added summarize_bills.py

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2026-04-21 22:44:52 -04:00
parent 4b768049c0
commit 1426b797e5

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"""Summarize bill_text rows with GPT-5 and store results in the database."""
from __future__ import annotations
import logging
import tomllib
from os import getenv
from pathlib import Path
from typing import Annotated, Any
import httpx
import typer
from sqlalchemy import Select, or_, select
from sqlalchemy.orm import Session, selectinload
from pipelines.config import get_config_dir
from pipelines.orm.common import get_postgres_engine
from pipelines.orm.data_science_dev.congress import Bill, BillText
from pipelines.tools.bill_token_compression import compress_bill_text
logger = logging.getLogger(__name__)
OPENAI_PROJECT_ID = "proj_fQBPEXFgnS87Fk6wZwploFwE"
def _find_prompts_path() -> Path:
return get_config_dir() / "prompts" / "summarization_prompts.toml"
def load_summarization_prompts(
section: str = "summarization",
) -> dict[str, str]:
return tomllib.loads(_find_prompts_path().read_text())[section]
class BillSummaryError(RuntimeError):
"""Raised when a bill summary request or response is invalid."""
def call_openai_summary(
*,
model: str,
messages: list[dict[str, str]],
) -> str:
"""Call GPT and return the assistant message content."""
api_key = getenv("CLOSEDAI_TOKEN")
if not api_key:
msg = "CLOSEDAI_TOKEN is required"
raise BillSummaryError(msg)
response = httpx.post(
"https://api.openai.com/v1/chat/completions",
headers={
"Authorization": f"Bearer {api_key}",
"OpenAI-Project": OPENAI_PROJECT_ID,
"Content-Type": "application/json",
},
json={
"model": model,
"messages": messages,
},
timeout=60,
)
response.raise_for_status()
return extract_message_content(response.json())
def build_bill_summary_messages(
*,
bill_text: BillText,
) -> list[dict[str, str]]:
"""Build the GPT prompt messages for one bill text row."""
if not bill_text.text_content:
msg = f"bill_text id={bill_text.id} has no text_content"
raise BillSummaryError(msg)
bill = bill_text.bill
compressed_text = compress_bill_text(bill_text.text_content)
if not compressed_text:
msg = f"bill_text id={bill_text.id} has no summarizable text_content"
raise BillSummaryError(msg)
metadata = "\n".join(
(
f"Congress: {bill.congress}",
f"Bill: {bill.bill_type} {bill.number}",
f"Title: {bill.title_short or bill.title or bill.official_title or ''}",
f"Top subject term: {bill.subjects_top_term or ''}",
f"Text version: {bill_text.version_code}"
+ (f" ({bill_text.version_name})" if bill_text.version_name else ""),
)
)
summarization_prompts = load_summarization_prompts()
user_prompt = "\n\n".join(
(
"BILL METADATA:",
metadata,
summarization_prompts["user_template"].format(text_content=compressed_text),
)
)
return [
{"role": "system", "content": summarization_prompts["system_prompt"]},
{
"role": "user",
"content": user_prompt,
},
]
def summarize_bill_text(
*,
model: str,
bill_text: BillText,
) -> str:
"""Generate and return a summary for one bill_text row."""
messages = build_bill_summary_messages(bill_text=bill_text)
summary = call_openai_summary(
model=model,
messages=messages,
).strip()
if not summary:
msg = f"Model returned an empty summary for bill_text id={bill_text.id}"
raise BillSummaryError(msg)
return summary
def store_bill_summary_result(
*,
bill_text: BillText,
summary: str,
model: str,
) -> None:
"""Store a generated summary and the prompt/model metadata that produced it."""
bill_text.summary = summary
bill_text.summarization_model = model
bill_text.summarization_system_prompt_version = "v1"
bill_text.summarization_user_prompt_version = "v1"
def create_select_bill_texts_for_summarization(
congress: int | None = None,
bill_ids: list[int] | None = None,
bill_text_ids: list[int] | None = None,
force: bool = False,
limit: int | None = None,
) -> Select:
"""Select bill_text rows that have source text and need summaries."""
stmt = (
select(BillText)
.join(Bill, Bill.id == BillText.bill_id)
.where(BillText.text_content.is_not(None), BillText.text_content != "")
.options(selectinload(BillText.bill))
.order_by(BillText.id)
)
if congress is not None:
stmt = stmt.where(Bill.congress == congress)
if bill_ids:
stmt = stmt.where(BillText.bill_id.in_(bill_ids))
if bill_text_ids:
stmt = stmt.where(BillText.id.in_(bill_text_ids))
if not force:
stmt = stmt.where(or_(BillText.summary.is_(None), BillText.summary == ""))
if limit is not None:
stmt = stmt.limit(limit)
return stmt
def extract_message_content(data: dict[str, Any]) -> str:
"""Extract message content from a chat-completions response body."""
choices = data.get("choices")
if not isinstance(choices, list) or not choices:
msg = "Chat completion response did not contain choices"
raise BillSummaryError(msg)
first = choices[0]
if not isinstance(first, dict):
msg = "Chat completion choice must be an object"
raise BillSummaryError(msg)
message = first.get("message")
if isinstance(message, dict) and isinstance(message.get("content"), str):
return message["content"]
if isinstance(first.get("text"), str):
return first["text"]
msg = "Chat completion response did not contain message content"
raise BillSummaryError(msg)
def main(
model: Annotated[str, typer.Option(help="OpenAI model id.")] = "gpt-5.4-mini",
congress: Annotated[
int | None, typer.Option(help="Only process one Congress.")
] = None,
bill_ids: Annotated[
list[int] | None,
typer.Option(
"--bill-id",
help="Only process one internal bill.id. Repeat for multiple bills.",
),
] = None,
bill_text_ids: Annotated[
list[int] | None,
typer.Option(
"--bill-text-id",
help="Only process one internal bill_text.id. Repeat for multiple rows.",
),
] = None,
limit: Annotated[int | None, typer.Option(help="Maximum rows to process.")] = None,
force: Annotated[
bool,
typer.Option(help="Regenerate summaries for rows that already have a summary."),
] = False,
dry_run: Annotated[
bool, typer.Option(help="Print summaries without writing them to the database.")
] = False,
log_level: Annotated[str, typer.Option(help="Log level.")] = "INFO",
) -> None:
"""CLI entrypoint for generating and storing bill summaries."""
logging.basicConfig(
level=log_level,
format="%(asctime)s %(levelname)s %(name)s: %(message)s",
)
if not getenv("CLOSEDAI_TOKEN"):
message = "CLOSEDAI_TOKEN is required"
raise typer.BadParameter(message)
engine = get_postgres_engine(name="DATA_SCIENCE_DEV")
with Session(engine) as session:
stmt = create_select_bill_texts_for_summarization(
congress=congress,
bill_ids=bill_ids,
bill_text_ids=bill_text_ids,
force=force,
limit=limit,
)
bill_texts = session.scalars(stmt).all()
logger.info("Selected %d bill_text rows for summarization", len(bill_texts))
written = 0
for index, bill_text in enumerate(bill_texts, 1):
summary = summarize_bill_text(
model=model,
bill_text=bill_text,
)
store_bill_summary_result(
bill_text=bill_text,
summary=summary,
model=model,
)
if index % 100 == 0:
session.commit()
written += 1
session.commit()
logger.info("Stored summary for bill_text id=%s", bill_text.id)
logger.info("Done: stored %d summaries", written)
def cli() -> None:
"""Typer entry point."""
typer.run(main)
if __name__ == "__main__":
cli()