Constrained, composable agents that hold by construction — a safety-first SDK for high-stakes, deterministic agent workflows.
Project description
Drawbore
Composable agents that hold by construction.
Drawbore is a Python SDK for building constrained, composable agent pipelines with safety guarantees baked in as architecture — for high-stakes, deterministic workflows in fintech, healthcare, legal, compliance, and beyond.
The thesis: capability is a liability in high-stakes workflows; constraint is the feature. You compose tightly scoped, typed, schema-enforced, audit-logged agents; the framework enforces the contracts and you write the business logic.
Install
pip install drawbore # core
pip install "drawbore[mcp]" # + MCP server tools
pip install "drawbore[otlp]" # + OTLP span export
Sixty seconds
from pydantic import BaseModel
from drawbore import agent, Pipeline
class Payment(BaseModel):
cents: int
class Normalized(BaseModel):
dollars: float
@agent(name="normalize", input=Payment, output=Normalized)
async def normalize(p: Payment) -> Normalized:
return Normalized(dollars=p.cents / 100)
pipeline = Pipeline(name="payments", version="1.0.0")
pipeline.add(normalize)
async def main():
async with pipeline.test_mode() as tp:
result = await tp.run(Payment(cents=2500))
assert result.status == "completed"
print(result.audit_trace.legible()) # a regulator-readable run record
Every step is schema-checked at both edges. Every tool call passes through a proxy with a single-use permission token. Every run produces a legible audit record. None of it is configurable off.
What the framework guarantees
- Typed contracts at every edge — Pydantic-validated inputs and outputs; a wrong shape halts the run with a readable reason, it never propagates.
- Least-privilege tools — agents call only the tools they declared, through one audited chokepoint, with single-use scoped tokens and circuit breakers.
- Halt-and-escalate by default — failures stop the pipeline and produce an escalation package a human can read; there is no silent degradation.
- Audit as a side effect —
result.audit_trace.legible()renders what ran, what was called, and why it stopped, with no tracing setup. - Test mode with the real safety layer —
pipeline.test_mode(...)mocks the outside world (models, tools, MCP) while every control runs for real.
Learn more
- Quickstart — install to first run.
- Guides — pipelines, tools, model-backed agents, escalation, testing, observability.
- Examples — runnable, tested pipelines from tiny to high-stakes.
License
MIT
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