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Data models for the Shopify Store Audit & Remediation Environment.
Defines the Action and Observation types that agents use to interact
with a simulated Shopify store, mirroring real Admin GraphQL API patterns.
"""
from typing import Any, Dict, List
from openenv.core.env_server.types import Action, Observation
from pydantic import Field
class ShopifyStoreAuditAction(Action):
"""Agent action that mirrors a Shopify Admin API operation.
Commands map to real Shopify GraphQL mutations/queries:
- query_products, query_product → products / product query
- query_collections, query_collection → collections query
- query_inventory → inventoryLevels query
- query_orders → orders query
- query_store_health → custom diagnostic summary
- update_product → productUpdate mutation
- update_variant → productVariantUpdate mutation
- update_product_seo → productUpdate (seo fields)
- update_image_alt_text → productImageUpdate mutation
- update_collection → collectionUpdate mutation
- add_product_to_collection → collectionAddProducts mutation
- remove_product_from_collection → collectionRemoveProducts mutation
- adjust_inventory → inventoryAdjustQuantities mutation
- update_metafield → metafieldsSet mutation
- publish_product → publishablePublish mutation
"""
command: str = Field(
...,
description="API command to execute, e.g. 'query_products', 'update_product'",
)
params: Dict[str, Any] = Field(
default_factory=dict,
description="Command parameters (varies by command)",
)
class ShopifyStoreAuditObservation(Observation):
"""Observation returned after each environment step.
Contains both human-readable feedback and structured data so that
LLM agents can reason about the store state and decide next actions.
"""
message: str = Field(default="", description="Human-readable result description")
data: Dict[str, Any] = Field(
default_factory=dict, description="Structured API response data"
)
issues_remaining: int = Field(default=0, description="Unfixed issues count")
issues_fixed: int = Field(default=0, description="Issues fixed so far")
total_issues: int = Field(default=0, description="Total issues in this task")
store_health_score: float = Field(
default=0.0, description="Store health 0.0-1.0"
)
available_commands: List[str] = Field(
default_factory=list, description="Commands the agent can use"
)
task_name: str = Field(default="", description="Current task identifier")
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