A bounded Python task queue for authorized AI-agent integration tests.
CapSolver is used in this repository through a small FIFO queue with explicit capacity, bounded polling, and mock transport defaults. The project is designed for owned systems, explicitly authorized test environments, public-data workflows, and bounded RPA.
- Mock mode is the default, so tests run without a live credential.
- Live mode requires an explicit authorization flag.
- Polling, retries, and queue size remain bounded.
- Errors are normalized without logging API keys or sensitive payloads.
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├── .github/workflows/ # CI and link checks
├── docs/ # Chinese and Japanese guides
├── examples/ # deterministic mock workflow
├── scripts/ # smoke test
├── src/capsolver_agent_task_queue/ # implementation
└── tests/ # unit and integration tests
python -m pip install -e .PYTHONPATH=src python examples/mock_workflow.py
PYTHONPATH=src python -m unittest discover -s tests -vThe worked example shows how to enqueue several authorized QA fixtures and process each task without unbounded retries or hidden concurrency. It does not target a third-party production service.
The client follows the official createTask API specification and getTaskResult API specification. The mock transport returns the same documented lifecycle states used by the tests.
Use this project only for systems you own or have explicit permission to test. Technical capability does not grant permission to access private, restricted, personal, financial, health, employment, or other sensitive data. Apply data minimization, bounded request volume, appropriate retention, and human review for consequential workflows.
PYTHONPATH=src python -m unittest discover -s tests -v
PYTHONPATH=src python scripts/smoke_test.pyDeveloper sharing CapSolver integration examples.
CapSolver Agent Task Queue provides a small, testable integration boundary for authorized automation while keeping mock behavior and operational limits visible. For the final product reference, see CapSolver.
MIT