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Refactor investor and company schemas to allow optional fields; update filtering logic in read_companies function and add find_similar_investors endpoint; change LLM model in InvestorProcessor and QueryProcessor for improved performance.

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bolade
2025-09-27 10:45:08 +01:00
parent d36367fbe9
commit 6d902345c0
10 changed files with 234 additions and 46 deletions
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app/routers/__pycache__/companies.cpython-312.pyc
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app/routers/__pycache__/investors.cpython-312.pyc
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app/routers/companies.py
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@@ -34,6 +34,10 @@ def read_companies(db: Session = Depends(get_db)):
"""Get all companies with their investor relationships"""
companies = (
db.query(CompanyTable)
.filter(
CompanyTable.name.isnot(None),
CompanyTable.description.isnot(None)
)
.options(
selectinload(CompanyTable.investors),
selectinload(CompanyTable.members),
app/routers/investors.py
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@@ -7,6 +7,7 @@ from fastapi import APIRouter, Depends, HTTPException, Query
from schemas.router_schemas import InvestmentStage, InvestorData
from pydantic import BaseModel
from sqlalchemy.orm import Session, selectinload
from services.querying import QueryProcessor
router = APIRouter(tags=["Investor Routes"])
@@ -234,3 +235,70 @@ def delete_investor(investor_id: int, db: Session = Depends(get_db)):
return {"message": "Investor deleted successfully"}
@router.get("/investors/{investor_id}/similar", response_model=List[InvestorData])
def find_similar_investors(investor_id: int, db: Session = Depends(get_db)):
"""Find investors similar to a given investor"""
# First, get the target investor
target_investor = (
db.query(InvestorTable)
.options(
selectinload(InvestorTable.portfolio_companies),
selectinload(InvestorTable.team_members),
selectinload(InvestorTable.sectors),
)
.filter(InvestorTable.id == investor_id)
.first()
)
if not target_investor:
raise HTTPException(status_code=404, detail="Investor not found")
# Build query to find similar investors
query = db.query(InvestorTable).options(
selectinload(InvestorTable.portfolio_companies),
selectinload(InvestorTable.team_members),
selectinload(InvestorTable.sectors),
).filter(InvestorTable.id != investor_id) # Exclude the target investor
# Filter by same stage focus
query = query.filter(InvestorTable.stage_focus == target_investor.stage_focus)
# Filter by similar geographic focus (partial match)
query = query.filter(InvestorTable.geographic_focus.ilike(f"%{target_investor.geographic_focus}%"))
# Filter by overlapping check size ranges
query = query.filter(
InvestorTable.check_size_upper >= target_investor.check_size_lower,
InvestorTable.check_size_lower <= target_investor.check_size_upper
)
# Filter by similar AUM (within 50% range)
aum_lower = int(target_investor.aum * 0.5)
aum_upper = int(target_investor.aum * 1.5)
query = query.filter(
InvestorTable.aum >= aum_lower,
InvestorTable.aum <= aum_upper
)
# Filter by common sectors
target_sector_names = [sector.name for sector in target_investor.sectors]
if target_sector_names:
query = query.join(InvestorTable.sectors).filter(
SectorTable.name.in_(target_sector_names)
)
investors = query.all()
# Transform to InvestorData format
investor_data_list = []
for investor in investors:
investor_data = InvestorData(
investor=investor,
portfolio_companies=investor.portfolio_companies,
team_members=investor.team_members,
sectors=investor.sectors,
)
investor_data_list.append(investor_data)
return investor_data_list
app/schemas/__pycache__/py_schemas.cpython-312.pyc
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app/schemas/py_schemas.py
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@@ -19,13 +19,32 @@ class SectorSchema(BaseModel):
Leave name empty if uncertain about the sector classification.
"""
id: int = Field(
ge=0, description="Sector ID, must be 0 or greater. Use 0 if uncertain."
id: Optional[int] = Field(
default=None,
ge=0,
description="Sector ID, must be 0 or greater. Use 0 if uncertain.",
)
name: str = Field(
description="Sector name. Leave empty string if not clearly identifiable from the data."
name: Optional[str] = Field(
default=None,
description="Sector name. Leave empty string if not clearly identifiable from the data.",
)
@field_validator("name", mode="before")
@classmethod
def empty_string_to_none(cls, v):
"""Convert empty strings to None"""
if v == "" or (isinstance(v, str) and v.strip() == ""):
return None
return v
@field_validator("id", mode="before")
@classmethod
def zero_to_none(cls, v):
"""Convert 0 to None for optional id field"""
if v == 0:
return None
return v
class Config:
from_attributes = True
@@ -36,22 +55,45 @@ class InvestorMemberSchema(BaseModel):
Leave fields empty if uncertain about the member details.
"""
id: int = Field(
ge=0, description="Member ID, must be 0 or greater. Use 0 if uncertain."
id: Optional[int] = Field(
default=None,
ge=0,
description="Member ID, must be 0 or greater. Use 0 if uncertain.",
)
name: str = Field(
description="Team member name. Leave empty string if not clearly identifiable."
name: Optional[str] = Field(
default=None,
description="Team member name. Leave empty string if not clearly identifiable.",
)
role: str = Field(
description="Team member role/title. Leave empty string if not clearly identifiable."
role: Optional[str] = Field(
default=None,
description="Team member role/title. Leave empty string if not clearly identifiable.",
)
email: str = Field(
description="Team member email. Leave empty string if not clearly identifiable or not provided."
email: Optional[str] = Field(
default=None,
description="Team member email. Leave empty string if not clearly identifiable or not provided.",
)
investor_id: int = Field(
ge=0, description="Investor ID, must be 0 or greater. Use 0 if uncertain."
investor_id: Optional[int] = Field(
default=None,
ge=0,
description="Investor ID, must be 0 or greater. Use 0 if uncertain.",
)
@field_validator("name", "role", "email", mode="before")
@classmethod
def empty_string_to_none(cls, v):
"""Convert empty strings to None"""
if v == "" or (isinstance(v, str) and v.strip() == ""):
return None
return v
@field_validator("id", "investor_id", mode="before")
@classmethod
def zero_to_none(cls, v):
"""Convert 0 to None for optional integer fields"""
if v == 0:
return None
return v
class Config:
from_attributes = True
@@ -62,25 +104,45 @@ class CompanyMemberSchema(BaseModel):
Leave fields empty if uncertain about the member details.
"""
id: int = Field(
ge=0, description="Member ID, must be 0 or greater. Use 0 if uncertain."
id: Optional[int] = Field(
default=None,
ge=0,
description="Member ID, must be 0 or greater. Use 0 if uncertain.",
)
name: Optional[str] = Field(
default="",
default=None,
description="Company member name. Leave empty if not clearly identifiable.",
)
linkedin: Optional[str] = Field(
default="",
default=None,
description="LinkedIn profile URL. Leave empty if not provided or uncertain.",
)
role: Optional[str] = Field(
default="",
default=None,
description="Company member role/title. Leave empty if not clearly identifiable.",
)
company_id: int = Field(
ge=0, description="Company ID, must be 0 or greater. Use 0 if uncertain."
company_id: Optional[int] = Field(
default=None,
ge=0,
description="Company ID, must be 0 or greater. Use 0 if uncertain.",
)
@field_validator("name", "linkedin", "role", mode="before")
@classmethod
def empty_string_to_none(cls, v):
"""Convert empty strings to None"""
if v == "" or (isinstance(v, str) and v.strip() == ""):
return None
return v
@field_validator("id", "company_id", mode="before")
@classmethod
def zero_to_none(cls, v):
"""Convert 0 to None for optional integer fields"""
if v == 0:
return None
return v
class Config:
from_attributes = True
@@ -91,20 +153,25 @@ class CompanySchema(BaseModel):
Leave optional fields empty if uncertain. Integer values must be 0 or greater.
"""
id: int = Field(
ge=0, description="Company ID, must be 0 or greater. Use 0 if uncertain."
id: Optional[int] = Field(
default=None,
ge=0,
description="Company ID, must be 0 or greater. Use 0 if uncertain.",
)
name: str = Field(
description="Company name. Leave empty string if not clearly identifiable."
name: Optional[str] = Field(
default=None,
description="Company name. Leave empty string if not clearly identifiable.",
)
industry: str = Field(
description="Company industry/sector. Leave empty string if not clearly identifiable."
industry: Optional[str] = Field(
default=None,
description="Company industry/sector. Leave empty string if not clearly identifiable.",
)
location: str = Field(
description="Company location/address. Leave empty string if not clearly identifiable."
location: Optional[str] = Field(
default=None,
description="Company location/address. Leave empty string if not clearly identifiable.",
)
description: Optional[str] = Field(
default="",
default=None,
description="Company description. Leave empty if not clearly available or uncertain.",
)
founded_year: Optional[int] = Field(
@@ -113,10 +180,28 @@ class CompanySchema(BaseModel):
description="Year company was founded, must be 0 or greater. Leave None if not clearly identifiable or uncertain.",
)
website: Optional[str] = Field(
default="",
default=None,
description="Company website URL. Leave empty if not provided or uncertain.",
)
@field_validator(
"name", "industry", "location", "description", "website", mode="before"
)
@classmethod
def empty_string_to_none(cls, v):
"""Convert empty strings to None"""
if v == "" or (isinstance(v, str) and v.strip() == ""):
return None
return v
@field_validator("id", "founded_year", mode="before")
@classmethod
def zero_to_none(cls, v):
"""Convert 0 to None for founded_year"""
if v == 0:
return None
return v
@field_validator("founded_year", mode="before")
@classmethod
def validate_founded_year(cls, v):
@@ -141,40 +226,71 @@ class InvestorSchema(BaseModel):
Leave optional fields empty if uncertain. All numeric values must be 0 or greater.
"""
id: int = Field(
ge=0, description="Investor ID, must be 0 or greater. Use 0 if uncertain."
id: Optional[int] = Field(
default=None,
ge=0,
description="Investor ID, must be 0 or greater. Use 0 if uncertain.",
)
name: str = Field(
description="Investor name. Do not return any special characters, Just the name as a string."
name: Optional[str] = Field(
default=None,
description="Investor name. Do not return any special characters, Just the name as a string.",
)
description: Optional[str] = Field(
default="",
default=None,
description="Investor description. Leave empty if not clearly available or uncertain.",
)
aum: int | None = Field(
aum: Optional[int] = Field(
default=None,
ge=0,
description="Assets Under Management in USD, must be 0 or greater. Use 0 if not clearly identifiable or uncertain.",
)
check_size_lower: int | None = Field(
check_size_lower: Optional[int] = Field(
default=None,
ge=0,
description="Lower bound of typical investment check size in USD, must be 0 or greater. Use 0 if not clearly identifiable.",
)
check_size_upper: int | None = Field(
check_size_upper: Optional[int] = Field(
default=None,
ge=0,
description="Upper bound of typical investment check size in USD, must be 0 or greater. Use 0 if not clearly identifiable.",
)
geographic_focus: str | None = Field(
geographic_focus: Optional[str] = Field(
default=None,
description="Geographic investment focus. Do not return any special characters, Just locations separated by commas. Leave empty if not clearly identifiable.",
)
stage_focus: InvestmentStage = Field(
description="Investment stage focus. Use SEED as default if uncertain."
default=InvestmentStage.SEED,
description="Investment stage focus. Use SEED as default if uncertain.",
)
number_of_investments: int | None = Field(
number_of_investments: Optional[int] = Field(
default=None,
ge=0,
default=0,
description="Total number of investments made, must be 0 or greater. Use 0 if not clearly identifiable.",
)
@field_validator("name", "description", "geographic_focus", mode="before")
@classmethod
def empty_string_to_none(cls, v):
"""Convert empty strings to None"""
if v == "" or (isinstance(v, str) and v.strip() == ""):
return None
return v
@field_validator(
"id",
"aum",
"check_size_lower",
"check_size_upper",
"number_of_investments",
mode="before",
)
@classmethod
def zero_to_none(cls, v):
"""Convert 0 to None for optional integer fields"""
if v == 0:
return None
return v
class Config:
from_attributes = True
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app/services/llm_parser.py
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@@ -21,7 +21,7 @@ class InvestorProcessor:
self.llm = ChatOpenAI(
api_key=os.getenv("OPENROUTER_API_KEY"),
base_url="https://openrouter.ai/api/v1",
model="google/gemini-2.5-flash-lite",
model="openai/gpt-4o-mini",
temperature=0,
)
app/services/querying.py
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@@ -21,8 +21,8 @@ class QueryProcessor:
self.llm = ChatOpenAI(
api_key=os.getenv("OPENROUTER_API_KEY"),
base_url="https://openrouter.ai/api/v1",
model="openai/gpt-5-nano",
temperature=0.3,
model="openai/gpt-4o-mini",
temperature=0,
)
self.toolkit = SQLDatabaseToolkit(db=db, llm=self.llm)
# Update system message to specifically request only investor IDs