---

name: core-runtime description: "Guides LazyLLM installation, optional extras, CLI commands, configuration, launcher, components, prompters, and base runtime diagnostics." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

LazyLLM Core Runtime

Use this sub-skill for base LazyLLM setup and runtime questions: package installation, optional extras, CLI command routing, lazyllm.config, namespace behavior, launchers, components/registries, prompters, dependency diagnostics, and safe source-checkout smoke tests.

Start here when

• The user asks to install LazyLLM or choose between base, rag, standard, full, dev, or backend-specific extras.
• An import error names missing optional packages or lazyllm install <extra>.
• The task mentions lazyllm CLI commands: install, deploy, run, skills, review, or review-local.
• The task concerns lazyllm.config, environment-backed options, lazyllm.namespace, ComponentBase, component registration, prompt templates, or launcher/service scaffolding.
• You need a no-network check before moving to RAG, agents, models, writer, or flows.

Files to read

• config-cli-components.md for CLI command families, config behavior, prompters, components, and launcher notes.
• troubleshooting.md for core install/import/CLI/config failure modes.
• Root Installation and optional extras for extra selection across workflows.
• scripts/config_cli_smoke.py for a safe local smoke check of config, prompt, component registration, and CLI command table assumptions.

Core workflow checklist

1. Identify the selected workflow. If the task is only config/CLI/import, keep it here. If it needs a domain feature, route onward after checking dependencies:
   • RAG/document import → rag-document-processing
   • Agents/tools/MCP → agents-tools
   • Model serving/provider/fine-tuning → model-deployment
   • Flow composition → flow-orchestration
   • Writer/review → writer-review
2. Check Python and install state. LazyLLM 0.7.5 expects Python >=3.10,<3.14.
3. Run a safe import/CLI diagnostic when environment state is unclear:

   python ../../scripts/check_lazyllm_env.py --check-cli
   python scripts/config_cli_smoke.py
   

4. Install the smallest extra named by the failure. For example, RAG import failures usually require lazyllm install rag, not full.
5. Avoid side effects. Core runtime checks should not download models, call providers, start external services, or post reviews.

CLI command families

The dispatcher recognizes these top-level commands:

lazyllm install <extra1> <extra2> <pkg1> ...
lazyllm deploy modelname
lazyllm deploy mcp_server <command> [args ...] [options]
lazyllm run graph.json
lazyllm run chatbot
lazyllm run rag
lazyllm skills init/list/info/delete/add/import/install
lazyllm review ...
lazyllm review-local ...

A bare lazyllm --help can print usage and exit non-zero. Use concrete subcommands such as lazyllm skills list for smoke checks.

Config and namespace facts

• lazyllm.config supports key lookup and mutation with option validation, aliases, default fallback for empty strings, and post-action hooks.
• Environment-backed values can be refreshed, and namespace contexts can redirect environment prefixes, for example lazyllm.namespace("my").
• Tests verify LAZYLLM_GPU_TYPE, LAZYLLM_DISPLAY, alias normalization, strict options, and namespace isolation behavior.

Component and prompt facts

• lazyllm.components.register can create groups and register callables/classes under lowercase and capitalization-preserving names.
• fc_register belongs to agents/tools, but simple tool registration metadata is often debugged from core runtime imports.
• Prompter, AlpacaPrompter, and ChatPrompter generate string prompts and OpenAI-style messages payloads with history support.

Review before handing off

Before routing to a heavier sub-skill, leave the user with:

• active Python interpreter and LazyLLM version,
• selected optional extra or reason none is needed,
• safe command to reproduce the import/CLI/config state,
• explicit note if a provider, GPU, model download, external DB, parser service, MCP process, or remote review action is required.