feat(workers): extract.pdf with Tesseract fallback
pdftotext first; falls back to per-page pdftoppm rasterization +
Tesseract OCR when the extracted text is < 200 chars. Updates
refs.body_text + metadata.extract.{method,chars} via the repo shim;
audit entry emitted with actor_kind='worker'.
born_digital.pdf fixture padded so pdftotext yields > 200 chars and
the test exercises the pdftotext path, not the OCR fallback.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
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workers/tests/fixtures/born_digital.pdf
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workers/tests/fixtures/born_digital.pdf
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58
workers/tests/test_pdf.py
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58
workers/tests/test_pdf.py
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import subprocess
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from pathlib import Path
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from void_workers.handlers.pdf import handle as handle_pdf
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FIXTURES = Path(__file__).parent / "fixtures"
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def _run_node_migrations():
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subprocess.run(
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["node", "lib/db/migrate.js", "up"],
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cwd="/project/src/void-v2",
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check=True
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)
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def _reset_void_schema(conn):
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"""Mirror tests/helpers/db.js::resetDb on the Node side."""
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conn.execute("DROP SCHEMA IF EXISTS public CASCADE")
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conn.execute("CREATE SCHEMA public")
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conn.execute("CREATE EXTENSION IF NOT EXISTS pgcrypto")
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conn.execute("CREATE EXTENSION IF NOT EXISTS vector")
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def _seed_space_and_ref(conn, blob_path, kind="pdf"):
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sp = conn.execute(
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"INSERT INTO spaces(slug, name) VALUES('plan4-tests', 'P4') "
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"ON CONFLICT (slug) DO UPDATE SET name=EXCLUDED.name RETURNING id"
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).fetchone()[0]
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ref = conn.execute(
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"INSERT INTO refs(space_id, kind, source_url, title, blob_path) "
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"VALUES(%s, %s, NULL, 'fixture', %s) RETURNING id",
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(sp, kind, str(blob_path))
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).fetchone()[0]
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return sp, ref
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def test_pdf_born_digital_uses_pdftotext(conn):
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_reset_void_schema(conn)
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_run_node_migrations()
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blob = FIXTURES / "born_digital.pdf"
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sp, ref = _seed_space_and_ref(conn, blob)
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out = handle_pdf({"ref_id": str(ref), "blob_path": str(blob)})
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assert out["ref_id"] == str(ref)
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assert out["method"] == "pdftotext"
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assert out["chars"] > 0
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row = conn.execute("SELECT body_text FROM refs WHERE id=%s", (ref,)).fetchone()
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assert "void-workers" in (row[0] or "").lower()
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def test_pdf_scanned_falls_back_to_tesseract(conn):
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_reset_void_schema(conn)
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_run_node_migrations()
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blob = FIXTURES / "scanned.pdf"
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sp, ref = _seed_space_and_ref(conn, blob)
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out = handle_pdf({"ref_id": str(ref), "blob_path": str(blob)})
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assert out["method"] == "tesseract"
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row = conn.execute("SELECT body_text FROM refs WHERE id=%s", (ref,)).fetchone()
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assert "blackflame" in (row[0] or "").lower()
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@@ -1,5 +1,6 @@
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from . import echo
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from . import echo, pdf
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REGISTRY = {
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REGISTRY = {
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echo.NAME: echo.handle,
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echo.NAME: echo.handle,
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pdf.NAME: pdf.handle,
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}
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}
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47
workers/void_workers/handlers/pdf.py
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workers/void_workers/handlers/pdf.py
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import subprocess
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import tempfile
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from pathlib import Path
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from PIL import Image
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import pytesseract
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from .. import repo
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NAME = "extract.pdf"
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FALLBACK_THRESHOLD = 200 # chars below which we OCR
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def _pdftotext(blob_path):
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return subprocess.check_output(
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["pdftotext", "-layout", blob_path, "-"], timeout=120
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).decode("utf-8", errors="replace")
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def _ocr_pdf(blob_path):
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"""Rasterize each page with pdftoppm, OCR each with Tesseract."""
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with tempfile.TemporaryDirectory() as tmp:
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subprocess.run(
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["pdftoppm", "-r", "200", "-png", blob_path, f"{tmp}/p"],
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check=True, timeout=300
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)
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pages = sorted(Path(tmp).glob("p-*.png"))
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parts = []
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for p in pages:
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img = Image.open(p)
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parts.append(pytesseract.image_to_string(img, lang="eng"))
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return "\n".join(parts)
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def handle(job_data: dict) -> dict:
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ref_id = job_data["ref_id"]
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blob_path = job_data["blob_path"]
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method = "pdftotext"
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text = _pdftotext(blob_path).strip()
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if len(text) < FALLBACK_THRESHOLD:
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method = "tesseract"
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text = _ocr_pdf(blob_path).strip()
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body_text = text[:200_000]
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repo.update_ref(
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ref_id,
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body_text=body_text,
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metadata_patch={"extract": {"method": method, "chars": len(body_text)}}
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)
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return {"ref_id": ref_id, "chars": len(body_text), "method": method}
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99
workers/void_workers/repo.py
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workers/void_workers/repo.py
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import json
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import psycopg
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from psycopg.rows import dict_row
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from .config import DATABASE_URL
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def _conn():
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return psycopg.connect(
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DATABASE_URL, autocommit=True, row_factory=dict_row, client_encoding='UTF8'
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)
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def _maybe_json(v):
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return json.dumps(v) if isinstance(v, (dict, list)) else v
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def update_ref(ref_id, *, body_text=None, metadata_patch=None):
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"""UPDATE refs ... and emit an audit_log row with actor_kind='worker'."""
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with _conn() as conn:
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before = conn.execute("SELECT * FROM refs WHERE id=%s", (ref_id,)).fetchone()
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sets, args = [], []
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if body_text is not None:
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sets.append("body_text=%s"); args.append(body_text)
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if metadata_patch is not None:
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sets.append("metadata = coalesce(metadata, '{}'::jsonb) || %s::jsonb")
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args.append(json.dumps(metadata_patch))
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if not sets:
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return before
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sets.append("updated_at=now()")
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args.append(ref_id)
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after = conn.execute(
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f"UPDATE refs SET {', '.join(sets)} WHERE id=%s RETURNING *",
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args
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).fetchone()
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diff = {}
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if body_text is not None and (before or {}).get("body_text") != body_text:
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diff["body_text"] = {"before_len": len((before or {}).get("body_text") or ""),
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"after_len": len(body_text)}
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conn.execute("""
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INSERT INTO audit_log(actor_kind, actor_id, entity_type, entity_id, action, diff)
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VALUES('worker', NULL, 'ref', %s, 'update', %s)
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""", (ref_id, json.dumps({"kind": "update", "changes": diff})))
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return after
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def create_ref(input_):
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"""INSERT INTO refs(...) RETURNING id; emit an audit_log row."""
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fields = ["space_id", "kind", "source_url", "title", "summary", "body_text",
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"blob_path", "metadata", "source_kind", "external_id", "captured_at"]
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cols, vals = [], []
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for f in fields:
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if f in input_:
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cols.append(f)
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vals.append(_maybe_json(input_[f]))
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placeholders = ",".join("%s" for _ in cols)
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sql = f"INSERT INTO refs({','.join(cols)}) VALUES({placeholders}) RETURNING id"
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with _conn() as conn:
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ref_id = conn.execute(sql, vals).fetchone()["id"]
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conn.execute("""
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INSERT INTO audit_log(actor_kind, actor_id, entity_type, entity_id, action, diff)
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VALUES('worker', NULL, 'ref', %s, 'create', %s)
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""", (ref_id, json.dumps({"kind": "create"})))
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return str(ref_id)
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def get_source_doc(source_doc_id):
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with _conn() as conn:
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return conn.execute(
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"SELECT * FROM source_docs WHERE id=%s", (source_doc_id,)
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).fetchone()
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def update_source_doc(source_doc_id, *, body_text=None, last_synced=None, metadata_patch=None):
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with _conn() as conn:
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before = conn.execute(
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"SELECT * FROM source_docs WHERE id=%s", (source_doc_id,)
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).fetchone()
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sets, args = [], []
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if body_text is not None:
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sets.append("body_text=%s"); args.append(body_text)
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if last_synced is not None:
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sets.append("last_synced=%s"); args.append(last_synced)
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if metadata_patch is not None:
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sets.append("metadata = coalesce(metadata, '{}'::jsonb) || %s::jsonb")
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args.append(json.dumps(metadata_patch))
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if not sets:
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return before
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sets.append("updated_at=now()")
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args.append(source_doc_id)
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after = conn.execute(
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f"UPDATE source_docs SET {', '.join(sets)} WHERE id=%s RETURNING *", args
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).fetchone()
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conn.execute("""
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INSERT INTO audit_log(actor_kind, actor_id, entity_type, entity_id, action, diff)
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VALUES('worker', NULL, 'source_doc', %s, 'update', %s)
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""", (source_doc_id,
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json.dumps({"kind": "update",
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"changes": {"body_text": "updated" if body_text is not None else None}})))
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return after
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