YoVinchen
ecdb10c37a
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Separate local parsing from model indexing, bind review decisions to immutable manifests, persist vectors behind active profiles, and expose retrieval, chat, evaluation, and document workflows through the React workbench. Constraint: Live Bailian authentication currently fails for all three configured capabilities Rejected: Direct upload-to-embedding flow | bypasses local review and manifest binding Confidence: high Scope-risk: broad Directive: Keep private-data deployment blocked until authentication, RBAC, and separate database roles land Tested: make verify; fresh and replay Docker document smoke; worker recovery smoke; frozen synthetic evaluation; migration 0003-0004 roundtrip Not-tested: Successful live Bailian calls, OCR, real multi-user authorization
38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
"""Stable identity and embedding profile for the public synthetic demo corpus."""
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from __future__ import annotations
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import hashlib
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import json
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import uuid
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DEMO_SCOPE_NAME = "synthetic-demo"
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DEMO_EXPECTED_CHUNKS = 20
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DEMO_FAKE_EMBEDDING_MODEL = "fake-feature-hash-v1"
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IDENTITY_NAMESPACE = uuid.UUID("eef85571-1f64-4a09-86d7-53fd329c3eb2")
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KNOWLEDGE_BASE_ID = uuid.uuid5(IDENTITY_NAMESPACE, "synthetic-demo-knowledge-base")
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ACCESS_SCOPE_ID = uuid.uuid5(IDENTITY_NAMESPACE, "synthetic-demo-public-scope")
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BAILIAN_KNOWLEDGE_BASE_ID = uuid.uuid5(IDENTITY_NAMESPACE, "synthetic-bailian-knowledge-base")
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BAILIAN_ACCESS_SCOPE_ID = uuid.uuid5(IDENTITY_NAMESPACE, "synthetic-bailian-public-scope")
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def offline_embedding_profile_hash(dimension: int) -> str:
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"""Return the exact profile bound to vectors produced by the offline embedder."""
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profile = {
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"api_mode": "deterministic-offline",
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"dimension": dimension,
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"endpoint_identity_hash": "local-fake",
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"model": DEMO_FAKE_EMBEDDING_MODEL,
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"normalization": "provider-default",
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"profile_version": 1,
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}
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serialized = json.dumps(
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profile,
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ensure_ascii=False,
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sort_keys=True,
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separators=(",", ":"),
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)
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return hashlib.sha256(serialized.encode("utf-8")).hexdigest()
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