@genkit-ai/ai/lib/model-types.mjs.map

Genkit AI framework generative AI APIs.

{"version":3,"sources":["../src/model-types.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\nimport { OperationSchema, z } from '@genkit-ai/core';\nimport { DocumentDataSchema } from './document.js';\nimport {\n  CustomPartSchema,\n  DataPartSchema,\n  MediaPartSchema,\n  ReasoningPartSchema,\n  ResourcePartSchema,\n  TextPartSchema,\n  ToolRequestPartSchema,\n  ToolResponsePartSchema,\n} from './parts.js';\n\n//\n// IMPORTANT: Please keep type definitions in sync with\n//   genkit-tools/src/types/model.ts\n//\n\n/**\n * Zod schema of message part.\n */\nexport const PartSchema = z.union([\n  TextPartSchema,\n  MediaPartSchema,\n  ToolRequestPartSchema,\n  ToolResponsePartSchema,\n  DataPartSchema,\n  CustomPartSchema,\n  ReasoningPartSchema,\n  ResourcePartSchema,\n]);\n\n/**\n * Message part.\n */\nexport type Part = z.infer<typeof PartSchema>;\n\n/**\n * Zod schema of a message role.\n */\nexport const RoleSchema = z.enum(['system', 'user', 'model', 'tool']);\n\n/**\n * Message role.\n */\nexport type Role = z.infer<typeof RoleSchema>;\n\n/**\n * Zod schema of a message.\n */\nexport const MessageSchema = z.object({\n  role: RoleSchema,\n  content: z.array(PartSchema),\n  metadata: z.record(z.unknown()).optional(),\n});\n\n/**\n * Model message data.\n */\nexport type MessageData = z.infer<typeof MessageSchema>;\n\n/**\n * Zod schema of model info metadata.\n */\nexport const ModelInfoSchema = z.object({\n  /** Acceptable names for this model (e.g. different versions). */\n  versions: z.array(z.string()).optional(),\n  /** Friendly label for this model (e.g. \"Google AI - Gemini Pro\") */\n  label: z.string().optional(),\n  /** Model Specific configuration. */\n  configSchema: z.record(z.any()).optional(),\n  /** Supported model capabilities. */\n  supports: z\n    .object({\n      /** Model can process historical messages passed with a prompt. */\n      multiturn: z.boolean().optional(),\n      /** Model can process media as part of the prompt (multimodal input). */\n      media: z.boolean().optional(),\n      /** Model can perform tool calls. */\n      tools: z.boolean().optional(),\n      /** Model can accept messages with role \"system\". */\n      systemRole: z.boolean().optional(),\n      /** Model can output this type of data. */\n      output: z.array(z.string()).optional(),\n      /** Model supports output in these content types. */\n      contentType: z.array(z.string()).optional(),\n      /** Model can natively support document-based context grounding. */\n      context: z.boolean().optional(),\n      /** Model can natively support constrained generation. */\n      constrained: z.enum(['none', 'all', 'no-tools']).optional(),\n      /** Model supports controlling tool choice, e.g. forced tool calling. */\n      toolChoice: z.boolean().optional(),\n    })\n    .optional(),\n  /** At which stage of development this model is.\n   * - `featured` models are recommended for general use.\n   * - `stable` models are well-tested and reliable.\n   * - `unstable` models are experimental and may change.\n   * - `legacy` models are no longer recommended for new projects.\n   * - `deprecated` models are deprecated by the provider and may be removed in future versions.\n   */\n  stage: z\n    .enum(['featured', 'stable', 'unstable', 'legacy', 'deprecated'])\n    .optional(),\n});\n\n/**\n * Model info metadata.\n */\nexport type ModelInfo = z.infer<typeof ModelInfoSchema>;\n\n/**\n * Zod schema of a tool definition.\n */\nexport const ToolDefinitionSchema = z.object({\n  name: z.string(),\n  description: z.string(),\n  inputSchema: z\n    .record(z.any())\n    .describe('Valid JSON Schema representing the input of the tool.')\n    .nullish(),\n  outputSchema: z\n    .record(z.any())\n    .describe('Valid JSON Schema describing the output of the tool.')\n    .nullish(),\n  metadata: z\n    .record(z.any())\n    .describe('additional metadata for this tool definition')\n    .optional(),\n});\n\n/**\n * Tool definition.\n */\nexport type ToolDefinition = z.infer<typeof ToolDefinitionSchema>;\n\n/**\n * Configuration parameter descriptions.\n */\nexport const GenerationCommonConfigDescriptions = {\n  temperature:\n    'Controls the degree of randomness in token selection. A lower value is ' +\n    'good for a more predictable response. A higher value leads to more ' +\n    'diverse or unexpected results.',\n  maxOutputTokens: 'The maximum number of tokens to include in the response.',\n  topK: 'The maximum number of tokens to consider when sampling.',\n  topP:\n    'Decides how many possible words to consider. A higher value means ' +\n    'that the model looks at more possible words, even the less likely ' +\n    'ones, which makes the generated text more diverse.',\n};\n\n/**\n * Zod schema of a common config object.\n */\nexport const GenerationCommonConfigSchema = z\n  .object({\n    version: z\n      .string()\n      .describe(\n        'A specific version of a model family, e.g. `gemini-2.5-flash` ' +\n          'for the `googleai` family.'\n      )\n      .optional(),\n    temperature: z\n      .number()\n      .describe(GenerationCommonConfigDescriptions.temperature)\n      .optional(),\n    maxOutputTokens: z\n      .number()\n      .describe(GenerationCommonConfigDescriptions.maxOutputTokens)\n      .optional(),\n    topK: z\n      .number()\n      .describe(GenerationCommonConfigDescriptions.topK)\n      .optional(),\n    topP: z\n      .number()\n      .describe(GenerationCommonConfigDescriptions.topP)\n      .optional(),\n    stopSequences: z\n      .array(z.string())\n      .max(5)\n      .describe(\n        'Set of character sequences (up to 5) that will stop output generation.'\n      )\n      .optional(),\n    apiKey: z\n      .string()\n      .describe(\n        'API Key to use for the model call, overrides API key provided in plugin config.'\n      )\n      .optional(),\n  })\n  .passthrough();\n\n/**\n * Common config object.\n */\nexport type GenerationCommonConfig = typeof GenerationCommonConfigSchema;\n\n/**\n * Zod schema of output config.\n */\nexport const OutputConfigSchema = z.object({\n  format: z.string().optional(),\n  schema: z.record(z.any()).optional(),\n  constrained: z.boolean().optional(),\n  contentType: z.string().optional(),\n});\n\n/**\n * Output config.\n */\nexport type OutputConfig = z.infer<typeof OutputConfigSchema>;\n\n/** ModelRequestSchema represents the parameters that are passed to a model when generating content. */\nexport const ModelRequestSchema = z.object({\n  messages: z.array(MessageSchema),\n  config: z.any().optional(),\n  tools: z.array(ToolDefinitionSchema).optional(),\n  toolChoice: z.enum(['auto', 'required', 'none']).optional(),\n  output: OutputConfigSchema.optional(),\n  docs: z.array(DocumentDataSchema).optional(),\n});\n/** ModelRequest represents the parameters that are passed to a model when generating content. */\nexport interface ModelRequest<\n  CustomOptionsSchema extends z.ZodTypeAny = z.ZodTypeAny,\n> extends z.infer<typeof ModelRequestSchema> {\n  config?: z.infer<CustomOptionsSchema>;\n}\n/**\n * Zod schema of a generate request.\n */\nexport const GenerateRequestSchema = ModelRequestSchema.extend({\n  /** @deprecated All responses now return a single candidate. This will always be `undefined`. */\n  candidates: z.number().optional(),\n});\n\n/**\n * Generate request data.\n */\nexport type GenerateRequestData = z.infer<typeof GenerateRequestSchema>;\n\n/**\n * Generate request.\n */\nexport interface GenerateRequest<\n  CustomOptionsSchema extends z.ZodTypeAny = z.ZodTypeAny,\n> extends z.infer<typeof GenerateRequestSchema> {\n  config?: z.infer<CustomOptionsSchema>;\n}\n\n/**\n * Zod schema of usage info from a generate request.\n */\nexport const GenerationUsageSchema = z.object({\n  inputTokens: z.number().optional(),\n  outputTokens: z.number().optional(),\n  totalTokens: z.number().optional(),\n  inputCharacters: z.number().optional(),\n  outputCharacters: z.number().optional(),\n  inputImages: z.number().optional(),\n  outputImages: z.number().optional(),\n  inputVideos: z.number().optional(),\n  outputVideos: z.number().optional(),\n  inputAudioFiles: z.number().optional(),\n  outputAudioFiles: z.number().optional(),\n  custom: z.record(z.number()).optional(),\n  thoughtsTokens: z.number().optional(),\n  cachedContentTokens: z.number().optional(),\n});\n\n/**\n * Usage info from a generate request.\n */\nexport type GenerationUsage = z.infer<typeof GenerationUsageSchema>;\n\n/** Model response finish reason enum. */\nexport const FinishReasonSchema = z.enum([\n  'stop',\n  'length',\n  'blocked',\n  'interrupted',\n  'other',\n  'unknown',\n]);\n\n/** @deprecated All responses now return a single candidate. Only the first candidate will be used if supplied. */\nexport const CandidateSchema = z.object({\n  index: z.number(),\n  message: MessageSchema,\n  usage: GenerationUsageSchema.optional(),\n  finishReason: FinishReasonSchema,\n  finishMessage: z.string().optional(),\n  custom: z.unknown(),\n});\n/** @deprecated All responses now return a single candidate. Only the first candidate will be used if supplied. */\nexport type CandidateData = z.infer<typeof CandidateSchema>;\n\n/** @deprecated All responses now return a single candidate. Only the first candidate will be used if supplied. */\nexport const CandidateErrorSchema = z.object({\n  index: z.number(),\n  code: z.enum(['blocked', 'other', 'unknown']),\n  message: z.string().optional(),\n});\n/** @deprecated All responses now return a single candidate. Only the first candidate will be used if supplied. */\nexport type CandidateError = z.infer<typeof CandidateErrorSchema>;\n\n/**\n * Zod schema of a model response.\n */\nexport const ModelResponseSchema = z.object({\n  message: MessageSchema.optional(),\n  finishReason: FinishReasonSchema,\n  finishMessage: z.string().optional(),\n  latencyMs: z.number().optional(),\n  usage: GenerationUsageSchema.optional(),\n  /** @deprecated use `raw` instead */\n  custom: z.unknown(),\n  raw: z.unknown(),\n  request: GenerateRequestSchema.optional(),\n  operation: OperationSchema.optional(),\n});\n\n/**\n * Model response data.\n */\nexport type ModelResponseData = z.infer<typeof ModelResponseSchema>;\n\n/**\n * Zod schema of generaete response.\n */\nexport const GenerateResponseSchema = ModelResponseSchema.extend({\n  /** @deprecated All responses now return a single candidate. Only the first candidate will be used if supplied. Return `message`, `finishReason`, and `finishMessage` instead. */\n  candidates: z.array(CandidateSchema).optional(),\n  finishReason: FinishReasonSchema.optional(),\n});\n\n/**\n * Generate response data.\n */\nexport type GenerateResponseData = z.infer<typeof GenerateResponseSchema>;\n\n/** ModelResponseChunkSchema represents a chunk of content to stream to the client. */\nexport const ModelResponseChunkSchema = z.object({\n  role: RoleSchema.optional(),\n  /** index of the message this chunk belongs to. */\n  index: z.number().optional(),\n  /** The chunk of content to stream right now. */\n  content: z.array(PartSchema),\n  /** Model-specific extra information attached to this chunk. */\n  custom: z.unknown().optional(),\n  /** If true, the chunk includes all data from previous chunks. Otherwise, considered to be incremental. */\n  aggregated: z.boolean().optional(),\n});\nexport type ModelResponseChunkData = z.infer<typeof ModelResponseChunkSchema>;\n\nexport const GenerateResponseChunkSchema = ModelResponseChunkSchema;\nexport type GenerateResponseChunkData = z.infer<\n  typeof GenerateResponseChunkSchema\n>;\n\nexport const GenerateActionOutputConfig = z.object({\n  format: z.string().optional(),\n  contentType: z.string().optional(),\n  instructions: z.union([z.boolean(), z.string()]).optional(),\n  jsonSchema: z.any().optional(),\n  constrained: z.boolean().optional(),\n});\n\nexport const GenerateActionOptionsSchema = z.object({\n  /** A model name (e.g. `vertexai/gemini-1.0-pro`). */\n  model: z.string().optional(),\n  /** Retrieved documents to be used as context for this generation. */\n  docs: z.array(DocumentDataSchema).optional(),\n  /** Conversation history for multi-turn prompting when supported by the underlying model. */\n  messages: z.array(MessageSchema),\n  /** List of registered tool names for this generation if supported by the underlying model. */\n  tools: z.array(z.string()).optional(),\n  /** List of registered resource names for this generation if supported by the underlying model. */\n  resources: z.array(z.string()).optional(),\n  /** Tool calling mode. `auto` lets the model decide whether to use tools, `required` forces the model to choose a tool, and `none` forces the model not to use any tools. Defaults to `auto`.  */\n  toolChoice: z.enum(['auto', 'required', 'none']).optional(),\n  /** Configuration for the generation request. */\n  config: z.any().optional(),\n  /** Configuration for the desired output of the request. Defaults to the model's default output if unspecified. */\n  output: GenerateActionOutputConfig.optional(),\n  /** Options for resuming an interrupted generation. */\n  resume: z\n    .object({\n      respond: z.array(ToolResponsePartSchema).optional(),\n      restart: z.array(ToolRequestPartSchema).optional(),\n      metadata: z.record(z.any()).optional(),\n    })\n    .optional(),\n  /** When true, return tool calls for manual processing instead of automatically resolving them. */\n  returnToolRequests: z.boolean().optional(),\n  /** Maximum number of tool call iterations that can be performed in a single generate call (default 5). */\n  maxTurns: z.number().optional(),\n  /** Custom step name for this generate call to display in trace views. Defaults to \"generate\". */\n  stepName: z.string().optional(),\n});\nexport type GenerateActionOptions = z.infer<typeof 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