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| """ | |
| Pydantic models for OpenEnv compliance. | |
| """ | |
| from typing import Any, Callable, Dict, List, Optional | |
| from pydantic import BaseModel, Field | |
| class Customer(BaseModel): | |
| """Customer entity.""" | |
| customer_id: str | |
| name: str | |
| email: str | |
| tier: str # Bronze, Silver, Gold | |
| phone: str | |
| created_at: str | |
| class Order(BaseModel): | |
| """Order entity.""" | |
| order_id: str | |
| customer_id: str | |
| product: str | |
| amount: float | |
| status: str # Pending, Completed, Cancelled | |
| created_at: str | |
| class SupportTicket(BaseModel): | |
| """Support ticket entity.""" | |
| ticket_id: str | |
| customer_id: str | |
| subject: str | |
| priority: str # Low, Medium, High | |
| status: str # Open, Closed | |
| created_at: str | |
| class SearchCustomersAction(BaseModel): | |
| """Action to search customers.""" | |
| tool: str = Field(default="search_customers", frozen=True) | |
| arguments: Dict[str, Any] = Field( | |
| description="Filter arguments: customer_id, name, email, tier, phone" | |
| ) | |
| class SearchOrdersAction(BaseModel): | |
| """Action to search orders.""" | |
| tool: str = Field(default="search_orders", frozen=True) | |
| arguments: Dict[str, Any] = Field( | |
| description="Filter arguments: order_id, customer_id, product, status" | |
| ) | |
| class SearchTicketsAction(BaseModel): | |
| """Action to search support tickets.""" | |
| tool: str = Field(default="search_tickets", frozen=True) | |
| arguments: Dict[str, Any] = Field( | |
| description="Filter arguments: ticket_id, customer_id, priority, status" | |
| ) | |
| class SubmitAnswerAction(BaseModel): | |
| """Action to submit final answer.""" | |
| tool: str = Field(default="submit_answer", frozen=True) | |
| arguments: Dict[str, Any] = Field( | |
| description="Final answer: customer_ids list" | |
| ) | |
| class Action(BaseModel): | |
| """Union of all possible actions.""" | |
| tool: str | |
| arguments: Dict[str, Any] | |
| model_config = {"extra": "forbid"} | |
| class Observation(BaseModel): | |
| """Observation returned by environment.""" | |
| task_id: str | |
| task_description: str | |
| step_count: int | |
| max_steps: int | |
| available_tools: List[str] | |
| last_action_result: Optional[Dict[str, Any]] = None | |
| tables_summary: Dict[str, Any] | |
| done: bool | |
| message: str | |
| memory_cache: Optional[Dict[str, List[Dict[str, Any]]]] = Field(default_factory=dict, description="Cached entities from previous queries") | |
| step_summaries: List[str] = Field(default_factory=list, description="Compact summaries of executed steps") | |
| class Reward(BaseModel): | |
| """Reward signal.""" | |
| value: float = Field(ge=-10.0, le=10.0) | |
| components: Dict[str, float] = Field(default_factory=dict) | |
| message: str | |
| class State(BaseModel): | |
| """Environment state.""" | |
| current_task_id: str | |
| step_count: int | |
| max_steps: int | |
| history: List[Dict[str, Any]] = Field(default_factory=list) | |
| done: bool | |
| final_answer: Optional[Dict[str, Any]] = None | |
| retrieved_entities: Dict[str, List[Dict[str, Any]]] = Field(default_factory=dict, description="Cache of retrieved entities") | |
| step_summaries: List[str] = Field(default_factory=list, description="Summaries of each step for memory reuse") | |
| class Info(BaseModel): | |
| """Additional info.""" | |
| task_id: str | |
| episode_reward: float | |
| intermediate_results: Dict[str, Any] = Field(default_factory=dict) | |
| class Task(BaseModel): | |
| """Task definition.""" | |
| task_id: str | |
| difficulty: str # easy, medium, hard | |
| description: str | |
| ground_truth: Dict[str, Any] | |
| max_steps: int | |
| action_schema: Dict[str, Any] | |
| grader: Optional[Callable[[Dict[str, Any]], float]] = Field(default=None, exclude=True, description="Grader function for this task") | |
| model_config = {"arbitrary_types_allowed": True} | |