portfolio-optimiser/docs/extending.md
Kjell Tore Guttormsen ae01127510 docs(truth): S1 truth maintenance — CHANGELOG, stack line, MCP claim, conflict semantics, 90% cut-list
Findings 4-7 from the 2026-07-02 status analysis, per the session plan (S1):
- CHANGELOG rewritten truthfully (was: 'Plan phase - no framework code yet')
- README stack line names the split GA packages, not the agent-framework meta-package
- CLAUDE.md: MCP downgraded to extension point (in-process FunctionTool is the default seam)
- Verdict conflict semantics documented as chosen (store first-write-wins per id,
  disk/wiki last-write-wins per file; full B10 taxonomy deliberately deferred)
- docs/extending.md: explicit 90%-principle cut-list (B10, B11, U12, U14, concurrent fan-out)
- .gitignore covers .trekexecute-progress-* (docs/.DS_Store was already untracked/ignored -
  the plan's git rm --cached assumption was stale; no-op)

No code behavior changed (docstring only in verdicts.py). Suite 152/4 green, mypy clean,
ruff format --check clean.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01AaQCFnfsh3tfq1VfzdJpoi
2026-07-03 00:34:56 +02:00

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4.7 KiB
Markdown

# Extending the framework (extension points)
portfolio-optimiser is a generic core with explicit **config seams** (D4/D5, 90 %-prinsippet):
you onboard a new project, a new data source, or a new model-map **without editing the core
`src/portfolio_optimiser/*.py`**. The three guides below name the exact seam for each.
> **Honesty note (rent teknisk rammeverk).** The bundled reference domain
> (`data/reference_projects.json` + `data/docs/<id>/`) is a set of **SYNTHETIC, AI-authored
> fixtures** — fictional construction-cost projects, dummy estimates, and placeholder
> `verdict_input` decisions. They are flagged in each file's `_note`. A production deployer
> **replaces the data source** with their own and supplies **Layer-2 verdicts via real HITL**
> (fageksperter), not static config. The static `verdict_input` field is a test-fixture
> convenience that stands in for the durable HITL verdict in the offline synthetic framework.
## Legg til eget prosjekt
A new project is **config + docs only** — no code change (this is exercised by the SC1 test
`test_e_new_project_flows_through_via_config_only` + the `test_f_no_hardcoded_project_ids_in_src`
guard, which fails if any project id leaks into `src/`).
1. Append an entry to `src/portfolio_optimiser/data/reference_projects.json` with the full key
set: `id`, `name`, `description`, `currency`, `cost_items`, **`docs_dir`**, and
**`verdict_input`** (`{"decision", "rationale"}`).
- `docs_dir` is a path **relative to the package `data/` root** (e.g. `"docs/MY-PROJECT"`);
the loader (`reference_domain.load_reference_projects`) resolves it to an absolute path.
- `verdict_input` carries the (synthetic) Layer-2 decision/rationale; flag it in the file's
`_note` as synthetic if it is not a real expert verdict.
2. Create the bundled docs folder `src/portfolio_optimiser/data/docs/<id>/` with at least one
text file whose content names the cost-saving measure/terms (so `retrieve_chunks` returns at
least one citable chunk).
3. Run the project: `run_portfolio(["MY-PROJECT"], "local", client_factory=...)` (or include it
in the default fan-out by passing no `project_ids`).
## Legg til egen datakilde
The retriever (`retrieval.py` / `datasource.py`) reads a **local docs folder** per project,
selected by the project's `docs_dir` in `reference_projects.json`. To point a project at your own
data, change its `docs_dir` to your folder and drop your cost documentation there — the citation
seam (`{file, locator, snippet, score}`) is identical on the in-process tool and MCP paths. The
folder is boundary-checked (fail-closed) against path traversal, so keep documents inside the
configured `docs_dir`. A real deployer swaps the bundled synthetic docs for their own source.
## Legg til egen modell-map
Model choice is **config, not code** (B12): `src/portfolio_optimiser/data/model_map.json` maps
`profile -> role -> model/deployment` (`resolve_model(profile, role)`). To use your own models:
- Edit the `local` block to your local model ids (Ollama/LM Studio), and/or
- Edit the `azure` block to your Foundry deployment names (the placeholders
`REPLACE-WITH-FOUNDRY-DEPLOYMENT` are tenant-specific — replace them or supply via env).
The role keys (`proposer`, `checker`, `default`) let you assign a distinct model per debate role;
`default` is the fallback when a role is unmapped.
## Bevisst ikke bygget (90 %-kuttlista)
Per the design philosophy (a ~90 % generic core with clear extension points — we do not chase
the last 10 %), the following are **deliberate cuts**, not roadmap debt. Each is extension
territory for a deployer, with the seam named:
- **B10 — full verdict-conflict taxonomy.** Chosen minimal semantics (documented in
`verdicts.py` + README): the in-memory store is first-write-wins per verdict id; the disk
layers (`write_verdict`, `promote_verdict`) are last-write-wins per file. The full taxonomy
(rejection categories + a rule for conflicting expert verdicts) is deferred until real experts
produce conflicting verdicts.
- **B11 — expert notification.** `run_project(notify=...)` is a stub seam (`run.py`): pass any
callable; no delivery mechanism (e-mail/Teams/webhook) ships with the core.
- **U12 — checkpointing / crash-survival of a run.** A run either completes or is re-run; the
async verdict inbox (step 7) is the resumable boundary, not intra-run state.
- **U14 — OpenTelemetry / observability.** Provenance stamping is the audit trail the core
ships; OTEL wiring is a deployer concern.
- **Concurrent fan-out.** `run_portfolio` iterates projects sequentially by design (fresh
per-project execution state; one threaded `VerdictStore`); parallel orchestration is left to
the deployer and would need budget-cap coordination.