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Settings

Server configuration — restart CoderAI to apply changes

Server
IP address or hostname to bind to (0.0.0.0 = all interfaces)
Maximum number of concurrent queued requests. Authenticated requests arriving when the queue is full receive a 429 response.
First internal port for engine subprocesses (the front assigns this and the next free ports). Keep it different from the listen port above. Restart to apply.
Concurrency
How many requests each engine runs at once. Each engine is its own process, so this applies per-engine — total concurrency is the sum across engines.
Default number of concurrent copies of one model. Override per model on the Models page.
Storage
Models will inherit this as default when configured
Server-wide ceiling on host RAM (process-tree RSS). New model loads get a CPU-offload budget clamped to the remaining headroom, so the overflow spills to the offload directory (disk) instead of pushing past the limit. Applied live on save.
Unload least-recently-used idle models to free real RAM before forcing disk offload.
Background watcher samples RSS; when it keeps climbing while idle or nears the cap it runs gc / CUDA cache release / heap trim and (if enabled) evicts idle models.
When the watcher mitigates, let it call torch.cuda.empty_cache(). Turn this off on a GPU that drops off the bus (Xid 79) to stop the background thread from touching CUDA — host-RAM mitigation (gc / heap trim / idle eviction) still runs. Loads are always skipped regardless.
How often the watcher samples process-tree RSS.
Fraction of the RAM cap at which the mitigation ladder engages.
Scratch space for frame extraction, upscaling and interpolation. Point it at a large volume — 4× upscaling can exhaust a small /tmp ("No space left on device"). Applied live on save.
Video Enhancement

Upscaling and FPS interpolation run on in-process torch models by default (ESRGAN upscaler, RIFE/FILM interpolator) — no external tools. Enable these only to fall back to external tools when no model is configured.

Off = use PyAV + models only. On = ffmpeg may be used as a fallback.
Off = use an in-process RIFE/FILM model. On = the external rife-ncnn-vulkan binary may be used when no model is configured.
Generation Archive
When enabled, every generation (image, video, audio, text) is logged with its prompt, model, and output files.
Absolute path or relative to the config directory. Leave blank to use the default.
Archived entries older than this are automatically deleted. Takes effect immediately on save.
Thermal Protection
Before serving a request against a loaded model, wait until temperatures are safe so a long sequence of heavy generations can't overheat the machine and trip its power-off protection. The wait is non-blocking (other requests keep being accepted) and takes effect immediately on save. Temperatures in °C.
How often to re-read temperatures while waiting for cooldown.
Before the hard pause, gently slow generation (short per-step sleeps) once the CPU enters the warm band, so its temperature climbs slower and the full cooldown is rarely hit. CPU only — GPU is unaffected.
Background Jobs
Controls how interrupted LoRA training is handled when CoderAI restarts. Equivalent to the --no-resume-jobs launch flag.
When off, a training job that was running at restart is marked cancelled instead of resuming. Its checkpoint is kept, so you can still restart it manually from the Tasks page.
AISBF Broker
Registers this CoderAI instance with an AISBF broker so it can receive brokered requests.
DeepSeek V4 (ds4)

Run DeepSeek V4 through antirez's native ds4 / DwarfStar engine as a managed subprocess. When enabled, requests for a matching model name are proxied to ds4-server. First use clones + builds ds4 and downloads several GB of weights — this is slow and needs lots of RAM (96 GB+).

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