Phase 0B ran the upstream application on a network with no route out and the first turn died in tiktoken, which downloads its BPE table the first time anything counts a token. The browser separately fetched three font families from Google on every page load. Neither is visible on a machine that has been online once, which is why both now have tests. The tokenizer table is vendored at backend/app/context/vendor/cl100k_base.tiktoken and backend/app/context/encoding.py builds the encoding from it directly, verifying its SHA-256 against the digest tiktoken itself pins for that URL. No code path in the tokenizer can reach the network any more — not a warm cache, not an environment variable a deployment could forget. The encoding was checked token for token against tiktoken's own. The three font families are self-hosted as variable fonts under frontend/public/fonts/ (343 KiB, Latin and Latin Extended), declared in frontend/src/styles/fonts.css, and re-vendored by frontend/tools/vendor_fonts.py. Their OFL licences ship beside them. With no remote asset left, the CSP drops both Google hosts and gains object-src, base-uri and form-action; woff2 also gets its real media type, which Python's table lacks on a slim image. A trusted-LAN Ollama turned out not to work at all over HTTPS. httpx verifies against the certifi bundle, so an endpoint whose certificate comes from a CA the user installed on their own machines — a StartOS server's Ollama, for one — was refused with CERTIFICATE_VERIFY_FAILED while curl and the browser on the same host accepted it. app/tlstrust.py builds one context that unions the platform CA store with certifi's, and all four outbound clients use it. A union rather than a swap, so an image with an empty system store cannot start failing on endpoints that worked before. Verification itself is untouched: CERT_REQUIRED, hostname checking on, and no insecure escape hatch. The storyteller listener is now loopback by explicit statement rather than by inheriting uvicorn's default: start.sh, start.ps1, and docker-compose.yml, which publishes to 127.0.0.1 rather than every interface. Reaching an Ollama on another machine is outbound and needs none of that inbound exposure. backend/requirements.lock pins the exact tested closure; requirements.txt keeps the ranges. DEVELOPMENT.md covers setup, the same-host and trusted-LAN Ollama configurations, and how to re-run the offline proof. PROVENANCE.md records the upstream commit, the MIT terms, and both vendored assets. Verified, not just compiled. On an --internal Docker network with 1.1.1.1 unreachable and no name resolving, a campaign was created and played for six turns through same-host Ollama, restarted, and resumed. A second run played ten turns through Ollama on a separate physical machine on the LAN over verified HTTPS, summaries and embeddings included, with the storyteller's default route deleted so the LAN was reachable and the Internet was not. Its capture: 893 packets to the approved host, 730 loopback, zero anywhere else, and zero DNS queries. Two induced model failures left the accepted story bit-identical. The inherited SPA was opened in a browser and a campaign read back from it. Evidence is in planning/reports/M1-BASELINE-REPORT.md, along with the findings that did not belong in this change. 648 backend tests pass, up from the inherited 632; frontend lint and build are clean; the image builds. No M2 work is included: the hosted, cloud, analytics, Postgres and scripting surfaces are untouched. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017foPNqFjAJa2Ngebf5mEfL
130 lines
5.1 KiB
Python
130 lines
5.1 KiB
Python
import httpx
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from fastapi import APIRouter, Depends, Request
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from sqlalchemy.orm import Session
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from starlette.concurrency import run_in_threadpool
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from .. import auth, limits, models, netguard, schemas, security, tlstrust
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from ..database import get_db
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router = APIRouter(prefix="/api/settings", tags=["settings"])
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def get_settings(db: Session, user: models.User) -> models.Settings:
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"""Returns the user's settings row, creating it on first access.
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Phase 8 made settings per user rather than global. They cover the endpoint,
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the key, the models, and the memory configuration.
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"""
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settings = (
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db.query(models.Settings).filter(models.Settings.user_id == user.id).first()
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)
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if settings is None:
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settings = models.Settings(user_id=user.id)
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db.add(settings)
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db.commit()
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return settings
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@router.get("", response_model=schemas.SettingsOut)
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def read_settings(
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db: Session = Depends(get_db),
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user: models.User = Depends(auth.get_current_user),
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):
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return get_settings(db, user)
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@router.put("", response_model=schemas.SettingsOut)
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def update_settings(
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payload: schemas.SettingsUpdate,
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db: Session = Depends(get_db),
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user: models.User = Depends(auth.get_current_user),
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):
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settings = get_settings(db, user)
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fields = payload.model_dump(exclude_unset=True)
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# Write-only API key: absent = unchanged, "" = cleared, else encrypted.
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if "api_key" in fields:
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fields["api_key"] = security.encrypt_secret(fields["api_key"].strip())
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embedding_model_changed = (
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"embedding_model" in fields
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and fields["embedding_model"] != settings.embedding_model
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)
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for field, value in fields.items():
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setattr(settings, field, value)
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if embedding_model_changed:
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# Vectors from the old model have a different dimensionality/space;
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# clear them so the post-turn task re-embeds with the new model.
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# This covers only this user's adventures, because settings are per
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# user now.
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#
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# Both columns, and the flag. This is the one place that clears vectors
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# in bulk rather than through memorybank.set_vector, and when the
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# vectors moved to embedding_blob it kept nulling the old JSON column
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# alone. The blob survived, `embedded` stayed true, and
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# `_embed_pending`, which selects rows where `embedded IS FALSE`, never
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# found the rows. The bank kept ranking against the previous model's
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# vectors.
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owned = (
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db.query(models.Adventure.id)
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.filter(models.Adventure.user_id == user.id)
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.scalar_subquery()
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)
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db.query(models.Memory).filter(models.Memory.adventure_id.in_(owned)).update(
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{"embedding_blob": None, "embedded": False}, synchronize_session=False
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)
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# No cache invalidation needed, and deliberately none added: clearing
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# `embedded` drops these rows out of the catalogue query, so retrieval
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# stops asking for them, and by the time _embed_pending puts one back
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# it has gone through set_vector, which evicts that entry. The rule
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# holds: anything that removes a memory from play corrects itself.
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db.commit()
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return settings
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async def list_endpoint_models(cfg: auth.ProviderConfig) -> dict:
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"""Fetches the endpoint's /models listing.
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The call also serves as a connectivity check, so a failure returns
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`{"ok": False, "detail": ...}` rather than raising.
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"""
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# SSRF guard. Never probe a non-public address the user supplied.
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reason = await run_in_threadpool(netguard.endpoint_block_reason, cfg.endpoint_url)
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if reason:
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return {"ok": False, "detail": f"Can't reach that endpoint — {reason}."}
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url = cfg.endpoint_url.rstrip("/") + "/models"
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headers = {}
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if cfg.api_key:
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headers["Authorization"] = f"Bearer {cfg.api_key}"
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try:
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async with httpx.AsyncClient(timeout=10, verify=tlstrust.ssl_context()) as client:
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resp = await client.get(url, headers=headers)
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except httpx.HTTPError as exc:
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return {"ok": False, "detail": f"Connection failed: {exc}"}
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if resp.status_code != 200:
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return {"ok": False, "detail": f"HTTP {resp.status_code}: {resp.text[:300]}"}
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models_available: list[str] = []
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try:
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data = resp.json()
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models_available = [m.get("id", "?") for m in data.get("data", [])]
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except (ValueError, AttributeError, TypeError):
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pass # The body is not JSON or has an unexpected shape. The endpoint
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# is still reachable.
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return {"ok": True, "models": models_available}
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@router.post("/test")
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async def test_connection(
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request: Request,
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db: Session = Depends(get_db),
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user: models.User = Depends(auth.get_current_user),
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):
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"""Runs a cheap connectivity check against whatever the turn engine would use.
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That includes the shared demo endpoint, when the user has no key of their
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own.
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"""
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limits.rate_limit("connection-test", request, user)
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settings = get_settings(db, user)
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return await list_endpoint_models(auth.resolve_provider_config(settings))
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