fleet-memory/hindsight-api/hindsight_api/engine/directives/models.py
Nicolò Boschi 9db64ecda3
feat: revisit mental models, directives and reflections (#179)
* chore: run benchmarks with reflect mode

* chore: run benchmarks with reflect mode

* fixes

* new mm

* bunch of fixes

* initial commit

* fixes

* fixes

* fixes

* fix: sometimes memories gets extracted in the wrong language
2026-01-22 17:13:16 +01:00

37 lines
1.5 KiB
Python

"""Pydantic models for directives."""
from datetime import datetime, timezone
from uuid import UUID
from pydantic import BaseModel, Field
class Directive(BaseModel):
"""A directive is a hard rule injected into prompts.
Directives are user-defined rules that guide agent behavior. Unlike mental models
which are automatically consolidated from memories, directives are explicit
instructions that are always included in relevant prompts.
Examples:
- "Always respond in formal English"
- "Never share personal data with third parties"
- "Prefer conservative investment recommendations"
"""
id: UUID = Field(description="Unique identifier")
bank_id: str = Field(description="Bank this directive belongs to")
name: str = Field(description="Human-readable name")
content: str = Field(description="The directive text to inject into prompts")
priority: int = Field(default=0, description="Higher priority directives are injected first")
is_active: bool = Field(default=True, description="Whether this directive is currently active")
tags: list[str] = Field(default_factory=list, description="Tags for filtering")
created_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc), description="When this directive was created"
)
updated_at: datetime = Field(
default_factory=lambda: datetime.now(timezone.utc), description="When this directive was last updated"
)
class Config:
from_attributes = True