feat(store): record per-run finding sightings
This commit is contained in:
Hiten Shah
@@ -159,7 +159,30 @@ _UPDATABLE_FINDING_COLUMNS = frozenset({
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})
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# Future migrations keyed by version number
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MIGRATIONS: Dict[int, str] = {}
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MIGRATIONS: Dict[int, str] = {
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2: """
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CREATE TABLE IF NOT EXISTS finding_sightings (
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id INTEGER PRIMARY KEY,
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finding_id INTEGER REFERENCES findings(id) ON DELETE CASCADE,
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run_id INTEGER REFERENCES research_runs(id) ON DELETE CASCADE,
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topic_id INTEGER REFERENCES topics(id) ON DELETE CASCADE,
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source TEXT NOT NULL,
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source_url TEXT NOT NULL,
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source_title TEXT,
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engagement_score REAL,
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relevance_score REAL,
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seen_at TEXT DEFAULT (datetime('now')),
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UNIQUE(run_id, finding_id)
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);
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CREATE INDEX IF NOT EXISTS idx_finding_sightings_run
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ON finding_sightings(run_id, topic_id);
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CREATE INDEX IF NOT EXISTS idx_finding_sightings_topic_seen
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ON finding_sightings(topic_id, seen_at);
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CREATE INDEX IF NOT EXISTS idx_finding_sightings_url
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ON finding_sightings(source_url);
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""",
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}
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def _connect(db_path: Optional[Path] = None) -> sqlite3.Connection:
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@@ -423,6 +446,7 @@ def store_findings(
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new_count = len(insert_rows)
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updated_count = len(update_rows)
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_record_sightings(conn, run_id, topic_id, with_urls)
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conn.execute(
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"UPDATE research_runs SET findings_new = ?, findings_updated = ? WHERE id = ?",
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(new_count, updated_count, run_id),
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@@ -434,6 +458,68 @@ def store_findings(
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return {"new": new_count, "updated": updated_count}
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def _record_sightings(
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conn: sqlite3.Connection,
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run_id: int,
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topic_id: int,
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findings_with_urls: List[tuple[str, Dict[str, Any]]],
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) -> None:
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"""Record the findings observed during this run.
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The aggregate findings table keeps one row per URL and updates that row on
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re-sighting. This ledger preserves the run/topic membership needed for
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watchlist deltas and dossiers.
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"""
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if not findings_with_urls:
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return
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by_url = {url: finding for url, finding in findings_with_urls}
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placeholders = ",".join("?" for _ in by_url)
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rows = conn.execute(
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f"SELECT id, source_url FROM findings WHERE source_url IN ({placeholders})",
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list(by_url),
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).fetchall()
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sighting_rows = []
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for row in rows:
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finding = by_url[row["source_url"]]
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sighting_rows.append((
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row["id"],
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run_id,
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topic_id,
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finding.get("source", "unknown"),
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row["source_url"],
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finding.get("source_title") or finding.get("title", ""),
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finding.get("engagement_score", 0),
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finding.get("relevance_score", 0),
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))
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if not sighting_rows:
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return
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conn.executemany(
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"""INSERT OR IGNORE INTO finding_sightings
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(finding_id, run_id, topic_id, source, source_url, source_title,
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engagement_score, relevance_score)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?)""",
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sighting_rows,
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)
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def get_sightings_for_run(topic_id: int, run_id: int) -> List[Dict[str, Any]]:
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"""Return findings observed for a topic during a specific run."""
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conn = _connect()
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try:
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rows = conn.execute(
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"""SELECT * FROM finding_sightings
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WHERE topic_id = ? AND run_id = ?
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ORDER BY id""",
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(topic_id, run_id),
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).fetchall()
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return [dict(r) for r in rows]
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finally:
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conn.close()
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def get_new_findings(
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topic_id: int,
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since: Optional[str] = None,
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+155
-4
@@ -59,7 +59,68 @@ def sample_report():
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"source_weights": {},
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},
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"clusters": [],
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"ranked_candidates": [],
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"ranked_candidates": [
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{
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"candidate_id": "c-r1",
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"item_id": "R1",
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"source": "reddit",
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"title": "Test Reddit Post",
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"url": "https://reddit.com/r/test/1",
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"snippet": "Reddit snippet",
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"subquery_labels": ["primary"],
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"native_ranks": {"reddit": 1},
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"local_relevance": 0.8,
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"freshness": 100,
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"engagement": 50.0,
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"source_quality": 0.8,
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"rrf_score": 1.0,
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"final_score": 0.8,
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"explanation": "Reddit snippet",
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"source_items": [
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{
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"item_id": "R1",
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"source": "reddit",
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"title": "Test Reddit Post",
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"body": "Reddit discussion content",
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"url": "https://reddit.com/r/test/1",
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"author": "testuser",
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"engagement_score": 50.0,
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"local_relevance": 0.8,
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"snippet": "Reddit snippet",
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}
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],
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},
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{
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"candidate_id": "c-x1",
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"item_id": "X1",
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"source": "x",
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"title": "Test X Post",
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"url": "https://x.com/test/status/1",
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"snippet": "X snippet",
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"subquery_labels": ["primary"],
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"native_ranks": {"x": 1},
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"local_relevance": 0.85,
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"freshness": 100,
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"engagement": 75.0,
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"source_quality": 0.8,
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"rrf_score": 1.0,
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"final_score": 0.85,
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"explanation": "X snippet",
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"source_items": [
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{
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"item_id": "X1",
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"source": "x",
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"title": "Test X Post",
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"body": "X post content",
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"url": "https://x.com/test/status/1",
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"author": "xuser",
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"engagement_score": 75.0,
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"local_relevance": 0.85,
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"snippet": "X snippet",
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}
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],
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},
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],
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"items_by_source": {
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"reddit": [
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{
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@@ -236,13 +297,13 @@ def test_findings_from_report_handles_missing_fields():
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"clusters": [],
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"ranked_candidates": [],
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"items_by_source": {
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"reddit": [
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"hackernews": [
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{
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"item_id": "R1",
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"source": "reddit",
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"source": "hackernews",
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"title": "Test",
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"body": "Content",
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"url": "https://reddit.com/1",
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"url": "https://news.ycombinator.com/item?id=1",
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"author": None, # Missing author
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"engagement_score": None, # Missing engagement
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"local_relevance": None, # Missing relevance
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@@ -384,6 +445,96 @@ def test_store_findings_skips_items_without_url(temp_db):
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assert counts["new"] == 1
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def test_init_db_creates_finding_sightings_table(temp_db):
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"""Test that the per-run sightings ledger is available on fresh databases."""
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conn = sqlite3.connect(str(temp_db))
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table = conn.execute(
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"SELECT name FROM sqlite_master WHERE type='table' AND name='finding_sightings'"
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).fetchone()
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conn.close()
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assert table is not None
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def test_store_findings_records_sightings_for_new_findings(temp_db):
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"""Test that each stored finding is linked to the run that observed it."""
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topic = store.add_topic("Test Topic")
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run_id = store.record_run(topic["id"], source_mode="v3")
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findings = [
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{
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"source": "reddit",
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"source_url": "https://reddit.com/1",
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"source_title": "Reddit 1",
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"content": "Content 1",
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"engagement_score": 10.0,
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"relevance_score": 0.7,
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},
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{
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"source": "x",
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"source_url": "https://x.com/a/status/1",
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"source_title": "X 1",
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"content": "Content 2",
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"engagement_score": 20.0,
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"relevance_score": 0.8,
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},
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]
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store.store_findings(run_id, topic["id"], findings)
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sightings = store.get_sightings_for_run(topic["id"], run_id)
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assert [s["source_url"] for s in sightings] == [
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"https://reddit.com/1",
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"https://x.com/a/status/1",
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]
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assert {s["source"] for s in sightings} == {"reddit", "x"}
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def test_store_findings_records_sightings_for_resighted_findings(temp_db):
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"""Test that a re-seen finding is recorded for each run that observes it."""
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topic = store.add_topic("Test Topic")
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first_run_id = store.record_run(topic["id"], source_mode="v3")
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second_run_id = store.record_run(topic["id"], source_mode="v3")
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finding = {
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"source": "reddit",
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"source_url": "https://reddit.com/1",
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"source_title": "Reddit 1",
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"content": "Content",
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"engagement_score": 10.0,
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"relevance_score": 0.7,
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}
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store.store_findings(first_run_id, topic["id"], [finding])
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store.store_findings(second_run_id, topic["id"], [{**finding, "engagement_score": 15.0}])
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first_sightings = store.get_sightings_for_run(topic["id"], first_run_id)
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second_sightings = store.get_sightings_for_run(topic["id"], second_run_id)
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assert len(first_sightings) == 1
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assert len(second_sightings) == 1
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assert first_sightings[0]["source_url"] == second_sightings[0]["source_url"]
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assert second_sightings[0]["engagement_score"] == 15.0
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def test_store_findings_sightings_are_idempotent_per_run(temp_db):
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"""Test that storing the same finding twice for one run does not duplicate sightings."""
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topic = store.add_topic("Test Topic")
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run_id = store.record_run(topic["id"], source_mode="v3")
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finding = {
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"source": "reddit",
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"source_url": "https://reddit.com/1",
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"source_title": "Reddit 1",
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"content": "Content",
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"engagement_score": 10.0,
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"relevance_score": 0.7,
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}
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store.store_findings(run_id, topic["id"], [finding])
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store.store_findings(run_id, topic["id"], [finding])
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sightings = store.get_sightings_for_run(topic["id"], run_id)
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assert len(sightings) == 1
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def test_update_validates_allowed_columns(temp_db, sample_report):
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"""Test update_run/update_finding accept valid keys and reject invalid keys."""
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topic = store.add_topic("Test Topic")
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@@ -251,7 +251,38 @@ def test_run_topic_success(mock_subprocess, temp_db):
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"source_weights": {},
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},
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"clusters": [],
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"ranked_candidates": [],
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"ranked_candidates": [
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{
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"candidate_id": "c-r1",
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"item_id": "R1",
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"source": "reddit",
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"title": "Test",
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"url": "https://reddit.com/1",
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"snippet": "Snippet",
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"subquery_labels": ["primary"],
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"native_ranks": {"reddit": 1},
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"local_relevance": 0.8,
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"freshness": 100,
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"engagement": 50.0,
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"source_quality": 0.8,
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"rrf_score": 1.0,
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"final_score": 0.8,
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"explanation": "Snippet",
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"source_items": [
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{
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"item_id": "R1",
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"source": "reddit",
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"title": "Test",
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"body": "Content",
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"url": "https://reddit.com/1",
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"author": "user",
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"engagement_score": 50.0,
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"local_relevance": 0.8,
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"snippet": "Snippet",
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}
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],
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}
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],
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"items_by_source": {
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"reddit": [
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{
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@@ -338,7 +369,38 @@ def test_run_topic_calls_delivery(mock_deliver, mock_subprocess, temp_db):
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"source_weights": {},
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},
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"clusters": [],
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"ranked_candidates": [],
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"ranked_candidates": [
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{
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"candidate_id": "c-r1",
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"item_id": "R1",
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"source": "reddit",
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"title": "Test",
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"url": "https://reddit.com/1",
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"snippet": "Snippet",
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"subquery_labels": ["primary"],
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"native_ranks": {"reddit": 1},
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"local_relevance": 0.8,
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"freshness": 100,
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"engagement": 50.0,
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"source_quality": 0.8,
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"rrf_score": 1.0,
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"final_score": 0.8,
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"explanation": "Snippet",
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"source_items": [
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{
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"item_id": "R1",
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"source": "reddit",
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"title": "Test",
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"body": "Content",
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"url": "https://reddit.com/1",
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"author": "user",
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"engagement_score": 50.0,
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"local_relevance": 0.8,
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"snippet": "Snippet",
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}
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],
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}
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],
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"items_by_source": {
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"reddit": [
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{
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