tenbri-openai-agents

Tenbri for the OpenAI Agents SDK: every tool call, handoff and approval of an agent becomes a signed, chained decision that anyone holding the stream's key fingerprint can verify offline.

from agents import Runner
from tenbri import AsyncTenbri
from tenbri_openai_agents import TenbriRecorder

log = await AsyncTenbri.open("s3://acme-audit/tenbri/support")
async with TenbriRecorder(log) as recorder:
    result = await Runner.run(agent, "Refund ch_123", hooks=recorder, run_config=recorder.run_config())

The SDK awaits its run hooks, so the guarantee is enforce: if the intent cannot be written, the run stops before the tool runs. fail_open=True lets the tool run instead and logs a warning.

Tool arguments, results and prompts are never written. Choose what is:

TenbriRecorder(
    log,
    tools=["issue_refund", "close_ticket"],                 # default: every tool
    target=lambda tool, args: f"stripe:{args['charge']}",   # action.target
    inputs=lambda tool, args: [{"ref": "policy:refund", "version": "14", "content": policy}],
    subject=customer_handle,                                # per-subject keys, for erasure
)
recorder.read("ticket:4821", "3", ticket_text)              # pinned to the next decision

Contents are pinned by keyed digest (digest_key at AsyncTenbri.open). Entries carry the SDK's trace id, so a decision and its trace find each other.

Use one recorder per run, or per conversation when a run resumes after approvals. Pass run_config=recorder.run_config(your_config): it is how the recorder hears that a tool raised (otherwise only the SDK's default error message tells). Use async with so a run that raises closes its open intents; a process that dies mid-action leaves its intent open, and the next writer session reconciles it as unknown.

examples/refunds.py runs end to end, with or without an OpenAI API key.