智能体工作流

configuring-lookup-caches

celigo/ai

Configure Celigo lookup cache resources -- in-memory key-value stores used for fast lookups, deduplication, cross-reference resolution, and state tracking during flow execution. Use when creating caches, loading data, referencing caches in import lookups, or managing cache lifecycle.

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安装命令

npx skills add https://github.com/celigo/ai --skill configuring-lookup-caches

SKILL.md

Configuring Lookup Caches

A lookup cache is an in-memory key-value store managed by Celigo for fast data retrieval during integration processing. Unlike export-based lookups that query external systems per-record, lookup caches provide sub-millisecond access to pre-loaded reference data without consuming API calls.

Lookup caches handle three concerns:

  • Cache metadata -- name, description, and whether data is included in templates/cloning
  • Data management -- loading, retrieving, updating, and purging key-value entries via dedicated data endpoints
  • Size governance -- each cache has a 50 MB limit; the per-environment aggregate limit across all caches is 1 GB

Lookup caches are consumed by import and export mappings through a lookup entry. The entry references a cache by _lookupCacheId and optionally extracts a specific field from the cached object via the extract JSON path, and a mapping row uses it by name. On an HTTP import the entry goes in http.lookups; on an export, in its Transformation 2.0 rules. This is configured on the import/export resource, not on the cache itself. A request template can also read a cache directly with {{getLookupCacheData}} (Reading a Cache from a Template).

Used across flows, APIs, and tools.

"Lookup" -- Which One Is Meant?

"Lookup" is overloaded in Celigo, and a lookup cache is only one thing the word can mean. When a request just says "the lookup," confirm which one before acting -- they live in different places and are configured differently. A single entry in lookups[] resolves its value one of three ways: