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d02bacd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | from __future__ import annotations
from typing import Any, Dict, List, Literal, Optional
from pydantic import BaseModel, ConfigDict, Field
class RewardBreakdown(BaseModel):
model_config = ConfigDict(extra="forbid")
immediate: float
cumulative: float
terminal_grader: Optional[float] = None
class CoSAction(BaseModel):
model_config = ConfigDict(extra="ignore")
action_type: Literal["consult", "ask", "summarize", "submit", "noop"]
expert_id: Optional[Literal["analyst", "finance", "hr", "strategy"]] = None
sub_question_id: Optional[str] = None
notes: Optional[str] = None
class ExpertReport(BaseModel):
model_config = ConfigDict(extra="forbid")
expert_id: Literal["analyst", "finance", "hr", "strategy"]
title: str
summary: str
metrics: Dict[str, float | int | str] = Field(default_factory=dict)
bullet_points: List[str] = Field(default_factory=list)
issues: List[str] = Field(default_factory=list)
citations: List[str] = Field(default_factory=list)
memory_citations: List[str] = Field(default_factory=list)
memory_snippets: List[str] = Field(default_factory=list)
memo: Optional[str] = None
score: Optional[float] = None
class Brief(BaseModel):
model_config = ConfigDict(extra="forbid")
summary: str
metrics: Dict[str, float | int | str] = Field(default_factory=dict)
recommendations: List[str] = Field(default_factory=list)
hr_memo: str = ""
consulted_experts: List[str] = Field(default_factory=list)
class CoSObservation(BaseModel):
model_config = ConfigDict(extra="forbid")
done: bool
reward: float = 0.0
instruction: str
history: List[str] = Field(default_factory=list)
issues: List[str] = Field(default_factory=list)
data_quality_score: float = 0.0
task_name: str
task_difficulty: str
rag_enabled: bool = False
max_steps: int = 12
step_count: int = 0
available_experts: List[str] = Field(default_factory=lambda: ["analyst", "finance", "hr", "strategy"])
consulted_experts: List[str] = Field(default_factory=list)
expert_reports: Dict[str, ExpertReport] = Field(default_factory=dict)
current_brief: Optional[Brief] = None
reward_breakdown: Optional[RewardBreakdown] = None
terminal_grader_score: Optional[float] = None
class CoSState(BaseModel):
model_config = ConfigDict(extra="forbid")
episode_id: str
task_name: str
step_count: int = 0
done: bool = False
rag_enabled: bool = False
consulted_experts: List[str] = Field(default_factory=list)
expert_reports: Dict[str, ExpertReport] = Field(default_factory=dict)
current_brief: Optional[Brief] = None
cumulative_reward: float = 0.0
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