CLI reference

Generated from the running dlm --help output. Auto-regeneration via typer-cli is planned for a follow-up sprint; until then this file is hand-maintained and gated by the test suite.

Global options

Applied to every subcommand:

Option	Env var	Default	Description
`--home PATH`	`DLM_HOME`	`~/.dlm`	Override the store root.
`-v, --verbose`	—	off	Emit plan / resolver diagnostics on stderr.
`-q, --quiet`	—	off	Suppress informational output.
`--version`	—	—	Print version and exit.
`--install-completion`	—	—	Install shell completion.
`--show-completion`	—	—	Print shell completion script.
`-h, --help`	—	—	Show command help.

Commands

`dlm init`

Bootstrap a new .dlm file with a fresh ULID, create the per-store directory, and persist the license-acceptance record (audit-05 B2).

dlm init <path> [--base <key>] [--template <name>]
                [--multimodal | --audio]
                [--skip-export-probes]
                [--i-accept-license] [--force]

Option	Default	Notes
`--base <key>`	`qwen2.5-1.5b`	Registry key or `hf:org/name`. Ignored when `--template` is used (the template's `recommended_base` wins). With `--multimodal`, defaults to `paligemma-3b-mix-224`.
`--template <name>`	None	Bootstrap from a named gallery template. See `dlm templates list`. Mutually exclusive with `--multimodal`.
`--skip-export-probes`	false	Skip the llama.cpp / GGUF compatibility probes so a brand-new architecture can still be used for training + HF inference. Forfeits `dlm export` to Ollama until the vendored exporter catches up.
`--multimodal`	false	Scaffold a vision-language `.dlm` with an `::image::` section (schema v10). Flips `--base` to `paligemma-3b-mix-224` unless explicitly overridden; a non-VL `--base` is refused. See multimodal-training cookbook.
`--audio`	false	Scaffold an audio-language `.dlm` with an `::audio::` section. Flips `--base` to `qwen2-audio-7b-instruct`, skips export probes, and refuses text / vision-language bases. See audio-training cookbook.
`--i-accept-license`	false	Required for gated bases (Llama-3.2, PaliGemma).
`--force`	false	Overwrite an existing `.dlm` at path.

Writes <path> with minimum frontmatter, provisions ~/.dlm/store/<dlm_id>/ with an initial manifest.json, and (for gated bases) stores the LicenseAcceptance record so dlm train / dlm export don't re-prompt. Refuses if the .dlm file already exists and --force wasn't passed.

`dlm train`

Train / retrain the adapter.

dlm train <path> [--resume|--fresh] [--seed N] [--max-steps N]
                 [--phase {sft,preference,all}]
                 [--i-accept-license]
                 [--strict-lock|--update-lock|--ignore-lock]
                 [--strict-metrics]
                 [--base <key>] [--include GLOB]... [--exclude GLOB]...
                 [--recursive|--no-recursive] [--name NAME]
                 [--policy {strict,permissive}] [--rescaffold]
                 [--skip-export-probes]

Option	Default	Notes
`--resume`	false	Continue from `training_state.pt`. Mutex with `--fresh`.
`--fresh`	false	Discard prior optimizer state; train from scratch. Mutex with `--resume`. Default when neither flag is set.
`--seed N`	frontmatter.training.seed	Override training seed.
`--max-steps N`	unlimited	Cap step count.
`--phase {sft,preference,all}`	`all`	Choose which training phases run: SFT only, preference only, or both in sequence. Preference-only requires a prior SFT adapter.
`--i-accept-license`	false	Required for gated bases (usually captured once at `dlm init` and persisted).
`--strict-lock`	false	Fail on any `dlm.lock` drift (even WARN).
`--update-lock`	false	Bypass validation; always write a fresh `dlm.lock`.
`--ignore-lock`	false	Bypass validation; don't write `dlm.lock`.
`--strict-metrics`	false	Promote metrics SQLite write failures to hard errors instead of best-effort degradation. Run-start / run-end are always hard-fail anchors; this flag extends that policy to step, eval, tokenization, and export streams.
`--gpus SPEC`	single-process	Multi-GPU training via Accelerate. `all` uses every visible CUDA device; `N` uses the first N; `0,1` selects exact device ids. Dispatches to `accelerate launch` when >1 device is selected. Refused on MPS/CPU/ROCm; heterogeneous CUDA SMs refused.
`--watch`	false	Save-to-train mode (Sprint 25). After the initial train, block on filesystem events and re-run bounded-step retrains on each settled save.
`--watch-max-steps N`	100	Per-cycle step cap for `--watch`. Keeps cycles responsive.
`--watch-debounce-ms N`	400	Quiet interval before a burst of saves triggers a retrain.
`--repl`	false	With `--watch`: also run `dlm repl` in the same process. Scaffolded only — threading integration is a followup; today the flag refuses with exit 2.
`--base <key>`	required on first auto-scaffold	Base model for `dlm train <dir>` auto-scaffold. Ignored when `<path>` already points at a `.dlm`.
`--include GLOB`	repeatable	Auto-scaffold include glob. Defaults to `*/` with `--recursive`, `*` with `--no-recursive`.
`--exclude GLOB`	repeatable	Auto-scaffold exclude glob. Directory-descent defaults still apply on top.
`--recursive` / `--no-recursive`	recursive	Auto-scaffold whether default include globs descend into subdirectories.
`--name NAME`	`corpus`	Auto-scaffold target file name under `<dir>/.dlm/<name>.dlm`. Lets one tree host multiple adapters.
`--policy {strict,permissive}`	`strict`	Auto-scaffold `training.sources_policy`. `strict` confines training sources to the target directory; `permissive` allows absolute paths anywhere.
`--rescaffold`	false	Rewrite an existing scaffolded `.dlm` in place with new auto-scaffold flags while preserving its `dlm_id`.
`--no-cache`	false	Bypass the tokenized-section cache for this run. Default is cache-on when the `.dlm` declares `training.sources`. Use when debugging tokenization or cross-checking cached-vs-uncached determinism. Entries from prior runs stay on disk; the next run without the flag picks them back up. See directive-cache.
`--skip-export-probes`	false	Skip the llama.cpp / GGUF compatibility probes so a brand-new architecture can still be trained for HF inference. Mirrors `dlm init --skip-export-probes`.

The three lock flags are mutually exclusive. See Determinism for the mismatch severity table.

--gpus multiplies the effective batch size by world_size; the resulting lock records world_size and warns on drift between runs. Multi-GPU + QLoRA on CUDA is permitted (bitsandbytes supports DDP); multi-GPU + ROCm is out of scope for Sprint 23.

`dlm prompt`

Run inference against the current adapter.

dlm prompt <path> [query] [--max-tokens N] [--temp F] [--top-p F]
                  [--adapter NAME] [--gate {auto,off}]
                  [--image PATH]... [--audio PATH]...
                  [--verbose]

Option	Default	Notes
`--max-tokens N`	256	Max new tokens to generate.
`--temp F`	0.7	Temperature. `0.0` = greedy decoding (deterministic).
`--top-p F`	None	Top-p sampling.
`--adapter NAME`	None	Select a named adapter from `training.adapters`. Required on multi-adapter documents; rejected on single-adapter ones.
`--gate {auto,off}`	`auto`	Learned adapter gate (Sprint 34). `auto` uses the trained gate when one exists in the store; `off` forces uniform weights across declared adapters. Silently ignored when `--adapter` pins a single adapter. See `docs/cookbook/learned-adapter-gate.md`.
`--image PATH`	none	Attach an image to the prompt. Repeat for multiple images; each expands to one `<image>` placeholder the processor slots pixels into. Required on vision-language bases; rejected on text bases. See multimodal-training cookbook.
`--audio PATH`	none	Attach an audio clip to the prompt. Repeat for multiple clips. Required on audio-language bases; rejected on text and vision-language bases. See audio-training cookbook.
`--backend {auto,pytorch,mlx}`	`auto`	Inference backend. `auto` picks MLX on Apple Silicon (when `uv sync --extra mlx` is installed), else PyTorch. Ignored on VL bases (the VL path always uses PyTorch + AutoModelForImageTextToText).
`--verbose`	false	Print resolved `InferencePlan` on stderr.

MLX backend caveat (darwin-arm64): the MLX path has known issues applying PEFT-format LoRA adapters — the converter runs without error but the resulting MLX adapter does not modify generation, producing output that matches the base model. If your trained adapter appears to behave like the base, pass --backend pytorch as a workaround. See docs/audits/13-followup/finding04/direct-query-results.md for the diagnostic walk-through.

Query is the CLI positional argument. Omit to read from stdin.

`dlm repl`

Interactive prompt-and-respond REPL against the trained adapter (Sprint 24).

dlm repl <path> [--adapter NAME] [--backend {auto,pytorch,mlx}]

Option	Default	Notes
`--adapter NAME`	None	Named adapter; required on multi-adapter docs.
`--backend {auto,pytorch,mlx}`	`auto`	Same contract as `dlm prompt --backend`.

Slash commands inside the REPL: /help, /exit, /clear, /save, /adapter, /params, /model, /history. Ctrl-D exits; Ctrl-C cancels generation or input. Session history persists at ~/.dlm/history. See the interactive-session cookbook.

`dlm metrics`

Query the per-store SQLite metrics DB (Sprint 26).

dlm metrics show <path> [--json|--csv] [--run-id N] [--phase PHASE] [--since WINDOW] [--limit N]
dlm metrics watch <path> [--poll-seconds N]

Option	Default	Notes
`--json`	false	Emit JSON object (`{runs: [...], steps: [...], evals: [...]}` when combined with `--run-id`).
`--csv`	false	Emit CSV of runs or (with `--run-id`) steps + evals.
`--run-id N`	None	Drill into one run; prints its step/eval counts.
`--phase`	None	Filter runs by phase (`sft`/`dpo`/`orpo`/`cpt`).
`--since`	None	Time window (`24h`, `7d`, `30m`, `10s`).
`--limit N`	20	Cap the number of runs returned.

dlm metrics watch <path> polls the DB and tails new step/eval rows as they arrive. See the metrics cookbook for the full flow + optional TensorBoard / W&B sinks (uv sync --extra observability).

`dlm preference`

Mine, stage, apply, revert, and inspect auto-mined preference sections (Sprint 42).

dlm preference mine <path> [--samples N] [--judge J] [--threshold F]
                          [--max-pairs N] [--temp F] [--top-p F]
                          [--backend {auto,pytorch,mlx}] [--adapter NAME]
                          [--apply]
dlm preference apply <path>
dlm preference revert <path>
dlm preference list <path>

Option	Default	Notes
`--samples N`	`4`	Candidate responses to sample per instruction prompt. Minimum `2`.
`--judge J`	`sway`	Judge selector: `sway`, `hf:<model>`, or `cli:<cmd>`.
`--threshold F`	judge default	Minimum chosen-vs-rejected score margin. Defaults to the selected judge's native threshold (`0.1` for sway, `1.0` for HF reward models).
`--max-pairs N`	unlimited	Cap the number of mined pairs kept from one run.
`--temp F`	`0.7`	Sampling temperature for candidate generation.
`--top-p F`	None	Optional top-p cutoff for candidate generation.
`--backend {auto,pytorch,mlx}`	`auto`	Generation backend. Follows the same selection contract as `dlm prompt`.
`--adapter NAME`	None	Required on multi-adapter documents so mining knows which adapter to sample. `--judge sway` is currently refused there; use `hf:` or `cli:` judges instead.
`--apply`	false	Write mined sections directly to the `.dlm`. Without it, `mine` stages the plan under the store root for `dlm preference apply`.

dlm preference mine requires a prior training run because the mined sections carry mined_run_id provenance. By default it stages the auto-mined ::preference:: sections under the store and prints the plan; dlm preference apply writes the staged plan into the .dlm, dlm preference revert strips every auto_mined: true preference section, and dlm preference list shows both applied and staged sections.

`dlm synth`

Synthesize instruction or preference training data (Sprint 43).

dlm synth instructions <path> [--teacher T] [--per-section N]
                             [--strategy {extraction,expansion,both}]
                             [--filter {sway,none,dedup-only}]
                             [--threshold F] [--max-pairs N]
                             [--max-new-tokens N] [--temp F] [--top-p F]
                             [--seed N] [--apply | --dry-run]
dlm synth preferences <path> [--samples N] [--judge J] [--threshold F]
                             [--max-pairs N] [--temp F] [--top-p F]
                             [--backend {auto,pytorch,mlx}] [--adapter NAME]
                             [--apply]
dlm synth revert <path>
dlm synth list <path>

Option	Default	Notes
`--teacher T`	`self`	Teacher selector: `self`, `hf:<model>`, `openai:<model>`, `anthropic:<model>`, or `vllm-server:<url>`.
`--per-section N`	`3`	Accepted instruction pairs to request per prose section before filtering.
`--strategy {extraction,expansion,both}`	`extraction`	`extraction` asks for questions answered directly by the prose, `expansion` extrapolates beyond it, and `both` splits the per-section budget across both prompts.
`--filter {sway,none,dedup-only}`	`sway`	Filter pipeline after generation. `sway` reuses Sprint 42's judge, `dedup-only` keeps near-duplicate suppression but skips judging, `none` accepts every deduped pair.
`--threshold F`	judge default	Minimum sway-judge margin. Only valid with `--filter sway`.
`--max-pairs N`	unlimited	Cap the number of accepted synth pairs from one invocation.
`--max-new-tokens N`	`512`	Teacher-side completion cap per prompt.
`--temp F`	`0.0`	Teacher sampling temperature.
`--top-p F`	None	Optional top-p cutoff for teacher sampling.
`--seed N`	None	Optional teacher sampling seed.
`--apply`	false	Write accepted auto-synth `::instruction::` sections directly to the `.dlm`.
`--dry-run`	false	Preview the synth plan without staging or writing anything. Default behavior stages the accepted plan under the store for inspection via `dlm synth list`.

dlm synth instructions prints the raw synth plan, then the filter summary (generated, dedup, judge passed, threshold/accepted). Without --apply or --dry-run, the accepted auto-synth ::instruction:: sections are staged under the store root so dlm synth list can show them before a later rerun. dlm synth revert strips every auto_synth: true instruction section from the document.

dlm synth preferences is an alias over dlm preference mine for the same Sprint 42 preference-mining loop. Use it when you want the umbrella synth surface but the output should be ::preference:: sections instead of ::instruction:: sections.

`dlm templates`

Browse the starter template gallery (Sprint 27).

dlm templates list [--json] [--refresh] [--accept-unsigned]

Option	Default	Notes
`--json`	false	Emit the full `TemplateMeta` for each entry as JSON.
`--refresh`	false	Refresh from the upstream gallery. Currently a no-op — upstream repo and signing key are pending (Sprint 27 deferred polish); the command warns and falls back to the bundled gallery.
`--accept-unsigned`	false	Reserved. Will bypass signed-tag verification once the live fetcher is wired.

Pair with dlm init --template <name> to create a new .dlm:

dlm init mydoc.dlm --template coding-tutor

See the template-gallery cookbook for the full walkthrough and the TemplateMeta schema.

`dlm export`

Produce GGUF files + runtime-target metadata.

dlm export <path> [--target NAME] [--quant Q] [--merged [--dequantize]]
                  [--name N] [--no-template] [--skip-ollama]
                  [--no-smoke] [--no-imatrix] [--verbose]
                  [--draft TAG | --no-draft]
                  [--adapter NAME | --adapter-mix SPEC]

Option	Default	Notes
`--target NAME`	`ollama`	Export destination. Sprint 41 currently supports `ollama`, `llama-server`, `vllm`, and `mlx-serve`. The `llama-server` path writes launch artifacts against the existing GGUF export and uses the shared OpenAI-compatible HTTP smoke harness. The `vllm` path writes `vllm_launch.sh` + `vllm_config.json` against the local adapter layout and ignores GGUF-only flags. On Apple Silicon, the generated `vllm` launch path forces the documented low-risk `vllm-metal` settings (`VLLM_METAL_USE_PAGED_ATTENTION=0`, `VLLM_METAL_MEMORY_FRACTION=auto`) and caps `--max-model-len` to the document's `training.sequence_len`. The `mlx-serve` path is Apple Silicon only, writes `mlx_serve_launch.sh` plus a staged MLX adapter directory, and currently supports text bases only.
`--quant Q`	frontmatter.export.default_quant	`Q4_K_M` / `Q5_K_M` / `Q6_K` / `Q8_0` / `F16`.
`--merged`	false	Merge LoRA into base before quantizing.
`--dequantize`	false	Required with `--merged` on a QLoRA adapter (pitfall #3).
`--name N`	derived	Ollama model name.
`--no-template`	false	Skip writing `TEMPLATE` into the Modelfile (power users only — Ollama will fuzzy-match, which Sprint 12 deliberately works around).
`--skip-ollama`	false	Emit GGUFs but don't register.
`--no-smoke`	false	Register but skip the smoke prompt.
`--no-imatrix`	false	Opt out of imatrix-calibrated quantization.
`--verbose`	false	Surface preflight + conversion diagnostics.
`--draft TAG`	auto	Override the speculative-decoding draft model.
`--no-draft`	false	Disable speculative decoding. Mutex with `--draft`.
`--adapter NAME`	None	Export a single named adapter from `training.adapters`. Rejected on single-adapter documents. Mutex with `--adapter-mix`.
`--adapter-mix SPEC`	None	Weighted composition like `knowledge:1.0,tone:0.5`. Produces one Ollama model by merging the named adapters at export time. LoRA-only; QLoRA sources require `--dequantize --merged`. Mutex with `--adapter`.
`--adapter-mix-method`	`linear`	PEFT merge strategy: `linear` (default; fast weighted sum) or `svd` (higher fidelity, heavier compute). Only meaningful with `--adapter-mix`.

`dlm pack`

Produce a portable .dlm.pack bundle.

dlm pack <path> [--out PATH] [--include-exports] [--include-base]
                [--include-logs] [--i-am-the-licensee URL]

Option	Default	Notes
`--out PATH`	`<name>.dlm.pack`	Pack output.
`--include-exports`	false	Bundle all GGUF exports.
`--include-base`	false	Bundle the base model weights. Requires license acknowledgement for gated bases.
`--include-logs`	false	Bundle per-run JSONL logs.
`--i-am-the-licensee URL`	none	URL acknowledging separate base-license acceptance.

`dlm unpack`

Install a .dlm.pack into the local store.

dlm unpack <pack> [--force] [--out DIR]

Option	Default	Notes
`--force`	false	Overwrite an existing store with the same `dlm_id`.
`--out DIR`	pack parent	Where to place the restored `.dlm`.

`dlm verify`

Verify a .dlm.pack provenance chain before trusting or installing it.

dlm verify <pack> [--trust-on-first-use]

Option	Default	Notes
`--trust-on-first-use`	false	Record an unknown signer's public key into `~/.dlm/trusted-keys/` on first verify. Without it, unknown signers are refused with exit code 2.

Exit codes: 0 verified, 1 broken chain or missing provenance, 2 untrusted signer, 3 signature rejected.

`dlm push`

Upload a .dlm (auto-packs) or .dlm.pack to a sharing destination (Sprint 28).

dlm push <path> --to <destination> [--sign] [pack flags]

Option	Default	Notes
`--to <destination>`	required	`hf:<org>/<repo>`, `https://...` URL endpoint, or a local path.
`--sign`	false	Sign the pack with `minisign` before upload (requires `minisign` on PATH + key at `~/.dlm/minisign.key`).
`--include-exports`	false	Forwarded to `dlm pack` when auto-packing a `.dlm`.
`--include-base`	false	Same.
`--include-logs`	false	Same.
`--i-am-the-licensee URL`	none	Required with `--include-base` on a non-redistributable base.

Destinations:

hf:<org>/<repo> — HuggingFace Hub. Uses $HF_TOKEN if set. Autogenerates a README.md with library_name: dlm tag. Creates the repo if missing (your personal namespace needs no approval).
https://… — any HTTPS endpoint that accepts a POST with an application/octet-stream body. Sets Authorization: from $DLM_SHARE_AUTH when present (e.g. Bearer <token>).
<local/path> — copy the pack to a filesystem path.

`dlm pull`

Download + verify + unpack a .dlm.pack from a remote source.

dlm pull <source> [--out DIR] [--force]

Option	Default	Notes
`<source>`	required	`hf:<org>/<repo>`, `https://…`, `peer://host:port/<id>?token=…`, or a local path.
`--out DIR`	CWD	Directory for the restored `.dlm`.
`--force`	false	Overwrite an existing store with the same `dlm_id`.

Pulls always verify sha256 checksums during unpack. If a .minisig sidecar is served alongside the pack, dlm pull tries every key in ~/.dlm/trusted-keys/*.pub — match → verified, no match → unverified warning (still installs, checksums are fine). No sidecar → unsigned (still installs).

`dlm serve`

Serve a .dlm's pack over LAN for peers to pull.

dlm serve <path> [--port N] [--public --i-know-this-is-public]
                 [--max-concurrency N] [--rate-limit N]
                 [--token-ttl-minutes N]

Option	Default	Notes
`--port N`	7337	Bind port.
`--public`	false	Bind `0.0.0.0` only when paired with `--i-know-this-is-public`. Without the confirmation flag, `--public` logs a refusal and binds `127.0.0.1`.
`--i-know-this-is-public`	false	Acknowledges the public bind. Meaningless without `--public`.
`--max-concurrency N`	4	Max concurrent connections per token. Excess returns HTTP 429.
`--rate-limit N`	30	Max requests per minute per token.
`--token-ttl-minutes N`	15	Issued token lifetime. Ctrl-C invalidates every outstanding token instantly — the session secret lives only in the serving process.

On start, prints the peer:// URL (with embedded token) that the other side pastes into dlm pull. Ctrl-C cleanly stops the server and deletes the temp pack.

`dlm doctor`

Inspect hardware + print the resolved training plan.

dlm doctor [--json]

No-network. Probes torch + psutil only; refuses to go online.

`dlm show`

Show training history, exports, and adapter state for a document.

dlm show <path> [--json]

Pretty-prints manifest + lock state. --json emits machine-readable output.

`dlm migrate`

Migrate a .dlm frontmatter to the current schema version.

dlm migrate <path> [--dry-run] [--no-backup]

Option	Default	Notes
`--dry-run`	false	Print the migrated frontmatter without writing.
`--no-backup`	false	Skip the `.dlm.bak` backup.

`dlm cache`

Inspect and manage the per-store tokenized-section cache (Sprint 31). The cache speeds up re-training on directive-sourced codebases by keying tokenized output on (section_id, tokenizer_sha, sequence_len).

dlm cache show <path> [--json]
dlm cache prune <path> [--older-than DURATION]
dlm cache clear <path> [--force]

Subcommand	Notes
`show`	Print entry count, size on disk, last-run hit rate. `--json` for machine-readable output.
`prune`	Delete entries not accessed within `--older-than` (e.g. `30d`, `12h`, `45m`). Default `90d`.
`clear`	Wipe the entire cache. Prompts for confirmation unless `--force` is passed.

See docs/cookbook/directive-cache.md for tuning, invalidation triggers, and maintenance patterns.

`dlm harvest`

Pull failing-probe results from a sway-style eval report back into the document as !probe-tagged ::instruction:: sections for the next retrain. See docs/cookbook/probe-driven-training.md.

dlm harvest <path> --sway-json <report> [--apply] [--dry-run]
                   [--tag NAME] [--min-confidence F]
                   [--strict | --lax]
dlm harvest <path> --revert

Option	Default	Notes
`--sway-json PATH`	required	Path to the sway probe report JSON.
`--apply`	false	Write changes to disk. Without it, dry-run.
`--dry-run`	true	Print the diff; no writes.
`--revert`	—	Strip all `auto_harvest=True` sections; mutually exclusive with `--sway-json`.
`--tag NAME`	`auto-harvest`	Provenance tag written into `harvest_source`.
`--min-confidence F`	`0.0`	Skip candidates below this confidence.
`--strict` / `--lax`	lax	Strict: fail if any failing probe lacks a reference. Lax: skip + log.

Exit codes: 0 success, 1 validation error (malformed JSON, strict miss, mutual-exclusion violation), 2 no candidates to harvest.

`dlm train --listen-rpc`

During --watch, open a JSON-RPC endpoint that accepts inject_probe pushes from external eval harnesses. Requires DLM_PROBE_TOKEN in the environment. See docs/cookbook/probe-driven-training.md for the wire protocol and security notes.

Option	Default	Notes
`--listen-rpc HOST:PORT`	off	Bind the probe-RPC endpoint. Requires `--watch` or `--max-cycles`.
`--max-cycles N`	`0`	Bounded-loop alternative to `--watch` for convergence runs (scaffolded — currently refuses execution without `--watch`).

Exit codes

Code	Meaning
0	Success.
1	Runtime failure (license refused, disk full, OOM, template drift, lock validation).
2	CLI misuse (mutex violation, missing argument).

Domain errors are formatted consistently via bare console.print calls in each subcommand (prefix convention: <subject>: <message>, e.g. lock: base_model_revision changed). Uncaught exceptions escape into dlm.cli.reporter which picks a matching prefix from the module the exception came from and renders a tier-3 generic message.

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Global options

Commands

`dlm init`

`dlm train`

`dlm prompt`

`dlm repl`

`dlm metrics`

`dlm preference`

`dlm synth`

`dlm templates`

`dlm export`

`dlm pack`

`dlm unpack`

`dlm verify`

`dlm push`

`dlm pull`

`dlm serve`

`dlm doctor`

`dlm show`

`dlm migrate`

`dlm cache`

`dlm harvest`

`dlm train --listen-rpc`

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CLI reference

Global options

Commands

dlm init

dlm train

dlm prompt

dlm repl

dlm metrics

dlm preference

dlm synth

dlm templates

dlm export

dlm pack

dlm unpack

dlm verify

dlm push

dlm pull

dlm serve

dlm doctor

dlm show

dlm migrate

dlm cache

dlm harvest

dlm train --listen-rpc

Exit codes

`dlm init`

`dlm train`

`dlm prompt`

`dlm repl`

`dlm metrics`

`dlm preference`

`dlm synth`

`dlm templates`

`dlm export`

`dlm pack`

`dlm unpack`

`dlm verify`

`dlm push`

`dlm pull`

`dlm serve`

`dlm doctor`

`dlm show`

`dlm migrate`

`dlm cache`

`dlm harvest`

`dlm train --listen-rpc`