cap-sdk-python 2.13.0

CAP (Cordum Agent Protocol) Python SDK

CAP Python SDK

Asyncio-first SDK with NATS helpers for CAP workers and clients.

Quick Start

1. Generate protobuf stubs into this SDK (one-time per proto change):

   python -m grpc_tools.protoc \
     -I../../proto \
     --python_out=./cap/pb \
     --grpc_python_out=./cap/pb \
     ../../proto/cordum/agent/v1/*.proto
   

   (Or run ./tools/make_protos.sh from repo root with CAP_RUN_PY=1 and copy /python into sdk/python/cap/pb if you want vendored stubs.)

2. Install:

   pip install -e .
   

3. Run a worker:

   import asyncio
   from cap import worker
   from cap.pb.cordum.agent.v1 import job_pb2
   
   async def handle(req: job_pb2.JobRequest):
       return job_pb2.JobResult(
           job_id=req.job_id,
           status=job_pb2.JOB_STATUS_SUCCEEDED,
           result_ptr=f"redis://res/{req.job_id}",
           worker_id="worker-echo-1",
       )
   
   asyncio.run(worker.run_worker("nats://127.0.0.1:4222", "job.echo", handle))
   

4. Submit a job (client):

   import asyncio
   from cryptography.hazmat.primitives.asymmetric import ec
   from cap import client
   from cap.pb.cordum.agent.v1 import job_pb2
   import nats
   
   async def main():
       nc = await nats.connect("nats://127.0.0.1:4222")
       priv = ec.generate_private_key(ec.SECP256R1())
       req = job_pb2.JobRequest(
           job_id="job-echo-1",
           topic="job.echo",
           context_ptr="redis://ctx/job-echo-1",
       )
       await client.submit_job(nc, req, "trace-1", "client-py", priv)
       await nc.drain()
   
   asyncio.run(main())
   

Files

• cap/bus.py — NATS connector.
• cap/worker.py — worker skeleton with handler hook.
• cap/client.py — publish JobRequest to sys.job.submit.
• cap/pb/ — protobuf stubs (generated).

Defaults

• Subjects: sys.job.submit, sys.job.result, sys.heartbeat.
• Protocol version: 1.
• Signing: submit_job and run_worker sign envelopes when given an ec.EllipticCurvePrivateKey. Signatures use deterministic protobuf serialization (map entries ordered by key) for cross-SDK verification. Generate a keypair with cryptography:

  from cryptography.hazmat.primitives.asymmetric import ec
  priv = ec.generate_private_key(ec.SECP256R1())
  pub = priv.public_key()
  

• Set public_keys on run_worker to verify incoming packets.
• Omit public_keys to accept unsigned packets.
• Pass private_key=None to submit_job if you want to send unsigned envelopes.

Swap out cap.bus if you need a different transport.

Testing

The cap.testing module lets you test handlers without running NATS or Redis.

from cap.testing import run_handler
from cap.pb.cordum.agent.v1 import job_pb2

async def test_echo():
    result = await run_handler(
        lambda ctx, data: {"echo": data["prompt"]},
        {"prompt": "hello"},
        topic="job.echo",
    )
    assert result.status == job_pb2.JOB_STATUS_SUCCEEDED

• run_handler(handler, input, **options) — runs a single handler invocation and returns the JobResult.
• create_test_agent(**options) — returns (agent, mock_nats, store) pre-wired with MockNATS + InMemoryBlobStore.
• MockNATS — in-memory NATS mock for custom test setups.

Runtime (High-Level SDK)

The runtime hides NATS/Redis plumbing and gives you typed handlers.

import asyncio
from pydantic import BaseModel
from cap.runtime import Agent, Context

class Input(BaseModel):
    prompt: str

class Output(BaseModel):
    summary: str

agent = Agent(retries=2)

@agent.job("job.summarize", input_model=Input, output_model=Output)
async def summarize(ctx: Context, data: Input) -> Output:
    return Output(summary=data.prompt[:140])

asyncio.run(agent.run())

Middleware

Add cross-cutting concerns (logging, auth, metrics) without modifying handlers:

from cap.middleware import logging_middleware

# Built-in logging middleware
agent.use(logging_middleware())

# Custom middleware
async def timing(ctx, data, next_fn):
    import time
    start = time.monotonic()
    result = await next_fn(ctx, data)
    elapsed = time.monotonic() - start
    print(f"job {ctx.job_id} took {elapsed:.3f}s")
    return result

agent.use(timing)

Middleware executes in registration order (FIFO). Each can inspect context, measure timing, or short-circuit by returning without calling next_fn.

Redis TLS

The Python SDK provides redis_ssl_context_from_env() to build an SSLContext for secure Redis connections. It reads:

• REDIS_TLS_CA (or SSL_CERT_FILE fallback): Path to CA certificate.
• REDIS_TLS_CERT / REDIS_TLS_KEY: Path to client certificate/key pair.
• REDIS_TLS_SERVER_NAME: SNI server name override.
• REDIS_TLS_INSECURE: Set to 1 or true to skip certificate verification (dev only).

Environment

• NATS_URL (default nats://127.0.0.1:4222)
• REDIS_URL (default redis://127.0.0.1:6379/0)

Generating API Docs

Generate HTML API reference locally using pdoc:

pip install cap-sdk-python[dev]
pdoc ./cap --output-dir docs

Output is written to docs/ (gitignored). Open docs/index.html to browse.

Observability

Structured Logging

The runtime Agent and Worker use logging.Logger (stdlib) for structured logging. All log calls include contextual fields (job_id, trace_id, topic, sender_id). Pass a custom logger or leave as default:

import logging
from cap.runtime import Agent

logger = logging.getLogger("my-agent")
logger.setLevel(logging.DEBUG)
agent = Agent(logger=logger)

MetricsHook

Implement the MetricsHook protocol to integrate with Prometheus, OpenTelemetry, or any metrics system:

from cap.metrics import MetricsHook

class MetricsHook(Protocol):
    def on_job_received(self, job_id: str, topic: str) -> None: ...
    def on_job_completed(self, job_id: str, duration_ms: int, status: str) -> None: ...
    def on_job_failed(self, job_id: str, error_msg: str) -> None: ...
    def on_heartbeat_sent(self, worker_id: str) -> None: ...

The default is NoopMetrics (zero overhead). Example Prometheus integration:

from cap.runtime import Agent

class PromMetrics:
    def on_job_received(self, job_id, topic):
        jobs_received.labels(topic=topic).inc()

    def on_job_completed(self, job_id, duration_ms, status):
        job_duration.labels(status=status).observe(duration_ms)

    def on_job_failed(self, job_id, error_msg):
        jobs_failed.inc()

    def on_heartbeat_sent(self, worker_id):
        pass

agent = Agent(metrics=PromMetrics())

The trace_id is propagated through all log and metrics calls for distributed tracing correlation.