Anto01
3a7e8ccba4
The API endpoint now passes the request's status field through to create_memory() so external scripts can create candidate memories directly without going through the extract endpoint. Default remains 'active' for backward compatibility. persist_llm_candidates.py reads a saved extractor eval baseline JSON (e.g. the Day 4 LLM run) and POSTs each candidate to Dalidou with status=candidate. Safe to re-run — duplicate content returns 400 which the script counts as 'skipped'. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
90 lines
2.7 KiB
Python
90 lines
2.7 KiB
Python
"""Persist LLM-extracted candidates from a baseline JSON to Dalidou.
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One-shot script: reads a saved extractor eval output file, filters to
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candidates the LLM actually produced, and POSTs each to the Dalidou
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memory API with ``status=candidate``. Deduplicates against already-
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existing candidate content so the script is safe to re-run.
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Usage:
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python scripts/persist_llm_candidates.py \\
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scripts/eval_data/extractor_llm_baseline_2026-04-11.json
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Then triage via:
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python scripts/atocore_client.py triage
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"""
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from __future__ import annotations
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import json
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import os
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import sys
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import urllib.error
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import urllib.parse
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import urllib.request
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BASE_URL = os.environ.get("ATOCORE_BASE_URL", "http://dalidou:8100")
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TIMEOUT = int(os.environ.get("ATOCORE_TIMEOUT_SECONDS", "10"))
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def post_json(path: str, body: dict) -> dict:
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data = json.dumps(body).encode("utf-8")
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req = urllib.request.Request(
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url=f"{BASE_URL}{path}",
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method="POST",
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headers={"Content-Type": "application/json"},
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data=data,
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)
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with urllib.request.urlopen(req, timeout=TIMEOUT) as resp:
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return json.loads(resp.read().decode("utf-8"))
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def main() -> int:
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if len(sys.argv) < 2:
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print(f"usage: {sys.argv[0]} <baseline_json>", file=sys.stderr)
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return 1
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data = json.loads(open(sys.argv[1], encoding="utf-8").read())
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results = data.get("results", [])
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persisted = 0
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skipped = 0
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errors = 0
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for r in results:
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for c in r.get("actual_candidates", []):
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content = (c.get("content") or "").strip()
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if not content:
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continue
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mem_type = c.get("memory_type", "knowledge")
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project = c.get("project", "")
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confidence = c.get("confidence", 0.5)
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try:
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resp = post_json("/memory", {
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"memory_type": mem_type,
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"content": content,
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"project": project,
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"confidence": float(confidence),
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"status": "candidate",
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})
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persisted += 1
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print(f" + {resp.get('id','?')[:8]} [{mem_type}] {content[:80]}")
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except urllib.error.HTTPError as exc:
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if exc.code == 400:
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skipped += 1
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else:
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errors += 1
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print(f" ! error {exc.code}: {content[:60]}", file=sys.stderr)
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except Exception as exc:
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errors += 1
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print(f" ! {exc}: {content[:60]}", file=sys.stderr)
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print(f"\npersisted={persisted} skipped={skipped} errors={errors}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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