@genkit-ai/dotprompt/lib/picoschema.mjs.map

Genkit AI framework `.prompt` file format and management library.

{"version":3,"sources":["../src/picoschema.ts"],"sourcesContent":["/**\n * Copyright 2024 Google LLC\n *\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n *     http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n */\n\nconst JSON_SCHEMA_SCALAR_TYPES = [\n  'string',\n  'boolean',\n  'null',\n  'number',\n  'integer',\n  'any',\n];\n\nconst WILDCARD_PROPERTY_NAME = '(*)';\n\nimport { JSONSchema } from '@genkit-ai/core/schema';\n\nexport function picoschema(schema: unknown): JSONSchema | null {\n  if (!schema) return null;\n  // if there's a JSON schema-ish type at the top level, treat as JSON schema\n  if (\n    [...JSON_SCHEMA_SCALAR_TYPES, 'object', 'array'].includes(\n      (schema as any)?.type\n    )\n  ) {\n    return schema;\n  }\n\n  if (typeof (schema as any)?.properties === 'object') {\n    return { ...schema, type: 'object' };\n  }\n\n  return parsePico(schema);\n}\n\nfunction extractDescription(input: string): [string, string | null] {\n  if (!input.includes(',')) return [input, null];\n\n  const match = input.match(/(.*?), *(.*)$/);\n  return [match![1], match![2]];\n}\n\nfunction parsePico(obj: any, path: string[] = []): JSONSchema {\n  if (typeof obj === 'string') {\n    const [type, description] = extractDescription(obj);\n    if (!JSON_SCHEMA_SCALAR_TYPES.includes(type)) {\n      throw new Error(`Picoschema: Unsupported scalar type '${type}'.`);\n    }\n\n    if (type === 'any') {\n      return description ? { description } : {};\n    }\n\n    return description ? { type, description } : { type };\n  } else if (typeof obj !== 'object') {\n    throw new Error(\n      'Picoschema: only consists of objects and strings. Got: ' +\n        JSON.stringify(obj)\n    );\n  }\n\n  const schema: JSONSchema = {\n    type: 'object',\n    properties: {},\n    required: [],\n    additionalProperties: false,\n  };\n\n  for (const key in obj) {\n    // wildcard property\n    if (key === WILDCARD_PROPERTY_NAME) {\n      schema.additionalProperties = parsePico(obj[key], [...path, key]);\n      continue;\n    }\n\n    const [name, typeInfo] = key.split('(');\n    const isOptional = name.endsWith('?');\n    const propertyName = isOptional ? name.slice(0, -1) : name;\n\n    if (!isOptional) {\n      schema.required.push(propertyName);\n    }\n\n    if (!typeInfo) {\n      const prop = parsePico(obj[key], [...path, key]);\n      // make all optional fields also nullable\n      if (isOptional && typeof prop.type === 'string') {\n        prop.type = [prop.type, 'null'];\n      }\n      schema.properties[propertyName] = prop;\n      continue;\n    }\n\n    const [type, description] = extractDescription(\n      typeInfo.substring(0, typeInfo.length - 1)\n    );\n    if (type === 'array') {\n      schema.properties[propertyName] = {\n        type: isOptional ? 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