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TapPass SDK — Zero Trust AI Agent Platform. Cryptographic capability tokens, governance pipeline, agent trust scoring.

Project description

tappass — Zero Trust Control Plane for Agentic AI (Python SDK)

Runtime governance for your LLM, agent, and tool calls. Embed in your code, get a typed audit trail, surface governance decisions as Python exceptions.

What this SDK is for:

  • Governing LLM calls, agent runs, and tool executions at runtime.
  • Emitting structured audit events with correlation IDs.
  • Handling governance decisions (block, redact, approve, trust-tier, break-glass) as typed exceptions in your code.

What this SDK is NOT for:

  • Policy CRUD, compliance report generation, Verified credential issuance, retention config, break-glass invocation, tool-integrity approval. Those live in the TapPass dashboard — not in your agent code.

Requirements

  • Python ≥ 3.11.
  • tappass server ≥ 0.6.0. (The SDK rejects older servers at construction time.)

Install

pip install tappass

Quickstart — a governed chat call

from tappass import Agent

agent = Agent("https://tappass.example.com", api_key="tp_...")
r = agent.chat("Summarize Q4 revenue")
print(r.content)
print(r.session_id, r.audit_url)   # correlation IDs, deep link to dashboard

Quickstart — govern a CrewAI run

from crewai import Agent, Task, Crew
from tappass.integrations.crewai import guard_crew

crew = Crew(agents=[...], tasks=[...])

with guard_crew(crew, tappass_url="https://tappass.example.com", api_key="tp_...") as session:
    result = session.kickoff()
    print(session.id, session.audit_url)

Decisions are typed exceptions

from tappass import GovernanceDecision, PolicyBlockError, ApprovalRequired

try:
    r = agent.chat("Show me all customer SSNs")
except PolicyBlockError as e:
    print(f"Blocked by {e.blocked_by}: {e.reason}. See {e.audit_url}")
except ApprovalRequired as e:
    print(f"Awaiting approval: {e.approval_url}")
except GovernanceDecision as e:
    print(f"Governance decision: {e}")

What's new in 0.6

See CHANGELOG.md. Breaking changes — no back-compat with 0.5.x. See the migration guide.

Publishing a release

Releases ship to PyPI via GitHub Actions using OIDC Trusted Publishing — no long-lived API token is stored anywhere. The workflow is .github/workflows/release.yml.

One-time PyPI configuration

Only needed once per project (or whenever the workflow name / environment changes):

  1. Log in to https://pypi.org/manage/account/publishing/.
  2. Under Add a new pending publisher (if the project isn't on PyPI yet) or the existing project's Publishing tab, add a GitHub publisher with:
    • PyPI Project Name: tappass
    • Owner: tappass
    • Repository name: tappass-sdk
    • Workflow name: release.yml
    • Environment name: pypi
  3. In the GitHub repo, go to Settings → Environments and create an environment named pypi. Optionally add a required-reviewers protection rule so a human approves each release.

That's it — no secrets, no tokens.

Cutting a release

  1. Bump version in pyproject.toml (and __version__ in tappass/__init__.py).
  2. Update CHANGELOG.md: flip ## [X.Y.Z] — Unreleased to ## [X.Y.Z] — YYYY-MM-DD.
  3. Commit: git commit -am "release: X.Y.Z".
  4. Tag and push:
    git tag vX.Y.Z
    git push origin main --tags
    

The workflow then:

  1. Verifies the tag matches pyproject.toml version (fails the release if not).
  2. Builds wheel + sdist.
  3. Runs twine check.
  4. Publishes to PyPI via OIDC.
  5. Creates a GitHub Release with the wheel + sdist attached and auto-generated notes.

Dry run

To build the artifacts without publishing, use Actions → Release to PyPI → Run workflow with dry_run checked. The publish and github_release jobs are skipped; the build job's artifacts are retained for inspection.

License

Apache-2.0. See LICENSE.

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