da3f5faa91
FastAPI + React + PostgreSQL salary benchmarking tool with AI research pipeline. - Seed data for 25+ New York roles (junior/mid/senior levels) - Single + bulk lookup with location alias mapping (NYC -> New York, etc.) - Research pipeline: Serper -> Firecrawl -> Cohere Rerank -> Claude analysis - Editable validation UI for AI-proposed benchmarks - CSV export, Montserrat font, black/white/#FFC407 design - Fully Dockerized (app + db + frontend) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
55 lines
1 KiB
Python
55 lines
1 KiB
Python
from pydantic import BaseModel
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class BenchmarkOut(BaseModel):
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role: str
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location: str
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level: str
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salary: int
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source: str
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validated: bool
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confidence_score: float | None = None
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model_config = {"from_attributes": True}
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class SingleLookupParams(BaseModel):
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title: str
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location: str
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class BulkLookupRequest(BaseModel):
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location: str
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titles: list[str]
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class BulkLookupResponse(BaseModel):
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found: dict[str, list[BenchmarkOut]]
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not_found: list[str]
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class ResearchRequest(BaseModel):
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title: str
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location: str
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class BulkResearchRequest(BaseModel):
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location: str
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titles: list[str]
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class ResearchStatusOut(BaseModel):
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session_id: str
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status: str
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proposed_benchmarks: dict | None = None
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claude_analysis: dict | None = None
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error_message: str | None = None
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class BenchmarkAdjustment(BaseModel):
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salary: int | None = None
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class ValidateRequest(BaseModel):
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approved: bool
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adjustments: dict[str, BenchmarkAdjustment] | None = None
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