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Deploy Trainer_LLM to llm-node / deploy (push) Successful in 2s
63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
#!/usr/bin/env python3
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# backfill_capability_facets.py
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import os, math
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from qdrant_client import QdrantClient
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from qdrant_client.models import Filter, WithPayloadSelector
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COLL = os.getenv("EXERCISE_COLLECTION", "exercises")
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client = QdrantClient(host=os.getenv("QDRANT_HOST","localhost"), port=int(os.getenv("QDRANT_PORT","6333")))
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def names_ge(caps, n):
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out=[]
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for k,v in (caps or {}).items():
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try:
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if int(v) >= n:
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out.append(k)
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except Exception:
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pass
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return sorted(out)
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scroll_filter = Filter(must=[]) # alles
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offset = None
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updated = 0
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while True:
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res = client.scroll(
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collection_name=COLL,
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scroll_filter=scroll_filter,
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with_payload=WithPayloadSelector(enable=True),
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limit=256,
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offset=offset
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)
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points, offset = res
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if not points:
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break
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set_list = []
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for pt in points:
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p = pt.payload or {}
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caps = p.get("capabilities") or {}
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cap_keys = sorted([k for k in caps.keys() if k])
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ge1 = names_ge(caps, 1)
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ge2 = names_ge(caps, 2)
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ge3 = names_ge(caps, 3)
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# nur setzen, wenn fehlt oder abweicht
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if p.get("capability_keys") != cap_keys or p.get("capability_ge1") != ge1 \
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or p.get("capability_ge2") != ge2 or p.get("capability_ge3") != ge3:
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set_list.append((pt.id, {
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"capability_keys": cap_keys,
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"capability_ge1": ge1,
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"capability_ge2": ge2,
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"capability_ge3": ge3
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}))
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if set_list:
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client.set_payload(collection_name=COLL, payload={pid: pay for pid, pay in set_list}, points=[pid for pid,_ in set_list])
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updated += len(set_list)
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print(f"[Backfill] updated {len(set_list)} points…")
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print(f"[Backfill] done. total={updated}")
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