sagaflow 0.10.9

Temporal-backed workflow runtime for Claude Code skills

sagaflow

Durable execution for long-running agent workflows, on top of Temporal.

You write a Python workflow that calls models, runs tools, and writes artifacts. sagaflow runs each step as a Temporal activity, so when the worker dies — or a 40-minute fan-out crashes halfway — the next launch resumes from the last completed step instead of starting over. Results land in ~/.sagaflow/INBOX.md whether or not you're still attached to the session that started them.

Quick start

pip install sagaflow
temporal server start-dev &
export ANTHROPIC_API_KEY=sk-ant-...

sagaflow launch hello-world --name alice --await
# → hello, alice

Kill the terminal mid-run and re-launch the same workflow ID: it picks up from where the worker died.

What you get

• Resumes after crashes. Activity-level checkpointing via Temporal — workers, sessions, and laptops can all die without losing in-flight work.
• Decoupled from the caller. Fire-and-forget submissions land in an append-only inbox; a session-start hook surfaces unread results next time you open Claude Code.
• Provider-agnostic transport. Anthropic SDK by default; point ANTHROPIC_BASE_URL at Bedrock, a model gateway, or any compatible proxy.
• Auto-managed worker. First sagaflow launch spawns a worker daemon; sagaflow doctor reports health.

Install

pip install sagaflow

Requirements:

• Python 3.11+
• Temporal CLI running locally: brew install temporal && temporal server start-dev
• An Anthropic API key (or a compatible proxy via ANTHROPIC_BASE_URL)

Authoring a workflow

from sagaflow import workflow, generate_text, parallel, write_file

@workflow(name="code-review", phases=["Critique", "Synthesize"])
async def run(diff: str):
    findings = await parallel(
        generate_text("security-critic", variables={"diff": diff}),
        generate_text("perf-critic", variables={"diff": diff}),
    )
    report = await generate_text("synth", variables={"findings": str(findings)})
    await write_file("report.md", report)
    return report

Prompts live in prompts/<name>.prompt next to the workflow file. Each generate_text and write_file call is a Temporal activity with its own retry policy and replay log.

CLI

sagaflow launch <name> --arg key=value [--await]   # submit a workflow
sagaflow inbox                                     # list unread results
sagaflow dismiss <run-id>                          # mark as read
sagaflow doctor                                    # diagnose temporal/worker/hook

How it works

sagaflow launch
   │
   ▼
preflight (install hook, spawn worker if missing)
   │
   ▼
Temporal (localhost:7233) ── workflow ID ── worker daemon
                                              │
                                              ▼
                                         activities:
                                          • model calls
                                          • file I/O
                                          • inbox emit
                                              │
                                              ▼
                              ~/.sagaflow/INBOX.md  +  desktop notify
                                              │
                                              ▼
                                  next session: SessionStart
                                  hook surfaces unread runs

If the worker crashes mid-run, the next sagaflow launch (or the next worker poll) resumes from the last completed activity. Activities that already succeeded don't re-execute.

Development

git clone https://github.com/npow/sagaflow
cd sagaflow
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

ruff check sagaflow tests
mypy sagaflow
pytest

# Opt-in end-to-end tests (require live Temporal + real Anthropic access)
SAGAFLOW_E2E=1 pytest

License

MIT