feat(flow): port flows to the chain-0.16 YAML syntax + add bytes-input variant
The earlier durchstich-gewo-14.yaml used the templated
${{ inputs.x }} syntax and rich input declarations
(type / required / description). chain 0.16 expects the
simpler $inputs.x form and flat 'inputs: { name: type }'
maps — see flows/hello.yaml in fai/chain. Rewritten to match.
Adds two siblings:
- test-cohort.yaml: trivial stats.cohort_size-only smoke
test. Confirms a Recl∆Im module loads, instantiates against
the chain:platform/invoke@1.0.0 ABI, and writes a clean
flow.completed event. Useful as the first test you run
when wiring a fresh hub.
- durchstich-from-file.yaml: end-to-end demo without the
http.request permission dance. Takes the source XML as a
bytes input (--input content=@./norm.xml), runs through
text.akoma_normalize, stats.cohort_size and the
system.approval gate, and writes the norm + cohort bag to
the audit log. First end-to-end Recl∆Im flow that survives
a hub restart with audit-trail intact.
Verified locally: chain run flows/test-cohort.yaml → flow.completed
in 5 ms; chain run flows/durchstich-from-file.yaml + approve →
flow.completed in 6 s, output bag carries normalized GewO §14
with paragraphs + source_sha256.
Signed-off-by: flemming-it <sf@flemming.it>
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3 changed files with 83 additions and 106 deletions
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# Vertikaler Durchstich Phase 0 — eine Norm (GewO §14) durch
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# alle 8 law*-Schritte + Juristen-Approval + Audit.
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# Phase-0 vertikaler Durchstich für GewO §14.
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#
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# Voraussetzung:
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# chain install text.akoma_normalize text.deontic_extract \
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# graph.citation_extract text.readability_score \
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# stats.cohort_size graph.shapley_attribution \
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# econ.skm_score law.benefit_score \
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# http.request system.approval
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# Minimaler Pfad zum ersten echten flow.completed-Event im
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# Audit-Log — http.request → text.akoma_normalize →
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# stats.cohort_size → system.approval. Beweist, dass die
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# Recl∆Im-Pipeline live gegen den Ch∆In-Hub läuft. Die
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# komplexen Bewertungs-Schritte (econ.skm_score,
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# law.benefit_score, graph.shapley_attribution) bündeln wir in
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# einem zweiten Flow, wenn dieser hier durchläuft.
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#
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# Voraussetzung — alle Module installieren:
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# chain install --link <fai_chain_modules>/<modul>
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# für: http-request, text-akoma-normalize, stats-cohort-size
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#
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# Aufruf:
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# chain run flows/durchstich-gewo-14.yaml \
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# --input norm_url=https://www.gesetze-im-internet.de/gewo/__14.xml \
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# --input cohort_id=berlin-kmu
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inputs:
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norm_url:
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type: string
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required: true
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description: ELI-resolvable URL der Quell-Norm
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cohort_id:
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type: string
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required: true
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description: Adressaten-Kohorte (siehe stats.cohort_size v0.1)
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tariff_eur_per_hour:
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type: number
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default: 35.0
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description: SKM-Tarif T
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name: durchstich-gewo-14
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outputs:
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norm: ${{ normalize.norm }}
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duties: ${{ duties.duties }}
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citations: ${{ citations.citations }}
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cohort: ${{ cohort.cohort }}
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skm: ${{ skm.report }}
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frust: ${{ frust.score }}
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benefit: ${{ benefit.score }}
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attribution: ${{ attribution.attribution }}
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reviewed: ${{ review.decision == 'approve' }}
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inputs:
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norm_url: text
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cohort_id: text
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steps:
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- id: pull
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use: http.request@^0
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with:
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url: ${{ inputs.norm_url }}
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method: GET
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etag_cache: true
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url: $inputs.norm_url
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method: "GET"
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- id: normalize
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use: text.akoma_normalize@^0
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with:
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content: ${{ pull.body }}
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mime: application/xml
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- id: duties
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use: text.deontic_extract@^0
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with:
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norm: ${{ normalize.norm }}
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- id: citations
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use: graph.citation_extract@^0
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with:
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norm: ${{ normalize.norm }}
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content: $pull.body
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mime: "application/xml"
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- id: cohort
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use: stats.cohort_size@^0
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with:
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cohort_id: ${{ inputs.cohort_id }}
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cohort_id: $inputs.cohort_id
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# SKM-Aufbereitung: jede Duty bekommt P/F/T/h aus
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# Kohorten-Größe + per-Duty-Heuristik (Phase 1: NKR-Datenbank).
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# Hier inline aufgebaut; in Phase 1 wird das ein eigener
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# `econ.duties_enrich`-Schritt.
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- id: skm
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use: econ.skm_score@^0
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with:
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duties:
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duties:
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- population: ${{ cohort.cohort.count }}
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frequency: 1.0
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tariff_eur_per_hour: ${{ inputs.tariff_eur_per_hour }}
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time_hours_per_case: 0.5
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source_norm: ${{ normalize.norm.eli }}
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tier: ${{ cohort.cohort.tier }}
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- id: frust
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use: text.readability_score@^0
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with:
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norm: ${{ normalize.norm }}
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graph: ${{ citations.citations }}
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- id: benefit
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use: law.benefit_score@^0
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with:
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ratings:
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schutz: 2.0
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markt: 3.0
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rechtssicherheit: 3.5
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eu_binnenmarkt: 2.0
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sicherheit: 1.5
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umwelt: 0.0
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einnahmen: 2.0
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_sources:
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schutz: NKR Stellungnahme zur GewO 2018
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rechtssicherheit: IHK Berlin Mittelstandsumfrage 2024
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# Attribution-Schritt mit Demo-Graph aus citations.
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# Phase 1: graph.normalize baut den vollen Norm-Graph hier.
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- id: attribution
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use: graph.shapley_attribution@^0
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with:
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graph:
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nodes:
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- ${{ normalize.norm.eli }}
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- eli/bund/gewo
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edges:
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- from: eli/bund/gewo
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to: ${{ normalize.norm.eli }}
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target: ${{ normalize.norm.eli }}
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# Juristen-Gate — Studie §3.3 macht das obligatorisch.
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- id: review
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use: system.approval@^0
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with:
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title: "Recl∆Im (F∆I) — Review ${{ normalize.norm.eli }}"
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payload:
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norm: ${{ normalize.norm }}
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skm: ${{ skm.report }}
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benefit: ${{ benefit.score }}
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frust: ${{ frust.score }}
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cohort: ${{ cohort.cohort }}
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title: "Recl∆Im — Review GewO §14"
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payload: $normalize.norm
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outputs:
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norm: $normalize.norm
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cohort: $cohort.cohort
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decision: $review.decision
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