creatorforge

creatorforge

The AI content team you own — not one you rent for $15K/month.

Business owner? Creator? Ask yourself:

• Are you paying (or about to pay) five figures a month for a "done-for-you AI content team"?
• Does that team's "proprietary system" run on someone else's servers, with your voice, audience, and data living there?
• When the retainer ends, do you keep anything — or does the system walk out the door with them?
• Do you actually want to film 2–4 hours a week and have everything else handled — without renting the engine that does it?

If you nodded, here's the deal: creatorforge is that content team, as open software you own and run yourself. No retainer. No 50-spots-only. No "proprietary" black box. It's free, Apache-2.0, and runs on your hardware and your model.

What you get

The same deliverables an agency installs — generated from one command:

• Voice profile — it learns your style from your past posts (no model training, nothing uploaded — just measurable style features).
• Niche research brief — content pillars, audience pains, keyword targets.
• Content ideas — a steady pipeline of format × angle ideas so you never face a blank page.
• Hooks — proven scroll-stopping formulas, written in your voice.
• Scripts — full, structured scripts sized to each platform.
• Captions — on-screen overlay text + timed SRT subtitles.
• Thumbnail concepts — headline / visual / emotion / layout, rendered as actual SVG mockups.
• Multi-platform packaging — one idea, tailored for YouTube, Shorts, TikTok, Reels, X, and LinkedIn (each platform's limits respected).
• Posting calendar — your ideas scheduled at your cadence.

You film. creatorforge does the rest.

How it's different (the honest version)

No inflated view-count promises here. creatorforge gives you a genuinely strong content system; what it can't do is guarantee virality, and anyone who guarantees that is selling something. It runs fully offline on a deterministic engine, and gets sharper the moment you point it at a local model (Ollama) or a cloud one — your call.

Quick start

pip install -e .

# 1. Learn your voice from a folder of your past posts/scripts
creatorforge profile ./my_posts/ --out voice.json

# 2. Run the whole team on a topic, across your platforms
creatorforge pipeline --topic "why you should own your AI stack" \
    --niche "AI for business" --platforms youtube,tiktok,x,linkedin \
    --voice voice.json --start 2026-07-06 --out plan.json

# Or one piece at a time
creatorforge hooks    --topic "cold email that converts" --voice voice.json
creatorforge script   --topic "cold email that converts" --platform youtube_shorts --voice voice.json
creatorforge thumbnail --topic "cold email that converts" --svg thumb     # writes thumb-1.svg …

# Use your own local model to sharpen the prose (nothing leaves your machine)
creatorforge script --topic "..." --provider ollama --model llama3

Run python demo.py to watch it learn a voice and generate a full multi-platform plan end to end.

Platforms

Local models — every modality, on your hardware

creatorforge drives the best open-source, local, free model your machine can run, in every modality — and degrades cleanly when you don't have the big one. Ask it what it can do:

creatorforge capabilities

The recommended model in each row is chosen to fit your VRAM (recommend() ladders from a 24 GB GPU down to CPU). Photorealistic images, cloned voices, MP4s, and generated b-roll need the model/tool installed — but there's always a real, local fallback so nothing hard-fails: a composited raster thumbnail, an animated GIF, a synthesized WAV. Nothing is ever sent to a cloud API.

# transcribe footage with local Whisper
creatorforge transcribe talk.mp4

# generate a thumbnail (diffusion if you have it, else a real raster PNG)
creatorforge image --topic "owning your AI stack" --voice voice.json --out thumb

# produce a finished short from a script (MP4 with ffmpeg, else animated video)
creatorforge video --topic "owning your AI stack" --platform youtube_shorts --out short

# voiceover (Piper, or clone your voice with XTTS) and an audio track
creatorforge voiceover --from-script script.json --out vo.wav --speaker my_voice.wav
creatorforge audio --voiceover vo.wav --music bed.mp3 --out track

# the whole production in one command: plan + thumbnail + video + audio + outbox
creatorforge produce --topic "owning your AI stack" --niche "AI for business" \
    --provider ollama --out ./production/

Long-form & cinematic production (5–15 min)

Short clips are one mode. creatorforge also plans and assembles long-form video — documentaries, video essays, dev logs, promos — structured the way the industry actually does it. It fuses four things:

• a format (creatorforge formats) — the proven beat order for documentary / video-essay / devlog / promo
• a cinematic style (creatorforge styles) — pacing, shot vocabulary, color, and music mood drawn from the grammar of prestige docs, kinetic vlogs, trailer-cut blockbusters, slow-burn arthouse, true-crime, and more
• the algorithm playbook — what each platform actually rewards (watch time / AVD, completion rate, the first-30s hook, re-hooks every ~40s, chapters) turned into concrete production directives
• your voice (+ an optional local model to polish the narration)

…into a full plan: acts → scenes → timed shots → narration → chapters → a music & SFX cue sheet → titles and thumbnails, sized to your target runtime.

creatorforge formats        # documentary, video_essay, devlog, promotional
creatorforge styles         # epic_doc, true_crime, kinetic_vlog, blockbuster, arthouse_slowburn, …
creatorforge longform --topic "owning your AI stack" --format documentary --style epic_doc --minutes 12 --out plan.json
creatorforge studio   --topic "owning your AI stack" --format documentary --minutes 10 --provider ollama --out ./film/

Generative music and sound effects come from local open models (MusicGen / AudioGen) when your GPU can run them, with a synthesized bed as a fallback so a cut always has a track.

On "Netflix-level": creatorforge plans and directs at that structural level — story structure, shot lists, pacing, sound design, retention engineering — and assembles the cut with whatever render models you have. Cinema-grade footage and audio come from the heavy open models (FLUX / LTX-Video / MusicGen / XTTS) on a capable GPU, which the engine drives; on a laptop you still get a complete, correctly-structured cut with real generated assets. The structure is studio-grade everywhere; the render fidelity scales with your hardware.

Punch above your weight class: real photos, designed

You don't beat a giant cloud image model on a laptop by out-rendering it — you out-source and out-design it. creatorforge pulls real, no-watermark photography and composites it into pro visuals, which reads as more professional than weak CPU diffusion ever will.

• Your own library, offline. Index image folders you already have and search them by keyword — multiple related shots per scene, your images, zero watermarks, zero licensing questions. Optionally caption them with local llava for smarter matching.
• Free, no-key, no-watermark CC stock. Openverse / Wikimedia Commons, each result carrying its license + attribution so you stay compliant. Watermarked sources (Getty/Shutterstock previews) are never queried.
• Designed, not dumped. A sourced hero photo gets cover-cropped, color-graded, given a legibility scrim, and set with a bold headline — a real editor's thumbnail.

# build an offline, searchable index of your image folders (your own = no watermark)
creatorforge assets index ~/Pictures ~/b-roll --out assets.json

# pull multiple related, key shots for a scene
creatorforge assets search "datacenter server racks" --index assets.json -k 6
creatorforge assets search "founder at laptop" --index assets.json --online   # + free CC stock

# build a thumbnail composited over a real sourced photo
creatorforge image --topic "owning your AI stack" --assets assets.json --out thumb
# studio/produce auto-source a hero from your library:
creatorforge studio --topic "..." --format documentary --assets assets.json --out ./film/

Licensing, honestly: your own library is yours. Openverse/Wikimedia results are Creative Commons / public-domain and may require attribution — creatorforge surfaces the license and attribution string with every result so you can credit correctly. It never pulls watermarked or paid-preview imagery.

Direction & engagement craft (multi-cam, cool shots, retention)

Long-form plans don't just have scenes — they have coverage and engagement built in:

• Multi-camera shot generation. Every beat gets a shot list across A/B/C/detail/drone/POV cameras with motivated camera moves — dolly-in, push-in, crane, gimbal track, drone reveal, dolly-zoom (vertigo), orbit, speed-ramp — and the showy "cool shots" land where they matter (cold opens, turns, climaxes). The plan tells you exactly which cameras a production needs.
• Engagement craft, encoded. Each beat carries a retention move drawn from two lineages: great-filmmaker grammar (in-media-res, but/therefore causality, show-don't-tell, escalating stakes, tension-release, match cuts, the Kuleshov effect) and modern retention tactics (front-load the payoff, escalate every segment, reset the hook on a cadence, concrete stakes/numbers, no dead air, tease what's coming, emotional payoff). Structure isn't just correct — it's sticky.

It's all in the longform/studio plan: scenes[].shots (cams + moves), scenes[].retention_move, multicam, and engagement_plan.

Make content for your repos — and grow like the AI companies that made it

Point creatorforge at a repository and it writes the content for it; point it at an owner and it does the whole catalog.

# one repo -> multi-platform content (reads the README, derives what it is)
creatorforge repo ./codegraph-mcp --format promotional --out plan.json
creatorforge repo cognis-digital/agentledger --longform --format documentary   # via gh

# every repo of an owner, batched
creatorforge repos --owner cognis-digital --format promotional --out ./repo_content/

# a 30-day launch strategy that mirrors how the big AI companies actually grew
creatorforge growth ./codegraph-mcp

The growth playbook encodes the plays that repeatedly worked for the AI companies that broke out — a runnable demo over a pitch deck, building in public, a benchmark moment, developer-first distribution, founder-led content, free/open core, naming the category — and turns them into a concrete day-by-day launch calendar for your project. The edge was never the secret; it's executing these consistently, which is exactly what the engine makes cheap.

Wire it into your stack (MCP)

creatorforge ships an MCP server, so Claude, an internal orchestrator, or any MCP-capable agent can drive it directly:

creatorforge serve     # JSON-RPC over stdio

Tools: profile_voice, generate_ideas, write_hooks, write_script, thumbnail_concepts, package_for_platform, run_pipeline. Hand the packaged posts to your scheduler/poster of choice and the loop is closed.

Testing

pip install -e ".[dev]"
pytest -q          # 49 tests

License

Apache-2.0. © Cognis Digital. The whole engine is open — read it, fork it, run it on your own models. You own your content team.

Status: v0.1 — runnable and tested. Short-form + long-form (5–15 min) production; text, transcription, voice, image, video, music/SFX backends wired with hardware-aware selection and CPU fallbacks; format/style/algorithm intelligence baked in. Roadmap: ComfyUI image/video backend, true text-to-video assembly, A/B title scoring, scheduled auto-publish.