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infra/images/bcda.Dockerfile follows api.Dockerfile (uv base, patched packages, curl for the healthcheck) with `uv sync --extra cli --extra bcda`; Streamlit's server settings live in infra/images/bcda/ streamlit.toml (headless, 0.0.0.0:8501, no usage stats, no file watcher); health is /_stcore/health. The compose service `bcda` sits on the gateway network, mounts ./data read-write (exports, aco.duckdb, replica publish) and ./dev read-only (vendored upstream, crosswalk seeds, vendor script), and takes BCDA_CLIENT_ID / BCDA_CLIENT_SECRET / BCDA_BASE_URL from .env with the public sandbox credentials as the default. Routed at bcda.<domain> behind git-sso with secure-headers, tiled on the dashboard, and added to [platform].subdomains (CoreDNS hosts and the SSO cert list follow) and [images] (deploy.yml builds, scans and pushes it on src/**, pyproject.toml or image-file changes; harden/rebuild-all/infra-ci regenerated accordingly). Built locally (2.15 GB), /_stcore/health -> ok, root -> 200; brought up on the host with compose. refs #1139
330 lines
11 KiB
TOML
330 lines
11 KiB
TOML
# stack.toml — centralised configuration for the stack platform.
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#
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# Paths are relative to the repository root unless absolute.
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# Secrets live in .env (never here).
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#
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# Context switching
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# -----------------
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# [context.active] selects the environment profile. Override at
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# runtime with STACK_CONTEXT=lake (env var beats this file).
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#
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# Each context sets db_backend and storage_backend. Modules call
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# conf.context() to decide *which* engine or filesystem to use;
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# the [db], [storage], and [lake] sections supply the concrete
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# connection details for the selected backend.
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[platform]
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domain = "fhirworx.io"
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registry = "git.fhirworx.io"
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image_prefix = "fhirworx"
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repo = "homelab/stack"
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ci_email = "ci@fhirworx.io"
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host_ip = "192.168.1.192"
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subdomains = [
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"dashboard", "docs", "git", "ci", "notebooks", "zotero",
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"webdav", "api", "nessie", "trino", "polaris",
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"grafana", "prometheus", "tempo", "loki",
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"s3", "s3console", "llm", "bcda",
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]
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[services]
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git = "http://git:3000"
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rustfs = "http://rustfs:9000"
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nessie = "http://nessie:19120"
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polaris = "http://polaris:8181"
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trino = "http://trino:8080"
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grafana = "http://grafana:3000"
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ollama = "http://ollama:11434"
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[context]
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active = "local"
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[context.local]
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db_backend = "duckdb"
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storage_backend = "local"
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[context.lake]
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db_backend = "iceberg"
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storage_backend = "s3"
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catalog = "nessie"
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[context.databricks]
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db_backend = "databricks"
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storage_backend = "dbfs"
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[context.trino]
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db_backend = "trino"
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storage_backend = "s3"
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[context.aws]
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db_backend = "iceberg"
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storage_backend = "s3"
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catalog = "glue"
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compute = "ecs"
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[context.gcp]
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db_backend = "iceberg"
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storage_backend = "gcs"
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catalog = "bigquery"
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compute = "cloud-run"
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[context.azure]
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db_backend = "iceberg"
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storage_backend = "abfs"
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catalog = "unity"
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compute = "container-apps"
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[db]
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aco = "data/aco.duckdb"
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bib = "data/bib.sqlite"
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zotero = "data/zotero/data/zotero.sqlite"
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[comments]
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seal_quiet_days = 30 # days after a docket's comment close date before an empty pull seals it
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[storage]
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bib = "data/bib/storage"
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zotero = "data/zotero/data/storage"
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bcda = "data/bcda"
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rex = "data/rex"
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pfs = "data/pfs"
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rec = "data/rec"
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cms_log = "data/cms/log.jsonl"
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bcda_log = "data/bcda/log.jsonl"
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[generate]
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table_out = "src/aco/table"
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base_import = "aco.table.base"
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[bcda]
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sandbox = "https://sandbox.bcda.cms.gov"
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production = "https://api.bcda.cms.gov"
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max_retries = 3
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retry_interval = 1.0
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token_lifetime = 1200
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timeout = 120.0
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[llm]
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ollama = "http://127.0.0.1:11434" # host-side default; containers override via LLM_OLLAMA_HOSTS
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embed_model = "nomic-embed-text" # 768-dim; bake-off (P33 #564) may revise
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instruct_model = "qwen2.5:14b" # baseline, pulled on every fleet host
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instruct_model_large = "qwen2.5:32b" # used when the chosen host declares >= large_min_vram_gb
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large_min_vram_gb = 20
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chat_num_ctx = 8192 # passed per request; no Modelfile ctx variants
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chat_temperature = 0.2 # grounded answers cite labels verbatim; low temperature keeps them literal
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chat_max_tokens = 1200 # num_predict: a history answer ran to 5,000 tokens (3 min) without a cap
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chat_chars_per_token = 2.4 # measured 2.5–2.9 on FR/regulatory text; sizes the excerpt budget so prompt + reply fit chat_num_ctx (overflow is caught and rebuilt)
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embed_dim = 768
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# HNSW index build. Safe since the postgres image ships an AVX-512-free
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# pgvector rebuild (infra/images/postgresql.Dockerfile, #580); before that it
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# SIGILLed this Zen2 host. Set false to fall back to exact search.
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build_ann_index = true
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pg_host = "127.0.0.1" # host-side default; containers set LLM_PG_HOST=postgres
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pg_port = 5432
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pg_db = "llm"
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pg_user = "llm"
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# Retrieval: similarity × recency blend (half-life in days), sources kept
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recency_half_life_days = 365
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recency_weight = 0.3
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top_n = 8
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timeline_per_era = 2 # era_balance: hits kept per rule year on the first pass (mode="timeline")
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timeline_overfetch = 6 # era_balance: k multiplier per kind for timeline mode (vs the recent-mode ×3)
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duckdb_replica = "data/replica/aco.ro.duckdb" # read-only DuckDB replica the chat reads valuations from
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valuation_years = 4 # final-rule vintages shown per code (plus the newest NPRM)
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code_cited_per_code = 3 # excerpts literally citing each detected code (or family)
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code_cited_collections = ["rules", "comments", "corpus"] # searched in this order
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code_cited_max = 12 # cited excerpts kept after round-robin interleave across collections; <= 0 = unlimited
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lineage_max_rows = 25 # collapsed lineage events kept in the prompt block (the SSE payload always carries every collapsed row)
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lineage_on_demand_max = 3 # detected codes per turn allowed to fall back to pfs.lineage.lineage() when pfs.code_event has no rows for them
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lineage_sources_max = 8 # FR paragraphs fetched as sources for events selected into the lineage prompt block, outside code_cited_max (Ruling B10: + up to 2 element-diff anchors, hard cap 10 total)
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chat_codes_max = 24 # Ruling B11: per-turn cap on detected codes (explicit codes first, then family order) — applied before valuation/lineage/code-cited queries
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valuation_rows_max = 24 # Ruling B11: valuation rows kept in the prompt block (explicit codes first, then newest vintage); the SSE payload always carries every row
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[llm.k_per_kind] # over-fetched ×3 per kind, then re-ranked
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comment = 8
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rule = 4
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corpus = 4
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[s3]
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endpoint = "http://rustfs:9000"
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region = "us-east-1"
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[lake]
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warehouse = "s3://lakehouse/"
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[lake.nessie]
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catalog_uri = "http://nessie:19120/iceberg/"
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[lake.polaris]
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catalog_uri = "http://polaris:8181/api/catalog"
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[lake.databricks]
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catalog_uri = "" # set via DATABRICKS_HOST env var
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warehouse = "main" # Unity Catalog name
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catalog = "aco" # default catalog for table references
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[lake.trino]
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host = "trino"
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port = 8080
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catalog = "iceberg"
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# DuckLake — the concurrent reference-data store chosen in the M3 spike
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# (docs/superpowers/specs/2026-07-10-ducklake-vs-iceberg-decision.md).
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# The postgres catalog serializes concurrent writers; data is Parquet on
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# RustFS. Password comes from the POSTGRES_PASSWORD env var; the catalog
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# host is compose-internal, so lake writers run inside a data-network
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# container.
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[lake.ducklake]
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catalog = "postgres:dbname=ducklake host=postgres user=postgres"
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# Read-only role for notebook readers (password: DUCKLAKE_RO_PASSWORD).
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catalog_ro = "postgres:dbname=ducklake host=postgres user=ducklake_ro"
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data_path = "s3://lakehouse/ducklake/"
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s3_endpoint = "rustfs:9000"
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# ── Databricks Asset Bundle generation ────────────────────────────
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# gen_config.py reads this to produce databricks.yml.
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# Add a new pipeline module → commit → databricks.yml updates automatically.
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[databricks]
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bundle_name = "stack"
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package_name = "stack"
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entry_point = "cli"
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schedule = "0 0 6 * * ?"
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timezone = "America/New_York"
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[databricks.clusters.default]
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spark_version = "15.4.x-scala2.12"
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node_type_id = "i3.xlarge"
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num_workers = 1
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[databricks.targets.dev]
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mode = "development"
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default = true
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catalog = "aco_dev"
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[databricks.targets.staging]
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catalog = "aco_staging"
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[databricks.targets.prod]
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mode = "production"
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catalog = "aco"
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[databricks.warehouse]
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name = "stack-sql-warehouse"
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size = "SMALL"
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auto_stop_mins = 10
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[databricks.secrets]
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scope = "stack"
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mapping = [
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{ env = "BCDA_CLIENT_ID", key = "bcda-client-id" },
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{ env = "BCDA_CLIENT_SECRET", key = "bcda-client-secret" },
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]
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[databricks.governance]
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phi_schemas = ["core", "claims_preprocessing", "cclf", "input_layer"]
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[databricks.governance.groups.analysts]
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schemas = ["readmissions", "quality_measures", "cms_quality_measures", "ahrq_measures"]
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privileges = ["SELECT"]
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[databricks.governance.groups.pipeline_svc]
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schemas = ["*"]
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privileges = ["ALL_PRIVILEGES"]
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[databricks.quality]
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monitored_schemas = ["core", "claims_preprocessing", "data_quality"]
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output_schema = "_monitoring"
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[default]
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target = "local" # duckdb | databricks | trino | lake
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[api]
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host = "0.0.0.0"
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port = 8000
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secret = "" # override via STACK_API_SECRET env var
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workers = 1
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[ci]
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backend = "gitea"
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coverage_threshold = 99
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[ci.github]
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runner = "ubuntu-latest"
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registry = "ghcr.io"
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uv_version = "latest"
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[ci.gitea]
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runner_labels = ["ubuntu-latest"]
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registry_secret = "REGISTRY_TOKEN"
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uv_version = "latest"
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ci_registry = "git:3000" # internal HTTP endpoint (avoids self-signed TLS)
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[telemetry]
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enabled = false
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endpoint = "http://otel-collector:4317"
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fallback = "traces/spans.jsonl"
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sample_rate = 1.0
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service_name = "stack"
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[lint]
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line_length = 88
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# ── Container images ──────────────────────────────────────────────
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# Single source of truth for all built images.
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# gen_config.py reads this to generate pipeline YAML, infra-ci
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# hadolint steps, trivy scans, S3 uploads, and vuln report loops.
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# Add a new image here → commit → all pipelines update automatically.
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[images.defaults]
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scan = true
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hadolint = true
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trivy_severity = "HIGH,CRITICAL"
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trivy_exit_code = 0
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# Repo-root context: the Dockerfile COPYs infra/marimo/theme, which only
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# exists at repo root (see .dockerignore carve-outs). Building from notebooks/
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# fails with `"/infra/marimo/theme": not found`.
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[images.notebooks]
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dockerfile = "infra/images/notebooks.Dockerfile"
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context = "."
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path_filter = ["notebooks/**", "infra/marimo/**", "infra/images/notebooks.Dockerfile"]
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# Repo-root context: the Dockerfile COPYs the desktop-bridge watchdog +
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# healthcheck from infra/images/zotero/ (carved out in .dockerignore).
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[images.zotero]
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dockerfile = "infra/images/zotero.Dockerfile"
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context = "."
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path_filter = ["infra/images/zotero.Dockerfile", "infra/images/zotero/**"]
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[images.docs]
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dockerfile = "infra/images/docs.Dockerfile"
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context = "."
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path_filter = ["docs/**", "infra/images/docs.Dockerfile"]
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prep_commands = [
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"mkdir -p data",
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"cp /host-data/bib.sqlite data/ 2>/dev/null || true",
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]
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[images.api]
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dockerfile = "infra/images/api.Dockerfile"
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context = "."
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path_filter = ["infra/images/api.Dockerfile", "src/**", "pyproject.toml"]
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# BCDA manager (Streamlit, src/bcda/ui) — P52.
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[images.bcda]
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dockerfile = "infra/images/bcda.Dockerfile"
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context = "."
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path_filter = ["infra/images/bcda.Dockerfile", "infra/images/bcda/**", "src/**", "pyproject.toml"]
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[images.llm]
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dockerfile = "infra/images/llm.Dockerfile"
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context = "."
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path_filter = ["infra/images/llm.Dockerfile", "src/**", "pyproject.toml"]
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[images.mc]
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dockerfile = "infra/images/mc.Dockerfile"
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context = "infra/rustfs/"
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path_filter = ["infra/rustfs/**", "infra/images/mc.Dockerfile"]
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scan = false
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