A worker restarts mid-render and resumes from its last save. <a href="docs/assets/pipeline.mp4">Full-quality MP4</a>, or <a href="https://reelsaw.com/#how-it-works">play it on reelsaw.com</a>.} </p> <p align="center"> <img src="docs/assets/workspace.png" alt="Project workspace with source player, transcript, and rendered clips" width="920"> </p> <p align="center"> <video src="docs/assets/demo-framing.mp4" poster="docs/assets/demo-framing-poster.jpg" width="280" controls playsinline> <a href="docs/assets/demo-framing.mp4">demo-framing.mp4</a> </video> </p> <p align="center"> _{Auto reframing in one clip: split → face → stack → fit} </p> <p align="center"> <img src="docs/assets/editor.png" alt="Clip editor with 9:16 preview, captions panel, and multi-lane timeline" width="450"> &nbsp; <img src="docs/assets/transcript-fixes.png" alt="Transcript with filler cuts and the fixes list" width="450"> </p>

Features

Pipeline

• Any AI vendor – language model, transcription model and caption-alignment model are each a provider:model string: OpenAI, Anthropic, Google, Groq, Deepgram, AssemblyAI, Vercel AI Gateway, or any OpenAI-compatible server (Ollama, vLLM, LM Studio, local Whisper servers). Fully local with no API keys is supported.
• Research-backed clip selection – map → pool → rank: the transcript is chunked at long pauses with 20% overlap (no "lost in the middle" on long videos), every standalone moment is collected per chunk in parallel, candidates are snapped/deduped, then scored on a rubric (hook / value / flow / shareability, plus relevance with a focus) as the median of k samples, and the top 10 get K sliding pairwise head-to-head passes (PRP-Sliding-K; ANALYZE_PAIRWISE_PASSES, default 3 so the top 3 you see first are placed reliably) with positions swapped to cancel judge bias. Cost: at most Σ(n−1−p) pairs × 2 calls, i.e. 48 calls for the top 10 with 3 passes (18 with 1); pairs met twice are judged once. No target count: in auto mode weak picks are dropped by a gate relative to the run, not a fixed number, because pointwise scores do not transfer between judge models: a clip is dropped below max(ANALYZE_MIN_SCORE_FLOOR = 25, median − ANALYZE_SCORE_MAD_K = 1 × MAD) of the pooled rubric totals, and the best clip is always kept (ANALYZE_SCORE_RULE=absolute restores the old fixed 45). The threshold and its median/MAD are in the project's candidates artifact. Candidates whose scoring failed are never compared with rubric totals; they only fill in when fewer than 3 scored clips survive. Optional "at most N" cap, and "Find clips about …" keeps only on-topic moments. Click a clip's score for the breakdown. ANALYZE_JUDGE_MODEL lets a different model score and compare (less self-preference than judging its own hooks). ANALYZE_CONCURRENCY, ANALYZE_SCORE_SAMPLES, ANALYZE_PAIRWISE tune cost (auto: 1 call at a time, 1 sample, no pairwise for a self-hosted judge; 4 / 3 / on for cloud).
• Clean transcripts – names are fixed from vocabulary hints and a constrained LLM correction, and fillers, repetitions and false starts are cut with jump cuts. Every cut is located by forced alignment and checked by listening to the seam, so karaoke highlights land on the syllable. Each fix shows inline in the transcript with accept/reject, and long pauses can be shortened (details below).
• Smart 9:16 reframing – UltraFace (1.2 MB ONNX, CPU, ~7 ms/frame via onnxruntime-node) samples each clip at 4 fps and picks a layout per segment (clips are split at scene cuts and face-presence changes, so a picture-in-picture intro can be "fit" and the talking head after it "face"; shot cuts are detected on every clip, and a multi-camera edit that alternates a close-up with a wide shot every second or two changes layout at each cut): face (crop follows the speaker with "heavy tripod" smoothing: dead zone, capped pan speed, instant snap at scene cuts), split (two speakers stacked), stack (slides/screen on top, the webcam tile below — the picture-in-picture box of a Zoom, Teams, Meet or OBS recording, not a face-sized crop that reaches into the slides), or fit (whole frame over a blurred background when there is no face, e.g. graphics and b-roll, or when three or more people share the frame). With two people in a wide shot the crop follows whoever is talking (mouth motion correlated with the audio envelope, minimum 2.5 s per shot), falling back to a split when detection isn't confident. Override per project, per clip or per section, including a hand-set crop. Reference for every layout, its triggers, caveats and fixtures: docs/LAYOUTS.md.
• Captions – AI-picked key words per clip coloured and enlarged (editable in the editor), readability limits (≈2 short lines, comma/sentence breaks, a line stays up long enough to read: at least 0.7 s, 0.3 s per word and 20 characters per second), ASS karaoke word highlight (any colour), boxed, or outlined; size, words on screen (1 = one word at a time), uppercase; hook overlay with its own duration. Caption and hook positions are free x/y set by dragging on a live 9:16 preview that uses the renderer's crop math and font metrics, with a platform safe-zone overlay. In split and stack sections that last 2.5 s or more, captions sit on the line between the two panes instead of on the lower speaker (a switch turns it off). Project-wide defaults, per-clip overrides. Burned in with ffmpeg + libass.

Editing

• Workspace and clip editor – source player and clickable transcript on the left, clips streaming in on the right as they render, with score, layout badge, post caption + hashtags copy and download. The editor has a live preview of the source with the clip's framing and captions and a multi-lane timeline (ruler, transcript words, clip range, layout track, layers) with zoom, snapping to words/scene cuts/playhead, nudge buttons, typed timestamps and I/O keys for frame-accurate trims. Split the layout track (⌘/Ctrl+B, the Split button, a double-click or the right-click menu) into sections that are Auto or forced to face/split/stack/fit/centre; drag the picture to re-centre a section; right-click for Set crop… (a box on the source, or crop / crop2 / contentCrop on update_clip); "Use for all clips…" copies one clip's framing to the project (apply_framing). Add, drag and remove transitions; ⌘/Ctrl+Z / ⇧⌘Z undo and redo every edit.
• Deletes can be undone – deleting a project or a clip (card ⋯, the selection bar, the editor, ⌘K) stops its work and hides it. The toast always offers Undo, Delete forever, and See deletions. Everything restorable lives on Deleted (account menu) as one selectable list: each row says when it was deleted and when it is deleted forever, and a compact bar restores the selection or deletes it forever. Storage still counts until you delete it forever (MCP list_deleted plus purge_project / purge_clip / purge_asset / purge_layer_template; reelsaw purge-project, purge-clip, library purge, templates purge). Minutes, hourly creates and first-video-free are never refunded. Re-picking moments keeps every clip you made or edited (text, bounds, framing, style, intro/outro) and only replaces untouched AI picks, which can be restored too. The same through MCP (delete_clip, delete_clips, restore_project, restore_clip, list_deleted) and the CLI (reelsaw deleted, restore, delete-clip, delete-clips, restore-clip, purge, purge-project, purge-clip).
• Learns from your decisions – what you accept, reject, cut, correct and edit is kept in a decision log (with the words or clip text it was about, the models that proposed it and a fingerprint of the source video) that outlives deleted projects: cuts you rejected are shown to the filler detector as examples to keep, and an export turns your decisions into eval cases (reelsaw decisions export, export_decisions, the decisions suite). Settings → Learning turns it off or forgets everything; deleting a project (or "Delete forever") can forget what it learned from that project, applied when it is purged, even automatically. It never leaves your instance. See docs/specs/decision-log.md.
• Command palette and bulk export – ⌘K searches projects and clips with status, length and age, opens a row's actions (open, export, resume, retry failed clips, re-run refine, re-render, download, delete project or clip), takes pasted links (one project each, or opens the existing one) and offers retry-all shortcuts. "Export all" zips every rendered clip with platform-ready metadata: a paste-ready .txt (title, description, tags, caption), a .youtube.json (YouTube Data API v3 videos.insert body, private by default) and a .tiktok.json (Content Posting API post_info, SELF_ONLY) per clip, plus manifest.json, clips.csv (with rendered duration) and a README. Descriptions carry a timestamped link to the exact moment in the parent video.
• Share links – a clip's ⋯ menu copies a link anyone can download it from without signing in (the project and selection menus do the same for the zip), for schedulers (Buffer, Metricool), Instagram's video_url, Zapier/Make file fields or a person. The link answers with the file itself (a plain 200, no redirect), serves the clip's latest render, lasts 90 days by default (MEDIA_LINK_TTL_DAYS; "Never" where MEDIA_LINK_ALLOW_NEVER), and can be revoked one at a time, per clip or project, or all at once under Settings → Share