{"named_endpoints":{"/rig":{"parameters":[{"label":"1st","parameter_name":"mesh_url","parameter_has_default":true,"parameter_default":"","type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api","example_input":""},{"label":"2nd","parameter_name":"example","parameter_has_default":true,"parameter_default":"","type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api","example_input":""},{"label":"3rd","parameter_name":"num_beams","parameter_has_default":true,"parameter_default":10,"type":{"type":"integer"},"python_type":{"type":"int","description":""},"component":"Api","example_input":10},{"label":"4th","parameter_name":"seed","parameter_has_default":true,"parameter_default":-1,"type":{"type":"integer"},"python_type":{"type":"int","description":""},"component":"Api","example_input":-1},{"label":"5th","parameter_name":"keep_skeleton","parameter_has_default":true,"parameter_default":false,"type":{"type":"boolean"},"python_type":{"type":"bool","description":""},"component":"Api","example_input":false},{"label":"6th","parameter_name":"preserve_original","parameter_has_default":true,"parameter_default":false,"type":{"type":"boolean"},"python_type":{"type":"bool","description":""},"component":"Api","example_input":false},{"label":"7th","parameter_name":"postprocess","parameter_has_default":true,"parameter_default":false,"type":{"type":"boolean"},"python_type":{"type":"bool","description":""},"component":"Api","example_input":false},{"label":"8th","parameter_name":"influences","parameter_has_default":true,"parameter_default":4,"type":{"type":"integer"},"python_type":{"type":"int","description":""},"component":"Api","example_input":4}],"returns":[{"label":"1st","type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api"}],"api_visibility":"public","description":"Rig a 3D mesh with SkinTokens: predict a skeleton and per-vertex skin weights, and return the result as JSON with a URL for every output file: the rigged GLB (mesh + armature + weights), rig.json (joint names, hierarchy, rest positions, skin statistics), skin.npz, preview.png (look at it with view_rig) and preview.glb (visible bones + a test motion). Takes 20-60 s of ZeroGPU time, billed to the caller.","code_snippets":{"python":"from gradio_client import Client\n\nclient = Client(\"townbox/skintokens-for-agents\")\nresult = client.predict(\n\tmesh_url=\"\",\n\texample=\"\",\n\tnum_beams=10,\n\tseed=-1,\n\tkeep_skeleton=False,\n\tpreserve_original=False,\n\tpostprocess=False,\n\tinfluences=4,\n\tapi_name=\"/rig\",\n)\nprint(result)","javascript":"import { Client } from \"@gradio/client\";\n\nconst client = await Client.connect(\"townbox/skintokens-for-agents\");\nconst result = await client.predict(\"/rig\", {\n\t\tmesh_url: \"\",\n\t\texample: \"\",\n\t\tnum_beams: 10,\n\t\tseed: -1,\n\t\tkeep_skeleton: false,\n\t\tpreserve_original: false,\n\t\tpostprocess: false,\n\t\tinfluences: 4,\n});\n\nconsole.log(result.data);","bash":"curl -X POST http://localhost:7860/gradio_api/call/v2/rig -s -H \"Content-Type: application/json\" \\\n  -d '{\"mesh_url\": \"\", \"example\": \"\", \"num_beams\": 10, \"seed\": -1, \"keep_skeleton\": false, \"preserve_original\": false, \"postprocess\": false, \"influences\": 4}' \\\n  | awk -F'\"' '{ print $4}' \\\n  | read EVENT_ID; curl -N http://localhost:7860/gradio_api/call/rig/$EVENT_ID","cli":"{command} predict townbox/skintokens-for-agents /rig '{\n  \"mesh_url\": \"\",\n  \"example\": \"\",\n  \"num_beams\": 10,\n  \"seed\": -1,\n  \"keep_skeleton\": false,\n  \"preserve_original\": false,\n  \"postprocess\": false,\n  \"influences\": 4\n}'\n"}},"/list_examples":{"parameters":[],"returns":[{"label":"1st","type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api"}],"api_visibility":"public","description":"The bundled example meshes (id, description, license, URL) that rig can take by id, and the real results this Space generated from them with the options that reproduce each.","code_snippets":{"python":"from gradio_client import Client\n\nclient = Client(\"townbox/skintokens-for-agents\")\nresult = client.predict(\n\tapi_name=\"/list_examples\",\n)\nprint(result)","javascript":"import { Client } from \"@gradio/client\";\n\nconst client = await Client.connect(\"townbox/skintokens-for-agents\");\nconst result = await client.predict(\"/list_examples\", {\n});\n\nconsole.log(result.data);","bash":"curl -X POST http://localhost:7860/gradio_api/call/v2/list_examples -s -H \"Content-Type: application/json\" \\\n  -d '{}' \\\n  | awk -F'\"' '{ print $4}' \\\n  | read EVENT_ID; curl -N http://localhost:7860/gradio_api/call/list_examples/$EVENT_ID","cli":"{command} predict townbox/skintokens-for-agents /list_examples '{}'\n"}},"/get_result":{"parameters":[{"label":"1st","parameter_name":"job_id","parameter_has_default":false,"parameter_default":null,"type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api","example_input":"..."}],"returns":[{"label":"1st","type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api"}],"api_visibility":"public","description":"A finished rig result again (kept 24 h): input, options, rig summary, file URLs, timings, provenance.","code_snippets":{"python":"from gradio_client import Client\n\nclient = Client(\"townbox/skintokens-for-agents\")\nresult = client.predict(\n\tjob_id=\"...\",\n\tapi_name=\"/get_result\",\n)\nprint(result)","javascript":"import { Client } from \"@gradio/client\";\n\nconst client = await Client.connect(\"townbox/skintokens-for-agents\");\nconst result = await client.predict(\"/get_result\", {\n\t\tjob_id: \"...\",\n});\n\nconsole.log(result.data);","bash":"curl -X POST http://localhost:7860/gradio_api/call/v2/get_result -s -H \"Content-Type: application/json\" \\\n  -d '{\"job_id\": \"...\"}' \\\n  | awk -F'\"' '{ print $4}' \\\n  | read EVENT_ID; curl -N http://localhost:7860/gradio_api/call/get_result/$EVENT_ID","cli":"{command} predict townbox/skintokens-for-agents /get_result '{\n  \"job_id\": \"...\"\n}'\n"}},"/view_rig":{"parameters":[{"label":"1st","parameter_name":"job_id","parameter_has_default":false,"parameter_default":null,"type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api","example_input":"..."}],"returns":[{"label":"1st","type":{"type":"object","additionalProperties":{}},"python_type":{"type":"dict(str, Any)","description":""},"component":"Api"}],"api_visibility":"public","description":"Look at a rig: the preview PNG (mesh with the predicted skeleton drawn over it, front and side views) of a rig result.","code_snippets":{"python":"from gradio_client import Client\n\nclient = Client(\"townbox/skintokens-for-agents\")\nresult = client.predict(\n\tjob_id=\"...\",\n\tapi_name=\"/view_rig\",\n)\nprint(result)","javascript":"import { Client } from \"@gradio/client\";\n\nconst client = await Client.connect(\"townbox/skintokens-for-agents\");\nconst result = await client.predict(\"/view_rig\", {\n\t\tjob_id: \"...\",\n});\n\nconsole.log(result.data);","bash":"curl -X POST http://localhost:7860/gradio_api/call/v2/view_rig -s -H \"Content-Type: application/json\" \\\n  -d '{\"job_id\": \"...\"}' \\\n  | awk -F'\"' '{ print $4}' \\\n  | read EVENT_ID; curl -N http://localhost:7860/gradio_api/call/view_rig/$EVENT_ID","cli":"{command} predict townbox/skintokens-for-agents /view_rig '{\n  \"job_id\": \"...\"\n}'\n"}},"/service_info":{"parameters":[],"returns":[{"label":"1st","type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api"}],"api_visibility":"public","description":"What this service does, every parameter with its default, limits, model provenance and licenses, and who pays the GPU time for this connection.","code_snippets":{"python":"from gradio_client import Client\n\nclient = Client(\"townbox/skintokens-for-agents\")\nresult = client.predict(\n\tapi_name=\"/service_info\",\n)\nprint(result)","javascript":"import { Client } from \"@gradio/client\";\n\nconst client = await Client.connect(\"townbox/skintokens-for-agents\");\nconst result = await client.predict(\"/service_info\", {\n});\n\nconsole.log(result.data);","bash":"curl -X POST http://localhost:7860/gradio_api/call/v2/service_info -s -H \"Content-Type: application/json\" \\\n  -d '{}' \\\n  | awk -F'\"' '{ print $4}' \\\n  | read EVENT_ID; curl -N http://localhost:7860/gradio_api/call/service_info/$EVENT_ID","cli":"{command} predict townbox/skintokens-for-agents /service_info '{}'\n"}},"/guide":{"parameters":[],"returns":[{"label":"1st","type":{"type":"string"},"python_type":{"type":"str","description":""},"component":"Api"}],"api_visibility":"public","description":"The full agent guide (same as /llms.txt): workflow, parameters, outputs, errors, examples.","code_snippets":{"python":"from gradio_client import Client\n\nclient = Client(\"townbox/skintokens-for-agents\")\nresult = client.predict(\n\tapi_name=\"/guide\",\n)\nprint(result)","javascript":"import { Client } from \"@gradio/client\";\n\nconst client = await Client.connect(\"townbox/skintokens-for-agents\");\nconst result = await client.predict(\"/guide\", {\n});\n\nconsole.log(result.data);","bash":"curl -X POST http://localhost:7860/gradio_api/call/v2/guide -s -H \"Content-Type: application/json\" \\\n  -d '{}' \\\n  | awk -F'\"' '{ print $4}' \\\n  | read EVENT_ID; curl -N http://localhost:7860/gradio_api/call/guide/$EVENT_ID","cli":"{command} predict townbox/skintokens-for-agents /guide '{}'\n"}}},"unnamed_endpoints":{}}