@genkit-ai/ai/lib/embedder.mjs.map

Genkit AI framework generative AI APIs.

{"version":3,"sources":["../src/embedder.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 {\n  action,\n  defineAction,\n  z,\n  type Action,\n  type ActionFnArg,\n  type ActionMetadata,\n  type ActionParams,\n} from '@genkit-ai/core';\nimport type { Registry } from '@genkit-ai/core/registry';\nimport { toJsonSchema } from '@genkit-ai/core/schema';\nimport { Document, DocumentDataSchema, type DocumentData } from './document.js';\n\n/**\n * A batch (array) of embeddings.\n */\nexport type EmbeddingBatch = { embedding: number[] }[];\n\n/**\n * EmbeddingSchema includes the embedding and also metadata so you know\n * which of multiple embeddings corresponds to which part of a document.\n */\nexport const EmbeddingSchema = z.object({\n  embedding: z.array(z.number()),\n  metadata: z.record(z.string(), z.unknown()).optional(),\n});\nexport type Embedding = z.infer<typeof EmbeddingSchema>;\n\n/**\n * A function used for embedder definition, encapsulates embedder implementation.\n */\nexport type EmbedderFn<EmbedderOptions extends z.ZodTypeAny> = (\n  input: Document[],\n  embedderOpts?: z.infer<EmbedderOptions>\n) => Promise<EmbedResponse>;\n\n/**\n * Zod schema of an embed request.\n */\nconst EmbedRequestSchema = z.object({\n  input: z.array(DocumentDataSchema),\n  options: z.any().optional(),\n});\n\nexport interface EmbedRequest<O = any> {\n  input: Document[];\n  options?: O;\n}\n\n/**\n * Zod schema of an embed response.\n */\nconst EmbedResponseSchema = z.object({\n  embeddings: z.array(EmbeddingSchema),\n  // TODO: stats, etc.\n});\ntype EmbedResponse = z.infer<typeof EmbedResponseSchema>;\n\n/**\n * Embedder action -- a subtype of {@link Action} with input/output types for embedders.\n */\nexport type EmbedderAction<CustomOptions extends z.ZodTypeAny = z.ZodTypeAny> =\n  Action<typeof EmbedRequestSchema, typeof EmbedResponseSchema> & {\n    __configSchema?: CustomOptions;\n  };\n\n/**\n * Options of an `embed` function.\n */\nexport interface EmbedderParams<\n  CustomOptions extends z.ZodTypeAny = z.ZodTypeAny,\n> {\n  embedder: EmbedderArgument<CustomOptions>;\n  content: string | DocumentData;\n  metadata?: Record<string, unknown>;\n  options?: z.infer<CustomOptions>;\n}\n\nfunction withMetadata<CustomOptions extends z.ZodTypeAny>(\n  embedder: Action<typeof EmbedRequestSchema, typeof EmbedResponseSchema>,\n  configSchema?: CustomOptions\n): EmbedderAction<CustomOptions> {\n  const withMeta = embedder as EmbedderAction<CustomOptions>;\n  withMeta.__configSchema = configSchema;\n  return withMeta;\n}\n\nexport interface EmbedderOptions<ConfigSchema extends z.ZodTypeAny> {\n  name: string;\n  configSchema?: ConfigSchema;\n  info?: EmbedderInfo;\n}\n\n/**\n * Creates embedder model for the provided {@link EmbedderFn} model implementation.\n *\n * Unlike `defineEmbedder` this function does not register the embedder in the reigistry.\n */\nexport function embedder<ConfigSchema extends z.ZodTypeAny = z.ZodTypeAny>(\n  options: EmbedderOptions<ConfigSchema>,\n  runner: (\n    input: EmbedRequest<z.infer<ConfigSchema>>,\n    opts: ActionFnArg<any>\n  ) => Promise<EmbedResponse>\n) {\n  const embedder = action(embedderActionOptions(options), (i, opts) =>\n    runner(\n      {\n        input: i.input.map((dd) => new Document(dd)),\n        options: i.options,\n      },\n      opts\n    )\n  );\n  const ewm = withMetadata(\n    embedder as Action<typeof EmbedRequestSchema, typeof EmbedResponseSchema>,\n    options.configSchema\n  );\n  return ewm;\n}\n\nfunction embedderActionOptions<\n  ConfigSchema extends z.ZodTypeAny = z.ZodTypeAny,\n>(\n  options: EmbedderOptions<ConfigSchema>\n): ActionParams<typeof EmbedRequestSchema, typeof EmbedResponseSchema> {\n  return {\n    actionType: 'embedder',\n    name: options.name,\n    inputSchema: EmbedRequestSchema,\n    outputSchema: EmbedResponseSchema,\n    metadata: {\n      type: 'embedder',\n      info: options.info,\n      embedder: {\n        customOptions: options.configSchema\n          ? toJsonSchema({ schema: options.configSchema })\n          : undefined,\n      },\n    },\n  };\n}\n\n/**\n * Creates embedder model for the provided {@link EmbedderFn} model implementation.\n */\nexport function defineEmbedder<\n  ConfigSchema extends z.ZodTypeAny = z.ZodTypeAny,\n>(\n  registry: Registry,\n  options: EmbedderOptions<ConfigSchema>,\n  runner: EmbedderFn<ConfigSchema>\n) {\n  const embedder = defineAction(registry, embedderActionOptions(options), (i) =>\n    runner(\n      i.input.map((dd) => new Document(dd)),\n      i.options\n    )\n  );\n  const ewm = withMetadata(\n    embedder as Action<typeof EmbedRequestSchema, typeof EmbedResponseSchema>,\n    options.configSchema\n  );\n  return ewm;\n}\n\n/**\n * A union type representing all the types that can refer to an embedder.\n */\nexport type EmbedderArgument<\n  CustomOptions extends z.ZodTypeAny = z.ZodTypeAny,\n> = string | EmbedderAction<CustomOptions> | EmbedderReference<CustomOptions>;\n\n/**\n * A veneer for interacting with embedder models.\n */\nexport async function embed<CustomOptions extends z.ZodTypeAny = z.ZodTypeAny>(\n  registry: Registry,\n  params: EmbedderParams<CustomOptions>\n): Promise<Embedding[]> {\n  const embedder = await resolveEmbedder(registry, params);\n  if (!embedder.embedderAction) {\n    let embedderId: string;\n    if (typeof params.embedder === 'string') {\n      embedderId = params.embedder;\n    } else if ((params.embedder as EmbedderAction)?.__action?.name) {\n      embedderId = (params.embedder as EmbedderAction).__action.name;\n    } else {\n      embedderId = (params.embedder as EmbedderReference<any>).name;\n    }\n    throw new Error(`Unable to resolve embedder ${embedderId}`);\n  }\n  const response = await embedder.embedderAction({\n    input:\n      typeof params.content === 'string'\n        ? [Document.fromText(params.content, params.metadata)]\n        : [params.content],\n    options: {\n      version: embedder.version,\n      ...embedder.config,\n      ...params.options,\n    },\n  });\n  return response.embeddings;\n}\n\ninterface ResolvedEmbedder<CustomOptions extends z.ZodTypeAny = z.ZodTypeAny> {\n  embedderAction: EmbedderAction<CustomOptions>;\n  config?: z.infer<CustomOptions>;\n  version?: string;\n}\n\nasync function resolveEmbedder<\n  CustomOptions extends z.ZodTypeAny = z.ZodTypeAny,\n>(\n  registry: Registry,\n  params: EmbedderParams<CustomOptions>\n): Promise<ResolvedEmbedder<CustomOptions>> {\n  if (typeof params.embedder === 'string') {\n    return {\n      embedderAction: await registry.lookupAction(\n        `/embedder/${params.embedder}`\n      ),\n    };\n  } else if (Object.hasOwnProperty.call(params.embedder, '__action')) {\n    return {\n      embedderAction: params.embedder as EmbedderAction<CustomOptions>,\n    };\n  } else if (Object.hasOwnProperty.call(params.embedder, 'name')) {\n    const ref = params.embedder as EmbedderReference<any>;\n    return {\n      embedderAction: await registry.lookupAction(\n        `/embedder/${(params.embedder as EmbedderReference).name}`\n      ),\n      config: {\n        ...ref.config,\n      },\n      version: ref.version,\n    };\n  }\n  throw new Error(`failed to resolve embedder ${params.embedder}`);\n}\n\n/**\n * A veneer for interacting with embedder models in bulk.\n */\nexport async function embedMany<\n  ConfigSchema extends z.ZodTypeAny = z.ZodTypeAny,\n>(\n  registry: Registry,\n  params: {\n    embedder: EmbedderArgument<ConfigSchema>;\n    content: string[] | DocumentData[];\n    metadata?: Record<string, unknown>;\n    options?: z.infer<ConfigSchema>;\n  }\n): Promise<EmbeddingBatch> {\n  let embedder: EmbedderAction<ConfigSchema>;\n  if (typeof params.embedder === 'string') {\n    embedder = await registry.lookupAction(`/embedder/${params.embedder}`);\n  } else if (Object.hasOwnProperty.call(params.embedder, 'info')) {\n    embedder = await registry.lookupAction(\n      `/embedder/${(params.embedder as EmbedderReference).name}`\n    );\n  } else {\n    embedder = params.embedder as EmbedderAction<ConfigSchema>;\n  }\n  if (!embedder) {\n    throw new Error('Unable to utilize the provided embedder');\n  }\n  const response = await embedder({\n    input: params.content.map((i) =>\n      typeof i === 'string' ? Document.fromText(i, params.metadata) : i\n    ),\n    options: params.options,\n  });\n  return response.embeddings;\n}\n\n/**\n * Zod schema of embedder info object.\n */\nexport const EmbedderInfoSchema = z.object({\n  /** Friendly label for this model (e.g. \"Google AI - Gemini Pro\") */\n  label: z.string().optional(),\n  /** Supported model capabilities. */\n  supports: z\n    .object({\n      /** Model can input this type of data. */\n      input: z.array(z.enum(['text', 'image', 'video'])).optional(),\n      /** Model can support multiple languages */\n      multilingual: z.boolean().optional(),\n    })\n    .optional(),\n  /** Embedding dimension */\n  dimensions: z.number().optional(),\n});\nexport type EmbedderInfo = z.infer<typeof EmbedderInfoSchema>;\n\n/**\n * A reference object that can used to resolve an embedder instance. 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