Expose a runnable backend without giving the ingress layer secrets

The backend can now be inspected through a loopback-only gateway while the database-aware API remains on the internal data network. A governed synthetic demo proves readiness, pgvector retrieval, reranking, and citation output through real HTTP without invoking cloud models.

Constraint: The previously exposed Bailian key is compromised and cannot be used for live validation

Constraint: The API must be locally reachable while retaining no internet egress

Rejected: Attach the API directly to the ingress network | a real socket test proved that configuration still had egress

Rejected: Publish a port from the internal-only network | Docker Desktop did not expose the host port

Confidence: high

Scope-risk: moderate

Reversibility: clean

Directive: Keep model and database credentials out of the gateway; do not relax the fixed demo identity/profile filters

Tested: make verify; 63 pytest tests; strict mypy; Ruff; Secret scan; Compose config; three backend image builds; API/DB/gateway healthy; migration exit 0; Swagger browser check; live/ready/meta/status/search HTTP; 20/20/20 index; API egress ENETUNREACH; empty gateway mounts and business environment

Not-tested: Live Bailian calls require a newly rotated key; full generated-answer flow and React UI are not implemented

backend/app/core/demo_identity.py

@@ -0,0 +1,35 @@
+"""Stable identity and embedding profile for the public synthetic demo corpus."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import uuid
+
+DEMO_SCOPE_NAME = "synthetic-demo"
+DEMO_EXPECTED_CHUNKS = 20
+DEMO_FAKE_EMBEDDING_MODEL = "fake-feature-hash-v1"
+
+IDENTITY_NAMESPACE = uuid.UUID("eef85571-1f64-4a09-86d7-53fd329c3eb2")
+KNOWLEDGE_BASE_ID = uuid.uuid5(IDENTITY_NAMESPACE, "synthetic-demo-knowledge-base")
+ACCESS_SCOPE_ID = uuid.uuid5(IDENTITY_NAMESPACE, "synthetic-demo-public-scope")
+
+
+def offline_embedding_profile_hash(dimension: int) -> str:
+    """Return the exact profile bound to vectors produced by the offline embedder."""
+
+    profile = {
+        "api_mode": "deterministic-offline",
+        "dimension": dimension,
+        "endpoint_identity_hash": "local-fake",
+        "model": DEMO_FAKE_EMBEDDING_MODEL,
+        "normalization": "provider-default",
+        "profile_version": 1,
+    }
+    serialized = json.dumps(
+        profile,
+        ensure_ascii=False,
+        sort_keys=True,
+        separators=(",", ":"),
+    )
+    return hashlib.sha256(serialized.encode("utf-8")).hexdigest()