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생산성 및 협업 · SKILL.md

llm-integration

llm-integration

Routes Memori Python LLM registration, provider/framework recipes, and wrapper troubleshooting.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: llm-integration description: "Routes Memori Python LLM registration, provider/framework recipes, and wrapper troubleshooting." metadata: disco-role: operating disable-model-invocation: true license: NOASSERTION

LLM Integration

Use this sub-skill for Python-side LLM client registration, provider choice, framework adapters, and wrapper troubleshooting.

Use when

  • The request mentions llm.register(...), OpenAI, Anthropic, Gemini, xAI, LangChain, Agno, PydanticAI, OpenAI-compatible clients, or unsupported provider errors.
  • The user is choosing between direct clients and named framework arguments.
  • The task is about Python provider wiring, not cloud API keys or database setup.

Read first

  • references/registration-api.md for exact signatures and routing rules.
  • references/provider-and-framework-recipes.md for supported provider patterns.
  • references/troubleshooting.md for mixed-registration and provider errors.
  • scripts/inspect_llm_registration.py for a safe local inspection helper.

What this sub-skill owns

  • Unified Memori().llm.register(...) usage.
  • Direct client registration and named framework registration.
  • Deprecated accessor migration notes.
  • Provider wrapper troubleshooting and optional SDK presence checks.

What it does not own

  • Cloud API key and MCP setup: use cli-and-cloud.
  • BYODB storage or provisioning: use byodb-storage.
  • Recall/session/embeddings/native runtime: use memory-and-search.
  • TypeScript llm.register details: use typescript-sdk.

Safe first check

Run the bundled inspection helper before suggesting provider-specific code:

python scripts/inspect_llm_registration.py

That helper only reads installed package metadata and optional SDK presence; it never contacts a provider.

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