AISBFCoderAI turns your machine into a multimodal AI backend.
CoderAI is an open source local model orchestrator with an OpenAI-compatible API, a Web Studio for generation tasks, GPU-aware model loading, and a broker client that lets AISBF route work to your machine over outbound WebSockets.
Source-backed from the CoderAI repository README, reverse-proxy docs, broker reference, and runtime config defaults.
Jump to: Full docs · Install · Docker / OCI · Docker install bundle · Gallery · API · Broker · Market · What it is · Features · Bundled apps · AISBF broker · Install · API surface · Operations
See the operator UI.
The 10-image CoderAI gallery shows the model configuration workflow: model configuration, live task monitoring, HuggingFace model discovery, active downloads, and repository detail drawers.
Model configuration screenshots
Use the 10-screenshot gallery for a quick visual tour of the model-management interface before installing CoderAI locally or connecting it to AISBF.
Local control, cloud-style API.
CoderAI is the local compute side of the stack: run models on your own GPUs, expose them through familiar HTTP routes, and optionally let AISBF treat that machine as a provider.
Drop-in API shape
It exposes OpenAI-style endpoints including GET /v1/models, POST /v1/chat/completions, completions, embeddings, image, video, and audio routes.
Browser UI for generation
The built-in Studio covers chat, image, video, audio, pipelines, archive browsing, model settings, users, tokens, and admin controls.
NVIDIA, AMD, Intel paths
CUDA, Vulkan, Metal, GGUF, Transformers, stable-diffusion.cpp, whisper.cpp, and related runtimes are handled by platform-specific build paths.
No giant CLI ceremony
Runtime state lives under ~/.coderai/: config.json, models.json, auth.json, pipelines.json, archive, and generated secrets.
Built for more than chat.
The repository describes CoderAI as a multimodal orchestrator, not only an LLM server. The useful bit: one local control plane for many heavy generation jobs.
Text and embeddings
Chat completions, text completions, embeddings, streaming responses, prompt caching, tool calling, per-model context and quantization settings.
Images
Text-to-image, image editing, inpainting, upscaling, deblur, unpixelate, outfit change, face swap, depth, segmentation, and 2D/3D conversion.
Video
Text-to-video, image-to-video, video-to-video, frame interpolation, upscaling, subtitles, dubbing, lip sync via Wav2Lip or SadTalker, and 3D video processing.
Audio
Kokoro TTS, Whisper STT, MusicGen/AudioGen/AudioLDM2, F5-TTS voice cloning, Seed-VC voice conversion, and saved voice profiles.
Profiles
Character profiles and environment profiles preserve visual identity and scene style across image/video generation. The README documents up to six of each per generation.
Pipelines
Built-in and custom pipelines chain steps like text → image → video → TTS. Template variables include {{input}}, {{stepN.output}}, and {{stepN.url}}.
Bundled example applications.
CoderAI is not only an API server. The source tree includes three practical demo/example web applications under tools/ — video_editor.py, videogen.py, and gen_township_fighters.py — and the Docker / OCI image starts them behind the same published port.
Video editor
A browser-based editor backed by CoderAI TTS and local ffmpeg. Pick or upload video, scrub a timeline, generate narration, place clips at exact positions, add music, speed up regions, and render the final result.
OCI route: /editor/
VideoGen studio
A small web app for managing character and environment profiles, assembling multi-clip short movies, and chaining image/video generation, speech, lip-sync, music, and sound effects through the CoderAI API.
OCI route: /videogen/
Township fighters demo
An example generator for fighter-match videos in an MMA-style workflow: generate characters, environments, and fight clips through CoderAI, then save the produced media under the container cache/output paths.
OCI route: /township/
The AISBF connection.
CoderAI does not need AISBF to work. Use CoderAI standalone for local generation, the browser UI, and direct OpenAI-compatible API calls. Add AISBF only when you want brokered routing, metering, clustering, or shared access to that local capacity.
CoderAI can also be a first-class AISBF provider. Direct HTTP works on a LAN/server. Broker mode is for machines behind NAT: CoderAI dials out, AISBF routes in.
Broker config in CoderAI
{
"broker": {
"enabled": true,
"base_url": "https://aisbf.cloud",
"scope": "user",
"username": "alice",
"provider_id": "coderai-local",
"client_id": "workstation-01",
"registration_token": "your-provider-token",
"transport": "websocket"
}
}AISBF provider shape
{
"type": "coderai",
"endpoint": "http://127.0.0.1:8776",
"api_key_required": false,
"coderai_config": {
"broker_enabled": true,
"broker_preferred": true,
"client_id": "workstation-01",
"registration_token": "provider-scoped-secret"
}
}Important broker rule
The broker identity must match on both sides. Keep provider_id, client_id, username, and registration_token stable. If AISBF sees the session but requests do not route, the first thing to check is usually a mismatched client_id or owner scope.
Sell access to local models through AISBF.
CoderAI broker mode is the local-model seller path: your machine dials AISBF, registers what it can run, and AISBF exposes that capacity through controlled provider routes.
Keep the GPU local
Run CoderAI on your workstation, home lab, private server, or rented GPU. The broker uses outbound WSS, so the worker does not need a public inbound port.
Advertise real capability
CoderAI can report hardware, endpoints, and model/media capabilities so AISBF can route buyers to the right worker.
Let AISBF manage access
AISBF sits in front for identity, tokens, quotas, routing, failover, and the market/access layer instead of exposing your raw CoderAI API.
Install and run.
The README’s quick start builds all backends, starts the server on localhost, then opens the admin UI. Default credentials are admin / admin and should be changed immediately.
Linux quick start
git clone git@git.nexlab.net:nexlab/coderai.git
cd coderai
./build.sh all
source venv_all/bin/activate
python coderaiDefault server: http://127.0.0.1:8776
Container install: run the provided Docker / OCI image with coderai-docker and persistent /config, /models, and /cache volumes. Download the ready-to-use Docker install bundle →
Access points
/admin— admin dashboard/chat— Web Studio/v1/*— OpenAI-compatible API/docs— interactive FastAPI docs
API surface.
CoderAI presents a broad set of generation endpoints while keeping OpenAI-compatible routes for the common integration path.
Core OpenAI-style
GET /v1/modelsPOST /v1/chat/completionsPOST /v1/completionsPOST /v1/embeddings
Image and 3D
/v1/images/generations/v1/images/edits/v1/images/faceswap/v1/3d/generate
Video
/v1/video/generations/v1/video/dub/v1/video/interpolate/v1/video/to3d
Audio
/v1/audio/speech/v1/audio/transcriptions/v1/audio/clone/v1/audio/convert
Operational shape.
CoderAI is designed like local infrastructure: model registry, request queueing, on-demand loading, offload rules, archive retention, auth, tokens, and reverse-proxy support.
Resource management
On-demand loading, idle unload, VRAM → RAM → disk offload, per-model settings, request queues, prompt cache reuse, and optional prompt aggregation.
Frontend/engine split
The config defaults include a thin frontend proxy plus one or more engine subprocesses so the UI can stay responsive while GPU workers load or generate.
Reverse proxy ready
The repo documents subdomain/root mounting and /coderai/ sub-path mounting using X-Forwarded-Prefix, long timeouts, large uploads, and disabled buffering for SSE.
Open source
CoderAI is GPLv3, authored by Stefy Lanza, with contributions via merge requests on Nexlab GitLab.