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Docs for briefcase-ai v3.3.0see what’s new.

Installation

Briefcase ships as briefcase-ai — a Python SDK over a Rust core. Install the base package, then add extras only when a concrete need appears.

Python 3.9+ Precompiled wheels No Rust toolchain needed

Base Install

Terminal window
pip install briefcase-ai

What ships in the base package

The base install carries the whole core loop — capture a decision, store it, replay it, verify it — with no extras. The exports below are grouped by the act of the journey they belong to.

Recording

capture · observe · setup · DecisionSnapshot · Snapshot · Input · Output · ModelParameters · ExecutionContext · HardwareMetadata

Plus the stock exporters under briefcase.exporters and enable_logging / get_logger. Record each classify_ticket call and emit it to the console, a file, or memory.

Store & query

init · init_with_config · is_initialized · BriefcaseConfig · SnapshotQuery

Start the native runtime and query stored decisions. Cost types live in briefcase.cost — also base, no extra.

Replay & verify

Wired through the runtime above

Persist a decision, then re-run it and confirm its record is intact. The replay engine itself is gated behind the replay extra below.

Extras

Extras gate the import surface of optional submodules. Most install nothing and simply mark intent — only otel, lakefs, bitemporal-iceberg, and mcp pull in third-party dependencies. Install only what your deployment needs.

GroupExtraWhat it addsRecommended for
Core storageSqliteBackend, BufferedBackendPersisting classify_ticket decisions to a SQLite file
Governance replayReplayEngineRe-running stored decisions to confirm a change reproduces them
Governance driftDriftCalculator, DriftMetricsMeasuring how consistent repeated decisions are
Governance validatePromptValidationEngineChecking prompt references before a call runs
Governance guardrailsGuardrailEnv frameworkAllowing or denying an action before it executes
Governance routingAgentRouter, PolicyRegistryVersioned, policy-based routing of decisions
Governance complianceExaminerBundleBuilding a tamper-evident, verifiable bundle for a decision
Governance bitemporalBitemporalRecord, in-memory storeReconstructing any past state of recorded facts
Governance bitemporal-icebergIceberg-backed store (installs pyiceberg, pyarrow)A scalable bitemporal store
Capture sanitizeSanitizer (redaction)Stripping sensitive spans from inputs/outputs
Store & Query externalExternalDataTrackerSnapshotting external data a decision read
Store & Query ragVersionedEmbeddingPipelineVersioning an embedding index for reproducible RAG
Store & Query lakefslakeFS VersionedClient (installs lakefs)Reading versioned files with their commit SHA
Store & Query vcsVCS client base protocolImplementing a custom versioned data source
Operate otelOpenTelemetry helpers (installs opentelemetry)Correlating decisions with existing traces
Operate correlationMulti-agent workflow tracingCorrelating decisions across agents in one workflow
Operate eventsBriefcaseEvent emitterEmitting events on low confidence or drift
Operate mcpbriefcase-mcp server (installs mcp)Exposing SDK tools to MCP clients
All allEverything aboveEvaluation or local development
Dev devTest and lint toolingContributing to Briefcase
  1. Install the base package — it covers recording and inspection, which is all the Quickstart needs to begin.

    Terminal window
    pip install briefcase-ai
  2. Add storage and replay for the Quickstart’s persist-and-replay steps.

    Terminal window
    pip install "briefcase-ai[replay,storage]"
  3. Add further extras later, only when a need appears — for example otel for tracing or guardrails to gate actions.

Install everything

Terminal window
pip install "briefcase-ai[all]"

Requirements

  • Python 3.9+ — that’s the only requirement. Wheels are precompiled, so no Rust toolchain is needed unless you build the Rust core yourself.

Where this fits

Installation is step zero of the journey. Next, capture and inspect a decision, then learn the data model behind it.