9db64ecda3
* 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
53 lines
2.1 KiB
Python
53 lines
2.1 KiB
Python
"""
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Pydantic models for mental models.
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"""
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from datetime import datetime, timezone
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from enum import Enum
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from pydantic import BaseModel, Field
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class MentalModelSubtype(str, Enum):
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"""Subtype of mental model.
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Currently only DIRECTIVE is supported. Other types of consolidated knowledge
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are handled by:
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- Learnings: Automatic bottom-up consolidation from facts
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- Pinned Reflections: User-curated living documents
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"""
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DIRECTIVE = "directive" # User-defined hard rules, observations user-provided
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class MentalModel(BaseModel):
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"""
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A mental model representing synthesized understanding.
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Mental models are the agent's consolidated knowledge. Unlike raw facts,
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mental models provide:
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- A one-liner description for quick scanning/retrieval
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- A full summary for deep understanding
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- Links to related mental models
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"""
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id: str = Field(description="Unique identifier within the bank")
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bank_id: str = Field(description="Bank this mental model belongs to")
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subtype: MentalModelSubtype = Field(description="How this model was created")
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name: str = Field(description="Human-readable name")
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description: str = Field(description="One-liner for quick scanning and retrieval matching")
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summary: str | None = Field(default=None, description="Full synthesized understanding")
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# References
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entity_id: str | None = Field(default=None, description="Reference to entities table when type=entity")
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source_facts: list[str] = Field(default_factory=list, description="Fact IDs used to generate summary")
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links: list[str] = Field(default_factory=list, description="Related mental model IDs")
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# Tags for scoped visibility (similar to document tags)
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tags: list[str] = Field(default_factory=list, description="Tags for scoped visibility filtering")
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# Timestamps
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last_updated: datetime | None = Field(default=None, description="When summary was last regenerated")
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created_at: datetime = Field(
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default_factory=lambda: datetime.now(timezone.utc), description="When this model was created"
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)
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