bolade
357 lines
11 KiB
Python
357 lines
11 KiB
Python
from enum import Enum
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from typing import List, Optional
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from pydantic import BaseModel, Field, field_validator
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class InvestmentStage(str, Enum):
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SEED = "SEED"
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SERIES_A = "SERIES_A"
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SERIES_B = "SERIES_B"
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SERIES_C = "SERIES_C"
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GROWTH = "GROWTH"
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LATE_STAGE = "LATE_STAGE"
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class SectorSchema(BaseModel):
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"""
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Expert parser: Only extract sector information if clearly identifiable.
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Leave name empty if uncertain about the sector classification.
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"""
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id: Optional[int] = Field(
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default=None,
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ge=0,
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description="Sector ID, must be 0 or greater. Use 0 if uncertain.",
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)
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name: Optional[str] = Field(
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default=None,
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description="Sector name. Leave empty string if not clearly identifiable from the data.",
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)
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@field_validator("name", mode="before")
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@classmethod
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def empty_string_to_none(cls, v):
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"""Convert empty strings to None"""
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if v == "" or (isinstance(v, str) and v.strip() == ""):
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return None
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return v
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@field_validator("id", mode="before")
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@classmethod
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def zero_to_none(cls, v):
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"""Convert 0 to None for optional id field"""
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if v == 0:
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return None
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return v
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class Config:
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from_attributes = True
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class InvestorMemberSchema(BaseModel):
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"""
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Expert parser: Only extract team member information if clearly identifiable.
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Leave fields empty if uncertain about the member details.
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"""
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id: Optional[int] = Field(
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default=None,
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ge=0,
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description="Member ID, must be 0 or greater. Use 0 if uncertain.",
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)
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name: Optional[str] = Field(
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default=None,
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description="Team member name. Leave empty string if not clearly identifiable.",
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)
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role: Optional[str] = Field(
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default=None,
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description="Team member role/title. Leave empty string if not clearly identifiable.",
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)
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email: Optional[str] = Field(
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default=None,
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description="Team member email. Leave empty string if not clearly identifiable or not provided.",
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)
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investor_id: Optional[int] = Field(
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default=None,
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ge=0,
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description="Investor ID, must be 0 or greater. Use 0 if uncertain.",
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)
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@field_validator("name", "role", "email", mode="before")
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@classmethod
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def empty_string_to_none(cls, v):
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"""Convert empty strings to None"""
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if v == "" or (isinstance(v, str) and v.strip() == ""):
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return None
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return v
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@field_validator("id", "investor_id", mode="before")
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@classmethod
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def zero_to_none(cls, v):
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"""Convert 0 to None for optional integer fields"""
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if v == 0:
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return None
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return v
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class Config:
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from_attributes = True
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class CompanyMemberSchema(BaseModel):
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"""
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Expert parser: Only extract company member information if clearly identifiable.
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Leave fields empty if uncertain about the member details.
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"""
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id: Optional[int] = Field(
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default=None,
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ge=0,
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description="Member ID, must be 0 or greater. Use 0 if uncertain.",
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)
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name: Optional[str] = Field(
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default=None,
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description="Company member name. Leave empty if not clearly identifiable.",
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)
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linkedin: Optional[str] = Field(
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default=None,
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description="LinkedIn profile URL. Leave empty if not provided or uncertain.",
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)
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role: Optional[str] = Field(
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default=None,
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description="Company member role/title. Leave empty if not clearly identifiable.",
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)
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company_id: Optional[int] = Field(
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default=None,
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ge=0,
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description="Company ID, must be 0 or greater. Use 0 if uncertain.",
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)
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@field_validator("name", "linkedin", "role", mode="before")
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@classmethod
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def empty_string_to_none(cls, v):
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"""Convert empty strings to None"""
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if v == "" or (isinstance(v, str) and v.strip() == ""):
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return None
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return v
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@field_validator("id", "company_id", mode="before")
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@classmethod
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def zero_to_none(cls, v):
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"""Convert 0 to None for optional integer fields"""
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if v == 0:
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return None
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return v
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class Config:
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from_attributes = True
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class CompanySchema(BaseModel):
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"""
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Expert parser: Only extract company information if clearly identifiable.
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Leave optional fields empty if uncertain. Integer values must be 0 or greater.
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"""
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id: Optional[int] = Field(
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default=None,
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ge=0,
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description="Company ID, must be 0 or greater. Use 0 if uncertain.",
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)
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name: Optional[str] = Field(
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default=None,
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description="Company name. Leave empty string if not clearly identifiable.",
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)
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industry: Optional[str] = Field(
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default=None,
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description="Company industry/sector. Leave empty string if not clearly identifiable.",
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)
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location: Optional[str] = Field(
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default=None,
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description="Company location/address. Leave empty string if not clearly identifiable.",
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)
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description: Optional[str] = Field(
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default=None,
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description="Company description. Leave empty if not clearly available or uncertain.",
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)
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founded_year: Optional[int] = Field(
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default=None,
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ge=0,
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description="Year company was founded, must be 0 or greater. Leave None if not clearly identifiable or uncertain.",
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)
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website: Optional[str] = Field(
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default=None,
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description="Company website URL. Leave empty if not provided or uncertain.",
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)
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@field_validator(
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"name", "industry", "location", "description", "website", mode="before"
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)
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@classmethod
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def empty_string_to_none(cls, v):
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"""Convert empty strings to None"""
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if v == "" or (isinstance(v, str) and v.strip() == ""):
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return None
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return v
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@field_validator("id", "founded_year", mode="before")
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@classmethod
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def zero_to_none(cls, v):
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"""Convert 0 to None for founded_year"""
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if v == 0:
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return None
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return v
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@field_validator("founded_year", mode="before")
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@classmethod
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def validate_founded_year(cls, v):
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"""Expert parser: Only accept clearly identifiable founding years"""
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if v is None or v == "Not Available" or v == "" or v == "Unknown":
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return None
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if isinstance(v, str):
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try:
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year = int(v)
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return year if year >= 0 else None
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except ValueError:
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return None
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return v if isinstance(v, int) and v >= 0 else None
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class Config:
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from_attributes = True
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class InvestorSchema(BaseModel):
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"""
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Expert parser: Only extract investor information if clearly identifiable.
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Leave optional fields empty if uncertain. All numeric values must be 0 or greater.
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"""
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id: Optional[int] = Field(
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default=None,
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ge=0,
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description="Investor ID, must be 0 or greater. Use 0 if uncertain.",
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)
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name: Optional[str] = Field(
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default=None,
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description="Investor name. Do not return any special characters, Just the name as a string.",
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)
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description: Optional[str] = Field(
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default=None,
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description="Investor description. Leave empty if not clearly available or uncertain.",
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)
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aum: Optional[int] = Field(
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default=None,
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ge=0,
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description="Assets Under Management in USD, must be 0 or greater. Use 0 if not clearly identifiable or uncertain.",
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)
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check_size_lower: Optional[int] = Field(
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default=None,
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ge=0,
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description="Lower bound of typical investment check size in USD, must be 0 or greater. Use 0 if not clearly identifiable.",
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)
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check_size_upper: Optional[int] = Field(
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default=None,
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ge=0,
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description="Upper bound of typical investment check size in USD, must be 0 or greater. Use 0 if not clearly identifiable.",
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)
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geographic_focus: Optional[str] = Field(
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default=None,
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description="Geographic investment focus. Do not return any special characters, Just locations separated by commas. Leave empty if not clearly identifiable.",
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)
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stage_focus: InvestmentStage = Field(
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default=InvestmentStage.SEED,
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description="Investment stage focus. Use SEED as default if uncertain.",
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)
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number_of_investments: Optional[int] = Field(
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default=None,
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ge=0,
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description="Total number of investments made, must be 0 or greater. Use 0 if not clearly identifiable.",
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)
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@field_validator("name", "description", "geographic_focus", mode="before")
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@classmethod
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def empty_string_to_none(cls, v):
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"""Convert empty strings to None"""
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if v == "" or (isinstance(v, str) and v.strip() == ""):
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return None
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return v
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@field_validator(
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"id",
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"aum",
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"check_size_lower",
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"check_size_upper",
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"number_of_investments",
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mode="before",
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)
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@classmethod
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def zero_to_none(cls, v):
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"""Convert 0 to None for optional integer fields"""
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if v == 0:
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return None
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return v
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class Config:
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from_attributes = True
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class InvestorData(BaseModel):
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"""
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Expert parser: Comprehensive investor data schema for LLM processing.
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Only populate fields with clearly identifiable information. Leave lists empty if uncertain.
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"""
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investor: InvestorSchema = Field(
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description="Core investor information. Only populate with clearly identifiable data."
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)
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portfolio_companies: List[CompanySchema] = Field(
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default=[],
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description="List of portfolio companies. Leave empty if not clearly identifiable.",
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)
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team_members: List[InvestorMemberSchema] = Field(
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default=[],
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description="List of team members. Leave empty if not clearly identifiable.",
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)
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sectors: List[SectorSchema] = Field(
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default=[],
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description="List of investment sectors. Leave empty if not clearly identifiable.",
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)
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class Config:
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from_attributes = True
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class CompanyData(BaseModel):
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"""
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Expert parser: Comprehensive company data schema for LLM processing.
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Only populate fields with clearly identifiable information. Leave lists empty if uncertain.
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"""
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company: CompanySchema = Field(
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description="Core company information. Only populate with clearly identifiable data."
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)
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sectors: List[SectorSchema] = Field(
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default=[],
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description="List of company sectors. Leave empty if not clearly identifiable.",
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)
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members: List[CompanyMemberSchema] = Field(
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default=[],
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description="List of company members. Leave empty if not clearly identifiable.",
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)
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investors: List[InvestorSchema] = Field(
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default=[],
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description="List of investors. Leave empty if not clearly identifiable.",
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)
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class Config:
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from_attributes = True
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class InvestorList(BaseModel):
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"""Expert parser: List of investors with clearly identifiable information only."""
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investors: List[InvestorData] = Field(
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default=[],
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description="List of investors. Leave empty if no clearly identifiable investors.",
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)
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