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Parses `.prompt.mdx` files and formats them into a neutral `{ messages, ...config }` shape you hand to whatever LLM SDK you already use — the Vercel AI SDK, the raw OpenAI or Anthropic client, Pydantic AI, or your own bespoke client.\n\n## Installation\n\n```bash\nnpm install @agentmark-ai/prompt-core\n```\n\n## Quick Start\n\n```typescript\nimport { createAgentMark } from \"@agentmark-ai/prompt-core\";\nimport { FileLoader } from \"@agentmark-ai/prompt-core/loader-file\";\n\n// Loads prompts pre-built by `agentmark build`\nconst agentmark = createAgentMark({\n loader: new FileLoader(\"./dist/agentmark\"),\n});\n\nconst prompt = await agentmark.loadTextPrompt(\"customer-support.prompt.mdx\");\nconst { messages, ...config } = await prompt.format({\n props: { customer_question: \"How long does shipping take?\" },\n});\n\n// Hand `messages` + `config` to your SDK of choice\n```\n\nSee the [bring-your-own-SDK guide](https://docs.agentmark.co/integrations/bring-your-own-sdk) for the full integration path.\n\n## API\n\n### `createAgentMark(options)`\n\nCreate an AgentMark instance.\n\n```typescript\nconst agentmark = createAgentMark({\n loader, // Optional: where prompts load from (file, API, or custom)\n evals, // Optional: eval functions keyed by name, for experiments\n builtInModels, // Optional: allowed model names (validates frontmatter model_name)\n templateEngine, // Optional: custom template engine (defaults to TemplateDX)\n});\n```\n\n### Loading prompts\n\nOne loader method per generation type. Each returns a typed prompt object with a `format()` method:\n\n- **`agentmark.loadTextPrompt(path)`** — text generation (`text_config`)\n- **`agentmark.loadObjectPrompt(path)`** — structured output (`object_config`)\n- **`agentmark.loadImagePrompt(path)`** — image generation (`image_config`)\n- **`agentmark.loadSpeechPrompt(path)`** — speech generation (`speech_config`)\n\n### Loaders\n\n- **`FileLoader`** (`@agentmark-ai/prompt-core/loader-file`) — load prompts pre-built by `agentmark build`. For self-hosted deployments with no runtime API calls.\n- **`ApiLoader`** (`@agentmark-ai/prompt-core/loader-api`) — load prompts from AgentMark Cloud or a local `agentmark dev` server.\n\nSee [Loaders](https://docs.agentmark.co/configure/loaders).\n\n> The standalone `@agentmark-ai/loader-api` and `@agentmark-ai/loader-file` packages are re-export shims of these subpaths — prefer the subpaths in new code.\n\n### Type safety\n\nGenerate types from your prompts with `agentmark generate-types`, then parameterize the instance for end-to-end type-safe props and outputs:\n\n```typescript\nimport type AgentmarkTypes from \"./agentmark.types\";\n\nconst agentmark = createAgentMark({ loader });\n```\n\nSee [Type safety](https://docs.agentmark.co/configure/type-safety).\n\n## Documentation\n\nFull documentation at [docs.agentmark.co](https://docs.agentmark.co).\n\n## License\n\n[AGPL-3.0-or-later](../../LICENSE.md)\n","readmeFilename":"README.md"}