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/tools/seed_demo.py

@@ -23,14 +23,17 @@ from psycopg.types.json import Jsonb
 from app.adapters.bailian import BailianEmbeddingAdapter, BailianRerankerAdapter
 from app.adapters.fake import FakeEmbeddingProvider, FakeReranker, lexical_features
 from app.core.config import Settings
+from app.core.demo_identity import (
+    ACCESS_SCOPE_ID,
+    IDENTITY_NAMESPACE,
+    KNOWLEDGE_BASE_ID,
+    offline_embedding_profile_hash,
+)
 from app.core.secrets import SecretFileError
 from app.ports.model_providers import EmbeddingProvider, ModelProviderError, Reranker
 
 PROJECT_ROOT = Path(__file__).resolve().parents[3]
 DEFAULT_SAMPLE_ROOT = PROJECT_ROOT / "data" / "samples" / "public"
-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")
 
 
 @dataclass(frozen=True, slots=True)
@@ -139,13 +142,12 @@ def load_queries(path: Path) -> list[DemoQuery]:
 
 
 def embedding_profile_hash(settings: Settings, mode: str) -> str:
-    endpoint_identity = "local-fake"
-    model = "fake-feature-hash-v1"
-    api_mode = "deterministic-offline"
-    if mode == "bailian":
-        endpoint_identity = sha256_text(urlsplit(settings.bailian_openai_base_url).hostname or "")
-        model = settings.embedding_model
-        api_mode = "openai-compatible"
+    if mode != "bailian":
+        return offline_embedding_profile_hash(settings.embedding_dimension)
+
+    endpoint_identity = sha256_text(urlsplit(settings.bailian_openai_base_url).hostname or "")
+    model = settings.embedding_model
+    api_mode = "openai-compatible"
     profile = {
         "api_mode": api_mode,
         "dimension": settings.embedding_dimension,