portfolio-optimiser/CHANGELOG.md

# Changelog

All notable changes to this project will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [1.1.0] - 2026-08-14

The release that makes the distribution stand on its own. `1.0.0` shipped a framework that could
only run from a checkout; this one runs from an installed wheel and inside a Foundry-hosted
container, and it is the first release whose artefacts are published alongside it.

### Added
- `shared/` now travels **as packaged data**. The wheel carries a byte-identical mirror of the tree
  under `portfolio_optimiser/_shared/`, and `shared_root()` resolves at call time in a fixed order:
  `PORTFOLIO_SHARED_ROOT`, then the working tree's `shared/` when one exists, then the packaged
  copy. The working tree stays authoritative in a checkout — that is what keeps the pull-only
  subtree contract and the byte-exact goldens untouched. Measured before and after: the `1.0.0`
  wheel carried 58 files and none under `shared/`; this one carries 122, of which 64 are the mirror.
- A **hosted entry point**: `main.py` wraps `run_project` on a single asyncio loop and serves the
  Foundry hosting contract (`GET /readiness`, `POST /invocations`, SIGTERM → exit 0), with a
  `Dockerfile` and `azure.yaml` beside it. The invocation payload is whitelisted against
  `run_project`'s own signature — an unknown field is refused by name with a 400 rather than
  silently dropped — and a rejected proposal is a successful run (200), because the negative outcome
  belongs to the payload and never to the transport.
- Wheel-install instructions in the README. A wheel is not installable on its own: two dependencies
  are pinned to git tags, and `[tool.uv.sources]` does not travel with wheel metadata, so both must
  be supplied as requirements alongside the wheel. The published command is the one that was
  measured (65 packages, exit 0), not one composed afterwards.
- Two gates on claims the **published surface** makes about itself: that `env.template` names the
  credentials `backends.py` actually constructs, and that the README's wheel-install command spells
  the version the build stamps on the file. Both read raw text and are line-anchored, because prose
  is the only place these claims live.

### Changed
- The AZURE profile now reads **its own environment** rather than the operator's laptop. The
  endpoint resolves to the first non-empty of `PORTFOLIO_FOUNDRY_PROJECT_ENDPOINT` and Foundry's
  injected `FOUNDRY_PROJECT_ENDPOINT`; precedence applies to *values*, so an exported-but-empty name
  falls through instead of masking a real one. The credential follows the same environment:
  `AzureCliCredential` on a developer host, `ManagedIdentityCredential` when
  `FOUNDRY_HOSTING_ENVIRONMENT` holds a non-empty value — never `DefaultAzureCredential`, whose
  probing would walk a credential chain that cannot succeed in a container and turn a config error
  into a slow one.
- `SECURITY.md` states a **deprecation notice period**: at least one minor release and no fewer than
  30 days between announcement and removal, with security-critical removals named as the explicit
  exception. The supported-versions table is deliberately version-free, since a release number
  written there would drift at the next tag.
- The README links the organisation's single canonical `GOVERNANCE.md` instead of vendoring a copy,
  and states the maintenance model (solo-maintained, no SLA, fork-and-own) on the first screen.
- `CLAUDE.md` opens with an English note explaining what the file is for a visitor: the working
  agreement with the AI agent that builds this repository, doubling as its invariant ledger.

### Fixed
- `env.template` claimed the AZURE profile resolved its credential through `DefaultAzureCredential`.
  It never has. An operator copying the template was told the wrong identity would be used.

## [1.0.0] - 2026-08-12

### Added
- Step 5 is now observable: `generate_via_llm` returns a `GenerationResult` carrying the validator
  falsifications that informed a later attempt, surfaced on `RunResult.refinements`. The offline
  simulation exercises it — the scripted proposer overclaims, the deterministic validator falsifies
  the number, and the refined proposal validates.
- Two console entry points ship with `uv sync`: `portfolio-optimiser` (the CLI) and
  `portfolio-optimiser-demo` (the offline walkthrough). Deliberately two of the package's five
  `main()` functions — `costsim`, `hitl` and `preflight` stay operator tools invoked as modules, and
  every name here is one a release has to carry. Both invocation forms write byte-identical stdout.
  The entry points are tested against the INSTALLED distribution's metadata rather than the TOML: a
  `[project.scripts]` line that has never been synced is a claim, not a command.
- The offline walkthrough's transcript is checked in as a golden fixture
  (`tests/golden/demo-transcript.stdout` and `.stderr`). Self-identity across two runs cannot detect
  a regression — two runs of a regressed walkthrough agree exactly as well as two runs of a correct
  one — so the fixture leaves the process. stdout is pinned verbatim; stderr is normalised on exactly
  two measured environment spans, the `site-packages` prefix and the temporary directory, leaving the
  `po-sim-` prefix visible because that belongs to the program rather than the environment. A
  companion control forbids the mask from widening: a normaliser that dropped whole lines, with the
  fixture regenerated beneath it, would keep both equality tests green.

### Changed
- **Breaking (library API):** `generate_via_llm` returns `GenerationResult` instead of
  `ValidatedProposal | Rejection`; read `.outcome` for the previous value. The refinement loop's
  bound is unchanged (`max_attempts` + token meter).
- `simulation.scripted_factory` accepts a per-role reply *selector* over `(prompt, role)` as well as
  a constant reply, so a scripted role can answer differently on a later attempt.
- The offline simulation's scripted proposer is now a candidate **registry** rather than a
  hand-written reply: `simulation.scripted_proposer(candidates)` builds the selector from
  `ScriptedCandidate` entries keyed on the project id the prompt names, and
  `simulate_learning_loop` takes `project_id` alongside `bundle_dir`. Adding a project to the
  walkthrough is a data entry. A prompt matching no entry — or more than one — raises
  `ScriptedCandidateError` rather than answering with another project's numbers.
- The offline simulation now EXERCISES the Step-7 file inbox it narrates. The verdict previously
  arrived as a function argument — the short, in-run capture — while the trace line described the
  long file loop. An expert now writes a real verdict file into an inbox between the two runs, and
  the second run is given `verdict_dir=`, so `run_project` merges it before the Step-1 fold. The
  inbox sits beside the bundle copy and never inside it: a verdict file within the bundle would reach
  the next run as navigable context, which is a different mechanism wearing this one's clothes. The
  two time-scales carry SEPARATE markers by construction, since one marker on both paths would let
  either seam alone satisfy the assertion and leave the other free to rot; `simulate_learning_loop`
  refuses equal markers.
- The offline walkthrough runs ANCHORED. Its deterministic gate reconciles each proposal against the
  project's real cost lines, which activates only when the knowledge base ships a `cost-baseline.json`;
  without one the gate reasoned solely about numbers the proposal supplied itself. The walkthrough now
  reads that file through exactly the seam a delivered knowledge base would use. For the synthetic
  fallback bundle, which cannot receive the file inside the pull-only `shared/` subtree, the baseline
  is DERIVED IN CODE from the scripted register rather than typed beside it — two sources of the same
  numbers drift, and drift is precisely what the walkthrough's own 10 % probe models. The declared
  baseline is printed, because an anchoring nobody can see is one nobody can check.
- The walkthrough's stderr is quieter. The expected round-cap notice is dropped by a filter on the
  emitting logger, keyed on the message and installed by `main()` — never at import, so a library
  consumer keeps its own logging configuration. The two `ExperimentalWarning` lines are deliberately
  NOT damped: they fire while the package `__init__` imports the agent framework, always before the
  simulation's own imports and under both invocation forms, so silencing them would mean filtering
  warnings inside the library on every consumer's behalf. They are pinned in the golden fixture
  instead. stderr went from six lines to four.
- The walkthrough DERIVES its provenance sentence for prior verdicts instead of stating it. The line
  above already computes the count, so a hand-written split would be a second copy of the same fact,
  free to drift the moment a knowledge base ships another seeded verdict.
- The shared expert-reviewer persona's canonical example verdict is worded domain-neutrally
  ("i tilsvarende anlegg" rather than "i kontorbygg"), pulled from the upstream commons repository.
  The walkthrough prints that `rationale` verbatim, so the wording was a building-type justification
  read out over a road-lighting project; it could not be fixed downstream, because overriding the
  text locally would re-stub the very artifact the shared skill exists to make load-bearing. The
  `marker` value is byte-unchanged, and the pinned transcript fixture was regenerated against a
  prediction written before the pull — the printed line is clipped at a fixed width, so the swap
  moves the tail as well, and a regeneration without a written prediction could not tell that
  expected shift apart from drift.

### Security
- Door A — the ingest path that materialises externally sourced documents into a knowledge base — can
  now scan generated content before it is published, through `ingest.materialize_gated`. The gate is
  **opt-in and requested by name**: `materialize` itself stays ungated by design, because golden
  suites pin its bytes and a caller that wants the gate asks for it.
  The seam sits *around* materialisation rather than inside it. The pinned upstream stages in memory
  and then performs its own disk phase, with no callback between the two, so a gate placed "at the
  write point" could only have run after the bytes had landed — a cleanup, not a gate. Instead the
  bundle is COPIED, materialised into the copy, scanned, and then published or discarded as a whole.
  The copy is load-bearing rather than convenient: the upstream's ownership scan, its collision gate
  against curated content, and its index merge all read the EXISTING bundle, so staging into an empty
  directory would publish a bundle stripped of its curated neighbours and their index links — data
  loss dressed as a security fix.
  Trust follows ORIGIN, never channel. The outcome is per BUNDLE, since partial publication would
  leave a bundle and index answering to no manifest, while diagnostics are per DOCUMENT so a single
  run reports every finding rather than only the first. Findings are written to the bundle's `log.md`
  and never to concept frontmatter, where four golden suites pin the bytes.

### Notes
- The `1.0.0` version signals a stable public surface, not a finished research programme. Two
  boundaries are open and named rather than implied: the ingest stamp predicate has diverged from the
  upstream specification (a value literal here, a structured field upstream) and does not touch the
  run path, and the mirroring of several seams to the sibling implementation is outstanding.

## [0.1.0] - 2026-08-06

First tagged release. There is no prior release, so the entries below describe what this version
**is**, not what changed since a predecessor.

### Added
- Deterministic backbone: mandatory blocking validator (solver + Monte Carlo against the shared
  golden suite), budget meter with hard fail-fast caps, provenance stamping.
- Agentic learning loop wired end to end, one load-bearing seam at a time (target-picture steps
  1, 3/4, 5, 7, 8): OKF-navigated bundle context with the gated ExpeL fold, maker-checker debate
  where the checker gates the reasoning, informed refinement (previous rejection reason fed into
  the next bounded attempt), async verdict file inbox, and gated wiki promotion (fail-closed).
- Offline end-to-end simulation proving the learning loop closes with a scripted client
  (`uv run python -m portfolio_optimiser.simulation`) — plumbing proof, not live-model proof.
- Framework-neutral shared core in `shared/`: OKF concept + example bundle, golden validator
  suite, and the expert-reviewer persona as an Agent Skill.
- CLI parity (S5.3): `run.py` drives the whole method from the command line in **two modes** —
  single-project (`--dimension-config`, `--outbox-dir`/`--run-id`, plus the already-wired
  `--bundle-dir`/`--verdict-dir`) and portfolio (`--portfolio` with `--goals`/`--ledger`), the
  latter printing an observable `goal reached: …` line when a savings goal is met. Adds a
  fail-fast `load_dimension` loader and structured refusals (rc 1, no traceback) for misuse and
  mode-exclusivity violations. The prior-verdict fold is on the `--bundle-dir` path only; a
  `--docs-dir`-only run is single-shot.
- Value report (S5.4): a read-only `--report [--json] --ledger <file>` surface on `run.py` that
  rolls up the accumulated `SavingsLedger` — per-project + portfolio totals (dimension-free-deduped
  integer øre), flagged cross-dimension overlaps (each counted once), and per-entry provenance — as
  a human table or deterministic JSON. Makes no model calls; mode-exclusive (only `--ledger`/`--json`
  permitted with `--report`, which requires `--ledger`). Honest scope boundary: the report core
  (`value_report.py`) now **exists** but is deliberately **not** wired into `costsim`'s
  `kost_mot_verdi` placeholder — that cost-vs-value integration is a separate, deferred step. The
  `costsim` seam note was reworded from the stale "fylles av S5.4 verdirapport" to a truthful
  forward reference so `costsim`'s own output no longer claims the wiring is done.
- Semantic retrieval seam (S3.1): a new MAF-free `semretrieval.py` adds an `Embedder`/`Retriever`
  pair and a `HybridRanker` blending a numpy cosine term over the embedded feature triple (sorted
  cost codes, measure type, magnitude bucket) with the existing structural score, exposed as
  `--semantic-retrieval`. **What ships is the seam, not better retrieval quality**: the bundled
  `FakeEmbedder` is a deterministic sha256 projection with no semantics, so over a structural tie
  the order is deterministic but arbitrary. A real embedder is selected from a CLOSED registry via
  `--embedder-config` / `build_embedder` — deliberately never an import path, so a config file can
  never name arbitrary code to load.
  **Off by default and additive**: with no retriever passed the store delegates to
  `StructuralRetriever`, which reproduces the pre-seam ranking exactly, so the text-excluded
  default and every existing test are unchanged. The embedding excludes `description`, matching
  `similarity` ("text is ignored by design") and the verdict-id hash — so a flag-on run reads no
  surface text either, and a genuine expert verdict can no longer be outranked by the framework's
  own echo of the query. The ranker is passed PER CALL, never assigned to the caller's store, so
  the opt-in cannot outlive the run that asked for it. Accepted in both run modes; in
  single-project mode it requires `--bundle-dir` and `--verdict-dir` and is refused — never
  silently ignored — without them.
  Determinism, precisely: ranking order rests on the total order `(-round(score, 9), id)`; the
  BLAS thread pins set before numpy is imported (`VECLIB_MAXIMUM_THREADS` for Accelerate,
  `OPENBLAS`/`MKL`/`OMP` for other backends) defend the narrower claim that vector artifacts are
  byte-identical across environments. Ships an optional, rebuildable `vectors.npy` +
  `vectors.jsonl` store (byte-identical regardless of insertion order; fail-fast on a row/line
  mismatch; missing loads as `None`) — an authoring primitive with no caller in `src/`, offered to
  extenders like `write_verdict` and `promote_verdict`. numpy is confined to `semretrieval.py` and
  never enters `okf.py`, `retrieval.py` or `shared/`.
- Cost-baseline anchoring of the deterministic gate (S4.0): `validate_proposal(..., baseline=...)`
  reconciles every `affected_item` against the project's real `CostBaseline` in a **stage 0, before
  the solver** — two independent rejections (unknown cost code; a real code whose
  `quantity`/`unit_cost` falls outside a configurable tolerance, default 5 %, of the baseline value).
  Before this, every stage reasoned only about numbers the proposal itself supplied, so an internally
  consistent hallucination cleared the whole gate. Validation, never repair: the proposal is
  rejected, never silently corrected to the baseline. The argument is **optional** (`None` reproduces
  the earlier behaviour) but both run paths set it — the road path always, the bundle path only when
  the bundle ships a `cost-baseline.json`, since a pre-amendment bundle is legitimately unanchored.
  A baseline that exists but is malformed raises on both loaders rather than reading as "no
  baseline". Method caps are looked up in an injectable `METHOD_CAPS` registry, so a second measure
  type is data rather than an edit to the validator.
- Deterministic stage-2 bound and band enclosure in the validator (S2.7).
- Per-candidate verdict keying (S3.2): `seed_store_from_bundle` reads each `type: verdict` file's own
  structural frontmatter (`affected_codes` / `measure_type` / `claimed_saving_nok`) instead of
  collapsing a multi-candidate bundle onto the single IR projection, where a verdict about candidate
  B scored a perfect structural match against candidate A's query. All three fields or none — a
  partial declaration raises rather than being merged with the bundle candidate, which would mint a
  key belonging to neither. Bundles that declare none fall back to the previous keying, so every
  pre-S3.2 seed is unchanged.
- Portfolio concurrency (S3.3): wave-partitioned execution with a per-project snapshot and a
  deterministic merge barrier, pinned by a concurrent-equals-sequential contract test; `k < 1` is
  fail-fast. Failures are collected and the pass continues, surfaced as `RunFailure` slots rather
  than aborting the portfolio. Goal-stop is evaluated at wave boundaries, with the intra-wave
  semantics documented and pinned.
- Global portfolio token cap (S3.4/F10): `PortfolioBudget` + `PortfolioMeter` form one ledger across
  a whole portfolio pass — and, seeded from a spend file, across passes — while the per-run
  `Budget`/`TokenMeter` is unchanged. Three enforcement points: a **startup refusal** when the
  remainder cannot fund a single run; **wave admission**, where an unfundable project is never
  started (a project that is merely aborted has already cost calls) and the pass stops structurally
  with the completed runs preserved; and a **pre-call guard** in `BudgetMiddleware`, so a call the
  remainder cannot pay for is refused rather than made. Because a whole wave is checked against the
  same pre-wave remainder, admission reserves each member's requirement. Resource exhaustion is
  reported in its own `budget_stop` field, never merged into `stop_reason` — a goal stop is success.
  The spend file is our own accounting state, so corrupt content raises instead of reading as zero.
- Ingest transports (S2.2, S2.4): the MCP connector as a transport inside the http family, and a
  time-bounded default http transport in front of the pinned ingest library. A server on the ingest
  path must expose a **zero-argument tool** (the URL carries both coordinates), which is a
  deliberately separate seam from the in-run data-source demo server.
- Azure/Foundry offline preflight config gate (`preflight.py`, S4.1).
- Offline live-dry-run drill (`--live-dry-run`, S4.2): walks the whole path up to the eager
  client build and stops before the first model call — zero chat calls.
- Out-of-band HITL verdict routing CLI (`hitl.py`, S5.1): code-prefix routing on the candidate id.
- Expert-notification contract (`notify.py`, S5.2): the declared `Notifier` with `ConsoleNotifier`,
  `FileNotifier` (byte-deterministic JSONL), and `WebhookNotifier`, plus a fail-fast
  `build_notifier`; the webhook is the only egress point, fail-closed behind an explicit per-run
  `allow_egress` opt-in. Not auto-wired into `run.py`.
- Offline whole-loop CLI door (`--scripted-replies`): drives the entire method over the caller's own
  data with no model budget, in **both** run modes. Resolved before the portfolio dispatch, because
  placing it after made `--portfolio --scripted-replies` silently drop the flag and attempt four real
  model calls (measured). Mutually exclusive with `--live-dry-run`: both are offline and they
  contradict, so the combination is refused rather than letting one quietly win.
- Run mandate (`mandate.py`, `--mandate`): a domain expert commissions **which approaches** a run
  evaluates, the run announces what it will do before doing it, and it settles for that — every
  commissioned approach is evaluated and every one appears in a coverage report. A mandate is not a
  dimension (`dimension.admits` filters what may pass the scoping gate; a mandate directs what the
  run spends its attempts on) and not a goal (the numeric target keeps its single home in
  `GoalContract`/`--goals` and is merely restated in the announcement). Two construction-time
  refusals: an empty commission, and a duplicate approach id — including one claiming the reserved
  `own-proposal` — since the id keys each coverage row and two rows under one key collapse silently.
  Pure module: pydantic + stdlib only, D7-portable, guarded MAF-free.
- MCP servers as in-run tools (`mcp_tools.py`, `--mcp-config`): concrete external servers become
  tools the agents can call **during** the debate. Opt-in and additive — with no config there are
  zero network calls and the tool list is unchanged. Three rules are load-bearing: an **allowlist is
  required** (an empty one would let the far end decide what the agents may call), **every server and
  every permitted tool is named in the announcement before the first call** (also without
  `--mandate` — no undeclared egress), and `--live-dry-run` opens nothing. A malformed config is
  refused rather than degraded to "no external services", which would make the announcement describe
  a run nobody configured. This is a separate seam from the ingest-path MCP transport above.
- Per-approach outbox artefacts: a run commissioned to evaluate three approaches previously wrote one
  proposal artefact, so only the selected approach could ever receive a verdict and the others taught
  the learning loop nothing. Artefacts are now keyed `{run_id}-{approach_id}-*.json` and carry
  `approach_id` in the payload, with the join key `(run_id, approach_id)` — widening only the
  filename would not have worked, because the reader joins on the `run_id` field read from file
  content. Two properties make them genuinely judgeable: `verdict_id` is minted per approach (so one
  delivered verdict cannot clear all three from the queue), and `provenance.validator_decision`
  follows its own approach rather than the run's. `verdicts.verdict_key` is the single public
  verdict-key rule.
- External-call provenance: the egress declaration says what a run **may** contact;
  `ToolCallRecorder` records what it **did**, landing on `ProvenanceStamp.external_calls` read after
  the debate. It only observes — `call_next` is always awaited, so a trace can never alter the run it
  traces. Only configured tools are recorded; logging in-process functions would turn the record into
  a false egress claim, and an empty list is therefore a positive statement that nothing outside the
  process was contacted. Attribution comes from our own config because MAF reports the bare tool name
  with no server prefix (measured, not assumed), so a name allowed by two servers is recorded
  unattributed rather than credited to the first match. Stated honesty limit: this is the call and
  its source — not evidence that the service's answer reached the proposal.
- `docs/knowledge-base-recipe.md` (S5.3, D-H item 1): the documented team process (technical +
  domain expert) for building a knowledge base, with the honest 1–2 week expectation.
- Test suite: 755 passing tests (4 skips are live-provider-only). Every wired seam is covered by a
  load-bearing test that goes red when the seam is detached, and each carries a recorded detach point
  verified by mutation. That property is maintained by measurement, not by assumption, and this
  release contains two recorded cases where it did not hold until it was checked: the S3.1
  `--semantic-retrieval` flag was covered only below the CLI, so hardcoding it off at `main()` level
  left the suite green; and four of the five `BudgetExceeded` raise sites could report any value in
  the `observed` field without a single test noticing. Both are now pinned.

### Fixed
Defects found and closed before this first tag. Nothing here was ever released; they are recorded
because each one changed an invariant an adopter depends on.

- Money quantisation happens in one order, from one source: `ledger.to_ore` is the framework's single
  NOK→øre conversion, applied **per amount**, after which integers are summed. Previously the goal
  baseline summed floats and quantised once while the ledger summed per-candidate integers, and the
  two orders met in exactly one place — the check that decides whether a portfolio pass stops early
  on a percentage goal. Measured divergence: three lines of `60000.005` NOK are `18000003` øre
  quantised first but `18000001` summed first, enough to flip a goal. Both call sites were fixed; a
  fix to only one survived the whole suite (measured).
- The MCP stdio ingest transport now runs against a real server, and its error contract is repaired:
  `stdio_client` and `ClientSession` are each a task group, and anyio wraps everything leaving one in
  an exception group, so the module's own `IngestError` reached callers as an exception group and
  never as the type the ingest door switches on. The owned error is unwrapped and re-raised; anything
  else is re-raised untouched. No canned-tool test could have caught this — the defect only appears
  once the code is actually run.
- The MCP timeout composes with anyio's own cancel scope (`anyio.fail_after` nested inside both task
  groups) instead of `asyncio.wait_for` from outside, which cancelled the structure anyio owns and
  produced a `BrokenResourceError` inside an exception group rather than a timeout. The translation
  is narrowed by `CancelScope.cancelled_caught`, so only the scope that hit its own deadline earns
  the timeout code — an unconditional `except TimeoutError` would mislabel any `TimeoutError`, since
  the builtin is also `socket.timeout` and `asyncio.TimeoutError`. `anyio` is now a declared direct
  dependency rather than a transitive one.
- Frontmatter scalars are unquoted by exactly one rule (`okf.unquote_scalar`).
- A non-finite embedding is refused rather than scored.
- `--embedder-config` is refused when `--semantic-retrieval` is absent, rather than silently dropped.
- The portfolio CLI no longer swallows its offline door or its failures.
- Constants cited in the live documentation are gated against the code, so a doc and the value it
  quotes cannot drift apart unnoticed.

### Notes
- Licensed under the MIT License (see `LICENSE`).
- Scope boundary: this is a technical framework. The deployer owns DPIA, risk assessment and
  processing purpose; the framework ships only the technical preconditions (local-only operation,
  provenance, no silent egress).
- The `shared/` directory is a git subtree of `portfolio-optimiser-commons` and is pull-only.