rawctx 0.3.24

rawctx CLI and SDK for semantic packages and answer audit evidence

rawctx CLI

Python CLI and SDK for rawctx Hub.

Guides:

• ../docs/guides/package-workflow.md
• ../docs/guides/metricflow-native-workflow.md
• ../docs/diff.md
• Answer Audit docs: https://hub.rawctx.dev/docs/answer-audit

Commands

User:

• rawctx login [--registry URL] [--id-token JWT] [--token-name NAME] [--expires-in-days N] [--no-browser] [--json]
• rawctx logout [--local-only] [--json]
• rawctx search [QUERY] [--format F] [--source-format F] [--origin all|native|indexed] [--domain D] [--source S] [--tags CSV] [--sort similarity|recent|name] [--page N] [--size N] [--json] [--offline] [--registry URL]
• rawctx info PACKAGE_REF [--json] [--offline] [--registry URL]
• rawctx download PACKAGE_REF MODEL_PATH [--local-dir DIR] [--stdout] [--offline] [--force] [--json] [--registry URL]
• rawctx snapshot-download PACKAGE_REF [--local-dir DIR] [--offline] [--force] [--json] [--registry URL]
• rawctx to-prompt PACKAGE_REF [--datasets CSV] [--max-tokens N] [--offline] [--mode agent_context|strict_metric] [--metrics CSV] [--question TEXT] [--budget-policy compact|error_if_required_missing] [--render-format text|xml] [--json] [--registry URL]
• rawctx validate [TARGET] [--format auto|manifest|osi] [--show-dataset-measures] [--json]
• rawctx pack [TARGET_DIR] [--output-dir DIR] [--json]
• rawctx convert --from metricflow --to osi INPUT_PATH --output DIR [--package-name @scope/name] [--package-version X.Y.Z] [--overwrite] [--json]
• rawctx publish [TARGET_DIR] [--private] [--org ORG] [--registry URL]
• rawctx publish --from-dbt DBT_PROJECT_DIR [--native] [--emit-package DIR] [--package-name @scope/name] [--package-version X.Y.Z] [--private] [--org ORG] [--registry URL]
• rawctx diff A B [--format text|json|github|markdown|junit] [--consumer sql|python|llm|all] [--severity breaking|behavioral|cosmetic|all] [--exit-code-on breaking|behavioral|none] [--max-tokens N] [--output PATH]
• rawctx diff semantic A B [--format text|json|github|markdown|junit] [--consumer sql|python|llm|all] [--severity breaking|behavioral|cosmetic|all]
• rawctx diff prompt A B [--format text|json|github|markdown|junit] [--max-tokens N]
• rawctx diff eval A B --questions FILE [--format text|json|github|markdown|junit] [--runs N] [--model NAME]

Maintainer:

• rawctx claim PACKAGE_REF [--json] [--registry URL]

Ops:

• rawctx index dbt --seed-file PATH [--only owner/name] [--limit N] [--dry-run] [--json] [--registry URL]
• rawctx index git --repo owner/name --source-ref REF --package-version X.Y.Z [--package-name NAME] [--scope SCOPE] [--model-glob GLOB ...] [--dry-run] [--json] [--registry URL]

Supported Package Lanes

rawctx currently supports two published package formats:

• format=osi: packaged OSI YAML files
• format=metricflow: native MetricFlow/dbt snapshot packages

Both lanes support:

• rawctx info
• rawctx snapshot-download
• rawctx.load()
• rawctx.to_prompt()
• rawctx diff

download PACKAGE_REF MODEL_PATH also works for both lanes, but only for files listed in manifest.models.

rawctx diff accepts three artifact inputs:

• @scope/name@version
• local package directories
• .rawctx.tar.gz archives

It compares artifacts only. It never queries a warehouse.

Answer Audit Evidence

The Python SDK can register reusable evidence first, then record one audit shell per application answer that cites approved semantic references, external trace ids, evidence source_refs, and later correction, void, or redaction events.

Answer logs are hash-only by default for raw question and answer text. Tenant settings can opt in to raw text storage, but question_hash and answer_hash remain available either way. P3 evidence APIs add a separate evidence path for text, audio, and video assets, sanitized segments, short-lived original media downloads, Text Gate alpha retrieval, tamper-evident ledger verification, and OpenTelemetry trace-bundle ingest. Reference audio and video evidence should be registered before the answer log, then cited through the returned source_ref.

Hub web follows the same reference-first model. Tenant managers register audio/video in private workspace settings, copy the source_ref, and pass it in source_refs when creating the answer log. The Media evidence vault is not exposed from the Public Hub navigation or public settings routes. Web uploads are capped at 5 MB; direct SDK/API registration can use the backend evidence limits. Original media retrieval always requires a purpose, records the access event, and returns a short-lived URL. Download filenames are emitted with a safe ASCII fallback plus UTF-8 filename* so non-ASCII filenames work with S3 presigned downloads.

from pathlib import Path

import rawctx

media = rawctx.register_media_evidence_asset(
    filename="support-call.wav",
    mime_type="audio/wav",
    asset_type="audio",
    content=Path("support-call.wav").read_bytes(),
    metadata={"case_id": "case-123"},
    registry="https://api.rawctx.dev",
)

log = rawctx.log_answer(
    application_key="analytics_bot",
    environment="production",
    idempotency_key="analytics_bot:req_123:msg_456",
    external_trace_id="req_123",
    question_text="Which plan drove expansion MRR?",
    answer_text="The Team plan drove the largest expansion.",
    semantic_refs=[
        {
            "package_ref": "@acme/revenue-metrics",
            "package_version": "1.2.0",
            "context_hash": "sha256:...",
            "metrics": ["mrr"],
        }
    ],
    source_refs=[media["source_ref"]],
    policy_flags={"approved_definition_only": True},
    registry="https://api.rawctx.dev",
)

media_assets = rawctx.list_media_evidence_assets(asset_type="audio", registry="https://api.rawctx.dev")
download = rawctx.request_media_evidence_asset_download(
    media["evidence_asset_id"],
    purpose="auditor_media_review",
    registry="https://api.rawctx.dev",
)
# Use download["download_url"] before it expires; rawctx records the access event.

supplemental = rawctx.list_answer_evidence_assets(log["id"], registry="https://api.rawctx.dev")
segments = rawctx.list_answer_segments(log["id"], registry="https://api.rawctx.dev")
retrieved = rawctx.retrieve_text_gate_alpha(
    "expansion MRR evidence",
    application_key="analytics_bot",
    include_hash_only=True,
    registry="https://api.rawctx.dev",
)
otel_log = rawctx.ingest_otel_trace_bundle(
    application_key="analytics_bot",
    external_trace_id="req_123",
    trace_bundle={"resourceSpans": []},
    semantic_refs=[{"package_ref": "@acme/revenue-metrics", "package_version": "1.2.0"}],
    registry="https://api.rawctx.dev",
)

Use RawctxClient or AsyncRawctxClient when a service should share one registry, token, and timeout across answer audit calls:

• create_answer_log(), also exposed as top-level log_answer()
• register_media_evidence_asset()
• list_media_evidence_assets()
• request_media_evidence_asset_download()
• request_answer_evidence_asset_upload() for log-scoped supplemental assets
• register_answer_evidence_asset() for log-scoped supplemental assets
• list_answer_evidence_assets() for sanitized answer detail evidence
• request_answer_evidence_asset_download() for supplemental original retrieval
• list_answer_segments()
• ingest_otel_trace_bundle()
• retrieve_text_gate_alpha()
• append_answer_log_event()
• export_answer_logs()

OpenTelemetry support is intentionally on-top: rawctx records the submitted trace bundle and binds it to approved definitions without claiming that the upstream runtime trace itself is ground truth.

Package Refs and latest

Package refs can be exact or pointer-based:

• @scope/name@1.2.3 pins one immutable published version
• @scope/name@latest asks the registry for the workspace-approved latest version
• @scope/name behaves like @scope/name@latest for download, load, and prompt workflows

When the registry returns resolution metadata, rawctx preserves the requested ref, resolved concrete version, and snapshot SHA-256 in the JSON-shaped response or prompt context. Use exact pins in CI or release automation when a job must be independent of future latest promotions.

Compare Packages

Use rawctx diff when you need semantic-level change review instead of raw file diffs.

rawctx diff ./pkg-v1 ./pkg-v2
rawctx diff semantic ./pkg-v1 ./pkg-v2 --format json
rawctx diff prompt ./pkg-v1 ./pkg-v2 --max-tokens 2000
rawctx diff eval ./pkg-v1 ./pkg-v2 --questions questions.jsonl --runs 5 --model mock

The top-level command runs semantic + prompt. eval stays opt-in because it measures model behavior, not deterministic package structure.

Notebook / Code

Search uses the public Hub index first so CLI and SDK results match the logged-out web experience. If a search returns no public matches and you have a token configured, rawctx retries with authenticated search.

Notebook shell style:

!rawctx search "semantic model" --sort similarity --json
!rawctx info @scope/name --json
!rawctx snapshot-download @scope/name --json
!rawctx download @scope/name models/customers.yml --json
!rawctx to-prompt @scope/name --datasets customers,order_item --max-tokens 2000
!rawctx validate ./my-package --json

Python API:

import rawctx

result = rawctx.search("semantic model", registry="https://api.rawctx.dev", sort="similarity")
pkg = rawctx.info("@scope/name", registry="https://api.rawctx.dev")
model = rawctx.load("@scope/name", registry="https://api.rawctx.dev")
prompt = rawctx.to_prompt(
    "@scope/name",
    datasets=["customers", "order_item"],
    max_tokens=2000,
    registry="https://api.rawctx.dev",
)

print(model.format_name)    # "osi" or "metricflow"
print(model.datasets)       # normalized dataset names
print(model.measures)       # [Measure(name="...", ...)]
print(model.dimensions)     # [Dimension(name="...", ...)]
print(model.relationships)  # [Relationship(name="...", ...)]
print(prompt)
print(pkg["model_paths"])

snapshot_dir = rawctx.snapshot_download("@scope/name", registry="https://api.rawctx.dev")
model_path = rawctx.download("@scope/name", "models/customers.yml", registry="https://api.rawctx.dev")
validation = rawctx.validate("./my-package")
semantic = rawctx.semantic_diff("./pkg-v1", "./pkg-v2")
prompt_diff = rawctx.prompt_diff("./pkg-v1", "./pkg-v2", max_tokens=2000)
combined = rawctx.diff_artifacts("./pkg-v1", "./pkg-v2")

Async Python API:

import asyncio
import rawctx

async def main():
    async with rawctx.AsyncRawctxClient(registry="https://api.rawctx.dev") as client:
        result = await client.search("semantic model", sort="similarity")
        model = await client.load("@scope/name")
        prompt = await client.to_prompt("@scope/name", datasets=["customers", "order_item"])
        snapshot_dir = await client.snapshot_download("@scope/name")
        diff_report = await client.diff("./pkg-v1", "./pkg-v2")
        return result, model, prompt, snapshot_dir, diff_report

asyncio.run(main())

to_prompt() Behavior

rawctx.to_prompt() turns a package snapshot into compact LLM context. It uses the same normalized semantic objects as load(), then applies package metadata, dataset filters, and prompt budget settings to render agent-ready text.

The same prompt compiler is available from the CLI:

rawctx to-prompt @scope/name --datasets customers,order_item --max-tokens 2000
rawctx to-prompt @scope/name --mode strict_metric --metrics mrr --render-format xml
rawctx to-prompt @scope/name --json

The rendered prompt keeps a predictable section shape:

Domain: {domain} ({package_name})

Models:
...

Datasets:
...

Metrics:
...

Relationships:
...

Dataset filters preserve the requested order, drop duplicates, and fail with UsageError: Unknown dataset(s): ... when a requested dataset is not present. Selecting a subset keeps context focused on the requested datasets and their relevant relationships.

max_tokens is a practical size target, not a model-specific tokenizer guarantee. When the budget is tight, rawctx prioritizes high-signal semantic context and compacts lower-priority detail. Use return_context=True when you need the selected objects, estimated size, render hash, omissions, and warnings for logging or review.

Download Behavior

• download fetches one file listed in manifest.models
• snapshot-download materializes the full extracted package tree
• for native MetricFlow packages, snapshot-download is the primary handoff because it restores the full dbt-style snapshot
• load() and to_prompt() normalize both OSI and native MetricFlow packages into the same typed Python structures
• when using snapshot-download --local-dir, prefer a new or empty directory. --force only replaces an existing rawctx snapshot directory and refuses to wipe the current working directory or unrelated folders
• indexed packages remain preview-only and cannot be downloaded directly

Validate / Pack / Publish

validate, pack, and publish all start from a local package directory.

• validate: checks the manifest and validates the package according to manifest.format
• pack: builds a deterministic local .rawctx.tar.gz
• publish: validates again, rebuilds a temporary archive, calculates the checksum, uploads bytes, and completes the version

Published versions are immutable release artifacts. Private workspaces can optionally require approval before a published version is promoted to latest. When that governance policy is enabled, publish still creates the version, but latest moves only after the request is reviewed and approved in rawctx Hub. When governance is disabled, direct latest promotion keeps the existing lightweight behavior.

Package directories are no longer OSI-only.

OSI package example:

my-osi-package/
  rawctx.yaml
  README.md
  models/
    sales_summary.osi.yaml
    customers.osi.yaml

Native MetricFlow package example:

my-metricflow-package/
  rawctx.yaml
  README.md
  dbt_project.yml
  models/
    customers.yml
    orders.yml

Native MetricFlow manifest example:

name: "@demo/jaffle-metrics"
version: "1.0.0"
format: "metricflow"
source_format: "metricflow"
description: "Native MetricFlow package"
models:
  - models/customers.yml
  - models/orders.yml
include:
  - dbt_project.yml
repository: "https://github.com/dbt-labs/jaffle-sl-template"

Notes:

• format supports osi and metricflow
• models must stay relative and must resolve inside the package directory
• include is optional and is mainly useful for native packages that need extra project files such as dbt_project.yml
• standalone file validation is still limited to manifest files and OSI files, so rawctx validate models/customers.yml is not a native MetricFlow file validator by itself

Convert Workflow

Inspect-first OSI flow:

rawctx convert --from metricflow --to osi ./my-dbt-project --output ./dist/pkg
rawctx validate ./dist/pkg --json
rawctx pack ./dist/pkg --output-dir ./dist --json

Publish Directly From dbt

Convert to OSI and publish:

rawctx login
rawctx publish --from-dbt ./my-dbt-project --emit-package ./dist/pkg

Publish a native MetricFlow package:

rawctx login
rawctx publish --from-dbt ./my-dbt-project --native --emit-package ./dist/native-pkg
rawctx publish --from-dbt ./my-dbt-project --native --package-name @your-scope/jaffle-shop --package-version 1.2.3

Use --emit-package when you want the generated package directory to remain on disk after the publish run.

Latest Promotion Governance

Governance is about changing the official pointer, not editing the artifact:

published immutable version
        |
request latest promotion in rawctx Hub
        |
review diff or prompt preview when required
        |
approval threshold reached
        |
latest resolves to that concrete version

Workspace admins can enable approval before latest promotion, set the required approval count, choose whether requesters may self-approve, and require semantic diff review. The first governance surface is in the authenticated Hub UI: workspace settings configure the policy, and package version pages create, approve, reject, or cancel latest promotion requests.

CLI and Python consumers do not need a separate governance command to use the result. They keep using exact refs or the approved latest pointer:

rawctx snapshot-download @scope/name@1.2.3
rawctx to-prompt @scope/name@latest --max-tokens 1200

If current latest changes while a request is pending, rawctx marks that request stale instead of moving latest from an unexpected base version. Existing pending requests keep the approval threshold captured when the request was created.

Auth Flow (Auto + Fallback)

1. Run rawctx login.
2. CLI opens or prints the OAuth URL from POST /api/auth/login and falls back to the legacy GitHub endpoint if needed.
3. Complete login in the browser.
4. CLI automatically polls OAuth session status and captures id_token when the registry supports it.
5. CLI calls POST /api/auth/token and stores the API token in ~/.rawctx/config.yaml.

Manual fallback:

• rawctx login --id-token '<JWT>'

Config and Environment

Config file (default): ~/.rawctx/config.yaml

registry: "https://api.rawctx.dev"
auth:
  token: "rxctx_..."
  token_id: "uuid"
  token_name: "rawctx-cli"
  issued_at: "2026-02-28T00:00:00+00:00"
profile:
  username: "owner"

Environment overrides:

• RAWCTX_CONFIG (config path)
• RAWCTX_REGISTRY (registry URL)
• RAWCTX_TOKEN (auth token)

Priority: CLI option > env var > config > default.

Offline Mode

--offline is supported for:

• search
• info
• download
• snapshot-download

Cache paths:

• index: ~/.rawctx/cache/packages.json
• archives: ~/.rawctx/cache/archives/@scope/name/<version>.rawctx.tar.gz
• snapshots: ~/.rawctx/packages/@scope/name/<version>/