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This package\nconnects `agent-core` to that runtime service and turns the live CaP-X session\ninto typed physical tools.\n\n```text\nagent-core model loop\n  -> @cuylabs/agent-physical-capx tools\n    -> capx-agent-runtime HTTP server\n      -> CaP-X Python runtime, selected YAML config, simulator or robot\n```\n\nUse `capx-agent-runtime` directly when an agent harness should call CaP-X over\nHTTP or MCP. Use this package when the harness is `agents-ts`.\n\n## Ownership Boundary\n\nThe runtime server owns the robotics side:\n\n- CaP-X clone and selected YAML config.\n- Simulator or robot dependencies.\n- CUDA, perception services, and model assets.\n- Output directory and skill-library path.\n- Execution of submitted Python Code-as-Policies programs.\n\nThis TypeScript package owns the `agents-ts` side:\n\n- `CapxSession`, which maps to one live runtime session.\n- `capx_*` tools for `agent-core`.\n- Approval-aware policy-code execution through `agent-core`.\n- Mapping observations, rendered frames, turn history, and artifacts into\n  model-usable context.\n\n## Quick Start\n\nFirst start the\n[CaP-X Agent Runtime](https://github.com/cuylabs-ai/capx-agent-runtime) on the\nmachine that has CaP-X, CUDA, and the selected simulator or robot stack\ninstalled. The runtime docs cover the workstation setup, server command,\nconfig selection, Docker path, and validation steps:\n\n1. Prepare the GPU workstation with\n   [Workstation Setup](https://github.com/cuylabs-ai/capx-agent-runtime/blob/main/docs/workstation-setup.md).\n2. Start and validate the runtime server with\n   [Runtime Server](https://github.com/cuylabs-ai/capx-agent-runtime/blob/main/docs/runtime-server.md).\n\nThen install the TypeScript packages in your `agents-ts` application and point\nthis adapter at the running runtime server:\n\n```bash\nnpm install @cuylabs/agent-core @cuylabs/agent-physical @cuylabs/agent-physical-capx\n```\n\nCreate an agent that connects to the running runtime service:\n\n```ts\nimport { createCapxAgent } from \"@cuylabs/agent-physical-capx\";\n\nconst { agent, session } = await createCapxAgent({\n  model,\n  startSession: true,\n  toolExecutionMode: \"plan\",\n  sessionOptions: {\n    mode: \"runtime\",\n    runtimeServerUrl: \"http://127.0.0.1:8210\",\n    physicalMode: \"simulation\",\n    enablePolicyCodeExecution: true,\n  },\n});\n```\n\n`startSession: true` creates one live CaP-X runtime session. Keep using that\nsame session across observe, execute, observe turns unless the host decides to\nreset or stop it.\n\n`toolExecutionMode: \"plan\"` is an `agent-core` dispatch setting. It does not\nmake the model write only a textual plan. The model can still call tools, but\n`agent-core` receives those planned tool calls first, applies approval and\nscheduling policy, executes the approved tools, then records the tool results\nfor the next model step.\n\n## Runtime Loop\n\nThe external agent owns reasoning and code generation. CaP-X owns robotics\nexecution.\n\n```text\nstart CapxSession\n  -> capx_observe returns task prompt, state, frame, and codeContext\n  -> agent writes one Python policy-code step\n  -> capx_run_policy_code submits that code to the live runtime session\n  -> agent observes the result, reward, artifacts, and next frame\n  -> host or agent continues, reports completion, resets, or stops\n```\n\n`capx_run_policy_code` is the tool that performs physical work. It can mutate a\nsimulator or move hardware, so it should stay approval-gated and dispatched by\nthe host harness.\n\n## Tools\n\nThis package generates the `agent-core` tools below. They are the\nTypeScript-facing tool surface for a `CapxSession`; internally they call the\n`capx-agent-runtime` HTTP API.\n\n- `capx_status`\n- `capx_observe`\n- `capx_artifacts`\n- `capx_stop`\n- `capx_run_policy_code` when `enablePolicyCodeExecution: true`\n- `capx_turn_history`\n\nThe raw runtime server exposes HTTP endpoints such as `/sessions`,\n`/sessions/{id}/observe`, `/sessions/{id}/execute-code`,\n`/sessions/{id}/artifacts`, and `/sessions/{id}/turns`. Its optional MCP\nwrapper has its own MCP-native tool names. The list above is the smaller\n`agents-ts` default surface.\n\nThe default model-facing surface is intentionally small. It gives the agent\nenough context to write better Code-as-Policies Python without exposing every\nruntime operation as a separate robot-action tool.\n\n## CaP-X Skills\n\nThere are two different skill concepts:\n\n- `agent-core` skills are `SKILL.md` instruction packs that teach the model how\n  to use the CaP-X tools.\n- CaP-X skills are Python helper functions in the runtime skill library.\n\nThe default agent tool surface exposes CaP-X skill-library information through\n`capx_observe` as policy-code context. Programmatic clients can still use\n`CapxLiveRuntime` to inspect, extract, or inject runtime skills deliberately\nwith host approval.\n\n## Examples\n\nThe runnable examples live in [examples/README.md](./examples/README.md).\nThey show the service-first flow, environment variables, approval modes,\nmulti-turn solving, video artifacts, and recovery behavior.\n\nFrom a local `agents-ts` checkout:\n\n```bash\ncd packages/agent-physical-capx\ncp examples/.env.example examples/.env\n```\n\nSet at least:\n\n```bash\nOPENAI_API_KEY=...\nOPENAI_MODEL=gpt-4o-mini\nCAPX_RUNTIME_SERVER_URL=http://127.0.0.1:8210\n```\n\nRun the single-turn solver in observe-only mode:\n\n```bash\nnpx tsx examples/01-capx-runtime-solver.ts\n```\n\nAllow policy-code execution in simulation:\n\n```bash\nCAPX_ALLOW_DESTRUCTIVE=1 \\\nnpx tsx examples/01-capx-runtime-solver.ts\n```\n\nRun the multi-turn autosolver:\n\n```bash\nCAPX_ALLOW_DESTRUCTIVE=1 \\\nCAPX_POLICY_EXECUTION_RECORD_VIDEO=1 \\\nCAPX_MAX_SOLVER_TURNS=6 \\\nCAPX_STOP_ON_EXIT=1 \\\nnpx tsx examples/02-capx-runtime-autosolve.ts\n```\n\nWith the default cube-stack runtime config, a successful run reports\n`executionOk=true`, `taskCompleted=true`, `reward=1`, `terminated=true`, and\n`sandboxRc=0`. Generated code, logs, rendered images, and videos are listed\nthrough `capx_artifacts` and the runtime console.\n\n## More Docs\n\n- [docs/README.md](./docs/README.md)\n- [docs/how-it-works.md](./docs/how-it-works.md)\n- [docs/agent-core-integration.md](./docs/agent-core-integration.md)\n- [docs/limitations.md](./docs/limitations.md)\n- [examples/README.md](./examples/README.md)\n\n## License\n\nApache-2.0\n","readmeFilename":"README.md"}