{"version":1,"pages":[{"id":"LThc2RqOxBKU56Qt3TMy","title":"Maniac: Continually optimizing models from your LLM telemetry and evals.","pathname":"/","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"Getting Started"}]},{"id":"ooyUwiWr0ym4n9dYs77n","title":"Agent Setup","pathname":"/getting-started/agent-setup","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"Getting Started"}]},{"id":"RO4qggzbdWtRp8hgLQAM","title":"Registering in Batches","pathname":"/datasets/registering-in-batches","siteSpaceId":"sitesp_uqdh3","description":"Adding pre-existing data to a container.","breadcrumbs":[{"label":"Datasets"}]},{"id":"mTiFGR7vYZAtHNkFI2xN","title":"Building New Agents","pathname":"/datasets/building-new-agents","siteSpaceId":"sitesp_uqdh3","description":"Register inputs for a new agent and let Maniac bootstrap completions and build a model.","breadcrumbs":[{"label":"Datasets"}]},{"id":"3fdft1kJ2l126lslxpNu","title":"Using the Datasets Feature","pathname":"/datasets/using-the-datasets-feature","siteSpaceId":"sitesp_uqdh3","description":"Deriving datasets from your inference logs.","breadcrumbs":[{"label":"Datasets"}]},{"id":"HpNIrSMAN0h88b6iOSx0","title":"Creating Evaluations","pathname":"/evaluations/creating-evaluations","siteSpaceId":"sitesp_uqdh3","description":"Code and judge evals for your Maniac models.","breadcrumbs":[{"label":"Evaluations"}]},{"id":"EbEVzAlIOUadjjm1fDHs","title":"Supported Models","pathname":"/optimization/supported-models","siteSpaceId":"sitesp_uqdh3","description":"Base and frontier models supported by Maniac for optimization and evaluation.","breadcrumbs":[{"label":"Optimization"}]},{"id":"d2ca529d6fa56c61d93298bf3f1d32d1f2343175","title":"Chat","pathname":"/api-reference/chat","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"8bdf1b1e73f3fbdbe1c634b54472f6a240b86282","title":"RLM","pathname":"/api-reference/rlm","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"dfebd8474d8fddd1811593ae6b64ae221a2fe31f","title":"Traces","pathname":"/api-reference/traces","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"5e5bad15c532207c2bc5795ad7fb95bf7ba2e8b0","title":"Containers","pathname":"/api-reference/containers","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"1c7f76c43a0ee880aed893cc579c183417375df6","title":"Files","pathname":"/api-reference/files","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"f3455b72e3021c269efd4589f45a276195e02b2b","title":"Models","pathname":"/api-reference/models","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"bcaa53485d26b026efc7ffe915de4376a2073bb7","title":"Evaluation","pathname":"/api-reference/evaluation","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"f1a34c5f4d0af31fbf4b8b96d273863e620c45cc","title":"Datasets","pathname":"/api-reference/datasets","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"ebcc280720211c0e76ffb64c2703de2dc2a0d15e","title":"Optimization","pathname":"/api-reference/optimization","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"42bb604151d3411fb30d9da39365011cb0fd44bc","title":"Health","pathname":"/api-reference/health","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"API Reference"}]},{"id":"5da91ea7e9ce801d3bde263c642fb9c1798d3005","title":"Models","pathname":"/api-reference/models-1","siteSpaceId":"sitesp_uqdh3","breadcrumbs":[{"label":"API Reference"}]},{"id":"olL9JLRfkIwfAROGGNBE","title":"Vercel AI SDK","pathname":"/examples/vercel-ai-sdk","siteSpaceId":"sitesp_uqdh3","description":"","breadcrumbs":[{"label":"Examples"}]}]}