9b0f25c105
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QA pipeline that matches control source_original_text directly against original PDF documents to verify article/paragraph assignments. Covers backfill, dedup, source normalization, Qdrant cleanup, and prod sync. Key results (2026-03-20): - 4,110/7,943 controls matched to PDF (100% for major EU regs) - 3,366 article corrections, 705 new assignments - 1,290 controls from Erwägungsgründe (preamble) identified - 779 controls from Anhänge (annexes) identified Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
28 lines
973 B
Python
28 lines
973 B
Python
"""Delete eu_2023_988 duplicate from production Qdrant."""
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import httpx
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PROD_URL = "https://qdrant-dev.breakpilot.ai"
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HEADERS = {"api-key": "z9cKbT74vl1aKPD1QGIlKWfET47VH93u"}
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# Delete
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resp = httpx.post(
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f"{PROD_URL}/collections/bp_compliance_ce/points/delete",
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json={"filter": {"must": [{"key": "regulation_id", "match": {"value": "eu_2023_988"}}]}},
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headers=HEADERS, timeout=60,
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)
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print(f"Delete status: {resp.json().get('status')}")
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# Verify
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resp2 = httpx.post(
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f"{PROD_URL}/collections/bp_compliance_ce/points/count",
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json={"filter": {"must": [{"key": "regulation_id", "match": {"value": "eu_2023_988"}}]}, "exact": True},
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headers=HEADERS, timeout=15,
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)
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remaining = resp2.json().get("result", {}).get("count", 0)
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print(f"Remaining: {remaining}")
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# Total
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resp3 = httpx.get(f"{PROD_URL}/collections/bp_compliance_ce", headers=HEADERS, timeout=10)
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total = resp3.json().get("result", {}).get("points_count", "?")
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print(f"Total points: {total}")
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