allium
무료Give your AI agents something more useful than a prompt. Velocity through clarity.
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Implement query handlers that read from event-sourced read models
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
(ns my.service.core.queries
(:require [ai.obney.grain.event-store-v3.interface :as es]
[ai.obney.grain.query-processor.interface :refer [defquery]]
[my.service.interface.read-models :as rm]
[cognitect.anomalies :as anom]))
(defquery :namespace query-name
"Docstring describing what the query returns."
[{{:keys [entity-id filter-param]} :query
:keys [event-store other-dependency]}]
(let [entity (rm/get-entity event-store entity-id)]
(if entity
{:query/result {:entity entity}}
{::anom/category ::anom/not-found
::anom/message "Entity not found"})))
{:query/result {:entity data
:related-data more-data}}
{::anom/category ::anom/not-found
::anom/message "Human readable message"}
Load all data needed for a UI screen in one query:
(defquery :advisor meetings-screen
"Fat query for meetings screen - returns all data needed."
[{{:keys [student-id]} :query
:keys [event-store]}]
(let [;; Get primary entity
student (rm/get-student event-store student-id)
;; Get related data
meetings (rm/get-meetings-for-student event-store student-id)
;; Get metadata/options
meeting-types (rm/get-meeting-types event-store)]
(if student
{:query/result {:student student
:meetings meetings
:meeting-types meeting-types}}
{::anom/category ::anom/not-found
::anom/message "Student not found"})))
(defquery :crm list-contacts
"List contacts with optional filters and pagination."
[{{:keys [type-slug status limit offset]} :query
:keys [event-store]}]
(let [;; Get all matching contacts
all-contacts (cond->> (rm/get-contacts-all event-store)
type-slug (filter #(= type-slug (:type-slug %)))
status (filter #(= status (:status %))))
total (count all-contacts)
;; Apply pagination
paginated (cond->> all-contacts
offset (drop offset)
limit (take limit))]
{:query/result {:contacts (vec paginated)
:total total}}))
Pre-load related data to avoid N+1 queries:
(defquery :crm list-contacts-with-types
[{{:keys [type-slug]} :query
:keys [event-store]}]
(let [;; Pre-load all contact types (1 query instead of N)
types-by-id (rm/get-contact-types-by-id event-store)
;; Get contacts
contacts (rm/get-contacts-by-type event-store type-slug)
;; Enrich with type data
enriched (mapv #(assoc % :contact-type (get types-by-id (:type-id %)))
contacts)]
{:query/result {:contacts enriched}}))
(defquery :crm get-contact
"Get contact with attribution in single query."
[{{:keys [contact-id]} :query
:keys [event-store]}]
(let [contact (rm/get-contact event-store contact-id)]
(if contact
(let [;; Get related data
relationships (rm/get-relationships-for-contact event-store contact-id)
attribution (rm/get-attribution event-store contact-id)]
{:query/result {:contact (cond-> contact
attribution (assoc :attribution attribution)
(seq relationships) (assoc :relationships relationships))}})
{::anom/category ::anom/not-found
::anom/message "Contact not found"})))
{:query/result {...}} for success:total) for list queriescomponents/crm-service/src/ai/obney/workshop/crm_service/core/queries.clj - CRM queries with batch loading아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Give your AI agents something more useful than a prompt. Velocity through clarity.
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Extract an Allium specification from an existing codebase. Use when the user has existing code and wants to distil behaviour into a spec, reverse engineer a specification from implementation, generate a spec from code, turn implementation into a behavioural specification, or document what a codebase does in Allium terms.
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Run a structured discovery session to build an Allium specification through conversation. Use when the user wants to create a new spec from scratch, elicit or gather requirements, capture domain behaviour, specify a feature or system, define what a system should do, or is describing functionality and needs help shaping it into a specification.
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Implement command handlers that validate state and emit events using the Grain framework
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Create scheduled background jobs that run on cron schedules
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Build read models by reducing events into queryable state
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