llm

name	llm
description	Configure the optional llmClient block in toolkit.conf so toolkit agent commands (discovery, pipeline-build, fix-sql, codegen ask) can call an LLM — Amazon Bedrock, OpenAI, or Anthropic. Use when agent commands fail for lack of an LLM, when switching providers or models, or when onboarding to the toolkit agent workflows.

Configure the toolkit LLM client (optional)

toolkit agent * commands (and toolkit codegen ask/prompt) call an LLM, configured by a top-level llmClient block in toolkit.conf — a peer of connections and ds.

phData consultants work without any block: the toolkit falls back to Amazon Bedrock and the phData auth flow brokers access automatically. Even then, recommend adding the Bedrock example block: the fallback runs on short AWS SDK default timeouts, and long agent calls (pipeline-build judge loops) can exceed them — the examples set requestTimeout/socketTimeout to 1000s.

Step 0 — current state

toolkit-check --level project finds the toolkit.conf to edit; toolkit-setup detect reports llm_client=<type|none>. none + phData auth = Bedrock fallback — functional, but add the Bedrock block anyway for the 1000s timeouts.

Step 1 — pick a provider

Supported type values (case-insensitive): AmazonBedrock, openai, anthropic.

Provider	When	Credentials
AmazonBedrock	phData auth flow (no block needed at all), or own AWS account with Bedrock access	AWS default chain (env/SSO/profile)
anthropic	Direct Anthropic API key	ANTHROPIC_API_KEY
openai	OpenAI (or compatible endpoint via url)	OPENAI_API_KEY

Step 2 — write the block

Read the matching example, examples/<provider>.conf, in this skill's directory and merge the llmClient block into the project's toolkit.conf at the top level.

Secrets rule (same as connections): API keys go in as ${ENV_VAR} references, never literal values. For openai/anthropic the apiKey line can also be omitted entirely — the client falls back to reading the standard env var directly.

Timeouts: default both requestTimeout and socketTimeout to 1000s (Bedrock and OpenAI; the Anthropic client doesn't expose timeout settings). Unset values fall back to short SDK/HTTP defaults that long agent runs routinely exceed.

Step 3 — verify

The cheapest end-to-end probe is one prompt round-trip:

toolkit codegen ask "Reply with the single word: ok"

A model response means the client works. Triage:

Symptom	Fix
Could not resolve substitution	export the API-key env var
401/403 from provider	wrong/expired key, or AWS credentials not active (aws sts get-caller-identity)
authorization error from toolkit itself	agent features are license-gated — toolkit auth / license tier, not LLM config
unknown model id	check the provider's current model list; update model