Kjell Tore Guttormsen
d6d83d42b5
Closes maalbilde §5 gap #1 (the one missing "feedback-into-prompt" dataflow) for the OKF-bundle path. Before, ExpeL was computed AFTER generation into a discarded SessionContext, so a prior verdict could not influence any hypothesis (context_providers=0). - New okf.py: framework-neutral OKF bundle navigation (index + frontmatter + cross-links), pure stdlib, no agent_framework/mcp (D7-portable), enforced by test_okf_is_maf_free. - verdicts.py: seed_store_from_bundle + bundle_candidate_features build the ExpeL substrate + the pre-hypothesis query key from a bundle. - run_project(bundle_dir=...): folds the candidate's prior verdicts into the generation context BEFORE generate_via_llm; the road path is unchanged. Load-bearing (maalbilde §7): test_step1_expel_loadbearing proves a prior verdict reaches the hypothesis prompt and goes RED when the fold is detached (shown via TDD red->green). The marker is the minted verdict id (content hash) because docs_dir==bundle_dir lets keyword chunk-stuffing leak the realization rate; clean layer separation is Fase 2b. Suite 121->133 passed; mypy + ruff check clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MHR8iKxJRxDiDfNw8HZmWE
37 lines
3 KiB
Markdown
37 lines
3 KiB
Markdown
# portfolio-optimiser
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Generic, open framework on **Microsoft Agent Framework (MAF)** for finding cost-savings / efficiency proposals *within* each project of a portfolio of independent projects. Multiple agents collaborate to generate candidate proposals; a mandatory deterministic validator (solver + Monte Carlo) decides the numbers; domain experts review via human-in-the-loop, and the system learns from their verdicts.
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> **Status:** Early development. The deterministic backbone is solid; the agentic learning loop is being wired one load-bearing seam at a time — **Step 1 (OKF context → hypothesis) is wired** (see below). Not yet end-to-end usable.
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> **Disclaimer — technical framework only.** This project is a *technical framework*. Organizations that deploy it are themselves responsible for ensuring a valid processing purpose and for any required assessments (DPIA, risk/ROS, security reviews, etc.). The framework ships technical affordances (local-only mode, provenance/audit logging, no silent data egress) to *enable* compliant use, but makes no compliance guarantees.
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## Design philosophy
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The result will never fit any single customer 100%. The goal is a **~90% genuinely generic core plus clear extension points**, so competent people can configure the last mile per customer. We deliberately do not chase the final 10%.
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## Agentic loop — wiring status
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The mandatory deterministic backbone (validator + budget meter + provenance) is solid and load-bearing. The agentic learning loop (see the [target picture](docs/plan/2026-06-26-maalbilde-agentic-loop.md) §11) is wired one seam at a time:
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- **Step 1 — OKF context → hypothesis (wired).** `run_project(..., bundle_dir=...)` navigates a project's [OKF bundle](shared/examples/bygg-energi-mikro/) and folds the candidate's prior expert verdicts (ExpeL retrieval) into the hypothesis prompt *before* generation — so a prior verdict provably influences the next hypothesis. Guarded by a load-bearing test that fails when the seam is detached (`tests/test_step1_expel_loadbearing.py`).
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- **Steps 3–8** (checker gating, informed refinement, async file feedback, gated wiki promotion) — not yet wired.
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## Docs
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- [`docs/plan/2026-06-26-maalbilde-agentic-loop.md`](docs/plan/2026-06-26-maalbilde-agentic-loop.md) — target picture: the agentic cost-saving loop + OKF knowledge architecture (north star).
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- [`docs/research/2026-06-23-prior-art-platform.md`](docs/research/2026-06-23-prior-art-platform.md) — prior-art & platform research (incl. implementation register §15).
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- [`docs/plan/2026-06-23-incremental-plan.md`](docs/plan/2026-06-23-incremental-plan.md) — incremental delivery plan (deterministic backbone).
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- [`shared/`](shared/) — framework-neutral shared core (concept + example OKF knowledge bundles), reused unchanged by both reference implementations.
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## Stack
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Python ≥3.10 · MAF (`agent-framework`) · `uv`. Backend profiles: Azure/Foundry (full) + local (fallback).
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## Develop
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```bash
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uv sync
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uv run pytest
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uv run ruff check .
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```
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