Documentation Index
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The shape AP teams need: a header (vendor, totals, dates) and a list of line items. The schema is the contract with downstream systems.
from typing import List, Optional
from agno.agent import Agent
from agno.media import File
from agno.models.openai import OpenAIResponses
from pydantic import BaseModel, Field
class LineItem(BaseModel):
description: str = Field(..., description="Line description as printed")
quantity: Optional[float] = None
unit_price: Optional[float] = None
amount: Optional[float] = Field(None, description="Line total in invoice currency")
class Invoice(BaseModel):
invoice_number: Optional[str] = None
vendor: Optional[str] = None
vendor_tax_id: Optional[str] = None
bill_to: Optional[str] = None
invoice_date: Optional[str] = Field(None, description="ISO 8601 if possible")
due_date: Optional[str] = None
currency: Optional[str] = Field(None, description="ISO 4217, e.g. USD, EUR")
subtotal: Optional[float] = None
tax: Optional[float] = None
total: Optional[float] = None
lines: List[LineItem] = Field(default_factory=list)
agent = Agent(
model=OpenAIResponses(id="gpt-5.5"),
instructions=(
"Extract every field and every line item from the attached invoice. "
"Numbers stay as numbers. Use ISO 8601 for dates when the format is "
"unambiguous. Null for missing fields. Do not invent line items."
),
output_schema=Invoice,
)
invoice = agent.run(
"Extract this invoice.",
files=[File(url="https://example.com/invoice-1042.pdf")],
).content
# Invoice(invoice_number='1042', vendor='Acme Corp', invoice_date='2026-04-12',
# total=1296.0, currency='USD', lines=[LineItem(description='Pro plan',
# quantity=12, unit_price=99.0, amount=1188.0), LineItem(...)])
total corrupts the AP ledger. Two lines in the instructions (“use exactly what the document shows”, “null if missing”) cut the hallucination rate substantially on noisy scans.
Persist the row
The agent’s job ends at a validated Invoice. The next step is a normal INSERT. Pydantic .model_dump() gives you a dict you can hand to any driver.
from sqlalchemy import create_engine, text
engine = create_engine("postgresql+psycopg://ai:ai@localhost:5532/ap")
with engine.begin() as conn:
invoice_id = conn.execute(
text(
"INSERT INTO invoices (invoice_number, vendor, invoice_date, "
"due_date, currency, subtotal, tax, total) "
"VALUES (:invoice_number, :vendor, :invoice_date, :due_date, "
":currency, :subtotal, :tax, :total) RETURNING id"
),
invoice.model_dump(exclude={"lines"}),
).scalar_one()
for line in invoice.lines:
conn.execute(
text(
"INSERT INTO invoice_lines (invoice_id, description, "
"quantity, unit_price, amount) "
"VALUES (:invoice_id, :description, :quantity, "
":unit_price, :amount)"
),
{"invoice_id": invoice_id, **line.model_dump()},
)
Receipts
Receipts are invoices with a thinner header. Drop due_date, vendor_tax_id, and bill_to. Keep the same line-item shape. The same agent and the same instructions work; only output_schema changes.
class Receipt(BaseModel):
merchant: Optional[str] = None
purchase_date: Optional[str] = None
currency: Optional[str] = None
total: Optional[float] = None
lines: List[LineItem] = Field(default_factory=list)
Confidence on noisy scans
Production AP sees faxed copies, partial scans, and mixed-language invoices. When you need a flag for “send this to a human”, wrap each value in a confidence carrier. The pattern is identical to the data labeling pattern and feeds the routing logic in human routing and eval.
Next steps
| Task | Guide |
|---|
| Process a folder of invoices | Batch and durability |
| Route low-confidence invoices to AP review | Human routing and eval |
| Extract contract clauses with the same primitive | Contracts |
Developer Resources
