67 lines
1.7 KiB
Python
67 lines
1.7 KiB
Python
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"""Pydantic schemas for the Reddit examples pipeline.
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`RawPost` — what PRAW gives us (title + body + metadata).
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`ExtractedExample`— what the LLM returns (all nullable; confidence-gated).
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`Summary` — per-country headline stats served from the API.
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"""
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from __future__ import annotations
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from datetime import date
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from decimal import Decimal
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from enum import StrEnum
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from pydantic import BaseModel, ConfigDict, Field
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class FiStatus(StrEnum):
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ACCUMULATING = "accumulating"
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COAST_FIRE = "coastFIRE"
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BARISTA_FIRE = "baristaFIRE"
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LEAN_FIRE = "leanFIRE"
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FIRE = "FIRE"
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FAT_FIRE = "fatFIRE"
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UNKNOWN = "unknown"
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class RawPost(BaseModel):
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"""A single Reddit post fetched from PRAW (no LLM processing yet)."""
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model_config = ConfigDict(frozen=True)
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reddit_id: str
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source_sub: str
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url: str
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title: str
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body: str
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created_at: date
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class ExtractedExample(BaseModel):
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"""LLM output — all extracted fields nullable except confidence + model."""
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country: str | None = None
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city: str | None = None
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portfolio_native: Decimal | None = None
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annual_exp_native: Decimal | None = None
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raw_currency: str | None = None
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age: int | None = Field(default=None, ge=0, le=120)
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family_size: int | None = Field(default=None, ge=1, le=20)
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fi_status: FiStatus | None = None
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is_retired: bool | None = None
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confidence: Decimal = Field(ge=Decimal("0"), le=Decimal("1"))
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llm_model: str
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class SummaryStats(BaseModel):
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median: Decimal | None
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p25: Decimal | None
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p75: Decimal | None
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class Summary(BaseModel):
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country: str
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count: int
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portfolio_gbp: SummaryStats
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annual_exp_gbp: SummaryStats
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sample_links: list[str]
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