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CLI Commands

Generated: December 12, 2025 Purpose: Reference for the aios CLI and subcommands Status: Implemented

Overview

  • Main entry point: aios
  • File: src/aios/cli/aios.py

Sub-commands overview: - hrm-hf – HuggingFace-based HRM training (see Core Training) - brains – Brain management - gui – Launch GUI (see GUI Features) - status – System status - datasets – Dataset management (see Datasets) - cache – Cache management - goals – Goals management - eval – Evaluation utilities (see Advanced Features → Evaluation) - artifacts – Artifacts management - cleanup – Cleanup utilities - crawl – Web crawling (see Tools & Integrations) - optimization – Optimization utilities (see Memory Optimization) - modelcard – Model card generation - agent – Agent commands - budgets – Budget management (see Advanced Features → Budgets) - core – Core commands - hf-cache – HuggingFace cache management - dml – DirectML utilities

HRM-HF Training

  • Command: aios hrm-hf
  • File: src/aios/cli/hrm_hf_cli.py
  • Subcommand: train-actv1 – Train HRM models with ACT v1
  • File: src/aios/cli/hrm_hf/train_actv1.py
  • Deep dive: See Core Training and Memory Optimization docs

Key parameters (selection): - Model: --model <name_or_path> - Brain naming: --brain-name, --bundle-dir - Training control: --steps, --batch-size, --lr, --max-seq-len, --iterate, --stop-file, --resume, --stop-after-epoch - Architecture: --h-layers, --l-layers, --hidden-size, --expansion, --num-heads, --h-cycles, --l-cycles, --halt-max-steps, --window-size, --pos-encodings - Memory optimization: --gradient-checkpointing|--no-gradient-checkpointing, --amp|--no-amp, --use-8bit-optimizer, --use-chunked-training, --chunk-size, --cpu-offload - Dataset: --dataset-file, --ascii-only, --linear-dataset, --dataset-start-offset, --dataset-chunk-size - Evaluation: --eval-file, --eval-batches, --log-file - Multi-GPU: --ddp, --cuda-ids, --world-size, --parallel-independent, --strict - DeepSpeed: --zero-stage <none|zero1|zero2|zero3> - MoE: --use-moe, --num-experts, --num-experts-per-tok, --moe-capacity-factor, --auto-adjust-lr - PEFT: --use-peft, --peft-method, --lora-r, --lora-alpha, --lora-dropout, --lora-target-modules - Precision/Quant: --model-dtype fp32|fp16|bf16, --load-in-8bit, --load-in-4bit - Inference hot‑reload: --inference-device, --hot-reload-steps

Brains Management

  • Command: aios brains
  • File: src/aios/cli/brains.py
  • Subcommands: list, load, info, delete, export, import
  • Related: Core Training → Brain Bundle System, GUI Features → Brains Panel

Datasets Management

  • Command: aios datasets
  • File: src/aios/cli/datasets_cli.py
  • Features: list/download, scan, metadata, verification
  • Related: Datasets doc

Goals Management

  • Command: aios goals
  • File: src/aios/cli/goals_cli.py
  • Create/list/activate goals, link to experts, goal-driven training.
  • Related: Dynamic Subbrains/MoE and Advanced Features → Orchestrator

Cache and HF Cache

  • aios cache → Clear/show stats
  • aios hf-cache → Location, move, clear, size reporting

Evaluation

  • Command: aios eval
  • File: src/aios/cli/eval_cli.py
  • Run evaluations, generate reports, compare models.
  • Related: Advanced Features → Evaluation

Crawling

  • Command: aios crawl
  • File: src/aios/cli/crawl_cli.py
  • Web crawling, dataset generation from web.
  • Related: Tools & Integrations

Optimization

  • Command: aios optimization
  • File: src/aios/cli/optimization_cli.py
  • Memory/VRAM estimation and parameter optimization.
  • Related: Memory Optimization

Back to Feature Index: COMPLETE_FEATURE_INDEX.md • Back to Guide Index: ../INDEX.MD