ai-utilities

Imported from gabrielmoreira/agent-skills-mirror (mirrors/repos/n8n-io@n8n/packages/@n8n/ai-utilities/AGENTS.md). Install upstream with npx skills add gabrielmoreira/agent-skills-mirror --skill ai-utilities. Copyright stays with the author.

AGENTS.md

@n8n/ai-utilities owns shared helpers that are specific to AI nodes, LLMs, model configuration, and model output.

Public subpaths

• agent-config
• fromai-helpers
• generic-text-editor
• http-proxy-agent
• json-schema
• llm-output
• model-discovery
• node-catalog
• text-editor
• tokenizer
• web-search

Package boundary

• Put shared AI- or LLM-specific helpers in @n8n/ai-utilities.
• Put generic helpers and generic secret or PII redaction in @n8n/utils.
• Put workflow graph and traversal utilities in n8n-workflow.
• Keep domain logic in the package that owns that domain.

Bounding AI response sizes

Every outbound AI client must bound the size of the response it buffers. A hostile or misbehaving endpoint can stream an unbounded or highly compressed body and exhaust the heap. The http-proxy-agent subpath applies the cap; it counts decoded bytes, so a compressed body cannot expand past the limit. The default is 100 MB, set through N8N_AI_MAX_RESPONSE_SIZE (0 disables it).

The general rule: never hand the SDK the raw transport. Give it the wrapper that matches how the SDK takes one.

• The SDK accepts a fetch: pass aiClientFetch.
• The SDK builds requests itself (Ollama, Mistral): call proxyFetch.
• The SDK returns a Node stream (AWS Bedrock): build the client with createBedrockRuntimeClient, which installs a response-limited request handler for the stream.

Get egressFilter for proxyFetch from this.helpers.getSecureEgressFilter().

Some SDK wrappers expose no such seam (Cohere, Google Gemini, Google Vertex, HuggingFace). Do not hand-roll a limiter for these. Flag the gap for a maintainer instead.