0x1998 - MANAGER

Düzenlenen Dosya: index.node.mjs.map

{"version":3,"file":"index.node.mjs","sources":["../src/constants.ts","../src/errors.ts","../src/types/enums.ts","../src/types/responses.ts","../src/types/error.ts","../src/types/schema.ts","../src/types/imagen/requests.ts","../src/public-types.ts","../src/backend.ts","../src/helpers.ts","../src/service.ts","../src/factory-node.ts","../src/models/utils.ts","../src/models/ai-model.ts","../src/logger.ts","../src/requests/request.ts","../src/requests/response-helpers.ts","../src/googleai-mappers.ts","../src/requests/stream-reader.ts","../src/requests/hybrid-helpers.ts","../src/methods/generate-content.ts","../src/requests/request-helpers.ts","../src/methods/chat-session-helpers.ts","../src/methods/chat-session.ts","../src/methods/count-tokens.ts","../src/models/generative-model.ts","../src/methods/live-session.ts","../src/models/live-generative-model.ts","../src/models/imagen-model.ts","../src/websocket.ts","../src/models/template-generative-model.ts","../src/models/template-imagen-model.ts","../src/requests/schema-builder.ts","../src/requests/imagen-image-format.ts","../src/methods/live-session-helpers.ts","../src/api.ts","../src/index.node.ts"],"sourcesContent":["/**\n * @license\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 { version } from '../package.json';\n\nexport const AI_TYPE = 'AI';\n\nexport const DEFAULT_LOCATION = 'us-central1';\n\nexport const DEFAULT_DOMAIN = 'firebasevertexai.googleapis.com';\n\nexport const STAGING_URL =\n 'https://staging-firebasevertexai.sandbox.googleapis.com';\n\nexport const DEFAULT_API_VERSION = 'v1beta';\n\nexport const PACKAGE_VERSION = version;\n\nexport const LANGUAGE_TAG = 'gl-js';\n\nexport const HYBRID_TAG = 'hybrid';\n\nexport const DEFAULT_FETCH_TIMEOUT_MS = 180 * 1000;\n\n/**\n * Defines the name of the default in-cloud model to use for hybrid inference.\n */\nexport const DEFAULT_HYBRID_IN_CLOUD_MODEL = 'gemini-2.5-flash-lite';\n","/**\n * @license\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 { FirebaseError } from '@firebase/util';\nimport { AIErrorCode, CustomErrorData } from './types';\nimport { AI_TYPE } from './constants';\n\n/**\n * Error class for the Firebase AI SDK.\n *\n * @public\n */\nexport class AIError extends FirebaseError {\n /**\n * Constructs a new instance of the `AIError` class.\n *\n * @param code - The error code from {@link (AIErrorCode:type)}.\n * @param message - A human-readable message describing the error.\n * @param customErrorData - Optional error data.\n */\n constructor(\n readonly code: AIErrorCode,\n message: string,\n readonly customErrorData?: CustomErrorData\n ) {\n // Match error format used by FirebaseError from ErrorFactory\n const service = AI_TYPE;\n const fullCode = `${service}/${code}`;\n const fullMessage = `${service}: ${message} (${fullCode})`;\n super(code, fullMessage);\n\n // FirebaseError initializes a stack trace, but it assumes the error is created from the error\n // factory. Since we break this assumption, we set the stack trace to be originating from this\n // constructor.\n // This is only supported in V8.\n if (Error.captureStackTrace) {\n // Allows us to initialize the stack trace without including the constructor itself at the\n // top level of the stack trace.\n Error.captureStackTrace(this, AIError);\n }\n\n // Allows instanceof AIError in ES5/ES6\n // https://github.com/Microsoft/TypeScript-wiki/blob/master/Breaking-Changes.md#extending-built-ins-like-error-array-and-map-may-no-longer-work\n // TODO(dlarocque): Replace this with `new.target`: https://www.typescriptlang.org/docs/handbook/release-notes/typescript-2-2.html#support-for-newtarget\n // which we can now use since we no longer target ES5.\n Object.setPrototypeOf(this, AIError.prototype);\n\n // Since Error is an interface, we don't inherit toString and so we define it ourselves.\n this.toString = () => fullMessage;\n }\n}\n","/**\n * @license\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\n/**\n * Role is the producer of the content.\n * @public\n */\nexport type Role = (typeof POSSIBLE_ROLES)[number];\n\n/**\n * Possible roles.\n * @public\n */\nexport const POSSIBLE_ROLES = ['user', 'model', 'function', 'system'] as const;\n\n/**\n * Harm categories that would cause prompts or candidates to be blocked.\n * @public\n */\nexport const HarmCategory = {\n HARM_CATEGORY_HATE_SPEECH: 'HARM_CATEGORY_HATE_SPEECH',\n HARM_CATEGORY_SEXUALLY_EXPLICIT: 'HARM_CATEGORY_SEXUALLY_EXPLICIT',\n HARM_CATEGORY_HARASSMENT: 'HARM_CATEGORY_HARASSMENT',\n HARM_CATEGORY_DANGEROUS_CONTENT: 'HARM_CATEGORY_DANGEROUS_CONTENT'\n} as const;\n\n/**\n * Harm categories that would cause prompts or candidates to be blocked.\n * @public\n */\nexport type HarmCategory = (typeof HarmCategory)[keyof typeof HarmCategory];\n\n/**\n * Threshold above which a prompt or candidate will be blocked.\n * @public\n */\nexport const HarmBlockThreshold = {\n /**\n * Content with `NEGLIGIBLE` will be allowed.\n */\n BLOCK_LOW_AND_ABOVE: 'BLOCK_LOW_AND_ABOVE',\n /**\n * Content with `NEGLIGIBLE` and `LOW` will be allowed.\n */\n BLOCK_MEDIUM_AND_ABOVE: 'BLOCK_MEDIUM_AND_ABOVE',\n /**\n * Content with `NEGLIGIBLE`, `LOW`, and `MEDIUM` will be allowed.\n */\n BLOCK_ONLY_HIGH: 'BLOCK_ONLY_HIGH',\n /**\n * All content will be allowed.\n */\n BLOCK_NONE: 'BLOCK_NONE',\n /**\n * All content will be allowed. This is the same as `BLOCK_NONE`, but the metadata corresponding\n * to the {@link (HarmCategory:type)} will not be present in the response.\n */\n OFF: 'OFF'\n} as const;\n\n/**\n * Threshold above which a prompt or candidate will be blocked.\n * @public\n */\nexport type HarmBlockThreshold =\n (typeof HarmBlockThreshold)[keyof typeof HarmBlockThreshold];\n\n/**\n * This property is not supported in the Gemini Developer API ({@link GoogleAIBackend}).\n *\n * @public\n */\nexport const HarmBlockMethod = {\n /**\n * The harm block method uses both probability and severity scores.\n */\n SEVERITY: 'SEVERITY',\n /**\n * The harm block method uses the probability score.\n */\n PROBABILITY: 'PROBABILITY'\n} as const;\n\n/**\n * This property is not supported in the Gemini Developer API ({@link GoogleAIBackend}).\n *\n * @public\n */\nexport type HarmBlockMethod =\n (typeof HarmBlockMethod)[keyof typeof HarmBlockMethod];\n\n/**\n * Probability that a prompt or candidate matches a harm category.\n * @public\n */\nexport const HarmProbability = {\n /**\n * Content has a negligible chance of being unsafe.\n */\n NEGLIGIBLE: 'NEGLIGIBLE',\n /**\n * Content has a low chance of being unsafe.\n */\n LOW: 'LOW',\n /**\n * Content has a medium chance of being unsafe.\n */\n MEDIUM: 'MEDIUM',\n /**\n * Content has a high chance of being unsafe.\n */\n HIGH: 'HIGH'\n} as const;\n\n/**\n * Probability that a prompt or candidate matches a harm category.\n * @public\n */\nexport type HarmProbability =\n (typeof HarmProbability)[keyof typeof HarmProbability];\n\n/**\n * Harm severity levels.\n * @public\n */\nexport const HarmSeverity = {\n /**\n * Negligible level of harm severity.\n */\n HARM_SEVERITY_NEGLIGIBLE: 'HARM_SEVERITY_NEGLIGIBLE',\n /**\n * Low level of harm severity.\n */\n HARM_SEVERITY_LOW: 'HARM_SEVERITY_LOW',\n /**\n * Medium level of harm severity.\n */\n HARM_SEVERITY_MEDIUM: 'HARM_SEVERITY_MEDIUM',\n /**\n * High level of harm severity.\n */\n HARM_SEVERITY_HIGH: 'HARM_SEVERITY_HIGH',\n /**\n * Harm severity is not supported.\n *\n * @remarks\n * The GoogleAI backend does not support `HarmSeverity`, so this value is used as a fallback.\n */\n HARM_SEVERITY_UNSUPPORTED: 'HARM_SEVERITY_UNSUPPORTED'\n} as const;\n\n/**\n * Harm severity levels.\n * @public\n */\nexport type HarmSeverity = (typeof HarmSeverity)[keyof typeof HarmSeverity];\n\n/**\n * Reason that a prompt was blocked.\n * @public\n */\nexport const BlockReason = {\n /**\n * Content was blocked by safety settings.\n */\n SAFETY: 'SAFETY',\n /**\n * Content was blocked, but the reason is uncategorized.\n */\n OTHER: 'OTHER',\n /**\n * Content was blocked because it contained terms from the terminology blocklist.\n */\n BLOCKLIST: 'BLOCKLIST',\n /**\n * Content was blocked due to prohibited content.\n */\n PROHIBITED_CONTENT: 'PROHIBITED_CONTENT'\n} as const;\n\n/**\n * Reason that a prompt was blocked.\n * @public\n */\nexport type BlockReason = (typeof BlockReason)[keyof typeof BlockReason];\n\n/**\n * Reason that a candidate finished.\n * @public\n */\nexport const FinishReason = {\n /**\n * Natural stop point of the model or provided stop sequence.\n */\n STOP: 'STOP',\n /**\n * The maximum number of tokens as specified in the request was reached.\n */\n MAX_TOKENS: 'MAX_TOKENS',\n /**\n * The candidate content was flagged for safety reasons.\n */\n SAFETY: 'SAFETY',\n /**\n * The candidate content was flagged for recitation reasons.\n */\n RECITATION: 'RECITATION',\n /**\n * Unknown reason.\n */\n OTHER: 'OTHER',\n /**\n * The candidate content contained forbidden terms.\n */\n BLOCKLIST: 'BLOCKLIST',\n /**\n * The candidate content potentially contained prohibited content.\n */\n PROHIBITED_CONTENT: 'PROHIBITED_CONTENT',\n /**\n * The candidate content potentially contained Sensitive Personally Identifiable Information (SPII).\n */\n SPII: 'SPII',\n /**\n * The function call generated by the model was invalid.\n */\n MALFORMED_FUNCTION_CALL: 'MALFORMED_FUNCTION_CALL'\n} as const;\n\n/**\n * Reason that a candidate finished.\n * @public\n */\nexport type FinishReason = (typeof FinishReason)[keyof typeof FinishReason];\n\n/**\n * @public\n */\nexport const FunctionCallingMode = {\n /**\n * Default model behavior; model decides to predict either a function call\n * or a natural language response.\n */\n AUTO: 'AUTO',\n /**\n * Model is constrained to always predicting a function call only.\n * If `allowed_function_names` is set, the predicted function call will be\n * limited to any one of `allowed_function_names`, else the predicted\n * function call will be any one of the provided `function_declarations`.\n */\n ANY: 'ANY',\n /**\n * Model will not predict any function call. Model behavior is same as when\n * not passing any function declarations.\n */\n NONE: 'NONE'\n} as const;\n\n/**\n * @public\n */\nexport type FunctionCallingMode =\n (typeof FunctionCallingMode)[keyof typeof FunctionCallingMode];\n\n/**\n * Content part modality.\n * @public\n */\nexport const Modality = {\n /**\n * Unspecified modality.\n */\n MODALITY_UNSPECIFIED: 'MODALITY_UNSPECIFIED',\n /**\n * Plain text.\n */\n TEXT: 'TEXT',\n /**\n * Image.\n */\n IMAGE: 'IMAGE',\n /**\n * Video.\n */\n VIDEO: 'VIDEO',\n /**\n * Audio.\n */\n AUDIO: 'AUDIO',\n /**\n * Document (for example, PDF).\n */\n DOCUMENT: 'DOCUMENT'\n} as const;\n\n/**\n * Content part modality.\n * @public\n */\nexport type Modality = (typeof Modality)[keyof typeof Modality];\n\n/**\n * Generation modalities to be returned in generation responses.\n *\n * @beta\n */\nexport const ResponseModality = {\n /**\n * Text.\n * @beta\n */\n TEXT: 'TEXT',\n /**\n * Image.\n * @beta\n */\n IMAGE: 'IMAGE',\n /**\n * Audio.\n * @beta\n */\n AUDIO: 'AUDIO'\n} as const;\n\n/**\n * Generation modalities to be returned in generation responses.\n *\n * @beta\n */\nexport type ResponseModality =\n (typeof ResponseModality)[keyof typeof ResponseModality];\n\n/**\n * Determines whether inference happens on-device or in-cloud.\n *\n * @remarks\n * <b>PREFER_ON_DEVICE:</b> Attempt to make inference calls using an\n * on-device model. If on-device inference is not available, the SDK\n * will fall back to using a cloud-hosted model.\n * <br/>\n * <b>ONLY_ON_DEVICE:</b> Only attempt to make inference calls using an\n * on-device model. The SDK will not fall back to a cloud-hosted model.\n * If on-device inference is not available, inference methods will throw.\n * <br/>\n * <b>ONLY_IN_CLOUD:</b> Only attempt to make inference calls using a\n * cloud-hosted model. The SDK will not fall back to an on-device model.\n * <br/>\n * <b>PREFER_IN_CLOUD:</b> Attempt to make inference calls to a\n * cloud-hosted model. If not available, the SDK will fall back to an\n * on-device model.\n *\n * @beta\n */\nexport const InferenceMode = {\n 'PREFER_ON_DEVICE': 'prefer_on_device',\n 'ONLY_ON_DEVICE': 'only_on_device',\n 'ONLY_IN_CLOUD': 'only_in_cloud',\n 'PREFER_IN_CLOUD': 'prefer_in_cloud'\n} as const;\n\n/**\n * Determines whether inference happens on-device or in-cloud.\n *\n * @beta\n */\nexport type InferenceMode = (typeof InferenceMode)[keyof typeof InferenceMode];\n\n/**\n * Indicates whether inference happened on-device or in-cloud.\n *\n * @beta\n */\nexport const InferenceSource = {\n 'ON_DEVICE': 'on_device',\n 'IN_CLOUD': 'in_cloud'\n} as const;\n\n/**\n * Indicates whether inference happened on-device or in-cloud.\n *\n * @beta\n */\nexport type InferenceSource =\n (typeof InferenceSource)[keyof typeof InferenceSource];\n\n/**\n * Represents the result of the code execution.\n *\n * @public\n */\nexport const Outcome = {\n UNSPECIFIED: 'OUTCOME_UNSPECIFIED',\n OK: 'OUTCOME_OK',\n FAILED: 'OUTCOME_FAILED',\n DEADLINE_EXCEEDED: 'OUTCOME_DEADLINE_EXCEEDED'\n};\n\n/**\n * Represents the result of the code execution.\n *\n * @public\n */\nexport type Outcome = (typeof Outcome)[keyof typeof Outcome];\n\n/**\n * The programming language of the code.\n *\n * @public\n */\nexport const Language = {\n UNSPECIFIED: 'LANGUAGE_UNSPECIFIED',\n PYTHON: 'PYTHON'\n};\n\n/**\n * The programming language of the code.\n *\n * @public\n */\nexport type Language = (typeof Language)[keyof typeof Language];\n\n/**\n * A preset that controls the model's \"thinking\" process. Use\n * `ThinkingLevel.LOW` for faster responses on less complex tasks, and\n * `ThinkingLevel.HIGH` for better reasoning on more complex tasks.\n *\n * @public\n */\nexport const ThinkingLevel = {\n MINIMAL: 'MINIMAL',\n LOW: 'LOW',\n MEDIUM: 'MEDIUM',\n HIGH: 'HIGH'\n};\n\n/**\n * A preset that controls the model's \"thinking\" process. Use\n * `ThinkingLevel.LOW` for faster responses on less complex tasks, and\n * `ThinkingLevel.HIGH` for better reasoning on more complex tasks.\n *\n * @public\n */\nexport type ThinkingLevel = (typeof ThinkingLevel)[keyof typeof ThinkingLevel];\n","/**\n * @license\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 { Content, FunctionCall, InlineDataPart } from './content';\nimport {\n BlockReason,\n FinishReason,\n HarmCategory,\n HarmProbability,\n HarmSeverity,\n InferenceSource,\n Modality\n} from './enums';\n\n/**\n * Result object returned from {@link GenerativeModel.generateContent} call.\n *\n * @public\n */\nexport interface GenerateContentResult {\n response: EnhancedGenerateContentResponse;\n}\n\n/**\n * Result object returned from {@link GenerativeModel.generateContentStream} call.\n * Iterate over `stream` to get chunks as they come in and/or\n * use the `response` promise to get the aggregated response when\n * the stream is done.\n *\n * @public\n */\nexport interface GenerateContentStreamResult {\n stream: AsyncGenerator<EnhancedGenerateContentResponse>;\n response: Promise<EnhancedGenerateContentResponse>;\n}\n\n/**\n * Response object wrapped with helper methods.\n *\n * @public\n */\nexport interface EnhancedGenerateContentResponse\n extends GenerateContentResponse {\n /**\n * Returns the text string from the response, if available.\n * Throws if the prompt or candidate was blocked.\n */\n text: () => string;\n /**\n * Aggregates and returns every {@link InlineDataPart} from the first candidate of\n * {@link GenerateContentResponse}.\n *\n * @throws If the prompt or candidate was blocked.\n */\n inlineDataParts: () => InlineDataPart[] | undefined;\n /**\n * Aggregates and returns every {@link FunctionCall} from the first candidate of\n * {@link GenerateContentResponse}.\n *\n * @throws If the prompt or candidate was blocked.\n */\n functionCalls: () => FunctionCall[] | undefined;\n /**\n * Aggregates and returns every {@link TextPart} with their `thought` property set\n * to `true` from the first candidate of {@link GenerateContentResponse}.\n *\n * @throws If the prompt or candidate was blocked.\n *\n * @remarks\n * Thought summaries provide a brief overview of the model's internal thinking process,\n * offering insight into how it arrived at the final answer. This can be useful for\n * debugging, understanding the model's reasoning, and verifying its accuracy.\n *\n * Thoughts will only be included if {@link ThinkingConfig.includeThoughts} is\n * set to `true`.\n */\n thoughtSummary: () => string | undefined;\n /**\n * Indicates whether inference happened on-device or in-cloud.\n *\n * @beta\n */\n inferenceSource?: InferenceSource;\n}\n\n/**\n * Individual response from {@link GenerativeModel.generateContent} and\n * {@link GenerativeModel.generateContentStream}.\n * `generateContentStream()` will return one in each chunk until\n * the stream is done.\n * @public\n */\nexport interface GenerateContentResponse {\n candidates?: GenerateContentCandidate[];\n promptFeedback?: PromptFeedback;\n usageMetadata?: UsageMetadata;\n}\n\n/**\n * Usage metadata about a {@link GenerateContentResponse}.\n *\n * @public\n */\nexport interface UsageMetadata {\n promptTokenCount: number;\n candidatesTokenCount: number;\n /**\n * The number of tokens used by the model's internal \"thinking\" process.\n */\n thoughtsTokenCount?: number;\n totalTokenCount: number;\n /**\n * The number of tokens used by tools.\n */\n toolUsePromptTokenCount?: number;\n promptTokensDetails?: ModalityTokenCount[];\n candidatesTokensDetails?: ModalityTokenCount[];\n /**\n * A list of tokens used by tools, broken down by modality.\n */\n toolUsePromptTokensDetails?: ModalityTokenCount[];\n /**\n * The number of tokens in the prompt that were served from the cache.\n * If implicit caching is not active or no content was cached,\n * this will be 0.\n */\n cachedContentTokenCount?: number;\n /**\n * Detailed breakdown of the cached tokens by modality (for example, text or\n * image). This list provides granular insight into which parts of\n * the content were cached.\n */\n cacheTokensDetails?: ModalityTokenCount[];\n}\n\n/**\n * Represents token counting info for a single modality.\n *\n * @public\n */\nexport interface ModalityTokenCount {\n /** The modality associated with this token count. */\n modality: Modality;\n /** The number of tokens counted. */\n tokenCount: number;\n}\n\n/**\n * If the prompt was blocked, this will be populated with `blockReason` and\n * the relevant `safetyRatings`.\n * @public\n */\nexport interface PromptFeedback {\n blockReason?: BlockReason;\n safetyRatings: SafetyRating[];\n /**\n * A human-readable description of the `blockReason`.\n *\n * This property is only supported in the Vertex AI Gemini API ({@link VertexAIBackend}).\n */\n blockReasonMessage?: string;\n}\n\n/**\n * A candidate returned as part of a {@link GenerateContentResponse}.\n * @public\n */\nexport interface GenerateContentCandidate {\n index: number;\n content: Content;\n finishReason?: FinishReason;\n finishMessage?: string;\n safetyRatings?: SafetyRating[];\n citationMetadata?: CitationMetadata;\n groundingMetadata?: GroundingMetadata;\n urlContextMetadata?: URLContextMetadata;\n}\n\n/**\n * Citation metadata that may be found on a {@link GenerateContentCandidate}.\n * @public\n */\nexport interface CitationMetadata {\n citations: Citation[];\n}\n\n/**\n * A single citation.\n * @public\n */\nexport interface Citation {\n startIndex?: number;\n endIndex?: number;\n uri?: string;\n license?: string;\n /**\n * The title of the cited source, if available.\n *\n * This property is only supported in the Vertex AI Gemini API ({@link VertexAIBackend}).\n */\n title?: string;\n /**\n * The publication date of the cited source, if available.\n *\n * This property is only supported in the Vertex AI Gemini API ({@link VertexAIBackend}).\n */\n publicationDate?: Date;\n}\n\n/**\n * Metadata returned when grounding is enabled.\n *\n * Currently, only Grounding with Google Search is supported (see {@link GoogleSearchTool}).\n *\n * Important: If using Grounding with Google Search, you are required to comply with the\n * \"Grounding with Google Search\" usage requirements for your chosen API provider: {@link https://ai.google.dev/gemini-api/terms#grounding-with-google-search | Gemini Developer API}\n * or Vertex AI Gemini API (see {@link https://cloud.google.com/terms/service-terms | Service Terms}\n * section within the Service Specific Terms).\n *\n * @public\n */\nexport interface GroundingMetadata {\n /**\n * Google Search entry point for web searches. This contains an HTML/CSS snippet that must be\n * embedded in an app to display a Google Search entry point for follow-up web searches related to\n * a model's \"Grounded Response\".\n */\n searchEntryPoint?: SearchEntrypoint;\n /**\n * A list of {@link GroundingChunk} objects. Each chunk represents a piece of retrieved content\n * (for example, from a web page). that the model used to ground its response.\n */\n groundingChunks?: GroundingChunk[];\n /**\n * A list of {@link GroundingSupport} objects. Each object details how specific segments of the\n * model's response are supported by the `groundingChunks`.\n */\n groundingSupports?: GroundingSupport[];\n /**\n * A list of web search queries that the model performed to gather the grounding information.\n * These can be used to allow users to explore the search results themselves.\n */\n webSearchQueries?: string[];\n /**\n * @deprecated Use {@link GroundingSupport} instead.\n */\n retrievalQueries?: string[];\n}\n\n/**\n * Google search entry point.\n *\n * @public\n */\nexport interface SearchEntrypoint {\n /**\n * HTML/CSS snippet that must be embedded in a web page. The snippet is designed to avoid\n * undesired interaction with the rest of the page's CSS.\n *\n * To ensure proper rendering and prevent CSS conflicts, it is recommended\n * to encapsulate this `renderedContent` within a shadow DOM when embedding it\n * into a webpage. See {@link https://developer.mozilla.org/en-US/docs/Web/API/Web_components/Using_shadow_DOM | MDN: Using shadow DOM}.\n *\n * @example\n * ```javascript\n * const container = document.createElement('div');\n * document.body.appendChild(container);\n * container.attachShadow({ mode: 'open' }).innerHTML = renderedContent;\n * ```\n */\n renderedContent?: string;\n}\n\n/**\n * Represents a chunk of retrieved data that supports a claim in the model's response. This is part\n * of the grounding information provided when grounding is enabled.\n *\n * @public\n */\nexport interface GroundingChunk {\n /**\n * Contains details if the grounding chunk is from a web source.\n */\n web?: WebGroundingChunk;\n}\n\n/**\n * A grounding chunk from the web.\n *\n * Important: If using Grounding with Google Search, you are required to comply with the\n * {@link https://cloud.google.com/terms/service-terms | Service Specific Terms} for \"Grounding with Google Search\".\n *\n * @public\n */\nexport interface WebGroundingChunk {\n /**\n * The URI of the retrieved web page.\n */\n uri?: string;\n /**\n * The title of the retrieved web page.\n */\n title?: string;\n /**\n * The domain of the original URI from which the content was retrieved.\n *\n * This property is only supported in the Vertex AI Gemini API ({@link VertexAIBackend}).\n * When using the Gemini Developer API ({@link GoogleAIBackend}), this property will be\n * `undefined`.\n */\n domain?: string;\n}\n\n/**\n * Provides information about how a specific segment of the model's response is supported by the\n * retrieved grounding chunks.\n *\n * @public\n */\nexport interface GroundingSupport {\n /**\n * Specifies the segment of the model's response content that this grounding support pertains to.\n */\n segment?: Segment;\n /**\n * A list of indices that refer to specific {@link GroundingChunk} objects within the\n * {@link GroundingMetadata.groundingChunks} array. These referenced chunks\n * are the sources that support the claim made in the associated `segment` of the response.\n * For example, an array `[1, 3, 4]` means that `groundingChunks[1]`, `groundingChunks[3]`,\n * and `groundingChunks[4]` are the retrieved content supporting this part of the response.\n */\n groundingChunkIndices?: number[];\n}\n\n/**\n * Represents a specific segment within a {@link Content} object, often used to\n * pinpoint the exact location of text or data that grounding information refers to.\n *\n * @public\n */\nexport interface Segment {\n /**\n * The zero-based index of the {@link Part} object within the `parts` array\n * of its parent {@link Content} object. This identifies which part of the\n * content the segment belongs to.\n */\n partIndex: number;\n /**\n * The zero-based start index of the segment within the specified `Part`,\n * measured in UTF-8 bytes. This offset is inclusive, starting from 0 at the\n * beginning of the part's content (e.g., `Part.text`).\n */\n startIndex: number;\n /**\n * The zero-based end index of the segment within the specified `Part`,\n * measured in UTF-8 bytes. This offset is exclusive, meaning the character\n * at this index is not included in the segment.\n */\n endIndex: number;\n /**\n * The text corresponding to the segment from the response.\n */\n text: string;\n}\n\n/**\n * Metadata related to {@link URLContextTool}.\n *\n * @public\n */\nexport interface URLContextMetadata {\n /**\n * List of URL metadata used to provide context to the Gemini model.\n */\n urlMetadata: URLMetadata[];\n}\n\n/**\n * Metadata for a single URL retrieved by the {@link URLContextTool} tool.\n *\n * @public\n */\nexport interface URLMetadata {\n /**\n * The retrieved URL.\n */\n retrievedUrl?: string;\n /**\n * The status of the URL retrieval.\n */\n urlRetrievalStatus?: URLRetrievalStatus;\n}\n\n/**\n * The status of a URL retrieval.\n *\n * @remarks\n * <b>URL_RETRIEVAL_STATUS_UNSPECIFIED:</b> Unspecified retrieval status.\n * <br/>\n * <b>URL_RETRIEVAL_STATUS_SUCCESS:</b> The URL retrieval was successful.\n * <br/>\n * <b>URL_RETRIEVAL_STATUS_ERROR:</b> The URL retrieval failed.\n * <br/>\n * <b>URL_RETRIEVAL_STATUS_PAYWALL:</b> The URL retrieval failed because the content is behind a paywall.\n * <br/>\n * <b>URL_RETRIEVAL_STATUS_UNSAFE:</b> The URL retrieval failed because the content is unsafe.\n * <br/>\n *\n * @public\n */\nexport const URLRetrievalStatus = {\n /**\n * Unspecified retrieval status.\n */\n URL_RETRIEVAL_STATUS_UNSPECIFIED: 'URL_RETRIEVAL_STATUS_UNSPECIFIED',\n /**\n * The URL retrieval was successful.\n */\n URL_RETRIEVAL_STATUS_SUCCESS: 'URL_RETRIEVAL_STATUS_SUCCESS',\n /**\n * The URL retrieval failed.\n */\n URL_RETRIEVAL_STATUS_ERROR: 'URL_RETRIEVAL_STATUS_ERROR',\n /**\n * The URL retrieval failed because the content is behind a paywall.\n */\n URL_RETRIEVAL_STATUS_PAYWALL: 'URL_RETRIEVAL_STATUS_PAYWALL',\n /**\n * The URL retrieval failed because the content is unsafe.\n */\n URL_RETRIEVAL_STATUS_UNSAFE: 'URL_RETRIEVAL_STATUS_UNSAFE'\n};\n\n/**\n * The status of a URL retrieval.\n *\n * @remarks\n * <b>URL_RETRIEVAL_STATUS_UNSPECIFIED:</b> Unspecified retrieval status.\n * <br/>\n * <b>URL_RETRIEVAL_STATUS_SUCCESS:</b> The URL retrieval was successful.\n * <br/>\n * <b>URL_RETRIEVAL_STATUS_ERROR:</b> The URL retrieval failed.\n * <br/>\n * <b>URL_RETRIEVAL_STATUS_PAYWALL:</b> The URL retrieval failed because the content is behind a paywall.\n * <br/>\n * <b>URL_RETRIEVAL_STATUS_UNSAFE:</b> The URL retrieval failed because the content is unsafe.\n * <br/>\n *\n * @public\n */\nexport type URLRetrievalStatus =\n (typeof URLRetrievalStatus)[keyof typeof URLRetrievalStatus];\n\n/**\n * @public\n */\nexport interface WebAttribution {\n uri: string;\n title: string;\n}\n\n/**\n * @public\n */\nexport interface RetrievedContextAttribution {\n uri: string;\n title: string;\n}\n\n/**\n * Protobuf google.type.Date\n * @public\n */\nexport interface Date {\n year: number;\n month: number;\n day: number;\n}\n\n/**\n * A safety rating associated with a {@link GenerateContentCandidate}\n * @public\n */\nexport interface SafetyRating {\n category: HarmCategory;\n probability: HarmProbability;\n /**\n * The harm severity level.\n *\n * This property is only supported when using the Vertex AI Gemini API ({@link VertexAIBackend}).\n * When using the Gemini Developer API ({@link GoogleAIBackend}), this property is not supported and will default to `HarmSeverity.UNSUPPORTED`.\n */\n severity: HarmSeverity;\n /**\n * The probability score of the harm category.\n *\n * This property is only supported when using the Vertex AI Gemini API ({@link VertexAIBackend}).\n * When using the Gemini Developer API ({@link GoogleAIBackend}), this property is not supported and will default to 0.\n */\n probabilityScore: number;\n /**\n * The severity score of the harm category.\n *\n * This property is only supported when using the Vertex AI Gemini API ({@link VertexAIBackend}).\n * When using the Gemini Developer API ({@link GoogleAIBackend}), this property is not supported and will default to 0.\n */\n severityScore: number;\n blocked: boolean;\n}\n\n/**\n * Response from calling {@link GenerativeModel.countTokens}.\n * @public\n */\nexport interface CountTokensResponse {\n /**\n * The total number of tokens counted across all instances from the request.\n */\n totalTokens: number;\n /**\n * @deprecated Use `totalTokens` instead. This property is undefined when using models greater than `gemini-1.5-*`.\n *\n * The total number of billable characters counted across all instances\n * from the request.\n */\n totalBillableCharacters?: number;\n /**\n * The breakdown, by modality, of how many tokens are consumed by the prompt.\n */\n promptTokensDetails?: ModalityTokenCount[];\n}\n\n/**\n * An incremental content update from the model.\n *\n * @beta\n */\nexport interface LiveServerContent {\n type: 'serverContent';\n /**\n * The content that the model has generated as part of the current conversation with the user.\n */\n modelTurn?: Content;\n /**\n * Indicates whether the turn is complete. This is `undefined` if the turn is not complete.\n */\n turnComplete?: boolean;\n /**\n * Indicates whether the model was interrupted by the client. An interruption occurs when\n * the client sends a message before the model finishes it's turn. This is `undefined` if the\n * model was not interrupted.\n */\n interrupted?: boolean;\n /**\n * Transcription of the audio that was input to the model.\n */\n inputTranscription?: Transcription;\n /**\n * Transcription of the audio output from the model.\n */\n outputTranscription?: Transcription;\n}\n\n/**\n * Transcription of audio. This can be returned from a {@link LiveGenerativeModel} if transcription\n * is enabled with the `inputAudioTranscription` or `outputAudioTranscription` properties on\n * the {@link LiveGenerationConfig}.\n *\n * @beta\n */\n\nexport interface Transcription {\n /**\n * The text transcription of the audio.\n */\n text?: string;\n}\n\n/**\n * A request from the model for the client to execute one or more functions.\n *\n * @beta\n */\nexport interface LiveServerToolCall {\n type: 'toolCall';\n /**\n * An array of function calls to run.\n */\n functionCalls: FunctionCall[];\n}\n\n/**\n * Notification to cancel a previous function call triggered by {@link LiveServerToolCall}.\n *\n * @beta\n */\nexport interface LiveServerToolCallCancellation {\n type: 'toolCallCancellation';\n /**\n * IDs of function calls that were cancelled. These refer to the `id` property of a {@link FunctionCall}.\n */\n functionIds: string[];\n}\n\n/**\n * Notification that the server will not be able to service the client soon.\n *\n * @beta\n */\nexport interface LiveServerGoingAwayNotice {\n type: 'goingAwayNotice';\n /**\n * The remaining time (in seconds) before the connection will be terminated.\n */\n timeLeft: number;\n}\n\n/**\n * The types of responses that can be returned by {@link LiveSession.receive}.\n *\n * @beta\n */\nexport const LiveResponseType = {\n SERVER_CONTENT: 'serverContent',\n TOOL_CALL: 'toolCall',\n TOOL_CALL_CANCELLATION: 'toolCallCancellation',\n GOING_AWAY_NOTICE: 'goingAwayNotice'\n};\n\n/**\n * The types of responses that can be returned by {@link LiveSession.receive}.\n * This is a property on all messages that can be used for type narrowing. This property is not\n * returned by the server, it is assigned to a server message object once it's parsed.\n *\n * @beta\n */\nexport type LiveResponseType =\n (typeof LiveResponseType)[keyof typeof LiveResponseType];\n","/**\n * @license\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 { GenerateContentResponse } from './responses';\n\n/**\n * Details object that may be included in an error response.\n *\n * @public\n */\nexport interface ErrorDetails {\n '@type'?: string;\n\n /** The reason for the error. */\n reason?: string;\n\n /** The domain where the error occurred. */\n domain?: string;\n\n /** Additional metadata about the error. */\n metadata?: Record<string, unknown>;\n\n /** Any other relevant information about the error. */\n [key: string]: unknown;\n}\n\n/**\n * Details object that contains data originating from a bad HTTP response.\n *\n * @public\n */\nexport interface CustomErrorData {\n /** HTTP status code of the error response. */\n status?: number;\n\n /** HTTP status text of the error response. */\n statusText?: string;\n\n /** Response from a {@link GenerateContentRequest} */\n response?: GenerateContentResponse;\n\n /** Optional additional details about the error. */\n errorDetails?: ErrorDetails[];\n}\n\n/**\n * Standardized error codes that {@link AIError} can have.\n *\n * @public\n */\nexport const AIErrorCode = {\n /** A generic error occurred. */\n ERROR: 'error',\n\n /** An error occurred in a request. */\n REQUEST_ERROR: 'request-error',\n\n /** An error occurred in a response. */\n RESPONSE_ERROR: 'response-error',\n\n /** An error occurred while performing a fetch. */\n FETCH_ERROR: 'fetch-error',\n\n /** An error occurred because an operation was attempted on a closed session. */\n SESSION_CLOSED: 'session-closed',\n\n /** An error associated with a Content object. */\n INVALID_CONTENT: 'invalid-content',\n\n /** An error due to the Firebase API not being enabled in the Console. */\n API_NOT_ENABLED: 'api-not-enabled',\n\n /** An error due to invalid Schema input. */\n INVALID_SCHEMA: 'invalid-schema',\n\n /** An error occurred due to a missing Firebase API key. */\n NO_API_KEY: 'no-api-key',\n\n /** An error occurred due to a missing Firebase app ID. */\n NO_APP_ID: 'no-app-id',\n\n /** An error occurred due to a model name not being specified during initialization. */\n NO_MODEL: 'no-model',\n\n /** An error occurred due to a missing project ID. */\n NO_PROJECT_ID: 'no-project-id',\n\n /** An error occurred while parsing. */\n PARSE_FAILED: 'parse-failed',\n\n /** An error occurred due an attempt to use an unsupported feature. */\n UNSUPPORTED: 'unsupported'\n} as const;\n\n/**\n * Standardized error codes that {@link AIError} can have.\n *\n * @public\n */\nexport type AIErrorCode = (typeof AIErrorCode)[keyof typeof AIErrorCode];\n","/**\n * @license\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\n/**\n * Contains the list of OpenAPI data types\n * as defined by the\n * {@link https://swagger.io/docs/specification/data-models/data-types/ | OpenAPI specification}\n * @public\n */\nexport const SchemaType = {\n /** String type. */\n STRING: 'string',\n /** Number type. */\n NUMBER: 'number',\n /** Integer type. */\n INTEGER: 'integer',\n /** Boolean type. */\n BOOLEAN: 'boolean',\n /** Array type. */\n ARRAY: 'array',\n /** Object type. */\n OBJECT: 'object'\n} as const;\n\n/**\n * Contains the list of OpenAPI data types\n * as defined by the\n * {@link https://swagger.io/docs/specification/data-models/data-types/ | OpenAPI specification}\n * @public\n */\nexport type SchemaType = (typeof SchemaType)[keyof typeof SchemaType];\n\n/**\n * Basic {@link Schema} properties shared across several Schema-related\n * types.\n * @public\n */\nexport interface SchemaShared<T> {\n /**\n * An array of {@link Schema}. The generated data must be valid against any of the schemas\n * listed in this array. This allows specifying multiple possible structures or types for a\n * single field.\n */\n anyOf?: T[];\n /** Optional. The format of the property.\n * When using the Gemini Developer API ({@link GoogleAIBackend}), this must be either `'enum'` or\n * `'date-time'`, otherwise requests will fail.\n */\n format?: string;\n /** Optional. The description of the property. */\n description?: string;\n /**\n * The title of the property. This helps document the schema's purpose but does not typically\n * constrain the generated value. It can subtly guide the model by clarifying the intent of a\n * field.\n */\n title?: string;\n /** Optional. The items of the property. */\n items?: T;\n /** The minimum number of items (elements) in a schema of {@link (SchemaType:type)} `array`. */\n minItems?: number;\n /** The maximum number of items (elements) in a schema of {@link (SchemaType:type)} `array`. */\n maxItems?: number;\n /** Optional. Map of `Schema` objects. */\n properties?: {\n [k: string]: T;\n };\n /** A hint suggesting the order in which the keys should appear in the generated JSON string. */\n propertyOrdering?: string[];\n /** Optional. The enum of the property. */\n enum?: string[];\n /** Optional. The example of the property. */\n example?: unknown;\n /** Optional. Whether the property is nullable. */\n nullable?: boolean;\n /** The minimum value of a numeric type. */\n minimum?: number;\n /** The maximum value of a numeric type. */\n maximum?: number;\n [key: string]: unknown;\n}\n\n/**\n * Params passed to {@link Schema} static methods to create specific\n * {@link Schema} classes.\n * @public\n */\nexport interface SchemaParams extends SchemaShared<SchemaInterface> {}\n\n/**\n * Final format for {@link Schema} params passed to backend requests.\n * @public\n */\nexport interface SchemaRequest extends SchemaShared<SchemaRequest> {\n /**\n * The type of the property. this can only be undefined when using `anyOf` schemas,\n * which do not have an explicit type in the {@link https://swagger.io/docs/specification/v3_0/data-models/data-types/#any-type | OpenAPI specification }.\n */\n type?: SchemaType;\n /** Optional. Array of required property. */\n required?: string[];\n}\n\n/**\n * Interface for {@link Schema} class.\n * @public\n */\nexport interface SchemaInterface extends SchemaShared<SchemaInterface> {\n /**\n * The type of the property. this can only be undefined when using `anyof` schemas,\n * which do not have an explicit type in the {@link https://swagger.io/docs/specification/v3_0/data-models/data-types/#any-type | OpenAPI Specification}.\n */\n type?: SchemaType;\n}\n\n/**\n * Interface for JSON parameters in a schema of {@link (SchemaType:type)}\n * \"object\" when not using the `Schema.object()` helper.\n * @public\n */\nexport interface ObjectSchemaRequest extends SchemaRequest {\n type: 'object';\n /**\n * This is not a property accepted in the final request to the backend, but is\n * a client-side convenience property that is only usable by constructing\n * a schema through the `Schema.object()` helper method. Populating this\n * property will cause response errors if the object is not wrapped with\n * `Schema.object()`.\n */\n optionalProperties?: never;\n}\n","/**\n * @license\n * Copyright 2025 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 { ImagenImageFormat } from '../../requests/imagen-image-format';\n\n/**\n * Parameters for configuring an {@link ImagenModel}.\n *\n * @public\n */\nexport interface ImagenModelParams {\n /**\n * The Imagen model to use for generating images.\n * For example: `imagen-3.0-generate-002`.\n *\n * Only Imagen 3 models (named `imagen-3.0-*`) are supported.\n *\n * See {@link https://firebase.google.com/docs/vertex-ai/models | model versions}\n * for a full list of supported Imagen 3 models.\n */\n model: string;\n /**\n * Configuration options for generating images with Imagen.\n */\n generationConfig?: ImagenGenerationConfig;\n /**\n * Safety settings for filtering potentially inappropriate content.\n */\n safetySettings?: ImagenSafetySettings;\n}\n\n/**\n * Configuration options for generating images with Imagen.\n *\n * See the {@link http://firebase.google.com/docs/vertex-ai/generate-images-imagen | documentation} for\n * more details.\n *\n * @public\n */\nexport interface ImagenGenerationConfig {\n /**\n * A description of what should be omitted from the generated images.\n *\n * Support for negative prompts depends on the Imagen model.\n *\n * See the {@link http://firebase.google.com/docs/vertex-ai/model-parameters#imagen | documentation} for more details.\n *\n * This is no longer supported in the Gemini Developer API ({@link GoogleAIBackend}) in versions\n * greater than `imagen-3.0-generate-002`.\n */\n negativePrompt?: string;\n /**\n * The number of images to generate. The default value is 1.\n *\n * The number of sample images that may be generated in each request depends on the model\n * (typically up to 4); see the <a href=\"http://firebase.google.com/docs/vertex-ai/model-parameters#imagen\">sampleCount</a>\n * documentation for more details.\n */\n numberOfImages?: number;\n /**\n * The aspect ratio of the generated images. The default value is square 1:1.\n * Supported aspect ratios depend on the Imagen model, see {@link (ImagenAspectRatio:type)}\n * for more details.\n */\n aspectRatio?: ImagenAspectRatio;\n /**\n * The image format of the generated images. The default is PNG.\n *\n * See {@link ImagenImageFormat} for more details.\n */\n imageFormat?: ImagenImageFormat;\n /**\n * Whether to add an invisible watermark to generated images.\n *\n * If set to `true`, an invisible SynthID watermark is embedded in generated images to indicate\n * that they are AI generated. If set to `false`, watermarking will be disabled.\n *\n * For Imagen 3 models, the default value is `true`; see the <a href=\"http://firebase.google.com/docs/vertex-ai/model-parameters#imagen\">addWatermark</a>\n * documentation for more details.\n *\n * When using the Gemini Developer API ({@link GoogleAIBackend}), this will default to true,\n * and cannot be turned off.\n */\n addWatermark?: boolean;\n}\n\n/**\n * A filter level controlling how aggressively to filter sensitive content.\n *\n * Text prompts provided as inputs and images (generated or uploaded) through Imagen on Vertex AI\n * are assessed against a list of safety filters, which include 'harmful categories' (for example,\n * `violence`, `sexual`, `derogatory`, and `toxic`). This filter level controls how aggressively to\n * filter out potentially harmful content from responses. See the {@link http://firebase.google.com/docs/vertex-ai/generate-images | documentation }\n * and the {@link https://cloud.google.com/vertex-ai/generative-ai/docs/image/responsible-ai-imagen#safety-filters | Responsible AI and usage guidelines}\n * for more details.\n *\n * @public\n */\nexport const ImagenSafetyFilterLevel = {\n /**\n * The most aggressive filtering level; most strict blocking.\n */\n BLOCK_LOW_AND_ABOVE: 'block_low_and_above',\n /**\n * Blocks some sensitive prompts and responses.\n */\n BLOCK_MEDIUM_AND_ABOVE: 'block_medium_and_above',\n /**\n * Blocks few sensitive prompts and responses.\n */\n BLOCK_ONLY_HIGH: 'block_only_high',\n /**\n * The least aggressive filtering level; blocks very few sensitive prompts and responses.\n *\n * Access to this feature is restricted and may require your case to be reviewed and approved by\n * Cloud support.\n */\n BLOCK_NONE: 'block_none'\n} as const;\n\n/**\n * A filter level controlling how aggressively to filter sensitive content.\n *\n * Text prompts provided as inputs and images (generated or uploaded) through Imagen on Vertex AI\n * are assessed against a list of safety filters, which include 'harmful categories' (for example,\n * `violence`, `sexual`, `derogatory`, and `toxic`). This filter level controls how aggressively to\n * filter out potentially harmful content from responses. See the {@link http://firebase.google.com/docs/vertex-ai/generate-images | documentation }\n * and the {@link https://cloud.google.com/vertex-ai/generative-ai/docs/image/responsible-ai-imagen#safety-filters | Responsible AI and usage guidelines}\n * for more details.\n *\n * @public\n */\nexport type ImagenSafetyFilterLevel =\n (typeof ImagenSafetyFilterLevel)[keyof typeof ImagenSafetyFilterLevel];\n\n/**\n * A filter level controlling whether generation of images containing people or faces is allowed.\n *\n * See the <a href=\"http://firebase.google.com/docs/vertex-ai/generate-images\">personGeneration</a>\n * documentation for more details.\n *\n * @public\n */\nexport const ImagenPersonFilterLevel = {\n /**\n * Disallow generation of images containing people or faces; images of people are filtered out.\n */\n BLOCK_ALL: 'dont_allow',\n /**\n * Allow generation of images containing adults only; images of children are filtered out.\n *\n * Generation of images containing people or faces may require your use case to be\n * reviewed and approved by Cloud support; see the {@link https://cloud.google.com/vertex-ai/generative-ai/docs/image/responsible-ai-imagen#person-face-gen | Responsible AI and usage guidelines}\n * for more details.\n */\n ALLOW_ADULT: 'allow_adult',\n /**\n * Allow generation of images containing adults only; images of children are filtered out.\n *\n * Generation of images containing people or faces may require your use case to be\n * reviewed and approved by Cloud support; see the {@link https://cloud.google.com/vertex-ai/generative-ai/docs/image/responsible-ai-imagen#person-face-gen | Responsible AI and usage guidelines}\n * for more details.\n */\n ALLOW_ALL: 'allow_all'\n} as const;\n\n/**\n * A filter level controlling whether generation of images containing people or faces is allowed.\n *\n * See the <a href=\"http://firebase.google.com/docs/vertex-ai/generate-images\">personGeneration</a>\n * documentation for more details.\n *\n * @public\n */\nexport type ImagenPersonFilterLevel =\n (typeof ImagenPersonFilterLevel)[keyof typeof ImagenPersonFilterLevel];\n\n/**\n * Settings for controlling the aggressiveness of filtering out sensitive content.\n *\n * See the {@link http://firebase.google.com/docs/vertex-ai/generate-images | documentation }\n * for more details.\n *\n * @public\n */\nexport interface ImagenSafetySettings {\n /**\n * A filter level controlling how aggressive to filter out sensitive content from generated\n * images.\n */\n safetyFilterLevel?: ImagenSafetyFilterLevel;\n /**\n * A filter level controlling whether generation of images containing people or faces is allowed.\n */\n personFilterLevel?: ImagenPersonFilterLevel;\n}\n\n/**\n * Aspect ratios for Imagen images.\n *\n * To specify an aspect ratio for generated images, set the `aspectRatio` property in your\n * {@link ImagenGenerationConfig}.\n *\n * See the {@link http://firebase.google.com/docs/vertex-ai/generate-images | documentation }\n * for more details and examples of the supported aspect ratios.\n *\n * @public\n */\nexport const ImagenAspectRatio = {\n /**\n * Square (1:1) aspect ratio.\n */\n 'SQUARE': '1:1',\n /**\n * Landscape (3:4) aspect ratio.\n */\n 'LANDSCAPE_3x4': '3:4',\n /**\n * Portrait (4:3) aspect ratio.\n */\n 'PORTRAIT_4x3': '4:3',\n /**\n * Landscape (16:9) aspect ratio.\n */\n 'LANDSCAPE_16x9': '16:9',\n /**\n * Portrait (9:16) aspect ratio.\n */\n 'PORTRAIT_9x16': '9:16'\n} as const;\n\n/**\n * Aspect ratios for Imagen images.\n *\n * To specify an aspect ratio for generated images, set the `aspectRatio` property in your\n * {@link ImagenGenerationConfig}.\n *\n * See the {@link http://firebase.google.com/docs/vertex-ai/generate-images | documentation }\n * for more details and examples of the supported aspect ratios.\n *\n * @public\n */\nexport type ImagenAspectRatio =\n (typeof ImagenAspectRatio)[keyof typeof ImagenAspectRatio];\n","/**\n * @license\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 { FirebaseApp } from '@firebase/app';\nimport { Backend } from './backend';\n\nexport * from './types';\n\n/**\n * An instance of the Firebase AI SDK.\n *\n * Do not create this instance directly. Instead, use {@link getAI | getAI()}.\n *\n * @public\n */\nexport interface AI {\n /**\n * The {@link @firebase/app#FirebaseApp} this {@link AI} instance is associated with.\n */\n app: FirebaseApp;\n /**\n * A {@link Backend} instance that specifies the configuration for the target backend,\n * either the Gemini Developer API (using {@link GoogleAIBackend}) or the\n * Vertex AI Gemini API (using {@link VertexAIBackend}).\n */\n backend: Backend;\n /**\n * Options applied to this {@link AI} instance.\n */\n options?: AIOptions;\n /**\n * @deprecated use `AI.backend.location` instead.\n *\n * The location configured for this AI service instance, relevant for Vertex AI backends.\n */\n location: string;\n}\n\n/**\n * An enum-like object containing constants that represent the supported backends\n * for the Firebase AI SDK.\n * This determines which backend service (Vertex AI Gemini API or Gemini Developer API)\n * the SDK will communicate with.\n *\n * These values are assigned to the `backendType` property within the specific backend\n * configuration objects ({@link GoogleAIBackend} or {@link VertexAIBackend}) to identify\n * which service to target.\n *\n * @public\n */\nexport const BackendType = {\n /**\n * Identifies the backend service for the Vertex AI Gemini API provided through Google Cloud.\n * Use this constant when creating a {@link VertexAIBackend} configuration.\n */\n VERTEX_AI: 'VERTEX_AI',\n\n /**\n * Identifies the backend service for the Gemini Developer API ({@link https://ai.google/ | Google AI}).\n * Use this constant when creating a {@link GoogleAIBackend} configuration.\n */\n GOOGLE_AI: 'GOOGLE_AI'\n} as const; // Using 'as const' makes the string values literal types\n\n/**\n * Type alias representing valid backend types.\n * It can be either `'VERTEX_AI'` or `'GOOGLE_AI'`.\n *\n * @public\n */\nexport type BackendType = (typeof BackendType)[keyof typeof BackendType];\n\n/**\n * Options for initializing the AI service using {@link getAI | getAI()}.\n * This allows specifying which backend to use (Vertex AI Gemini API or Gemini Developer API)\n * and configuring its specific options (like location for Vertex AI).\n *\n * @public\n */\nexport interface AIOptions {\n /**\n * The backend configuration to use for the AI service instance.\n * Defaults to the Gemini Developer API backend ({@link GoogleAIBackend}).\n */\n backend?: Backend;\n /**\n * Whether to use App Check limited use tokens. Defaults to false.\n */\n useLimitedUseAppCheckTokens?: boolean;\n}\n","/**\n * @license\n * Copyright 2025 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 { DEFAULT_API_VERSION, DEFAULT_LOCATION } from './constants';\nimport { BackendType } from './public-types';\n\n/**\n * Abstract base class representing the configuration for an AI service backend.\n * This class should not be instantiated directly. Use its subclasses; {@link GoogleAIBackend} for\n * the Gemini Developer API (via {@link https://ai.google/ | Google AI}), and\n * {@link VertexAIBackend} for the Vertex AI Gemini API.\n *\n * @public\n */\nexport abstract class Backend {\n /**\n * Specifies the backend type.\n */\n readonly backendType: BackendType;\n\n /**\n * Protected constructor for use by subclasses.\n * @param type - The backend type.\n */\n protected constructor(type: BackendType) {\n this.backendType = type;\n }\n\n /**\n * @internal\n */\n abstract _getModelPath(project: string, model: string): string;\n\n /**\n * @internal\n */\n abstract _getTemplatePath(project: string, templateId: string): string;\n}\n\n/**\n * Configuration class for the Gemini Developer API.\n *\n * Use this with {@link AIOptions} when initializing the AI service via\n * {@link getAI | getAI()} to specify the Gemini Developer API as the backend.\n *\n * @public\n */\nexport class GoogleAIBackend extends Backend {\n /**\n * Creates a configuration object for the Gemini Developer API backend.\n */\n constructor() {\n super(BackendType.GOOGLE_AI);\n }\n\n /**\n * @internal\n */\n _getModelPath(project: string, model: string): string {\n return `/${DEFAULT_API_VERSION}/projects/${project}/${model}`;\n }\n\n /**\n * @internal\n */\n _getTemplatePath(project: string, templateId: string): string {\n return `/${DEFAULT_API_VERSION}/projects/${project}/templates/${templateId}`;\n }\n}\n\n/**\n * Configuration class for the Vertex AI Gemini API.\n *\n * Use this with {@link AIOptions} when initializing the AI service via\n * {@link getAI | getAI()} to specify the Vertex AI Gemini API as the backend.\n *\n * @public\n */\nexport class VertexAIBackend extends Backend {\n /**\n * The region identifier.\n * See {@link https://firebase.google.com/docs/vertex-ai/locations#available-locations | Vertex AI locations}\n * for a list of supported locations.\n */\n readonly location: string;\n\n /**\n * Creates a configuration object for the Vertex AI backend.\n *\n * @param location - The region identifier, defaulting to `us-central1`;\n * see {@link https://firebase.google.com/docs/vertex-ai/locations#available-locations | Vertex AI locations}\n * for a list of supported locations.\n */\n constructor(location: string = DEFAULT_LOCATION) {\n super(BackendType.VERTEX_AI);\n if (!location) {\n this.location = DEFAULT_LOCATION;\n } else {\n this.location = location;\n }\n }\n\n /**\n * @internal\n */\n _getModelPath(project: string, model: string): string {\n return `/${DEFAULT_API_VERSION}/projects/${project}/locations/${this.location}/${model}`;\n }\n\n /**\n * @internal\n */\n _getTemplatePath(project: string, templateId: string): string {\n return `/${DEFAULT_API_VERSION}/projects/${project}/locations/${this.location}/templates/${templateId}`;\n }\n}\n","/**\n * @license\n * Copyright 2025 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 { AI_TYPE } from './constants';\nimport { AIError } from './errors';\nimport { AIErrorCode } from './types';\nimport { Backend, GoogleAIBackend, VertexAIBackend } from './backend';\n\n/**\n * Encodes a {@link Backend} into a string that will be used to uniquely identify {@link AI}\n * instances by backend type.\n *\n * @internal\n */\nexport function encodeInstanceIdentifier(backend: Backend): string {\n if (backend instanceof GoogleAIBackend) {\n return `${AI_TYPE}/googleai`;\n } else if (backend instanceof VertexAIBackend) {\n return `${AI_TYPE}/vertexai/${backend.location}`;\n } else {\n throw new AIError(\n AIErrorCode.ERROR,\n `Invalid backend: ${JSON.stringify(backend.backendType)}`\n );\n }\n}\n\n/**\n * Decodes an instance identifier string into a {@link Backend}.\n *\n * @internal\n */\nexport function decodeInstanceIdentifier(instanceIdentifier: string): Backend {\n const identifierParts = instanceIdentifier.split('/');\n if (identifierParts[0] !== AI_TYPE) {\n throw new AIError(\n AIErrorCode.ERROR,\n `Invalid instance identifier, unknown prefix '${identifierParts[0]}'`\n );\n }\n const backendType = identifierParts[1];\n switch (backendType) {\n case 'vertexai':\n const location: string | undefined = identifierParts[2];\n if (!location) {\n throw new AIError(\n AIErrorCode.ERROR,\n `Invalid instance identifier, unknown location '${instanceIdentifier}'`\n );\n }\n return new VertexAIBackend(location);\n case 'googleai':\n return new GoogleAIBackend();\n default:\n throw new AIError(\n AIErrorCode.ERROR,\n `Invalid instance identifier string: '${instanceIdentifier}'`\n );\n }\n}\n","/**\n * @license\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 { FirebaseApp, _FirebaseService } from '@firebase/app';\nimport {\n AI,\n AIOptions,\n ChromeAdapter,\n InferenceMode,\n OnDeviceParams\n} from './public-types';\nimport {\n AppCheckInternalComponentName,\n FirebaseAppCheckInternal\n} from '@firebase/app-check-interop-types';\nimport { Provider } from '@firebase/component';\nimport {\n FirebaseAuthInternal,\n FirebaseAuthInternalName\n} from '@firebase/auth-interop-types';\nimport { Backend, VertexAIBackend } from './backend';\n\nexport class AIService implements AI, _FirebaseService {\n auth: FirebaseAuthInternal | null;\n appCheck: FirebaseAppCheckInternal | null;\n _options?: Omit<AIOptions, 'backend'>;\n location: string; // This is here for backwards-compatibility\n\n constructor(\n public app: FirebaseApp,\n public backend: Backend,\n authProvider?: Provider<FirebaseAuthInternalName>,\n appCheckProvider?: Provider<AppCheckInternalComponentName>,\n public chromeAdapterFactory?: (\n mode: InferenceMode,\n window?: Window,\n params?: OnDeviceParams\n ) => ChromeAdapter | undefined\n ) {\n const appCheck = appCheckProvider?.getImmediate({ optional: true });\n const auth = authProvider?.getImmediate({ optional: true });\n this.auth = auth || null;\n this.appCheck = appCheck || null;\n\n if (backend instanceof VertexAIBackend) {\n this.location = backend.location;\n } else {\n this.location = '';\n }\n }\n\n _delete(): Promise<void> {\n return Promise.resolve();\n }\n\n set options(optionsToSet: AIOptions) {\n this._options = optionsToSet;\n }\n\n get options(): AIOptions | undefined {\n return this._options;\n }\n}\n","/**\n * @license\n * Copyright 2025 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 ComponentContainer,\n InstanceFactoryOptions\n} from '@firebase/component';\nimport { AIError } from './errors';\nimport { decodeInstanceIdentifier } from './helpers';\nimport { AIService } from './service';\nimport { AIErrorCode } from './types';\n\nexport function factory(\n container: ComponentContainer,\n { instanceIdentifier }: InstanceFactoryOptions\n): AIService {\n if (!instanceIdentifier) {\n throw new AIError(\n AIErrorCode.ERROR,\n 'AIService instance identifier is undefined.'\n );\n }\n\n const backend = decodeInstanceIdentifier(instanceIdentifier);\n\n // getImmediate for FirebaseApp will always succeed\n const app = container.getProvider('app').getImmediate();\n const auth = container.getProvider('auth-internal');\n const appCheckProvider = container.getProvider('app-check-internal');\n\n return new AIService(app, backend, auth, appCheckProvider);\n}\n","/**\n * @license\n * Copyright 2025 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 { _isFirebaseServerApp } from '@firebase/app';\nimport { AIError } from '../errors';\nimport { AI, AIErrorCode } from '../public-types';\nimport { AIService } from '../service';\nimport { ApiSettings } from '../types/internal';\n\n/**\n * Initializes an {@link ApiSettings} object from an {@link AI} instance.\n *\n * If this is a Server App, the {@link ApiSettings} object's `getAppCheckToken()` will resolve\n * with the `FirebaseServerAppSettings.appCheckToken`, instead of requiring that an App Check\n * instance is initialized.\n */\nexport function initApiSettings(ai: AI): ApiSettings {\n if (!ai.app?.options?.apiKey) {\n throw new AIError(\n AIErrorCode.NO_API_KEY,\n `The \"apiKey\" field is empty in the local Firebase config. Firebase AI requires this field to contain a valid API key.`\n );\n } else if (!ai.app?.options?.projectId) {\n throw new AIError(\n AIErrorCode.NO_PROJECT_ID,\n `The \"projectId\" field is empty in the local Firebase config. Firebase AI requires this field to contain a valid project ID.`\n );\n } else if (!ai.app?.options?.appId) {\n throw new AIError(\n AIErrorCode.NO_APP_ID,\n `The \"appId\" field is empty in the local Firebase config. Firebase AI requires this field to contain a valid app ID.`\n );\n }\n\n const apiSettings: ApiSettings = {\n apiKey: ai.app.options.apiKey,\n project: ai.app.options.projectId,\n appId: ai.app.options.appId,\n automaticDataCollectionEnabled: ai.app.automaticDataCollectionEnabled,\n location: ai.location,\n backend: ai.backend\n };\n\n if (_isFirebaseServerApp(ai.app) && ai.app.settings.appCheckToken) {\n const token = ai.app.settings.appCheckToken;\n apiSettings.getAppCheckToken = () => {\n return Promise.resolve({ token });\n };\n } else if ((ai as AIService).appCheck) {\n if (ai.options?.useLimitedUseAppCheckTokens) {\n apiSettings.getAppCheckToken = () =>\n (ai as AIService).appCheck!.getLimitedUseToken();\n } else {\n apiSettings.getAppCheckToken = () =>\n (ai as AIService).appCheck!.getToken();\n }\n }\n\n if ((ai as AIService).auth) {\n apiSettings.getAuthToken = () => (ai as AIService).auth!.getToken();\n }\n\n return apiSettings;\n}\n","/**\n * @license\n * Copyright 2025 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 { AI, BackendType } from '../public-types';\nimport { ApiSettings } from '../types/internal';\nimport { initApiSettings } from './utils';\n\n/**\n * Base class for Firebase AI model APIs.\n *\n * Instances of this class are associated with a specific Firebase AI {@link Backend}\n * and provide methods for interacting with the configured generative model.\n *\n * @public\n */\nexport abstract class AIModel {\n /**\n * The fully qualified model resource name to use for generating images\n * (for example, `publishers/google/models/imagen-3.0-generate-002`).\n */\n readonly model: string;\n\n /**\n * @internal\n */\n _apiSettings: ApiSettings;\n\n /**\n * Constructs a new instance of the {@link AIModel} class.\n *\n * This constructor should only be called from subclasses that provide\n * a model API.\n *\n * @param ai - an {@link AI} instance.\n * @param modelName - The name of the model being used. It can be in one of the following formats:\n * - `my-model` (short name, will resolve to `publishers/google/models/my-model`)\n * - `models/my-model` (will resolve to `publishers/google/models/my-model`)\n * - `publishers/my-publisher/models/my-model` (fully qualified model name)\n *\n * @throws If the `apiKey` or `projectId` fields are missing in your\n * Firebase config.\n *\n * @internal\n */\n protected constructor(ai: AI, modelName: string) {\n this._apiSettings = initApiSettings(ai);\n this.model = AIModel.normalizeModelName(\n modelName,\n this._apiSettings.backend.backendType\n );\n }\n\n /**\n * Normalizes the given model name to a fully qualified model resource name.\n *\n * @param modelName - The model name to normalize.\n * @returns The fully qualified model resource name.\n *\n * @internal\n */\n static normalizeModelName(\n modelName: string,\n backendType: BackendType\n ): string {\n if (backendType === BackendType.GOOGLE_AI) {\n return AIModel.normalizeGoogleAIModelName(modelName);\n } else {\n return AIModel.normalizeVertexAIModelName(modelName);\n }\n }\n\n /**\n * @internal\n */\n private static normalizeGoogleAIModelName(modelName: string): string {\n return `models/${modelName}`;\n }\n\n /**\n * @internal\n */\n private static normalizeVertexAIModelName(modelName: string): string {\n let model: string;\n if (modelName.includes('/')) {\n if (modelName.startsWith('models/')) {\n // Add 'publishers/google' if the user is only passing in 'models/model-name'.\n model = `publishers/google/${modelName}`;\n } else {\n // Any other custom format (e.g. tuned models) must be passed in correctly.\n model = modelName;\n }\n } else {\n // If path is not included, assume it's a non-tuned model.\n model = `publishers/google/models/${modelName}`;\n }\n\n return model;\n }\n}\n","/**\n * @license\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 { Logger } from '@firebase/logger';\n\nexport const logger = new Logger('@firebase/vertexai');\n","/**\n * @license\n * Copyright 2025 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 { SingleRequestOptions, AIErrorCode, ErrorDetails } from '../types';\nimport { AIError } from '../errors';\nimport { ApiSettings } from '../types/internal';\nimport {\n DEFAULT_DOMAIN,\n DEFAULT_FETCH_TIMEOUT_MS,\n HYBRID_TAG,\n LANGUAGE_TAG,\n PACKAGE_VERSION\n} from '../constants';\nimport { logger } from '../logger';\nimport { BackendType, InferenceMode } from '../public-types';\n\nexport const TIMEOUT_EXPIRED_MESSAGE = 'Timeout has expired.';\nexport const ABORT_ERROR_NAME = 'AbortError';\n\nexport const enum Task {\n GENERATE_CONTENT = 'generateContent',\n STREAM_GENERATE_CONTENT = 'streamGenerateContent',\n COUNT_TOKENS = 'countTokens',\n PREDICT = 'predict'\n}\n\nexport const enum ServerPromptTemplateTask {\n TEMPLATE_GENERATE_CONTENT = 'templateGenerateContent',\n TEMPLATE_STREAM_GENERATE_CONTENT = 'templateStreamGenerateContent',\n TEMPLATE_PREDICT = 'templatePredict'\n}\n\ninterface BaseRequestURLParams {\n apiSettings: ApiSettings;\n stream: boolean;\n singleRequestOptions?: SingleRequestOptions;\n}\n\n/**\n * Parameters used to construct the URL of a request to use a model.\n */\ninterface ModelRequestURLParams extends BaseRequestURLParams {\n task: Task;\n model: string;\n templateId?: never;\n}\n\n/**\n * Parameters used to construct the URL of a request to use server side prompt templates.\n */\ninterface TemplateRequestURLParams extends BaseRequestURLParams {\n task: ServerPromptTemplateTask;\n templateId: string;\n model?: never;\n}\n\nexport class RequestURL {\n constructor(\n public readonly params: ModelRequestURLParams | TemplateRequestURLParams\n ) {}\n\n toString(): string {\n const url = new URL(this.baseUrl); // Throws if the URL is invalid\n url.pathname = this.pathname;\n url.search = this.queryParams.toString();\n return url.toString();\n }\n\n private get pathname(): string {\n // We need to construct a different URL if the request is for server side prompt templates,\n // since the URL patterns are different. Server side prompt templates expect a templateId\n // instead of a model name.\n if (this.params.templateId) {\n return `${this.params.apiSettings.backend._getTemplatePath(\n this.params.apiSettings.project,\n this.params.templateId\n )}:${this.params.task}`;\n } else {\n return `${this.params.apiSettings.backend._getModelPath(\n this.params.apiSettings.project,\n (this.params as ModelRequestURLParams).model\n )}:${this.params.task}`;\n }\n }\n\n private get baseUrl(): string {\n return (\n this.params.singleRequestOptions?.baseUrl ?? `https://${DEFAULT_DOMAIN}`\n );\n }\n\n private get queryParams(): URLSearchParams {\n const params = new URLSearchParams();\n if (this.params.stream) {\n params.set('alt', 'sse');\n }\n\n return params;\n }\n}\n\nexport class WebSocketUrl {\n constructor(public apiSettings: ApiSettings) {}\n toString(): string {\n const url = new URL(`wss://${DEFAULT_DOMAIN}`);\n url.pathname = this.pathname;\n\n const queryParams = new URLSearchParams();\n queryParams.set('key', this.apiSettings.apiKey);\n url.search = queryParams.toString();\n\n return url.toString();\n }\n\n private get pathname(): string {\n if (this.apiSettings.backend.backendType === BackendType.GOOGLE_AI) {\n return 'ws/google.firebase.vertexai.v1beta.GenerativeService/BidiGenerateContent';\n } else {\n return `ws/google.firebase.vertexai.v1beta.LlmBidiService/BidiGenerateContent/locations/${this.apiSettings.location}`;\n }\n }\n}\n\n/**\n * Log language and \"fire/version\" to x-goog-api-client\n */\nfunction getClientHeaders(url: RequestURL): string {\n const loggingTags = [];\n loggingTags.push(`${LANGUAGE_TAG}/${PACKAGE_VERSION}`);\n loggingTags.push(`fire/${PACKAGE_VERSION}`);\n /**\n * No call would be made if ONLY_ON_DEVICE.\n * ONLY_IN_CLOUD does not indicate an intention to use hybrid.\n */\n if (\n url.params.apiSettings.inferenceMode === InferenceMode.PREFER_ON_DEVICE ||\n url.params.apiSettings.inferenceMode === InferenceMode.PREFER_IN_CLOUD\n ) {\n // No version\n loggingTags.push(HYBRID_TAG);\n }\n return loggingTags.join(' ');\n}\n\nexport async function getHeaders(url: RequestURL): Promise<Headers> {\n const headers = new Headers();\n headers.append('Content-Type', 'application/json');\n headers.append('x-goog-api-client', getClientHeaders(url));\n headers.append('x-goog-api-key', url.params.apiSettings.apiKey);\n if (url.params.apiSettings.automaticDataCollectionEnabled) {\n headers.append('X-Firebase-Appid', url.params.apiSettings.appId);\n }\n if (url.params.apiSettings.getAppCheckToken) {\n const appCheckToken = await url.params.apiSettings.getAppCheckToken();\n if (appCheckToken) {\n headers.append('X-Firebase-AppCheck', appCheckToken.token);\n if (appCheckToken.error) {\n logger.warn(\n `Unable to obtain a valid App Check token: ${appCheckToken.error.message}`\n );\n }\n }\n }\n\n if (url.params.apiSettings.getAuthToken) {\n const authToken = await url.params.apiSettings.getAuthToken();\n if (authToken) {\n headers.append('Authorization', `Firebase ${authToken.accessToken}`);\n }\n }\n\n return headers;\n}\n\nexport async function makeRequest(\n requestUrlParams: TemplateRequestURLParams | ModelRequestURLParams,\n body: string\n): Promise<Response> {\n const url = new RequestURL(requestUrlParams);\n let response;\n\n const externalSignal = requestUrlParams.singleRequestOptions?.signal;\n const timeoutMillis =\n requestUrlParams.singleRequestOptions?.timeout != null &&\n requestUrlParams.singleRequestOptions.timeout >= 0\n ? requestUrlParams.singleRequestOptions.timeout\n : DEFAULT_FETCH_TIMEOUT_MS;\n\n const internalAbortController = new AbortController();\n const fetchTimeoutId = setTimeout(() => {\n internalAbortController.abort(\n new DOMException(TIMEOUT_EXPIRED_MESSAGE, ABORT_ERROR_NAME)\n );\n logger.debug(\n `Aborting request to ${url} due to timeout (${timeoutMillis}ms)`\n );\n }, timeoutMillis);\n\n // Used to abort the fetch if either the user-defined `externalSignal` is aborted, or if the\n // internal signal (triggered by timeouts) is aborted.\n const combinedSignal = AbortSignal.any(\n externalSignal\n ? [externalSignal, internalAbortController.signal]\n : [internalAbortController.signal]\n );\n\n if (externalSignal && externalSignal.aborted) {\n clearTimeout(fetchTimeoutId);\n throw new DOMException(\n externalSignal.reason ?? 'Aborted externally before fetch',\n ABORT_ERROR_NAME\n );\n }\n\n try {\n const fetchOptions: RequestInit = {\n method: 'POST',\n headers: await getHeaders(url),\n signal: combinedSignal,\n body\n };\n\n response = await fetch(url.toString(), fetchOptions);\n if (!response.ok) {\n let message = '';\n let errorDetails;\n try {\n const json = await response.json();\n message = json.error.message;\n if (json.error.details) {\n message += ` ${JSON.stringify(json.error.details)}`;\n errorDetails = json.error.details;\n }\n } catch (e) {\n // ignored\n }\n if (\n response.status === 403 &&\n errorDetails &&\n errorDetails.some(\n (detail: ErrorDetails) => detail.reason === 'SERVICE_DISABLED'\n ) &&\n errorDetails.some((detail: ErrorDetails) =>\n (\n detail.links as Array<Record<string, string>>\n )?.[0]?.description.includes(\n 'Google developers console API activation'\n )\n )\n ) {\n throw new AIError(\n AIErrorCode.API_NOT_ENABLED,\n `The Firebase AI SDK requires the Firebase AI ` +\n `API ('firebasevertexai.googleapis.com') to be enabled in your ` +\n `Firebase project. Enable this API by visiting the Firebase Console ` +\n `at https://console.firebase.google.com/project/${url.params.apiSettings.project}/ailogic/ ` +\n `and clicking \"Get started\". If you enabled this API recently, ` +\n `wait a few minutes for the action to propagate to our systems and ` +\n `then retry.`,\n {\n status: response.status,\n statusText: response.statusText,\n errorDetails\n }\n );\n }\n throw new AIError(\n AIErrorCode.FETCH_ERROR,\n `Error fetching from ${url}: [${response.status} ${response.statusText}] ${message}`,\n {\n status: response.status,\n statusText: response.statusText,\n errorDetails\n }\n );\n }\n } catch (e) {\n let err = e as Error;\n if (\n (e as AIError).code !== AIErrorCode.FETCH_ERROR &&\n (e as AIError).code !== AIErrorCode.API_NOT_ENABLED &&\n e instanceof Error &&\n (e as DOMException).name !== ABORT_ERROR_NAME\n ) {\n err = new AIError(\n AIErrorCode.ERROR,\n `Error fetching from ${url.toString()}: ${e.message}`\n );\n err.stack = e.stack;\n }\n\n throw err;\n } finally {\n // When doing streaming requests, this will clear the timeout once the stream begins.\n // If a timeout it 3000ms, and the stream starts after 300ms and ends after 5000ms, the\n // timeout will be cleared after 300ms, so it won't abort the request.\n clearTimeout(fetchTimeoutId);\n }\n return response;\n}\n","/**\n * @license\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 EnhancedGenerateContentResponse,\n FinishReason,\n FunctionCall,\n GenerateContentCandidate,\n GenerateContentResponse,\n ImagenGCSImage,\n ImagenInlineImage,\n AIErrorCode,\n InlineDataPart,\n Part,\n InferenceSource\n} from '../types';\nimport { AIError } from '../errors';\nimport { logger } from '../logger';\nimport { ImagenResponseInternal } from '../types/internal';\n\n/**\n * Check that at least one candidate exists and does not have a bad\n * finish reason. Warns if multiple candidates exist.\n */\nfunction hasValidCandidates(response: GenerateContentResponse): boolean {\n if (response.candidates && response.candidates.length > 0) {\n if (response.candidates.length > 1) {\n logger.warn(\n `This response had ${response.candidates.length} ` +\n `candidates. Returning text from the first candidate only. ` +\n `Access response.candidates directly to use the other candidates.`\n );\n }\n if (hadBadFinishReason(response.candidates[0])) {\n throw new AIError(\n AIErrorCode.RESPONSE_ERROR,\n `Response error: ${formatBlockErrorMessage(\n response\n )}. Response body stored in error.response`,\n {\n response\n }\n );\n }\n return true;\n } else {\n return false;\n }\n}\n\n/**\n * Creates an EnhancedGenerateContentResponse object that has helper functions and\n * other modifications that improve usability.\n */\nexport function createEnhancedContentResponse(\n response: GenerateContentResponse,\n inferenceSource: InferenceSource = InferenceSource.IN_CLOUD\n): EnhancedGenerateContentResponse {\n /**\n * The Vertex AI backend omits default values.\n * This causes the `index` property to be omitted from the first candidate in the\n * response, since it has index 0, and 0 is a default value.\n * See: https://github.com/firebase/firebase-js-sdk/issues/8566\n */\n if (response.candidates && !response.candidates[0].hasOwnProperty('index')) {\n response.candidates[0].index = 0;\n }\n\n const responseWithHelpers = addHelpers(response);\n responseWithHelpers.inferenceSource = inferenceSource;\n return responseWithHelpers;\n}\n\n/**\n * Adds convenience helper methods to a response object, including stream\n * chunks (as long as each chunk is a complete GenerateContentResponse JSON).\n */\nexport function addHelpers(\n response: GenerateContentResponse\n): EnhancedGenerateContentResponse {\n (response as EnhancedGenerateContentResponse).text = () => {\n if (hasValidCandidates(response)) {\n return getText(response, part => !part.thought);\n } else if (response.promptFeedback) {\n throw new AIError(\n AIErrorCode.RESPONSE_ERROR,\n `Text not available. ${formatBlockErrorMessage(response)}`,\n {\n response\n }\n );\n }\n return '';\n };\n (response as EnhancedGenerateContentResponse).thoughtSummary = () => {\n if (hasValidCandidates(response)) {\n const result = getText(response, part => !!part.thought);\n return result === '' ? undefined : result;\n } else if (response.promptFeedback) {\n throw new AIError(\n AIErrorCode.RESPONSE_ERROR,\n `Thought summary not available. ${formatBlockErrorMessage(response)}`,\n {\n response\n }\n );\n }\n return undefined;\n };\n (response as EnhancedGenerateContentResponse).inlineDataParts = ():\n | InlineDataPart[]\n | undefined => {\n if (hasValidCandidates(response)) {\n return getInlineDataParts(response);\n } else if (response.promptFeedback) {\n throw new AIError(\n AIErrorCode.RESPONSE_ERROR,\n `Data not available. ${formatBlockErrorMessage(response)}`,\n {\n response\n }\n );\n }\n return undefined;\n };\n (response as EnhancedGenerateContentResponse).functionCalls = () => {\n if (hasValidCandidates(response)) {\n return getFunctionCalls(response);\n } else if (response.promptFeedback) {\n throw new AIError(\n AIErrorCode.RESPONSE_ERROR,\n `Function call not available. ${formatBlockErrorMessage(response)}`,\n {\n response\n }\n );\n }\n return undefined;\n };\n return response as EnhancedGenerateContentResponse;\n}\n\n/**\n * Returns all text from the first candidate's parts, filtering by whether\n * `partFilter()` returns true.\n *\n * @param response - The `GenerateContentResponse` from which to extract text.\n * @param partFilter - Only return `Part`s for which this returns true\n */\nexport function getText(\n response: GenerateContentResponse,\n partFilter: (part: Part) => boolean\n): string {\n const textStrings = [];\n if (response.candidates?.[0].content?.parts) {\n for (const part of response.candidates?.[0].content?.parts) {\n if (part.text && partFilter(part)) {\n textStrings.push(part.text);\n }\n }\n }\n if (textStrings.length > 0) {\n return textStrings.join('');\n } else {\n return '';\n }\n}\n\n/**\n * Returns every {@link FunctionCall} associated with first candidate.\n */\nexport function getFunctionCalls(\n response?: GenerateContentResponse\n): FunctionCall[] | undefined {\n if (!response) {\n return undefined;\n }\n const functionCalls: FunctionCall[] = [];\n if (response.candidates?.[0].content?.parts) {\n for (const part of response.candidates?.[0].content?.parts) {\n if (part.functionCall) {\n functionCalls.push(part.functionCall);\n }\n }\n }\n if (functionCalls.length > 0) {\n return functionCalls;\n } else {\n return undefined;\n }\n}\n\n/**\n * Returns every {@link InlineDataPart} in the first candidate if present.\n *\n * @internal\n */\nexport function getInlineDataParts(\n response: GenerateContentResponse\n): InlineDataPart[] | undefined {\n const data: InlineDataPart[] = [];\n\n if (response.candidates?.[0].content?.parts) {\n for (const part of response.candidates?.[0].content?.parts) {\n if (part.inlineData) {\n data.push(part);\n }\n }\n }\n\n if (data.length > 0) {\n return data;\n } else {\n return undefined;\n }\n}\n\nconst badFinishReasons = [FinishReason.RECITATION, FinishReason.SAFETY];\n\nfunction hadBadFinishReason(candidate: GenerateContentCandidate): boolean {\n return (\n !!candidate.finishReason &&\n badFinishReasons.some(reason => reason === candidate.finishReason)\n );\n}\n\nexport function formatBlockErrorMessage(\n response: GenerateContentResponse\n): string {\n let message = '';\n if (\n (!response.candidates || response.candidates.length === 0) &&\n response.promptFeedback\n ) {\n message += 'Response was blocked';\n if (response.promptFeedback?.blockReason) {\n message += ` due to ${response.promptFeedback.blockReason}`;\n }\n if (response.promptFeedback?.blockReasonMessage) {\n message += `: ${response.promptFeedback.blockReasonMessage}`;\n }\n } else if (response.candidates?.[0]) {\n const firstCandidate = response.candidates[0];\n if (hadBadFinishReason(firstCandidate)) {\n message += `Candidate was blocked due to ${firstCandidate.finishReason}`;\n if (firstCandidate.finishMessage) {\n message += `: ${firstCandidate.finishMessage}`;\n }\n }\n }\n return message;\n}\n\n/**\n * Convert a generic successful fetch response body to an Imagen response object\n * that can be returned to the user. This converts the REST APIs response format to our\n * APIs representation of a response.\n *\n * @internal\n */\nexport async function handlePredictResponse<\n T extends ImagenInlineImage | ImagenGCSImage\n>(response: Response): Promise<{ images: T[]; filteredReason?: string }> {\n const responseJson: ImagenResponseInternal = await response.json();\n\n const images: T[] = [];\n let filteredReason: string | undefined = undefined;\n\n // The backend should always send a non-empty array of predictions if the response was successful.\n if (!responseJson.predictions || responseJson.predictions?.length === 0) {\n throw new AIError(\n AIErrorCode.RESPONSE_ERROR,\n 'No predictions or filtered reason received from Vertex AI. Please report this issue with the full error details at https://github.com/firebase/firebase-js-sdk/issues.'\n );\n }\n\n for (const prediction of responseJson.predictions) {\n if (prediction.raiFilteredReason) {\n filteredReason = prediction.raiFilteredReason;\n } else if (prediction.mimeType && prediction.bytesBase64Encoded) {\n images.push({\n mimeType: prediction.mimeType,\n bytesBase64Encoded: prediction.bytesBase64Encoded\n } as T);\n } else if (prediction.mimeType && prediction.gcsUri) {\n images.push({\n mimeType: prediction.mimeType,\n gcsURI: prediction.gcsUri\n } as T);\n } else if (prediction.safetyAttributes) {\n // Ignore safetyAttributes \"prediction\" to avoid throwing an error below.\n } else {\n throw new AIError(\n AIErrorCode.RESPONSE_ERROR,\n `Unexpected element in 'predictions' array in response: '${JSON.stringify(\n prediction\n )}'`\n );\n }\n }\n\n return { images, filteredReason };\n}\n","/**\n * @license\n * Copyright 2025 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 { AIError } from './errors';\nimport { logger } from './logger';\nimport {\n CitationMetadata,\n CountTokensRequest,\n GenerateContentCandidate,\n GenerateContentRequest,\n GenerateContentResponse,\n HarmSeverity,\n InlineDataPart,\n PromptFeedback,\n SafetyRating,\n AIErrorCode\n} from './types';\nimport {\n GoogleAIGenerateContentResponse,\n GoogleAIGenerateContentCandidate,\n GoogleAICountTokensRequest\n} from './types/googleai';\n\n/**\n * This SDK supports both the Vertex AI Gemini API and the Gemini Developer API (using Google AI).\n * The public API prioritizes the format used by the Vertex AI Gemini API.\n * We avoid having two sets of types by translating requests and responses between the two API formats.\n * This translation allows developers to switch between the Vertex AI Gemini API and the Gemini Developer API\n * with minimal code changes.\n *\n * In here are functions that map requests and responses between the two API formats.\n * Requests in the Vertex AI format are mapped to the Google AI format before being sent.\n * Responses from the Google AI backend are mapped back to the Vertex AI format before being returned to the user.\n */\n\n/**\n * Maps a Vertex AI {@link GenerateContentRequest} to a format that can be sent to Google AI.\n *\n * @param generateContentRequest The {@link GenerateContentRequest} to map.\n * @returns A {@link GenerateContentResponse} that conforms to the Google AI format.\n *\n * @throws If the request contains properties that are unsupported by Google AI.\n *\n * @internal\n */\nexport function mapGenerateContentRequest(\n generateContentRequest: GenerateContentRequest\n): GenerateContentRequest {\n generateContentRequest.safetySettings?.forEach(safetySetting => {\n if (safetySetting.method) {\n throw new AIError(\n AIErrorCode.UNSUPPORTED,\n 'SafetySetting.method is not supported in the the Gemini Developer API. Please remove this property.'\n );\n }\n });\n\n if (generateContentRequest.generationConfig?.topK) {\n const roundedTopK = Math.round(\n generateContentRequest.generationConfig.topK\n );\n\n if (roundedTopK !== generateContentRequest.generationConfig.topK) {\n logger.warn(\n 'topK in GenerationConfig has been rounded to the nearest integer to match the format for requests to the Gemini Developer API.'\n );\n generateContentRequest.generationConfig.topK = roundedTopK;\n }\n }\n\n return generateContentRequest;\n}\n\n/**\n * Maps a {@link GenerateContentResponse} from Google AI to the format of the\n * {@link GenerateContentResponse} that we get from VertexAI that is exposed in the public API.\n *\n * @param googleAIResponse The {@link GenerateContentResponse} from Google AI.\n * @returns A {@link GenerateContentResponse} that conforms to the public API's format.\n *\n * @internal\n */\nexport function mapGenerateContentResponse(\n googleAIResponse: GoogleAIGenerateContentResponse\n): GenerateContentResponse {\n const generateContentResponse = {\n candidates: googleAIResponse.candidates\n ? mapGenerateContentCandidates(googleAIResponse.candidates)\n : undefined,\n prompt: googleAIResponse.promptFeedback\n ? mapPromptFeedback(googleAIResponse.promptFeedback)\n : undefined,\n usageMetadata: googleAIResponse.usageMetadata\n };\n\n return generateContentResponse;\n}\n\n/**\n * Maps a Vertex AI {@link CountTokensRequest} to a format that can be sent to Google AI.\n *\n * @param countTokensRequest The {@link CountTokensRequest} to map.\n * @param model The model to count tokens with.\n * @returns A {@link CountTokensRequest} that conforms to the Google AI format.\n *\n * @internal\n */\nexport function mapCountTokensRequest(\n countTokensRequest: CountTokensRequest,\n model: string\n): GoogleAICountTokensRequest {\n const mappedCountTokensRequest: GoogleAICountTokensRequest = {\n generateContentRequest: {\n model,\n ...countTokensRequest\n }\n };\n\n return mappedCountTokensRequest;\n}\n\n/**\n * Maps a Google AI {@link GoogleAIGenerateContentCandidate} to a format that conforms\n * to the Vertex AI API format.\n *\n * @param candidates The {@link GoogleAIGenerateContentCandidate} to map.\n * @returns A {@link GenerateContentCandidate} that conforms to the Vertex AI format.\n *\n * @throws If any {@link Part} in the candidates has a `videoMetadata` property.\n *\n * @internal\n */\nexport function mapGenerateContentCandidates(\n candidates: GoogleAIGenerateContentCandidate[]\n): GenerateContentCandidate[] {\n const mappedCandidates: GenerateContentCandidate[] = [];\n let mappedSafetyRatings: SafetyRating[];\n if (mappedCandidates) {\n candidates.forEach(candidate => {\n // Map citationSources to citations.\n let citationMetadata: CitationMetadata | undefined;\n if (candidate.citationMetadata) {\n citationMetadata = {\n citations: candidate.citationMetadata.citationSources\n };\n }\n\n // Assign missing candidate SafetyRatings properties to their defaults if undefined.\n if (candidate.safetyRatings) {\n mappedSafetyRatings = candidate.safetyRatings.map(safetyRating => {\n return {\n ...safetyRating,\n severity:\n safetyRating.severity ?? HarmSeverity.HARM_SEVERITY_UNSUPPORTED,\n probabilityScore: safetyRating.probabilityScore ?? 0,\n severityScore: safetyRating.severityScore ?? 0\n };\n });\n }\n\n // videoMetadata is not supported.\n // Throw early since developers may send a long video as input and only expect to pay\n // for inference on a small portion of the video.\n if (\n candidate.content?.parts?.some(\n part => (part as InlineDataPart)?.videoMetadata\n )\n ) {\n throw new AIError(\n AIErrorCode.UNSUPPORTED,\n 'Part.videoMetadata is not supported in the Gemini Developer API. Please remove this property.'\n );\n }\n\n const mappedCandidate = {\n index: candidate.index,\n content: candidate.content,\n finishReason: candidate.finishReason,\n finishMessage: candidate.finishMessage,\n safetyRatings: mappedSafetyRatings,\n citationMetadata,\n groundingMetadata: candidate.groundingMetadata,\n urlContextMetadata: candidate.urlContextMetadata\n };\n mappedCandidates.push(mappedCandidate);\n });\n }\n\n return mappedCandidates;\n}\n\nexport function mapPromptFeedback(\n promptFeedback: PromptFeedback\n): PromptFeedback {\n // Assign missing SafetyRating properties to their defaults if undefined.\n const mappedSafetyRatings: SafetyRating[] = [];\n promptFeedback.safetyRatings.forEach(safetyRating => {\n mappedSafetyRatings.push({\n category: safetyRating.category,\n probability: safetyRating.probability,\n severity: safetyRating.severity ?? HarmSeverity.HARM_SEVERITY_UNSUPPORTED,\n probabilityScore: safetyRating.probabilityScore ?? 0,\n severityScore: safetyRating.severityScore ?? 0,\n blocked: safetyRating.blocked\n });\n });\n\n const mappedPromptFeedback: PromptFeedback = {\n blockReason: promptFeedback.blockReason,\n safetyRatings: mappedSafetyRatings,\n blockReasonMessage: promptFeedback.blockReasonMessage\n };\n return mappedPromptFeedback;\n}\n","/**\n * @license\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 EnhancedGenerateContentResponse,\n GenerateContentCandidate,\n GenerateContentResponse,\n GenerateContentStreamResult,\n Part,\n AIErrorCode\n} from '../types';\nimport { AIError } from '../errors';\nimport { createEnhancedContentResponse } from './response-helpers';\nimport * as GoogleAIMapper from '../googleai-mappers';\nimport { GoogleAIGenerateContentResponse } from '../types/googleai';\nimport { ApiSettings } from '../types/internal';\nimport {\n BackendType,\n InferenceSource,\n URLContextMetadata\n} from '../public-types';\n\nconst responseLineRE = /^data\\: (.*)(?:\\n\\n|\\r\\r|\\r\\n\\r\\n)/;\n\n/**\n * Process a response.body stream from the backend and return an\n * iterator that provides one complete GenerateContentResponse at a time\n * and a promise that resolves with a single aggregated\n * GenerateContentResponse.\n *\n * @param response - Response from a fetch call\n */\nexport async function processStream(\n response: Response,\n apiSettings: ApiSettings,\n inferenceSource?: InferenceSource\n): Promise<\n GenerateContentStreamResult & { firstValue?: GenerateContentResponse }\n> {\n const inputStream = response.body!.pipeThrough(\n new TextDecoderStream('utf8', { fatal: true })\n );\n\n const responseStream =\n getResponseStream<GenerateContentResponse>(inputStream);\n\n // We split the stream so the user can iterate over partial results (stream1)\n // while we aggregate the full result for history/final response (stream2).\n const [stream1, stream2] = responseStream.tee();\n const { response: internalResponse, firstValue } =\n await processStreamInternal(stream2, apiSettings, inferenceSource);\n return {\n stream: generateResponseSequence(stream1, apiSettings, inferenceSource),\n response: internalResponse,\n firstValue\n };\n}\n\n/**\n * Consumes streams teed from the input stream for internal needs.\n * The streams need to be teed because each stream can only be consumed\n * by one reader.\n *\n * \"streamForPeek\"\n * This tee is used to peek at the first value for relevant information\n * that we need to evaluate before returning the stream handle to the\n * client. For example, we need to check if the response is a function\n * call that may need to be handled by automatic function calling before\n * returning a response to the client.\n *\n * \"streamForAggregation\"\n * We iterate through this tee independently from the user and aggregate\n * it into a single response when the stream is complete. We need this\n * aggregate object to add to chat history when using ChatSession. It's\n * also provided to the user if they want it.\n */\nasync function processStreamInternal(\n stream: ReadableStream<GenerateContentResponse>,\n apiSettings: ApiSettings,\n inferenceSource?: InferenceSource\n): Promise<{\n firstValue?: GenerateContentResponse;\n response: Promise<EnhancedGenerateContentResponse>;\n}> {\n const [streamForPeek, streamForAggregation] = stream.tee();\n const reader = streamForPeek.getReader();\n const { value } = await reader.read();\n return {\n firstValue: value,\n response: getResponsePromise(\n streamForAggregation,\n apiSettings,\n inferenceSource\n )\n };\n}\n\nasync function getResponsePromise(\n stream: ReadableStream<GenerateContentResponse>,\n apiSettings: ApiSettings,\n inferenceSource?: InferenceSource\n): Promise<EnhancedGenerateContentResponse> {\n const allResponses: GenerateContentResponse[] = [];\n const reader = stream.getReader();\n while (true) {\n const { done, value } = await reader.read();\n if (done) {\n let generateContentResponse = aggregateResponses(allResponses);\n if (apiSettings.backend.backendType === BackendType.GOOGLE_AI) {\n generateContentResponse = GoogleAIMapper.mapGenerateContentResponse(\n generateContentResponse as GoogleAIGenerateContentResponse\n );\n }\n return createEnhancedContentResponse(\n generateContentResponse,\n inferenceSource\n );\n }\n allResponses.push(value);\n }\n}\n\nasync function* generateResponseSequence(\n stream: ReadableStream<GenerateContentResponse>,\n apiSettings: ApiSettings,\n inferenceSource?: InferenceSource\n): AsyncGenerator<EnhancedGenerateContentResponse> {\n const reader = stream.getReader();\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n break;\n }\n\n let enhancedResponse: EnhancedGenerateContentResponse;\n if (apiSettings.backend.backendType === BackendType.GOOGLE_AI) {\n enhancedResponse = createEnhancedContentResponse(\n GoogleAIMapper.mapGenerateContentResponse(\n value as GoogleAIGenerateContentResponse\n ),\n inferenceSource\n );\n } else {\n enhancedResponse = createEnhancedContentResponse(value, inferenceSource);\n }\n\n const firstCandidate = enhancedResponse.candidates?.[0];\n if (\n !firstCandidate?.content?.parts &&\n !firstCandidate?.finishReason &&\n !firstCandidate?.citationMetadata &&\n !firstCandidate?.urlContextMetadata\n ) {\n continue;\n }\n\n yield enhancedResponse;\n }\n}\n\n/**\n * Reads a raw string stream, buffers incomplete chunks, and yields parsed JSON objects.\n */\nexport function getResponseStream<T>(\n inputStream: ReadableStream<string>\n): ReadableStream<T> {\n const reader = inputStream.getReader();\n const stream = new ReadableStream<T>({\n start(controller) {\n let currentText = '';\n return pump();\n function pump(): Promise<(() => Promise<void>) | undefined> {\n return reader.read().then(({ value, done }) => {\n if (done) {\n if (currentText.trim()) {\n controller.error(\n new AIError(AIErrorCode.PARSE_FAILED, 'Failed to parse stream')\n );\n return;\n }\n controller.close();\n return;\n }\n\n currentText += value;\n // SSE events may span chunk boundaries, so we buffer until we match\n // the full \"data: {json}\\n\\n\" pattern.\n let match = currentText.match(responseLineRE);\n let parsedResponse: T;\n while (match) {\n try {\n parsedResponse = JSON.parse(match[1]);\n } catch (e) {\n controller.error(\n new AIError(\n AIErrorCode.PARSE_FAILED,\n `Error parsing JSON response: \"${match[1]}`\n )\n );\n return;\n }\n controller.enqueue(parsedResponse);\n currentText = currentText.substring(match[0].length);\n match = currentText.match(responseLineRE);\n }\n return pump();\n });\n }\n }\n });\n return stream;\n}\n\n/**\n * Aggregates an array of `GenerateContentResponse`s into a single\n * GenerateContentResponse.\n */\nexport function aggregateResponses(\n responses: GenerateContentResponse[]\n): GenerateContentResponse {\n const lastResponse = responses[responses.length - 1];\n const aggregatedResponse: GenerateContentResponse = {\n promptFeedback: lastResponse?.promptFeedback\n };\n for (const response of responses) {\n if (response.candidates) {\n for (const candidate of response.candidates) {\n // Use 0 if index is undefined (protobuf default value omission).\n const i = candidate.index || 0;\n if (!aggregatedResponse.candidates) {\n aggregatedResponse.candidates = [];\n }\n if (!aggregatedResponse.candidates[i]) {\n aggregatedResponse.candidates[i] = {\n index: candidate.index\n } as GenerateContentCandidate;\n }\n\n // Overwrite with the latest metadata\n aggregatedResponse.candidates[i].citationMetadata =\n candidate.citationMetadata;\n aggregatedResponse.candidates[i].finishReason = candidate.finishReason;\n aggregatedResponse.candidates[i].finishMessage =\n candidate.finishMessage;\n aggregatedResponse.candidates[i].safetyRatings =\n candidate.safetyRatings;\n aggregatedResponse.candidates[i].groundingMetadata =\n candidate.groundingMetadata;\n\n // The urlContextMetadata object is defined in the first chunk of the response stream.\n // In all subsequent chunks, the urlContextMetadata object will be undefined. We need to\n // make sure that we don't overwrite the first value urlContextMetadata object with undefined.\n // FIXME: What happens if we receive a second, valid urlContextMetadata object?\n const urlContextMetadata = candidate.urlContextMetadata as unknown;\n if (\n typeof urlContextMetadata === 'object' &&\n urlContextMetadata !== null &&\n Object.keys(urlContextMetadata).length > 0\n ) {\n aggregatedResponse.candidates[i].urlContextMetadata =\n urlContextMetadata as URLContextMetadata;\n }\n\n if (candidate.content) {\n if (!candidate.content.parts) {\n continue;\n }\n if (!aggregatedResponse.candidates[i].content) {\n aggregatedResponse.candidates[i].content = {\n role: candidate.content.role || 'user',\n parts: []\n };\n }\n for (const part of candidate.content.parts) {\n const newPart: Part = { ...part };\n // The backend can send empty text parts. If these are sent back\n // (e.g. in chat history), the backend will respond with an error.\n // To prevent this, ignore empty text parts.\n if (part.text === '') {\n continue;\n }\n if (Object.keys(newPart).length > 0) {\n aggregatedResponse.candidates[i].content.parts.push(\n newPart as Part\n );\n }\n }\n }\n }\n }\n }\n return aggregatedResponse;\n}\n","/**\n * @license\n * Copyright 2025 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 { AIError } from '../errors';\nimport {\n GenerateContentRequest,\n InferenceMode,\n AIErrorCode,\n ChromeAdapter,\n InferenceSource\n} from '../types';\n\nconst errorsCausingFallback: AIErrorCode[] = [\n // most network errors\n AIErrorCode.FETCH_ERROR,\n // fallback code for all other errors in makeRequest\n AIErrorCode.ERROR,\n // error due to API not being enabled in project\n AIErrorCode.API_NOT_ENABLED\n];\n\ninterface CallResult<Response> {\n response: Response;\n inferenceSource: InferenceSource;\n}\n\n/**\n * Dispatches a request to the appropriate backend (on-device or in-cloud)\n * based on the inference mode.\n *\n * @param request - The request to be sent.\n * @param chromeAdapter - The on-device model adapter.\n * @param onDeviceCall - The function to call for on-device inference.\n * @param inCloudCall - The function to call for in-cloud inference.\n * @returns The response from the backend.\n */\nexport async function callCloudOrDevice<Response>(\n request: GenerateContentRequest,\n chromeAdapter: ChromeAdapter | undefined,\n onDeviceCall: () => Promise<Response>,\n inCloudCall: () => Promise<Response>\n): Promise<CallResult<Response>> {\n if (!chromeAdapter) {\n return {\n response: await inCloudCall(),\n inferenceSource: InferenceSource.IN_CLOUD\n };\n }\n switch (chromeAdapter.mode) {\n case InferenceMode.ONLY_ON_DEVICE:\n if (await chromeAdapter.isAvailable(request)) {\n return {\n response: await onDeviceCall(),\n inferenceSource: InferenceSource.ON_DEVICE\n };\n }\n throw new AIError(\n AIErrorCode.UNSUPPORTED,\n 'Inference mode is ONLY_ON_DEVICE, but an on-device model is not available.'\n );\n case InferenceMode.ONLY_IN_CLOUD:\n return {\n response: await inCloudCall(),\n inferenceSource: InferenceSource.IN_CLOUD\n };\n case InferenceMode.PREFER_IN_CLOUD:\n try {\n return {\n response: await inCloudCall(),\n inferenceSource: InferenceSource.IN_CLOUD\n };\n } catch (e) {\n if (e instanceof AIError && errorsCausingFallback.includes(e.code)) {\n return {\n response: await onDeviceCall(),\n inferenceSource: InferenceSource.ON_DEVICE\n };\n }\n throw e;\n }\n case InferenceMode.PREFER_ON_DEVICE:\n if (await chromeAdapter.isAvailable(request)) {\n return {\n response: await onDeviceCall(),\n inferenceSource: InferenceSource.ON_DEVICE\n };\n }\n return {\n response: await inCloudCall(),\n inferenceSource: InferenceSource.IN_CLOUD\n };\n default:\n throw new AIError(\n AIErrorCode.ERROR,\n `Unexpected infererence mode: ${chromeAdapter.mode}`\n );\n }\n}\n","/**\n * @license\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 GenerateContentRequest,\n GenerateContentResponse,\n GenerateContentResult,\n GenerateContentStreamResult,\n SingleRequestOptions\n} from '../types';\nimport {\n makeRequest,\n ServerPromptTemplateTask,\n Task\n} from '../requests/request';\nimport { createEnhancedContentResponse } from '../requests/response-helpers';\nimport { processStream } from '../requests/stream-reader';\nimport { ApiSettings } from '../types/internal';\nimport * as GoogleAIMapper from '../googleai-mappers';\nimport { BackendType } from '../public-types';\nimport { ChromeAdapter } from '../types/chrome-adapter';\nimport { callCloudOrDevice } from '../requests/hybrid-helpers';\n\nasync function generateContentStreamOnCloud(\n apiSettings: ApiSettings,\n model: string,\n params: GenerateContentRequest,\n singleRequestOptions?: SingleRequestOptions\n): Promise<Response> {\n if (apiSettings.backend.backendType === BackendType.GOOGLE_AI) {\n params = GoogleAIMapper.mapGenerateContentRequest(params);\n }\n return makeRequest(\n {\n task: Task.STREAM_GENERATE_CONTENT,\n model,\n apiSettings,\n stream: true,\n singleRequestOptions\n },\n JSON.stringify(params)\n );\n}\n\nexport async function generateContentStream(\n apiSettings: ApiSettings,\n model: string,\n params: GenerateContentRequest,\n chromeAdapter?: ChromeAdapter,\n singleRequestOptions?: SingleRequestOptions\n): Promise<\n GenerateContentStreamResult & { firstValue?: GenerateContentResponse }\n> {\n const callResult = await callCloudOrDevice(\n params,\n chromeAdapter,\n () => chromeAdapter!.generateContentStream(params),\n () =>\n generateContentStreamOnCloud(\n apiSettings,\n model,\n params,\n singleRequestOptions\n )\n );\n return processStream(\n callResult.response,\n apiSettings,\n callResult.inferenceSource\n );\n}\n\nasync function generateContentOnCloud(\n apiSettings: ApiSettings,\n model: string,\n params: GenerateContentRequest,\n singleRequestOptions?: SingleRequestOptions\n): Promise<Response> {\n if (apiSettings.backend.backendType === BackendType.GOOGLE_AI) {\n params = GoogleAIMapper.mapGenerateContentRequest(params);\n }\n return makeRequest(\n {\n model,\n task: Task.GENERATE_CONTENT,\n apiSettings,\n stream: false,\n singleRequestOptions\n },\n JSON.stringify(params)\n );\n}\n\nexport async function templateGenerateContent(\n apiSettings: ApiSettings,\n templateId: string,\n templateParams: object,\n singleRequestOptions?: SingleRequestOptions\n): Promise<GenerateContentResult> {\n const response = await makeRequest(\n {\n task: ServerPromptTemplateTask.TEMPLATE_GENERATE_CONTENT,\n templateId,\n apiSettings,\n stream: false,\n singleRequestOptions\n },\n JSON.stringify(templateParams)\n );\n const generateContentResponse = await processGenerateContentResponse(\n response,\n apiSettings\n );\n const enhancedResponse = createEnhancedContentResponse(\n generateContentResponse\n );\n return {\n response: enhancedResponse\n };\n}\n\nexport async function templateGenerateContentStream(\n apiSettings: ApiSettings,\n templateId: string,\n templateParams: object,\n singleRequestOptions?: SingleRequestOptions\n): Promise<GenerateContentStreamResult> {\n const response = await makeRequest(\n {\n task: ServerPromptTemplateTask.TEMPLATE_STREAM_GENERATE_CONTENT,\n templateId,\n apiSettings,\n stream: true,\n singleRequestOptions\n },\n JSON.stringify(templateParams)\n );\n return processStream(response, apiSettings);\n}\n\nexport async function generateContent(\n apiSettings: ApiSettings,\n model: string,\n params: GenerateContentRequest,\n chromeAdapter?: ChromeAdapter,\n singleRequestOptions?: SingleRequestOptions\n): Promise<GenerateContentResult> {\n const callResult = await callCloudOrDevice(\n params,\n chromeAdapter,\n () => chromeAdapter!.generateContent(params),\n () =>\n generateContentOnCloud(apiSettings, model, params, singleRequestOptions)\n );\n const generateContentResponse = await processGenerateContentResponse(\n callResult.response,\n apiSettings\n );\n const enhancedResponse = createEnhancedContentResponse(\n generateContentResponse,\n callResult.inferenceSource\n );\n return {\n response: enhancedResponse\n };\n}\n\nasync function processGenerateContentResponse(\n response: Response,\n apiSettings: ApiSettings\n): Promise<GenerateContentResponse> {\n const responseJson = await response.json();\n if (apiSettings.backend.backendType === BackendType.GOOGLE_AI) {\n return GoogleAIMapper.mapGenerateContentResponse(responseJson);\n } else {\n return responseJson;\n }\n}\n","/**\n * @license\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 { Content, GenerateContentRequest, Part, AIErrorCode } from '../types';\nimport { AIError } from '../errors';\nimport { ImagenGenerationParams, PredictRequestBody } from '../types/internal';\n\nexport function formatSystemInstruction(\n input?: string | Part | Content\n): Content | undefined {\n // null or undefined\n if (input == null) {\n return undefined;\n } else if (typeof input === 'string') {\n return { role: 'system', parts: [{ text: input }] } as Content;\n } else if ((input as Part).text) {\n return { role: 'system', parts: [input as Part] };\n } else if ((input as Content).parts) {\n if (!(input as Content).role) {\n return { role: 'system', parts: (input as Content).parts };\n } else {\n return input as Content;\n }\n }\n}\n\nexport function formatNewContent(\n request: string | Array<string | Part>\n): Content {\n let newParts: Part[] = [];\n if (typeof request === 'string') {\n newParts = [{ text: request }];\n } else {\n for (const partOrString of request) {\n if (typeof partOrString === 'string') {\n newParts.push({ text: partOrString });\n } else {\n newParts.push(partOrString);\n }\n }\n }\n return assignRoleToPartsAndValidateSendMessageRequest(newParts);\n}\n\n/**\n * When multiple Part types (i.e. FunctionResponsePart and TextPart) are\n * passed in a single Part array, we may need to assign different roles to each\n * part. Currently only FunctionResponsePart requires a role other than 'user'.\n * @private\n * @param parts Array of parts to pass to the model\n * @returns Array of content items\n */\nfunction assignRoleToPartsAndValidateSendMessageRequest(\n parts: Part[]\n): Content {\n const userContent: Content = { role: 'user', parts: [] };\n const functionContent: Content = { role: 'function', parts: [] };\n let hasUserContent = false;\n let hasFunctionContent = false;\n for (const part of parts) {\n if ('functionResponse' in part) {\n functionContent.parts.push(part);\n hasFunctionContent = true;\n } else {\n userContent.parts.push(part);\n hasUserContent = true;\n }\n }\n\n if (hasUserContent && hasFunctionContent) {\n throw new AIError(\n AIErrorCode.INVALID_CONTENT,\n 'Within a single message, FunctionResponse cannot be mixed with other type of Part in the request for sending chat message.'\n );\n }\n\n if (!hasUserContent && !hasFunctionContent) {\n throw new AIError(\n AIErrorCode.INVALID_CONTENT,\n 'No Content is provided for sending chat message.'\n );\n }\n\n if (hasUserContent) {\n return userContent;\n }\n\n return functionContent;\n}\n\nexport function formatGenerateContentInput(\n params: GenerateContentRequest | string | Array<string | Part>\n): GenerateContentRequest {\n let formattedRequest: GenerateContentRequest;\n if ((params as GenerateContentRequest).contents) {\n formattedRequest = params as GenerateContentRequest;\n } else {\n // Array or string\n const content = formatNewContent(params as string | Array<string | Part>);\n formattedRequest = { contents: [content] };\n }\n if ((params as GenerateContentRequest).systemInstruction) {\n formattedRequest.systemInstruction = formatSystemInstruction(\n (params as GenerateContentRequest).systemInstruction\n );\n }\n return formattedRequest;\n}\n\n/**\n * Convert the user-defined parameters in {@link ImagenGenerationParams} to the format\n * that is expected from the REST API.\n *\n * @internal\n */\nexport function createPredictRequestBody(\n prompt: string,\n {\n gcsURI,\n imageFormat,\n addWatermark,\n numberOfImages = 1,\n negativePrompt,\n aspectRatio,\n safetyFilterLevel,\n personFilterLevel\n }: ImagenGenerationParams\n): PredictRequestBody {\n // Properties that are undefined will be omitted from the JSON string that is sent in the request.\n const body: PredictRequestBody = {\n instances: [\n {\n prompt\n }\n ],\n parameters: {\n storageUri: gcsURI,\n negativePrompt,\n sampleCount: numberOfImages,\n aspectRatio,\n outputOptions: imageFormat,\n addWatermark,\n safetyFilterLevel,\n personGeneration: personFilterLevel,\n includeRaiReason: true,\n includeSafetyAttributes: true\n }\n };\n return body;\n}\n","/**\n * @license\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 { Content, POSSIBLE_ROLES, Part, Role, AIErrorCode } from '../types';\nimport { AIError } from '../errors';\n\n// https://ai.google.dev/api/rest/v1beta/Content#part\n\nconst VALID_PART_FIELDS: Array<keyof Part> = [\n 'text',\n 'inlineData',\n 'functionCall',\n 'functionResponse',\n 'thought',\n 'thoughtSignature'\n];\n\nconst VALID_PARTS_PER_ROLE: { [key in Role]: Array<keyof Part> } = {\n user: ['text', 'inlineData'],\n function: ['functionResponse'],\n model: ['text', 'functionCall', 'thought', 'thoughtSignature'],\n // System instructions shouldn't be in history anyway.\n system: ['text']\n};\n\nconst VALID_PREVIOUS_CONTENT_ROLES: { [key in Role]: Role[] } = {\n user: ['model'],\n function: ['model'],\n model: ['user', 'function'],\n // System instructions shouldn't be in history.\n system: []\n};\n\nexport function validateChatHistory(history: Content[]): void {\n let prevContent: Content | null = null;\n for (const currContent of history) {\n const { role, parts } = currContent;\n if (!prevContent && role !== 'user') {\n throw new AIError(\n AIErrorCode.INVALID_CONTENT,\n `First Content should be with role 'user', got ${role}`\n );\n }\n if (!POSSIBLE_ROLES.includes(role)) {\n throw new AIError(\n AIErrorCode.INVALID_CONTENT,\n `Each item should include role field. Got ${role} but valid roles are: ${JSON.stringify(\n POSSIBLE_ROLES\n )}`\n );\n }\n\n if (!Array.isArray(parts)) {\n throw new AIError(\n AIErrorCode.INVALID_CONTENT,\n `Content should have 'parts' property with an array of Parts`\n );\n }\n\n if (parts.length === 0) {\n throw new AIError(\n AIErrorCode.INVALID_CONTENT,\n `Each Content should have at least one part`\n );\n }\n\n const countFields: Record<keyof Part, number> = {\n text: 0,\n inlineData: 0,\n functionCall: 0,\n functionResponse: 0,\n thought: 0,\n thoughtSignature: 0,\n executableCode: 0,\n codeExecutionResult: 0\n };\n\n for (const part of parts) {\n for (const key of VALID_PART_FIELDS) {\n if (key in part) {\n countFields[key] += 1;\n }\n }\n }\n const validParts = VALID_PARTS_PER_ROLE[role];\n for (const key of VALID_PART_FIELDS) {\n if (!validParts.includes(key) && countFields[key] > 0) {\n throw new AIError(\n AIErrorCode.INVALID_CONTENT,\n `Content with role '${role}' can't contain '${key}' part`\n );\n }\n }\n\n if (prevContent) {\n const validPreviousContentRoles = VALID_PREVIOUS_CONTENT_ROLES[role];\n if (!validPreviousContentRoles.includes(prevContent.role)) {\n throw new AIError(\n AIErrorCode.INVALID_CONTENT,\n `Content with role '${role}' can't follow '${\n prevContent.role\n }'. Valid previous roles: ${JSON.stringify(\n VALID_PREVIOUS_CONTENT_ROLES\n )}`\n );\n }\n }\n prevContent = currContent;\n }\n}\n","/**\n * @license\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 AIErrorCode,\n Content,\n FunctionCall,\n FunctionDeclarationsTool,\n FunctionResponsePart,\n GenerateContentRequest,\n GenerateContentResponse,\n GenerateContentResult,\n GenerateContentStreamResult,\n Part,\n RequestOptions,\n SingleRequestOptions,\n StartChatParams\n} from '../types';\nimport { formatNewContent } from '../requests/request-helpers';\nimport {\n formatBlockErrorMessage,\n getFunctionCalls\n} from '../requests/response-helpers';\nimport { validateChatHistory } from './chat-session-helpers';\nimport { generateContent, generateContentStream } from './generate-content';\nimport { ApiSettings } from '../types/internal';\nimport { logger } from '../logger';\nimport { ChromeAdapter } from '../types/chrome-adapter';\nimport { AIError } from '../errors';\n\n/**\n * Used to break the internal promise chain when an error is already handled\n * by the user, preventing duplicate console logs.\n */\nconst SILENT_ERROR = 'SILENT_ERROR';\n\n/**\n * Prevent infinite loop if the model continues to request sequential\n * function calls during automatic function calling.\n */\nconst DEFAULT_MAX_SEQUENTIAL_FUNCTION_CALLS = 10;\n\n/**\n * ChatSession class that enables sending chat messages and stores\n * history of sent and received messages so far.\n *\n * @public\n */\nexport class ChatSession {\n private _apiSettings: ApiSettings;\n private _history: Content[] = [];\n\n /**\n * Ensures sequential execution of chat messages to maintain history order.\n * Each call waits for the previous one to settle before proceeding.\n */\n private _sendPromise: Promise<void> = Promise.resolve();\n\n constructor(\n apiSettings: ApiSettings,\n public model: string,\n private chromeAdapter?: ChromeAdapter,\n public params?: StartChatParams,\n public requestOptions?: RequestOptions\n ) {\n this._apiSettings = apiSettings;\n if (params?.history) {\n validateChatHistory(params.history);\n this._history = params.history;\n }\n }\n\n /**\n * Gets the chat history so far. Blocked prompts are not added to history.\n * Neither blocked candidates nor the prompts that generated them are added\n * to history.\n */\n async getHistory(): Promise<Content[]> {\n await this._sendPromise;\n return this._history;\n }\n\n /**\n * Format Content into a request for generateContent or\n * generateContentStream.\n * @internal\n */\n _formatRequest(\n incomingContent: Content,\n tempHistory: Content[]\n ): GenerateContentRequest {\n return {\n safetySettings: this.params?.safetySettings,\n generationConfig: this.params?.generationConfig,\n tools: this.params?.tools,\n toolConfig: this.params?.toolConfig,\n systemInstruction: this.params?.systemInstruction,\n contents: [...this._history, ...tempHistory, incomingContent]\n };\n }\n\n /**\n * Sends a chat message and receives a non-streaming\n * {@link GenerateContentResult}\n */\n async sendMessage(\n request: string | Array<string | Part>,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<GenerateContentResult> {\n let finalResult = {} as GenerateContentResult;\n await this._sendPromise;\n /**\n * Temporarily store multiple turns for cases like automatic function\n * calling, only writing them to official history when the entire\n * sequence has completed successfully.\n */\n const tempHistory: Content[] = [];\n\n this._sendPromise = this._sendPromise.then(async () => {\n let functionCalls: FunctionCall[] | undefined;\n let functionCallTurnCount = 0;\n const functionCallMaxTurns =\n this.requestOptions?.maxSequentalFunctionCalls ??\n DEFAULT_MAX_SEQUENTIAL_FUNCTION_CALLS;\n\n // Repeats until model returns a response with no function calls\n // or until `functionCallMaxTurns` is met or exceeded.\n do {\n let formattedContent;\n\n if (functionCalls) {\n functionCallTurnCount++;\n const functionResponseParts = await this._callFunctionsAsNeeded(\n functionCalls\n );\n formattedContent = formatNewContent(functionResponseParts);\n } else {\n formattedContent = formatNewContent(request);\n }\n const formattedRequest = this._formatRequest(\n formattedContent,\n tempHistory\n );\n\n tempHistory.push(formattedContent);\n\n const result = await generateContent(\n this._apiSettings,\n this.model,\n formattedRequest,\n this.chromeAdapter,\n {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n );\n if (result) {\n finalResult = result;\n functionCalls = this._getCallableFunctionCalls(result.response);\n if (\n result.response.candidates &&\n result.response.candidates.length > 0\n ) {\n // TODO: Make this update atomic. If creating `responseContent` throws,\n // history will contain the user message but not the response, causing\n // validation errors on the next request.\n const responseContent: Content = {\n parts: result.response.candidates?.[0].content.parts || [],\n // Response seems to come back without a role set.\n role: result.response.candidates?.[0].content.role || 'model'\n };\n tempHistory.push(responseContent);\n } else {\n const blockErrorMessage = formatBlockErrorMessage(result.response);\n if (blockErrorMessage) {\n logger.warn(\n `sendMessage() was unsuccessful. ${blockErrorMessage}. Inspect response object for details.`\n );\n }\n }\n } else {\n functionCalls = undefined;\n }\n } while (functionCalls && functionCallTurnCount < functionCallMaxTurns);\n\n if (functionCalls && functionCallTurnCount >= functionCallMaxTurns) {\n logger.warn(\n `Automatic function calling exceeded the limit of` +\n ` ${functionCallMaxTurns} function calls. Returning last model response.`\n );\n }\n });\n\n await this._sendPromise;\n this._history = this._history.concat(tempHistory);\n return finalResult;\n }\n\n /**\n * Sends a chat message and receives the response as a\n * {@link GenerateContentStreamResult} containing an iterable stream\n * and a response promise.\n */\n async sendMessageStream(\n request: string | Array<string | Part>,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<GenerateContentStreamResult> {\n await this._sendPromise;\n /**\n * Temporarily store multiple turns for cases like automatic function\n * calling, only writing them to official history when the entire\n * sequence has completed successfully.\n */\n const tempHistory: Content[] = [];\n\n const callGenerateContentStream =\n async (): Promise<GenerateContentStreamResult> => {\n let functionCalls: FunctionCall[] | undefined;\n let functionCallTurnCount = 0;\n const functionCallMaxTurns =\n this.requestOptions?.maxSequentalFunctionCalls ??\n DEFAULT_MAX_SEQUENTIAL_FUNCTION_CALLS;\n let result: GenerateContentStreamResult & {\n firstValue?: GenerateContentResponse;\n };\n\n // Repeats until model returns a response with no function calls\n // or until `functionCallMaxTurns` is met or exceeded.\n do {\n let formattedContent;\n\n if (functionCalls) {\n functionCallTurnCount++;\n const functionResponseParts = await this._callFunctionsAsNeeded(\n functionCalls\n );\n formattedContent = formatNewContent(functionResponseParts);\n } else {\n formattedContent = formatNewContent(request);\n }\n\n tempHistory.push(formattedContent);\n const formattedRequest = this._formatRequest(\n formattedContent,\n tempHistory\n );\n\n result = await generateContentStream(\n this._apiSettings,\n this.model,\n formattedRequest,\n this.chromeAdapter,\n {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n );\n\n functionCalls = this._getCallableFunctionCalls(result.firstValue);\n\n if (\n functionCalls &&\n result.firstValue &&\n result.firstValue.candidates &&\n result.firstValue.candidates.length > 0\n ) {\n const responseContent = {\n ...result.firstValue.candidates[0].content\n };\n if (!responseContent.role) {\n responseContent.role = 'model';\n }\n tempHistory.push(responseContent);\n }\n } while (functionCalls && functionCallTurnCount < functionCallMaxTurns);\n\n if (functionCalls && functionCallTurnCount >= functionCallMaxTurns) {\n logger.warn(\n `Automatic function calling exceeded the limit of` +\n ` ${functionCallMaxTurns} function calls. Returning last model response.`\n );\n }\n return { stream: result.stream, response: result.response };\n };\n\n const streamPromise = callGenerateContentStream();\n\n // Add onto the chain.\n this._sendPromise = this._sendPromise\n .then(async () => streamPromise)\n // This must be handled to avoid unhandled rejection, but jump\n // to the final catch block with a label to not log this error.\n .catch(_ignored => {\n // If the initial fetch fails, the user's `streamPromise` rejects.\n // We swallow the error here to prevent double logging in the final catch.\n throw new Error(SILENT_ERROR);\n })\n .then(streamResult => streamResult.response)\n .then(response => {\n // This runs after the stream completes. Runtime errors here cannot be\n // caught by the user because their promise has likely already resolved.\n // TODO: Move response validation logic upstream to `stream-reader` so\n // errors propagate to the user's `result.response` promise.\n if (response.candidates && response.candidates.length > 0) {\n this._history = this._history.concat(tempHistory);\n // TODO: Validate that `response.candidates[0].content` is not null.\n const responseContent = { ...response.candidates[0].content };\n if (!responseContent.role) {\n responseContent.role = 'model';\n }\n this._history.push(responseContent);\n } else {\n const blockErrorMessage = formatBlockErrorMessage(response);\n if (blockErrorMessage) {\n logger.warn(\n `sendMessageStream() was unsuccessful. ${blockErrorMessage}. Inspect response object for details.`\n );\n }\n }\n })\n .catch(e => {\n // Filter out errors already handled by the user or initiated by them.\n if (e.message !== SILENT_ERROR && e.name !== 'AbortError') {\n logger.error(e);\n }\n });\n return streamPromise;\n }\n\n /**\n * Get function calls that the SDK has references to actually call.\n * This is all-or-nothing. If the model is requesting multiple\n * function calls, all of them must have references in order for\n * automatic function calling to work.\n *\n * @internal\n */\n _getCallableFunctionCalls(\n response?: GenerateContentResponse\n ): FunctionCall[] | undefined {\n const functionDeclarationsTool = this.params?.tools?.find(\n tool => (tool as FunctionDeclarationsTool).functionDeclarations\n ) as FunctionDeclarationsTool;\n if (!functionDeclarationsTool?.functionDeclarations) {\n return;\n }\n const functionCalls = getFunctionCalls(response);\n if (!functionCalls) {\n return;\n }\n for (const functionCall of functionCalls) {\n const hasFunctionReference =\n functionDeclarationsTool.functionDeclarations?.some(\n declaration =>\n declaration.name === functionCall.name &&\n typeof declaration.functionReference === 'function'\n );\n if (!hasFunctionReference) {\n return;\n }\n }\n return functionCalls;\n }\n\n /**\n * Call user-defined functions if requested by the model, and return\n * the response that should be sent to the model.\n * @internal\n */\n async _callFunctionsAsNeeded(\n functionCalls: FunctionCall[]\n ): Promise<FunctionResponsePart[]> {\n const activeCallList = new Map<\n string,\n { id?: string; results: Promise<Record<string, unknown>> }\n >();\n const promiseList = [];\n const functionDeclarationsTool = this.params?.tools?.find(\n tool => (tool as FunctionDeclarationsTool).functionDeclarations\n ) as FunctionDeclarationsTool;\n if (\n functionDeclarationsTool &&\n functionDeclarationsTool.functionDeclarations\n ) {\n for (const functionCall of functionCalls) {\n const functionDeclaration =\n functionDeclarationsTool.functionDeclarations.find(\n declaration => declaration.name === functionCall.name\n );\n if (functionDeclaration?.functionReference) {\n const results = Promise.resolve(\n functionDeclaration.functionReference!(functionCall.args)\n ).catch(e => {\n const wrappedError = new AIError(\n AIErrorCode.ERROR,\n `Error in user-defined function \"${functionDeclaration.name}\": ${\n (e as Error).message\n }`\n );\n wrappedError.stack = (e as Error).stack;\n throw wrappedError;\n });\n activeCallList.set(functionCall.name, {\n id: functionCall.id,\n results\n });\n promiseList.push(results);\n }\n }\n // Wait for promises to finish.\n await Promise.all(promiseList);\n const functionResponseParts = [];\n for (const [name, callData] of activeCallList) {\n functionResponseParts.push({\n functionResponse: {\n name,\n response: await callData.results\n }\n });\n }\n return functionResponseParts;\n } else {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n `No function declarations were provided in \"tools\".`\n );\n }\n }\n}\n","/**\n * @license\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 { AIError } from '../errors';\nimport {\n CountTokensRequest,\n CountTokensResponse,\n SingleRequestOptions,\n InferenceMode,\n RequestOptions,\n AIErrorCode\n} from '../types';\nimport { makeRequest, Task } from '../requests/request';\nimport { ApiSettings } from '../types/internal';\nimport * as GoogleAIMapper from '../googleai-mappers';\nimport { BackendType } from '../public-types';\nimport { ChromeAdapter } from '../types/chrome-adapter';\n\nexport async function countTokensOnCloud(\n apiSettings: ApiSettings,\n model: string,\n params: CountTokensRequest,\n singleRequestOptions?: SingleRequestOptions\n): Promise<CountTokensResponse> {\n let body: string = '';\n if (apiSettings.backend.backendType === BackendType.GOOGLE_AI) {\n const mappedParams = GoogleAIMapper.mapCountTokensRequest(params, model);\n body = JSON.stringify(mappedParams);\n } else {\n body = JSON.stringify(params);\n }\n const response = await makeRequest(\n {\n model,\n task: Task.COUNT_TOKENS,\n apiSettings,\n stream: false,\n singleRequestOptions\n },\n body\n );\n return response.json();\n}\n\nexport async function countTokens(\n apiSettings: ApiSettings,\n model: string,\n params: CountTokensRequest,\n chromeAdapter?: ChromeAdapter,\n requestOptions?: RequestOptions\n): Promise<CountTokensResponse> {\n if (chromeAdapter?.mode === InferenceMode.ONLY_ON_DEVICE) {\n throw new AIError(\n AIErrorCode.UNSUPPORTED,\n 'countTokens() is not supported for on-device models.'\n );\n }\n return countTokensOnCloud(apiSettings, model, params, requestOptions);\n}\n","/**\n * @license\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 generateContent,\n generateContentStream\n} from '../methods/generate-content';\nimport {\n Content,\n CountTokensRequest,\n CountTokensResponse,\n GenerateContentRequest,\n GenerateContentResult,\n GenerateContentStreamResult,\n GenerationConfig,\n ModelParams,\n Part,\n SafetySetting,\n RequestOptions,\n StartChatParams,\n Tool,\n ToolConfig,\n SingleRequestOptions\n} from '../types';\nimport { ChatSession } from '../methods/chat-session';\nimport { countTokens } from '../methods/count-tokens';\nimport {\n formatGenerateContentInput,\n formatSystemInstruction\n} from '../requests/request-helpers';\nimport { AI, AIErrorCode } from '../public-types';\nimport { AIModel } from './ai-model';\nimport { ChromeAdapter } from '../types/chrome-adapter';\nimport { AIError } from '../errors';\n\n/**\n * Class for generative model APIs.\n * @public\n */\nexport class GenerativeModel extends AIModel {\n generationConfig: GenerationConfig;\n safetySettings: SafetySetting[];\n requestOptions?: RequestOptions;\n tools?: Tool[];\n toolConfig?: ToolConfig;\n systemInstruction?: Content;\n\n constructor(\n ai: AI,\n modelParams: ModelParams,\n requestOptions?: RequestOptions,\n private chromeAdapter?: ChromeAdapter\n ) {\n super(ai, modelParams.model);\n this.generationConfig = modelParams.generationConfig || {};\n validateGenerationConfig(this.generationConfig);\n this.safetySettings = modelParams.safetySettings || [];\n this.tools = modelParams.tools;\n this.toolConfig = modelParams.toolConfig;\n this.systemInstruction = formatSystemInstruction(\n modelParams.systemInstruction\n );\n this.requestOptions = requestOptions || {};\n }\n\n /**\n * Makes a single non-streaming call to the model\n * and returns an object containing a single {@link GenerateContentResponse}.\n */\n async generateContent(\n request: GenerateContentRequest | string | Array<string | Part>,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<GenerateContentResult> {\n const formattedParams = formatGenerateContentInput(request);\n return generateContent(\n this._apiSettings,\n this.model,\n {\n generationConfig: this.generationConfig,\n safetySettings: this.safetySettings,\n tools: this.tools,\n toolConfig: this.toolConfig,\n systemInstruction: this.systemInstruction,\n ...formattedParams\n },\n this.chromeAdapter,\n // Merge request options\n {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n );\n }\n\n /**\n * Makes a single streaming call to the model\n * and returns an object containing an iterable stream that iterates\n * over all chunks in the streaming response as well as\n * a promise that returns the final aggregated response.\n */\n async generateContentStream(\n request: GenerateContentRequest | string | Array<string | Part>,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<GenerateContentStreamResult> {\n const formattedParams = formatGenerateContentInput(request);\n const { stream, response } = await generateContentStream(\n this._apiSettings,\n this.model,\n {\n generationConfig: this.generationConfig,\n safetySettings: this.safetySettings,\n tools: this.tools,\n toolConfig: this.toolConfig,\n systemInstruction: this.systemInstruction,\n ...formattedParams\n },\n this.chromeAdapter,\n // Merge request options\n {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n );\n return { stream, response };\n }\n\n /**\n * Gets a new {@link ChatSession} instance which can be used for\n * multi-turn chats.\n */\n startChat(startChatParams?: StartChatParams): ChatSession {\n return new ChatSession(\n this._apiSettings,\n this.model,\n this.chromeAdapter,\n {\n tools: this.tools,\n toolConfig: this.toolConfig,\n systemInstruction: this.systemInstruction,\n generationConfig: this.generationConfig,\n safetySettings: this.safetySettings,\n /**\n * Overrides params inherited from GenerativeModel with those explicitly set in the\n * StartChatParams. For example, if startChatParams.generationConfig is set, it'll override\n * this.generationConfig.\n */\n ...startChatParams\n },\n this.requestOptions\n );\n }\n\n /**\n * Counts the tokens in the provided request.\n */\n async countTokens(\n request: CountTokensRequest | string | Array<string | Part>,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<CountTokensResponse> {\n const formattedParams = formatGenerateContentInput(request);\n return countTokens(\n this._apiSettings,\n this.model,\n formattedParams,\n this.chromeAdapter,\n // Merge request options\n {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n );\n }\n}\n\n/**\n * Client-side validation of some common `GenerationConfig` pitfalls, in order\n * to save the developer a wasted request.\n */\nfunction validateGenerationConfig(generationConfig: GenerationConfig): void {\n if (\n // != allows for null and undefined. 0 is considered \"set\" by the model\n generationConfig.thinkingConfig?.thinkingBudget != null &&\n generationConfig.thinkingConfig?.thinkingLevel\n ) {\n throw new AIError(\n AIErrorCode.UNSUPPORTED,\n `Cannot set both thinkingBudget and thinkingLevel in a config.`\n );\n }\n}\n","/**\n * @license\n * Copyright 2025 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 AIErrorCode,\n FunctionResponse,\n GenerativeContentBlob,\n LiveResponseType,\n LiveServerContent,\n LiveServerGoingAwayNotice,\n LiveServerToolCall,\n LiveServerToolCallCancellation,\n Part\n} from '../public-types';\nimport { formatNewContent } from '../requests/request-helpers';\nimport { AIError } from '../errors';\nimport { WebSocketHandler } from '../websocket';\nimport { logger } from '../logger';\nimport {\n _LiveClientContent,\n _LiveClientRealtimeInput,\n _LiveClientToolResponse\n} from '../types/live-responses';\n\n/**\n * Represents an active, real-time, bidirectional conversation with the model.\n *\n * This class should only be instantiated by calling {@link LiveGenerativeModel.connect}.\n *\n * @beta\n */\nexport class LiveSession {\n /**\n * Indicates whether this Live session is closed.\n *\n * @beta\n */\n isClosed = false;\n /**\n * Indicates whether this Live session is being controlled by an `AudioConversationController`.\n *\n * @beta\n */\n inConversation = false;\n\n /**\n * @internal\n */\n constructor(\n private webSocketHandler: WebSocketHandler,\n private serverMessages: AsyncGenerator<unknown>\n ) {}\n\n /**\n * Sends content to the server.\n *\n * @param request - The message to send to the model.\n * @param turnComplete - Indicates if the turn is complete. Defaults to false.\n * @throws If this session has been closed.\n *\n * @beta\n */\n async send(\n request: string | Array<string | Part>,\n turnComplete = true\n ): Promise<void> {\n if (this.isClosed) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'This LiveSession has been closed and cannot be used.'\n );\n }\n\n const newContent = formatNewContent(request);\n\n const message: _LiveClientContent = {\n clientContent: {\n turns: [newContent],\n turnComplete\n }\n };\n this.webSocketHandler.send(JSON.stringify(message));\n }\n\n /**\n * Sends text to the server in realtime.\n *\n * @example\n * ```javascript\n * liveSession.sendTextRealtime(\"Hello, how are you?\");\n * ```\n *\n * @param text - The text data to send.\n * @throws If this session has been closed.\n *\n * @beta\n */\n async sendTextRealtime(text: string): Promise<void> {\n if (this.isClosed) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'This LiveSession has been closed and cannot be used.'\n );\n }\n\n const message: _LiveClientRealtimeInput = {\n realtimeInput: {\n text\n }\n };\n this.webSocketHandler.send(JSON.stringify(message));\n }\n\n /**\n * Sends audio data to the server in realtime.\n *\n * @remarks The server requires that the audio data is base64-encoded 16-bit PCM at 16kHz\n * little-endian.\n *\n * @example\n * ```javascript\n * // const pcmData = ... base64-encoded 16-bit PCM at 16kHz little-endian.\n * const blob = { mimeType: \"audio/pcm\", data: pcmData };\n * liveSession.sendAudioRealtime(blob);\n * ```\n *\n * @param blob - The base64-encoded PCM data to send to the server in realtime.\n * @throws If this session has been closed.\n *\n * @beta\n */\n async sendAudioRealtime(blob: GenerativeContentBlob): Promise<void> {\n if (this.isClosed) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'This LiveSession has been closed and cannot be used.'\n );\n }\n\n const message: _LiveClientRealtimeInput = {\n realtimeInput: {\n audio: blob\n }\n };\n this.webSocketHandler.send(JSON.stringify(message));\n }\n\n /**\n * Sends video data to the server in realtime.\n *\n * @remarks The server requires that the video is sent as individual video frames at 1 FPS. It\n * is recommended to set `mimeType` to `image/jpeg`.\n *\n * @example\n * ```javascript\n * // const videoFrame = ... base64-encoded JPEG data\n * const blob = { mimeType: \"image/jpeg\", data: videoFrame };\n * liveSession.sendVideoRealtime(blob);\n * ```\n * @param blob - The base64-encoded video data to send to the server in realtime.\n * @throws If this session has been closed.\n *\n * @beta\n */\n async sendVideoRealtime(blob: GenerativeContentBlob): Promise<void> {\n if (this.isClosed) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'This LiveSession has been closed and cannot be used.'\n );\n }\n\n const message: _LiveClientRealtimeInput = {\n realtimeInput: {\n video: blob\n }\n };\n this.webSocketHandler.send(JSON.stringify(message));\n }\n\n /**\n * Sends function responses to the server.\n *\n * @param functionResponses - The function responses to send.\n * @throws If this session has been closed.\n *\n * @beta\n */\n async sendFunctionResponses(\n functionResponses: FunctionResponse[]\n ): Promise<void> {\n if (this.isClosed) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'This LiveSession has been closed and cannot be used.'\n );\n }\n\n const message: _LiveClientToolResponse = {\n toolResponse: {\n functionResponses\n }\n };\n this.webSocketHandler.send(JSON.stringify(message));\n }\n\n /**\n * Yields messages received from the server.\n * This can only be used by one consumer at a time.\n *\n * @returns An `AsyncGenerator` that yields server messages as they arrive.\n * @throws If the session is already closed, or if we receive a response that we don't support.\n *\n * @beta\n */\n async *receive(): AsyncGenerator<\n | LiveServerContent\n | LiveServerToolCall\n | LiveServerToolCallCancellation\n | LiveServerGoingAwayNotice\n > {\n if (this.isClosed) {\n throw new AIError(\n AIErrorCode.SESSION_CLOSED,\n 'Cannot read from a Live session that is closed. Try starting a new Live session.'\n );\n }\n for await (const message of this.serverMessages) {\n if (message && typeof message === 'object') {\n if (LiveResponseType.SERVER_CONTENT in message) {\n yield {\n type: 'serverContent',\n ...(message as { serverContent: Omit<LiveServerContent, 'type'> })\n .serverContent\n } as LiveServerContent;\n } else if (LiveResponseType.TOOL_CALL in message) {\n yield {\n type: 'toolCall',\n ...(message as { toolCall: Omit<LiveServerToolCall, 'type'> })\n .toolCall\n } as LiveServerToolCall;\n } else if (LiveResponseType.TOOL_CALL_CANCELLATION in message) {\n yield {\n type: 'toolCallCancellation',\n ...(\n message as {\n toolCallCancellation: Omit<\n LiveServerToolCallCancellation,\n 'type'\n >;\n }\n ).toolCallCancellation\n } as LiveServerToolCallCancellation;\n } else if ('goAway' in message) {\n const notice = (\n message as {\n goAway: { timeLeft: string };\n }\n ).goAway;\n yield {\n type: LiveResponseType.GOING_AWAY_NOTICE,\n timeLeft: parseDuration(notice.timeLeft)\n } as LiveServerGoingAwayNotice;\n } else {\n logger.warn(\n `Received an unknown message type from the server: ${JSON.stringify(\n message\n )}`\n );\n }\n } else {\n logger.warn(\n `Received an invalid message from the server: ${JSON.stringify(\n message\n )}`\n );\n }\n }\n }\n\n /**\n * Closes this session.\n * All methods on this session will throw an error once this resolves.\n *\n * @beta\n */\n async close(): Promise<void> {\n if (!this.isClosed) {\n this.isClosed = true;\n await this.webSocketHandler.close(1000, 'Client closed session.');\n }\n }\n\n /**\n * Sends realtime input to the server.\n *\n * @deprecated Use `sendTextRealtime()`, `sendAudioRealtime()`, and `sendVideoRealtime()` instead.\n *\n * @param mediaChunks - The media chunks to send.\n * @throws If this session has been closed.\n *\n * @beta\n */\n async sendMediaChunks(mediaChunks: GenerativeContentBlob[]): Promise<void> {\n if (this.isClosed) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'This LiveSession has been closed and cannot be used.'\n );\n }\n\n // The backend does not support sending more than one mediaChunk in one message.\n // Work around this limitation by sending mediaChunks in separate messages.\n mediaChunks.forEach(mediaChunk => {\n const message: _LiveClientRealtimeInput = {\n realtimeInput: { mediaChunks: [mediaChunk] }\n };\n this.webSocketHandler.send(JSON.stringify(message));\n });\n }\n\n /**\n * @deprecated Use `sendTextRealtime()`, `sendAudioRealtime()`, and `sendVideoRealtime()` instead.\n *\n * Sends a stream of {@link GenerativeContentBlob}.\n *\n * @param mediaChunkStream - The stream of {@link GenerativeContentBlob} to send.\n * @throws If this session has been closed.\n *\n * @beta\n */\n async sendMediaStream(\n mediaChunkStream: ReadableStream<GenerativeContentBlob>\n ): Promise<void> {\n if (this.isClosed) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'This LiveSession has been closed and cannot be used.'\n );\n }\n\n const reader = mediaChunkStream.getReader();\n while (true) {\n try {\n const { done, value } = await reader.read();\n\n if (done) {\n break;\n } else if (!value) {\n throw new Error('Missing chunk in reader, but reader is not done.');\n }\n\n await this.sendMediaChunks([value]);\n } catch (e) {\n // Re-throw any errors that occur during stream consumption or sending.\n const message =\n e instanceof Error ? e.message : 'Error processing media stream.';\n throw new AIError(AIErrorCode.REQUEST_ERROR, message);\n }\n }\n }\n}\n\n/**\n * Parses a duration string (e.g. \"3.000000001s\") into a number of seconds.\n *\n * @param duration - The duration string to parse.\n * @returns The duration in seconds.\n */\nfunction parseDuration(duration: string | undefined): number {\n if (!duration || !duration.endsWith('s')) {\n return 0;\n }\n return Number(duration.slice(0, -1)); // slice removes the trailing 's'.\n}\n","/**\n * @license\n * Copyright 2025 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 { AIModel } from './ai-model';\nimport { LiveSession } from '../methods/live-session';\nimport { AIError } from '../errors';\nimport {\n AI,\n AIErrorCode,\n BackendType,\n Content,\n LiveGenerationConfig,\n LiveModelParams,\n Tool,\n ToolConfig\n} from '../public-types';\nimport { WebSocketHandler } from '../websocket';\nimport { WebSocketUrl } from '../requests/request';\nimport { formatSystemInstruction } from '../requests/request-helpers';\nimport { _LiveClientSetup } from '../types/live-responses';\n\n/**\n * Class for Live generative model APIs. The Live API enables low-latency, two-way multimodal\n * interactions with Gemini.\n *\n * This class should only be instantiated with {@link getLiveGenerativeModel}.\n *\n * @beta\n */\nexport class LiveGenerativeModel extends AIModel {\n generationConfig: LiveGenerationConfig;\n tools?: Tool[];\n toolConfig?: ToolConfig;\n systemInstruction?: Content;\n\n /**\n * @internal\n */\n constructor(\n ai: AI,\n modelParams: LiveModelParams,\n /**\n * @internal\n */\n private _webSocketHandler: WebSocketHandler\n ) {\n super(ai, modelParams.model);\n this.generationConfig = modelParams.generationConfig || {};\n this.tools = modelParams.tools;\n this.toolConfig = modelParams.toolConfig;\n this.systemInstruction = formatSystemInstruction(\n modelParams.systemInstruction\n );\n }\n\n /**\n * Starts a {@link LiveSession}.\n *\n * @returns A {@link LiveSession}.\n * @throws If the connection failed to be established with the server.\n *\n * @beta\n */\n async connect(): Promise<LiveSession> {\n const url = new WebSocketUrl(this._apiSettings);\n await this._webSocketHandler.connect(url.toString());\n\n let fullModelPath: string;\n if (this._apiSettings.backend.backendType === BackendType.GOOGLE_AI) {\n fullModelPath = `projects/${this._apiSettings.project}/${this.model}`;\n } else {\n fullModelPath = `projects/${this._apiSettings.project}/locations/${this._apiSettings.location}/${this.model}`;\n }\n\n // inputAudioTranscription and outputAudioTranscription are on the generation config in the public API,\n // but the backend expects them to be in the `setup` message.\n const {\n inputAudioTranscription,\n outputAudioTranscription,\n ...generationConfig\n } = this.generationConfig;\n\n const setupMessage: _LiveClientSetup = {\n setup: {\n model: fullModelPath,\n generationConfig,\n tools: this.tools,\n toolConfig: this.toolConfig,\n systemInstruction: this.systemInstruction,\n inputAudioTranscription,\n outputAudioTranscription\n }\n };\n\n try {\n // Begin listening for server messages, and begin the handshake by sending the 'setupMessage'\n const serverMessages = this._webSocketHandler.listen();\n this._webSocketHandler.send(JSON.stringify(setupMessage));\n\n // Verify we received the handshake response 'setupComplete'\n const firstMessage = (await serverMessages.next()).value;\n if (\n !firstMessage ||\n !(typeof firstMessage === 'object') ||\n !('setupComplete' in firstMessage)\n ) {\n await this._webSocketHandler.close(1011, 'Handshake failure');\n throw new AIError(\n AIErrorCode.RESPONSE_ERROR,\n 'Server connection handshake failed. The server did not respond with a setupComplete message.'\n );\n }\n\n return new LiveSession(this._webSocketHandler, serverMessages);\n } catch (e) {\n // Ensure connection is closed on any setup error\n await this._webSocketHandler.close();\n throw e;\n }\n }\n}\n","/**\n * @license\n * Copyright 2025 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 { AI } from '../public-types';\nimport { makeRequest, Task } from '../requests/request';\nimport { createPredictRequestBody } from '../requests/request-helpers';\nimport { handlePredictResponse } from '../requests/response-helpers';\nimport {\n ImagenGCSImage,\n ImagenGenerationConfig,\n ImagenInlineImage,\n RequestOptions,\n ImagenModelParams,\n ImagenGenerationResponse,\n ImagenSafetySettings,\n SingleRequestOptions\n} from '../types';\nimport { AIModel } from './ai-model';\n\n/**\n * Class for Imagen model APIs.\n *\n * This class provides methods for generating images using the Imagen model.\n *\n * @example\n * ```javascript\n * const imagen = new ImagenModel(\n * ai,\n * {\n * model: 'imagen-3.0-generate-002'\n * }\n * );\n *\n * const response = await imagen.generateImages('A photo of a cat');\n * if (response.images.length > 0) {\n * console.log(response.images[0].bytesBase64Encoded);\n * }\n * ```\n *\n * @public\n */\nexport class ImagenModel extends AIModel {\n /**\n * The Imagen generation configuration.\n */\n generationConfig?: ImagenGenerationConfig;\n /**\n * Safety settings for filtering inappropriate content.\n */\n safetySettings?: ImagenSafetySettings;\n\n /**\n * Constructs a new instance of the {@link ImagenModel} class.\n *\n * @param ai - an {@link AI} instance.\n * @param modelParams - Parameters to use when making requests to Imagen.\n * @param requestOptions - Additional options to use when making requests.\n *\n * @throws If the `apiKey` or `projectId` fields are missing in your\n * Firebase config.\n */\n constructor(\n ai: AI,\n modelParams: ImagenModelParams,\n public requestOptions?: RequestOptions\n ) {\n const { model, generationConfig, safetySettings } = modelParams;\n super(ai, model);\n this.generationConfig = generationConfig;\n this.safetySettings = safetySettings;\n }\n\n /**\n * Generates images using the Imagen model and returns them as\n * base64-encoded strings.\n *\n * @param prompt - A text prompt describing the image(s) to generate.\n * @returns A promise that resolves to an {@link ImagenGenerationResponse}\n * object containing the generated images.\n *\n * @throws If the request to generate images fails. This happens if the\n * prompt is blocked.\n *\n * @remarks\n * If the prompt was not blocked, but one or more of the generated images were filtered, the\n * returned object will have a `filteredReason` property.\n * If all images are filtered, the `images` array will be empty.\n *\n * @public\n */\n async generateImages(\n prompt: string,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<ImagenGenerationResponse<ImagenInlineImage>> {\n const body = createPredictRequestBody(prompt, {\n ...this.generationConfig,\n ...this.safetySettings\n });\n const response = await makeRequest(\n {\n task: Task.PREDICT,\n model: this.model,\n apiSettings: this._apiSettings,\n stream: false,\n // Merge request options. Single request options overwrite the model's request options.\n singleRequestOptions: {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n },\n JSON.stringify(body)\n );\n return handlePredictResponse<ImagenInlineImage>(response);\n }\n\n /**\n * Generates images to Cloud Storage for Firebase using the Imagen model.\n *\n * @internal This method is temporarily internal.\n *\n * @param prompt - A text prompt describing the image(s) to generate.\n * @param gcsURI - The URI of file stored in a Cloud Storage for Firebase bucket.\n * This should be a directory. For example, `gs://my-bucket/my-directory/`.\n * @returns A promise that resolves to an {@link ImagenGenerationResponse}\n * object containing the URLs of the generated images.\n *\n * @throws If the request fails to generate images fails. This happens if\n * the prompt is blocked.\n *\n * @remarks\n * If the prompt was not blocked, but one or more of the generated images were filtered, the\n * returned object will have a `filteredReason` property.\n * If all images are filtered, the `images` array will be empty.\n */\n async generateImagesGCS(\n prompt: string,\n gcsURI: string,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<ImagenGenerationResponse<ImagenGCSImage>> {\n const body = createPredictRequestBody(prompt, {\n gcsURI,\n ...this.generationConfig,\n ...this.safetySettings\n });\n const response = await makeRequest(\n {\n task: Task.PREDICT,\n model: this.model,\n apiSettings: this._apiSettings,\n stream: false,\n // Merge request options. Single request options overwrite the model's request options.\n singleRequestOptions: {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n },\n JSON.stringify(body)\n );\n return handlePredictResponse<ImagenGCSImage>(response);\n }\n}\n","/**\n * @license\n * Copyright 2025 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 { AIError } from './errors';\nimport { logger } from './logger';\nimport { AIErrorCode } from './types';\n\n/**\n * A standardized interface for interacting with a WebSocket connection.\n * This abstraction allows the SDK to use the appropriate WebSocket implementation\n * for the current JS environment (Browser vs. Node) without\n * changing the core logic of the `LiveSession`.\n * @internal\n */\n\nexport interface WebSocketHandler {\n /**\n * Establishes a connection to the given URL.\n *\n * @param url The WebSocket URL (e.g., wss://...).\n * @returns A promise that resolves on successful connection or rejects on failure.\n */\n connect(url: string): Promise<void>;\n\n /**\n * Sends data over the WebSocket.\n *\n * @param data The string or binary data to send.\n */\n send(data: string | ArrayBuffer): void;\n\n /**\n * Returns an async generator that yields parsed JSON objects from the server.\n * The yielded type is `unknown` because the handler cannot guarantee the shape of the data.\n * The consumer is responsible for type validation.\n * The generator terminates when the connection is closed.\n *\n * @returns A generator that allows consumers to pull messages using a `for await...of` loop.\n */\n listen(): AsyncGenerator<unknown>;\n\n /**\n * Closes the WebSocket connection.\n *\n * @param code - A numeric status code explaining why the connection is closing.\n * @param reason - A human-readable string explaining why the connection is closing.\n */\n close(code?: number, reason?: string): Promise<void>;\n}\n\n/**\n * A wrapper for the native `WebSocket` available in both Browsers and Node >= 22.\n *\n * @internal\n */\nexport class WebSocketHandlerImpl implements WebSocketHandler {\n private ws?: WebSocket;\n\n constructor() {\n if (typeof WebSocket === 'undefined') {\n throw new AIError(\n AIErrorCode.UNSUPPORTED,\n 'The WebSocket API is not available in this environment. ' +\n 'The \"Live\" feature is not supported here. It is supported in ' +\n 'modern browser windows, Web Workers with WebSocket support, and Node >= 22.'\n );\n }\n }\n\n connect(url: string): Promise<void> {\n return new Promise((resolve, reject) => {\n this.ws = new WebSocket(url);\n this.ws.binaryType = 'blob'; // Only important to set in Node\n this.ws.addEventListener('open', () => resolve(), { once: true });\n this.ws.addEventListener(\n 'error',\n () =>\n reject(\n new AIError(\n AIErrorCode.FETCH_ERROR,\n `Error event raised on WebSocket`\n )\n ),\n { once: true }\n );\n this.ws!.addEventListener('close', (closeEvent: CloseEvent) => {\n if (closeEvent.reason) {\n logger.warn(\n `WebSocket connection closed by server. Reason: '${closeEvent.reason}'`\n );\n }\n });\n });\n }\n\n send(data: string | ArrayBuffer): void {\n if (!this.ws || this.ws.readyState !== WebSocket.OPEN) {\n throw new AIError(AIErrorCode.REQUEST_ERROR, 'WebSocket is not open.');\n }\n this.ws.send(data);\n }\n\n async *listen(): AsyncGenerator<unknown> {\n if (!this.ws) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'WebSocket is not connected.'\n );\n }\n\n const messageQueue: unknown[] = [];\n const errorQueue: Error[] = [];\n let resolvePromise: (() => void) | null = null;\n let isClosed = false;\n\n const messageListener = async (event: MessageEvent): Promise<void> => {\n let data: string;\n if (event.data instanceof Blob) {\n data = await event.data.text();\n } else if (typeof event.data === 'string') {\n data = event.data;\n } else {\n errorQueue.push(\n new AIError(\n AIErrorCode.PARSE_FAILED,\n `Failed to parse WebSocket response. Expected data to be a Blob or string, but was ${typeof event.data}.`\n )\n );\n if (resolvePromise) {\n resolvePromise();\n resolvePromise = null;\n }\n return;\n }\n\n try {\n const obj = JSON.parse(data) as unknown;\n messageQueue.push(obj);\n } catch (e) {\n const err = e as Error;\n errorQueue.push(\n new AIError(\n AIErrorCode.PARSE_FAILED,\n `Error parsing WebSocket message to JSON: ${err.message}`\n )\n );\n }\n\n if (resolvePromise) {\n resolvePromise();\n resolvePromise = null;\n }\n };\n\n const errorListener = (): void => {\n errorQueue.push(\n new AIError(AIErrorCode.FETCH_ERROR, 'WebSocket connection error.')\n );\n if (resolvePromise) {\n resolvePromise();\n resolvePromise = null;\n }\n };\n\n const closeListener = (event: CloseEvent): void => {\n if (event.reason) {\n logger.warn(\n `WebSocket connection closed by the server with reason: ${event.reason}`\n );\n }\n isClosed = true;\n if (resolvePromise) {\n resolvePromise();\n resolvePromise = null;\n }\n // Clean up listeners to prevent memory leaks\n this.ws?.removeEventListener('message', messageListener);\n this.ws?.removeEventListener('close', closeListener);\n this.ws?.removeEventListener('error', errorListener);\n };\n\n this.ws.addEventListener('message', messageListener);\n this.ws.addEventListener('close', closeListener);\n this.ws.addEventListener('error', errorListener);\n\n while (!isClosed) {\n if (errorQueue.length > 0) {\n const error = errorQueue.shift()!;\n throw error;\n }\n if (messageQueue.length > 0) {\n yield messageQueue.shift()!;\n } else {\n await new Promise<void>(resolve => {\n resolvePromise = resolve;\n });\n }\n }\n\n // If the loop terminated because isClosed is true, check for any final errors\n if (errorQueue.length > 0) {\n const error = errorQueue.shift()!;\n throw error;\n }\n }\n\n close(code?: number, reason?: string): Promise<void> {\n return new Promise(resolve => {\n if (!this.ws) {\n return resolve();\n }\n\n this.ws.addEventListener('close', () => resolve(), { once: true });\n // Calling 'close' during these states results in an error.\n if (\n this.ws.readyState === WebSocket.CLOSED ||\n this.ws.readyState === WebSocket.CONNECTING\n ) {\n return resolve();\n }\n\n if (this.ws.readyState !== WebSocket.CLOSING) {\n this.ws.close(code, reason);\n }\n });\n }\n}\n","/**\n * @license\n * Copyright 2025 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 templateGenerateContent,\n templateGenerateContentStream\n} from '../methods/generate-content';\nimport { GenerateContentResult, RequestOptions } from '../types';\nimport {\n AI,\n GenerateContentStreamResult,\n SingleRequestOptions\n} from '../public-types';\nimport { ApiSettings } from '../types/internal';\nimport { initApiSettings } from './utils';\n\n/**\n * {@link GenerativeModel} APIs that execute on a server-side template.\n *\n * This class should only be instantiated with {@link getTemplateGenerativeModel}.\n *\n * @beta\n */\nexport class TemplateGenerativeModel {\n /**\n * @internal\n */\n _apiSettings: ApiSettings;\n\n /**\n * Additional options to use when making requests.\n */\n requestOptions?: RequestOptions;\n\n /**\n * @hideconstructor\n */\n constructor(ai: AI, requestOptions?: RequestOptions) {\n this.requestOptions = requestOptions || {};\n this._apiSettings = initApiSettings(ai);\n }\n\n /**\n * Makes a single non-streaming call to the model and returns an object\n * containing a single {@link GenerateContentResponse}.\n *\n * @param templateId - The ID of the server-side template to execute.\n * @param templateVariables - A key-value map of variables to populate the\n * template with.\n *\n * @beta\n */\n async generateContent(\n templateId: string,\n templateVariables: object,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<GenerateContentResult> {\n return templateGenerateContent(\n this._apiSettings,\n templateId,\n { inputs: templateVariables },\n {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n );\n }\n\n /**\n * Makes a single streaming call to the model and returns an object\n * containing an iterable stream that iterates over all chunks in the\n * streaming response as well as a promise that returns the final aggregated\n * response.\n *\n * @param templateId - The ID of the server-side template to execute.\n * @param templateVariables - A key-value map of variables to populate the\n * template with.\n *\n * @beta\n */\n async generateContentStream(\n templateId: string,\n templateVariables: object,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<GenerateContentStreamResult> {\n return templateGenerateContentStream(\n this._apiSettings,\n templateId,\n { inputs: templateVariables },\n {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n );\n }\n}\n","/**\n * @license\n * Copyright 2025 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 { RequestOptions } from '../types';\nimport {\n AI,\n ImagenGenerationResponse,\n ImagenInlineImage,\n SingleRequestOptions\n} from '../public-types';\nimport { ApiSettings } from '../types/internal';\nimport { makeRequest, ServerPromptTemplateTask } from '../requests/request';\nimport { handlePredictResponse } from '../requests/response-helpers';\nimport { initApiSettings } from './utils';\n\n/**\n * Class for Imagen model APIs that execute on a server-side template.\n *\n * This class should only be instantiated with {@link getTemplateImagenModel}.\n *\n * @beta\n */\nexport class TemplateImagenModel {\n /**\n * @internal\n */\n _apiSettings: ApiSettings;\n\n /**\n * Additional options to use when making requests.\n */\n requestOptions?: RequestOptions;\n\n /**\n * @hideconstructor\n */\n constructor(ai: AI, requestOptions?: RequestOptions) {\n this.requestOptions = requestOptions || {};\n this._apiSettings = initApiSettings(ai);\n }\n\n /**\n * Makes a single call to the model and returns an object containing a single\n * {@link ImagenGenerationResponse}.\n *\n * @param templateId - The ID of the server-side template to execute.\n * @param templateVariables - A key-value map of variables to populate the\n * template with.\n *\n * @beta\n */\n async generateImages(\n templateId: string,\n templateVariables: object,\n singleRequestOptions?: SingleRequestOptions\n ): Promise<ImagenGenerationResponse<ImagenInlineImage>> {\n const response = await makeRequest(\n {\n task: ServerPromptTemplateTask.TEMPLATE_PREDICT,\n templateId,\n apiSettings: this._apiSettings,\n stream: false,\n singleRequestOptions: {\n ...this.requestOptions,\n ...singleRequestOptions\n }\n },\n JSON.stringify({ inputs: templateVariables })\n );\n return handlePredictResponse<ImagenInlineImage>(response);\n }\n}\n","/**\n * @license\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 { AIError } from '../errors';\nimport { AIErrorCode } from '../types';\nimport {\n SchemaInterface,\n SchemaType,\n SchemaParams,\n SchemaRequest\n} from '../types/schema';\n\n/**\n * Parent class encompassing all Schema types, with static methods that\n * allow building specific Schema types. This class can be converted with\n * `JSON.stringify()` into a JSON string accepted by Vertex AI REST endpoints.\n * (This string conversion is automatically done when calling SDK methods.)\n * @public\n */\nexport abstract class Schema implements SchemaInterface {\n /**\n * Optional. The type of the property.\n * This can only be undefined when using `anyOf` schemas, which do not have an\n * explicit type in the {@link https://swagger.io/docs/specification/v3_0/data-models/data-types/#any-type | OpenAPI specification}.\n */\n type?: SchemaType;\n /** Optional. The format of the property.\n * Supported formats:<br/>\n * <ul>\n * <li>for NUMBER type: \"float\", \"double\"</li>\n * <li>for INTEGER type: \"int32\", \"int64\"</li>\n * <li>for STRING type: \"email\", \"byte\", etc</li>\n * </ul>\n */\n format?: string;\n /** Optional. The description of the property. */\n description?: string;\n /** Optional. The items of the property. */\n items?: SchemaInterface;\n /** The minimum number of items (elements) in a schema of {@link (SchemaType:type)} `array`. */\n minItems?: number;\n /** The maximum number of items (elements) in a schema of {@link (SchemaType:type)} `array`. */\n maxItems?: number;\n /** Optional. Whether the property is nullable. Defaults to false. */\n nullable: boolean;\n /** Optional. The example of the property. */\n example?: unknown;\n /**\n * Allows user to add other schema properties that have not yet\n * been officially added to the SDK.\n */\n [key: string]: unknown;\n\n constructor(schemaParams: SchemaInterface) {\n // TODO(dlarocque): Enforce this with union types\n if (!schemaParams.type && !schemaParams.anyOf) {\n throw new AIError(\n AIErrorCode.INVALID_SCHEMA,\n \"A schema must have either a 'type' or an 'anyOf' array of sub-schemas.\"\n );\n }\n // eslint-disable-next-line guard-for-in\n for (const paramKey in schemaParams) {\n this[paramKey] = schemaParams[paramKey];\n }\n // Ensure these are explicitly set to avoid TS errors.\n this.type = schemaParams.type;\n this.format = schemaParams.hasOwnProperty('format')\n ? schemaParams.format\n : undefined;\n this.nullable = schemaParams.hasOwnProperty('nullable')\n ? !!schemaParams.nullable\n : false;\n }\n\n /**\n * Defines how this Schema should be serialized as JSON.\n * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/JSON/stringify#tojson_behavior\n * @internal\n */\n toJSON(): SchemaRequest {\n const obj: { type?: SchemaType; [key: string]: unknown } = {\n type: this.type\n };\n for (const prop in this) {\n if (this.hasOwnProperty(prop) && this[prop] !== undefined) {\n if (prop !== 'required' || this.type === SchemaType.OBJECT) {\n obj[prop] = this[prop];\n }\n }\n }\n return obj as SchemaRequest;\n }\n\n static array(arrayParams: SchemaParams & { items: Schema }): ArraySchema {\n return new ArraySchema(arrayParams, arrayParams.items);\n }\n\n static object(\n objectParams: SchemaParams & {\n properties: {\n [k: string]: Schema;\n };\n optionalProperties?: string[];\n }\n ): ObjectSchema {\n return new ObjectSchema(\n objectParams,\n objectParams.properties,\n objectParams.optionalProperties\n );\n }\n\n // eslint-disable-next-line id-blacklist\n static string(stringParams?: SchemaParams): StringSchema {\n return new StringSchema(stringParams);\n }\n\n static enumString(\n stringParams: SchemaParams & { enum: string[] }\n ): StringSchema {\n return new StringSchema(stringParams, stringParams.enum);\n }\n\n static integer(integerParams?: SchemaParams): IntegerSchema {\n return new IntegerSchema(integerParams);\n }\n\n // eslint-disable-next-line id-blacklist\n static number(numberParams?: SchemaParams): NumberSchema {\n return new NumberSchema(numberParams);\n }\n\n // eslint-disable-next-line id-blacklist\n static boolean(booleanParams?: SchemaParams): BooleanSchema {\n return new BooleanSchema(booleanParams);\n }\n\n static anyOf(\n anyOfParams: SchemaParams & { anyOf: TypedSchema[] }\n ): AnyOfSchema {\n return new AnyOfSchema(anyOfParams);\n }\n}\n\n/**\n * A type that includes all specific Schema types.\n * @public\n */\nexport type TypedSchema =\n | IntegerSchema\n | NumberSchema\n | StringSchema\n | BooleanSchema\n | ObjectSchema\n | ArraySchema\n | AnyOfSchema;\n\n/**\n * Schema class for \"integer\" types.\n * @public\n */\nexport class IntegerSchema extends Schema {\n constructor(schemaParams?: SchemaParams) {\n super({\n type: SchemaType.INTEGER,\n ...schemaParams\n });\n }\n}\n\n/**\n * Schema class for \"number\" types.\n * @public\n */\nexport class NumberSchema extends Schema {\n constructor(schemaParams?: SchemaParams) {\n super({\n type: SchemaType.NUMBER,\n ...schemaParams\n });\n }\n}\n\n/**\n * Schema class for \"boolean\" types.\n * @public\n */\nexport class BooleanSchema extends Schema {\n constructor(schemaParams?: SchemaParams) {\n super({\n type: SchemaType.BOOLEAN,\n ...schemaParams\n });\n }\n}\n\n/**\n * Schema class for \"string\" types. Can be used with or without\n * enum values.\n * @public\n */\nexport class StringSchema extends Schema {\n enum?: string[];\n constructor(schemaParams?: SchemaParams, enumValues?: string[]) {\n super({\n type: SchemaType.STRING,\n ...schemaParams\n });\n this.enum = enumValues;\n }\n\n /**\n * @internal\n */\n toJSON(): SchemaRequest {\n const obj = super.toJSON();\n if (this.enum) {\n obj['enum'] = this.enum;\n }\n return obj as SchemaRequest;\n }\n}\n\n/**\n * Schema class for \"array\" types.\n * The `items` param should refer to the type of item that can be a member\n * of the array.\n * @public\n */\nexport class ArraySchema extends Schema {\n constructor(schemaParams: SchemaParams, public items: TypedSchema) {\n super({\n type: SchemaType.ARRAY,\n ...schemaParams\n });\n }\n\n /**\n * @internal\n */\n toJSON(): SchemaRequest {\n const obj = super.toJSON();\n obj.items = this.items.toJSON();\n return obj;\n }\n}\n\n/**\n * Schema class for \"object\" types.\n * The `properties` param must be a map of `Schema` objects.\n * @public\n */\nexport class ObjectSchema extends Schema {\n constructor(\n schemaParams: SchemaParams,\n public properties: {\n [k: string]: TypedSchema;\n },\n public optionalProperties: string[] = []\n ) {\n super({\n type: SchemaType.OBJECT,\n ...schemaParams\n });\n }\n\n /**\n * @internal\n */\n toJSON(): SchemaRequest {\n const obj = super.toJSON();\n obj.properties = { ...this.properties };\n const required = [];\n if (this.optionalProperties) {\n for (const propertyKey of this.optionalProperties) {\n if (!this.properties.hasOwnProperty(propertyKey)) {\n throw new AIError(\n AIErrorCode.INVALID_SCHEMA,\n `Property \"${propertyKey}\" specified in \"optionalProperties\" does not exist.`\n );\n }\n }\n }\n for (const propertyKey in this.properties) {\n if (this.properties.hasOwnProperty(propertyKey)) {\n obj.properties[propertyKey] = this.properties[\n propertyKey\n ].toJSON() as SchemaRequest;\n if (!this.optionalProperties.includes(propertyKey)) {\n required.push(propertyKey);\n }\n }\n }\n if (required.length > 0) {\n obj.required = required;\n }\n delete obj.optionalProperties;\n return obj as SchemaRequest;\n }\n}\n\n/**\n * Schema class representing a value that can conform to any of the provided sub-schemas. This is\n * useful when a field can accept multiple distinct types or structures.\n * @public\n */\nexport class AnyOfSchema extends Schema {\n anyOf: TypedSchema[]; // Re-define field to narrow to required type\n constructor(schemaParams: SchemaParams & { anyOf: TypedSchema[] }) {\n if (schemaParams.anyOf.length === 0) {\n throw new AIError(\n AIErrorCode.INVALID_SCHEMA,\n \"The 'anyOf' array must not be empty.\"\n );\n }\n super({\n ...schemaParams,\n type: undefined // anyOf schemas do not have an explicit type\n });\n this.anyOf = schemaParams.anyOf;\n }\n\n /**\n * @internal\n */\n toJSON(): SchemaRequest {\n const obj = super.toJSON();\n // Ensure the 'anyOf' property contains serialized SchemaRequest objects.\n if (this.anyOf && Array.isArray(this.anyOf)) {\n obj.anyOf = (this.anyOf as TypedSchema[]).map(s => s.toJSON());\n }\n return obj;\n }\n}\n","/**\n * @license\n * Copyright 2025 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 { logger } from '../logger';\n\n/**\n * Defines the image format for images generated by Imagen.\n *\n * Use this class to specify the desired format (JPEG or PNG) and compression quality\n * for images generated by Imagen. This is typically included as part of\n * {@link ImagenModelParams}.\n *\n * @example\n * ```javascript\n * const imagenModelParams = {\n * // ... other ImagenModelParams\n * imageFormat: ImagenImageFormat.jpeg(75) // JPEG with a compression level of 75.\n * }\n * ```\n *\n * @public\n */\nexport class ImagenImageFormat {\n /**\n * The MIME type.\n */\n mimeType: string;\n /**\n * The level of compression (a number between 0 and 100).\n */\n compressionQuality?: number;\n\n private constructor() {\n this.mimeType = 'image/png';\n }\n\n /**\n * Creates an {@link ImagenImageFormat} for a JPEG image.\n *\n * @param compressionQuality - The level of compression (a number between 0 and 100).\n * @returns An {@link ImagenImageFormat} object for a JPEG image.\n *\n * @public\n */\n static jpeg(compressionQuality?: number): ImagenImageFormat {\n if (\n compressionQuality &&\n (compressionQuality < 0 || compressionQuality > 100)\n ) {\n logger.warn(\n `Invalid JPEG compression quality of ${compressionQuality} specified; the supported range is [0, 100].`\n );\n }\n return { mimeType: 'image/jpeg', compressionQuality };\n }\n\n /**\n * Creates an {@link ImagenImageFormat} for a PNG image.\n *\n * @returns An {@link ImagenImageFormat} object for a PNG image.\n *\n * @public\n */\n static png(): ImagenImageFormat {\n return { mimeType: 'image/png' };\n }\n}\n","/**\n * @license\n * Copyright 2025 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 { AIError } from '../errors';\nimport { logger } from '../logger';\nimport {\n AIErrorCode,\n FunctionCall,\n FunctionResponse,\n GenerativeContentBlob,\n LiveServerContent\n} from '../types';\nimport { LiveSession } from './live-session';\nimport { Deferred } from '@firebase/util';\n\nconst SERVER_INPUT_SAMPLE_RATE = 16_000;\nconst SERVER_OUTPUT_SAMPLE_RATE = 24_000;\n\nconst AUDIO_PROCESSOR_NAME = 'audio-processor';\n\n/**\n * The JS for an `AudioWorkletProcessor`.\n * This processor is responsible for taking raw audio from the microphone,\n * converting it to the required 16-bit 16kHz PCM, and posting it back to the main thread.\n *\n * See: https://developer.mozilla.org/en-US/docs/Web/API/AudioWorkletProcessor\n *\n * It is defined as a string here so that it can be converted into a `Blob`\n * and loaded at runtime.\n */\nconst audioProcessorWorkletString = `\n class AudioProcessor extends AudioWorkletProcessor {\n constructor(options) {\n super();\n this.targetSampleRate = options.processorOptions.targetSampleRate;\n // 'sampleRate' is a global variable available inside the AudioWorkletGlobalScope,\n // representing the native sample rate of the AudioContext.\n this.inputSampleRate = sampleRate;\n }\n\n /**\n * This method is called by the browser's audio engine for each block of audio data.\n * Input is a single input, with a single channel (input[0][0]).\n */\n process(inputs) {\n const input = inputs[0];\n if (input && input.length > 0 && input[0].length > 0) {\n const pcmData = input[0]; // Float32Array of raw audio samples.\n \n // Simple linear interpolation for resampling.\n const resampled = new Float32Array(Math.round(pcmData.length * this.targetSampleRate / this.inputSampleRate));\n const ratio = pcmData.length / resampled.length;\n for (let i = 0; i < resampled.length; i++) {\n resampled[i] = pcmData[Math.floor(i * ratio)];\n }\n\n // Convert Float32 (-1, 1) samples to Int16 (-32768, 32767)\n const resampledInt16 = new Int16Array(resampled.length);\n for (let i = 0; i < resampled.length; i++) {\n const sample = Math.max(-1, Math.min(1, resampled[i]));\n if (sample < 0) {\n resampledInt16[i] = sample * 32768;\n } else {\n resampledInt16[i] = sample * 32767;\n }\n }\n \n this.port.postMessage(resampledInt16);\n }\n // Return true to keep the processor alive and processing the next audio block.\n return true;\n }\n }\n\n // Register the processor with a name that can be used to instantiate it from the main thread.\n registerProcessor('${AUDIO_PROCESSOR_NAME}', AudioProcessor);\n`;\n\n/**\n * A controller for managing an active audio conversation.\n *\n * @beta\n */\nexport interface AudioConversationController {\n /**\n * Stops the audio conversation, closes the microphone connection, and\n * cleans up resources. Returns a promise that resolves when cleanup is complete.\n */\n stop: () => Promise<void>;\n}\n\n/**\n * Options for {@link startAudioConversation}.\n *\n * @beta\n */\nexport interface StartAudioConversationOptions {\n /**\n * An async handler that is called when the model requests a function to be executed.\n * The handler should perform the function call and return the result as a `Part`,\n * which will then be sent back to the model.\n */\n functionCallingHandler?: (\n functionCalls: FunctionCall[]\n ) => Promise<FunctionResponse>;\n}\n\n/**\n * Dependencies needed by the {@link AudioConversationRunner}.\n *\n * @internal\n */\ninterface RunnerDependencies {\n audioContext: AudioContext;\n mediaStream: MediaStream;\n sourceNode: MediaStreamAudioSourceNode;\n workletNode: AudioWorkletNode;\n}\n\n/**\n * Encapsulates the core logic of an audio conversation.\n *\n * @internal\n */\nexport class AudioConversationRunner {\n /** A flag to indicate if the conversation has been stopped. */\n private isStopped = false;\n /** A deferred that contains a promise that is resolved when stop() is called, to unblock the receive loop. */\n private readonly stopDeferred = new Deferred<void>();\n /** A promise that tracks the lifecycle of the main `runReceiveLoop`. */\n private readonly receiveLoopPromise: Promise<void>;\n\n /** A FIFO queue of 24kHz, 16-bit PCM audio chunks received from the server. */\n private readonly playbackQueue: ArrayBuffer[] = [];\n /** Tracks scheduled audio sources. Used to cancel scheduled audio when the model is interrupted. */\n private scheduledSources: AudioBufferSourceNode[] = [];\n /** A high-precision timeline pointer for scheduling gapless audio playback. */\n private nextStartTime = 0;\n /** A mutex to prevent the playback processing loop from running multiple times concurrently. */\n private isPlaybackLoopRunning = false;\n\n constructor(\n private readonly liveSession: LiveSession,\n private readonly options: StartAudioConversationOptions,\n private readonly deps: RunnerDependencies\n ) {\n this.liveSession.inConversation = true;\n\n // Start listening for messages from the server.\n this.receiveLoopPromise = this.runReceiveLoop().finally(() =>\n this.cleanup()\n );\n\n // Set up the handler for receiving processed audio data from the worklet.\n // Message data has been resampled to 16kHz 16-bit PCM.\n this.deps.workletNode.port.onmessage = event => {\n if (this.isStopped) {\n return;\n }\n\n const pcm16 = event.data as Int16Array;\n const base64 = btoa(\n String.fromCharCode.apply(\n null,\n Array.from(new Uint8Array(pcm16.buffer))\n )\n );\n\n const chunk: GenerativeContentBlob = {\n mimeType: 'audio/pcm',\n data: base64\n };\n void this.liveSession.sendAudioRealtime(chunk);\n };\n }\n\n /**\n * Stops the conversation and unblocks the main receive loop.\n */\n async stop(): Promise<void> {\n if (this.isStopped) {\n return;\n }\n this.isStopped = true;\n this.stopDeferred.resolve(); // Unblock the receive loop\n await this.receiveLoopPromise; // Wait for the loop and cleanup to finish\n }\n\n /**\n * Cleans up all audio resources (nodes, stream tracks, context) and marks the\n * session as no longer in a conversation.\n */\n private cleanup(): void {\n this.interruptPlayback(); // Ensure all audio is stopped on final cleanup.\n this.deps.workletNode.port.onmessage = null;\n this.deps.workletNode.disconnect();\n this.deps.sourceNode.disconnect();\n this.deps.mediaStream.getTracks().forEach(track => track.stop());\n if (this.deps.audioContext.state !== 'closed') {\n void this.deps.audioContext.close();\n }\n this.liveSession.inConversation = false;\n }\n\n /**\n * Adds audio data to the queue and ensures the playback loop is running.\n */\n private enqueueAndPlay(audioData: ArrayBuffer): void {\n this.playbackQueue.push(audioData);\n // Will no-op if it's already running.\n void this.processPlaybackQueue();\n }\n\n /**\n * Stops all current and pending audio playback and clears the queue. This is\n * called when the server indicates the model's speech was interrupted with\n * `LiveServerContent.modelTurn.interrupted`.\n */\n private interruptPlayback(): void {\n // Stop all sources that have been scheduled. The onended event will fire for each,\n // which will clean up the scheduledSources array.\n [...this.scheduledSources].forEach(source => source.stop(0));\n\n // Clear the internal buffer of unprocessed audio chunks.\n this.playbackQueue.length = 0;\n\n // Reset the playback clock to start fresh.\n this.nextStartTime = this.deps.audioContext.currentTime;\n }\n\n /**\n * Processes the playback queue in a loop, scheduling each chunk in a gapless sequence.\n */\n private async processPlaybackQueue(): Promise<void> {\n if (this.isPlaybackLoopRunning) {\n return;\n }\n this.isPlaybackLoopRunning = true;\n\n while (this.playbackQueue.length > 0 && !this.isStopped) {\n const pcmRawBuffer = this.playbackQueue.shift()!;\n try {\n const pcm16 = new Int16Array(pcmRawBuffer);\n const frameCount = pcm16.length;\n\n const audioBuffer = this.deps.audioContext.createBuffer(\n 1,\n frameCount,\n SERVER_OUTPUT_SAMPLE_RATE\n );\n\n // Convert 16-bit PCM to 32-bit PCM, required by the Web Audio API.\n const channelData = audioBuffer.getChannelData(0);\n for (let i = 0; i < frameCount; i++) {\n channelData[i] = pcm16[i] / 32768; // Normalize to Float32 range [-1.0, 1.0]\n }\n\n const source = this.deps.audioContext.createBufferSource();\n source.buffer = audioBuffer;\n source.connect(this.deps.audioContext.destination);\n\n // Track the source and set up a handler to remove it from tracking when it finishes.\n this.scheduledSources.push(source);\n source.onended = () => {\n this.scheduledSources = this.scheduledSources.filter(\n s => s !== source\n );\n };\n\n // To prevent gaps, schedule the next chunk to start either now (if we're catching up)\n // or exactly when the previous chunk is scheduled to end.\n this.nextStartTime = Math.max(\n this.deps.audioContext.currentTime,\n this.nextStartTime\n );\n source.start(this.nextStartTime);\n\n // Update the schedule for the *next* chunk.\n this.nextStartTime += audioBuffer.duration;\n } catch (e) {\n logger.error('Error playing audio:', e);\n }\n }\n\n this.isPlaybackLoopRunning = false;\n }\n\n /**\n * The main loop that listens for and processes messages from the server.\n */\n private async runReceiveLoop(): Promise<void> {\n const messageGenerator = this.liveSession.receive();\n while (!this.isStopped) {\n const result = await Promise.race([\n messageGenerator.next(),\n this.stopDeferred.promise\n ]);\n\n if (this.isStopped || !result || result.done) {\n break;\n }\n\n const message = result.value;\n if (message.type === 'serverContent') {\n const serverContent = message as LiveServerContent;\n if (serverContent.interrupted) {\n this.interruptPlayback();\n }\n\n const audioPart = serverContent.modelTurn?.parts.find(part =>\n part.inlineData?.mimeType.startsWith('audio/')\n );\n if (audioPart?.inlineData) {\n const audioData = Uint8Array.from(\n atob(audioPart.inlineData.data),\n c => c.charCodeAt(0)\n ).buffer;\n this.enqueueAndPlay(audioData);\n }\n } else if (message.type === 'toolCall') {\n if (!this.options.functionCallingHandler) {\n logger.warn(\n 'Received tool call message, but StartAudioConversationOptions.functionCallingHandler is undefined. Ignoring tool call.'\n );\n } else {\n try {\n const functionResponse = await this.options.functionCallingHandler(\n message.functionCalls\n );\n if (!this.isStopped) {\n void this.liveSession.sendFunctionResponses([functionResponse]);\n }\n } catch (e) {\n throw new AIError(\n AIErrorCode.ERROR,\n `Function calling handler failed: ${(e as Error).message}`\n );\n }\n }\n }\n }\n }\n}\n\n/**\n * Starts a real-time, bidirectional audio conversation with the model. This helper function manages\n * the complexities of microphone access, audio recording, playback, and interruptions.\n *\n * @remarks Important: This function must be called in response to a user gesture\n * (for example, a button click) to comply with {@link https://developer.mozilla.org/en-US/docs/Web/API/Web_Audio_API/Best_practices#autoplay_policy | browser autoplay policies}.\n *\n * @example\n * ```javascript\n * const liveSession = await model.connect();\n * let conversationController;\n *\n * // This function must be called from within a click handler.\n * async function startConversation() {\n * try {\n * conversationController = await startAudioConversation(liveSession);\n * } catch (e) {\n * // Handle AI-specific errors\n * if (e instanceof AIError) {\n * console.error(\"AI Error:\", e.message);\n * }\n * // Handle microphone permission and hardware errors\n * else if (e instanceof DOMException) {\n * console.error(\"Microphone Error:\", e.message);\n * }\n * // Handle other unexpected errors\n * else {\n * console.error(\"An unexpected error occurred:\", e);\n * }\n * }\n * }\n *\n * // Later, to stop the conversation:\n * // if (conversationController) {\n * // await conversationController.stop();\n * // }\n * ```\n *\n * @param liveSession - An active {@link LiveSession} instance.\n * @param options - Configuration options for the audio conversation.\n * @returns A `Promise` that resolves with an {@link AudioConversationController}.\n * @throws `AIError` if the environment does not support required Web APIs (`UNSUPPORTED`), if a conversation is already active (`REQUEST_ERROR`), the session is closed (`SESSION_CLOSED`), or if an unexpected initialization error occurs (`ERROR`).\n * @throws `DOMException` Thrown by `navigator.mediaDevices.getUserMedia()` if issues occur with microphone access, such as permissions being denied (`NotAllowedError`) or no compatible hardware being found (`NotFoundError`). See the {@link https://developer.mozilla.org/en-US/docs/Web/API/MediaDevices/getUserMedia#exceptions | MDN documentation} for a full list of exceptions.\n *\n * @beta\n */\nexport async function startAudioConversation(\n liveSession: LiveSession,\n options: StartAudioConversationOptions = {}\n): Promise<AudioConversationController> {\n if (liveSession.isClosed) {\n throw new AIError(\n AIErrorCode.SESSION_CLOSED,\n 'Cannot start audio conversation on a closed LiveSession.'\n );\n }\n\n if (liveSession.inConversation) {\n throw new AIError(\n AIErrorCode.REQUEST_ERROR,\n 'An audio conversation is already in progress for this session.'\n );\n }\n\n // Check for necessary Web API support.\n if (\n typeof AudioWorkletNode === 'undefined' ||\n typeof AudioContext === 'undefined' ||\n typeof navigator === 'undefined' ||\n !navigator.mediaDevices\n ) {\n throw new AIError(\n AIErrorCode.UNSUPPORTED,\n 'Audio conversation is not supported in this environment. It requires the Web Audio API and AudioWorklet support.'\n );\n }\n\n let audioContext: AudioContext | undefined;\n try {\n // 1. Set up the audio context. This must be in response to a user gesture.\n // See: https://developer.mozilla.org/en-US/docs/Web/API/Web_Audio_API/Best_practices#autoplay_policy\n audioContext = new AudioContext();\n if (audioContext.state === 'suspended') {\n await audioContext.resume();\n }\n\n // 2. Prompt for microphone access and get the media stream.\n // This can throw a variety of permission or hardware-related errors.\n const mediaStream = await navigator.mediaDevices.getUserMedia({\n audio: true\n });\n\n // 3. Load the AudioWorklet processor.\n // See: https://developer.mozilla.org/en-US/docs/Web/API/AudioWorklet\n const workletBlob = new Blob([audioProcessorWorkletString], {\n type: 'application/javascript'\n });\n const workletURL = URL.createObjectURL(workletBlob);\n await audioContext.audioWorklet.addModule(workletURL);\n\n // 4. Create the audio graph: Microphone -> Source Node -> Worklet Node\n const sourceNode = audioContext.createMediaStreamSource(mediaStream);\n const workletNode = new AudioWorkletNode(\n audioContext,\n AUDIO_PROCESSOR_NAME,\n {\n processorOptions: { targetSampleRate: SERVER_INPUT_SAMPLE_RATE }\n }\n );\n sourceNode.connect(workletNode);\n\n // 5. Instantiate and return the runner which manages the conversation.\n const runner = new AudioConversationRunner(liveSession, options, {\n audioContext,\n mediaStream,\n sourceNode,\n workletNode\n });\n\n return { stop: () => runner.stop() };\n } catch (e) {\n // Ensure the audio context is closed on any setup error.\n if (audioContext && audioContext.state !== 'closed') {\n void audioContext.close();\n }\n\n // Re-throw specific, known error types directly. The user may want to handle `DOMException`\n // errors differently (for example, if permission to access audio device was denied).\n if (e instanceof AIError || e instanceof DOMException) {\n throw e;\n }\n\n // Wrap any other unexpected errors in a standard AIError.\n throw new AIError(\n AIErrorCode.ERROR,\n `Failed to initialize audio recording: ${(e as Error).message}`\n );\n }\n}\n","/**\n * @license\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 { FirebaseApp, getApp, _getProvider } from '@firebase/app';\nimport { Provider } from '@firebase/component';\nimport { getModularInstance } from '@firebase/util';\nimport { AI_TYPE, DEFAULT_HYBRID_IN_CLOUD_MODEL } from './constants';\nimport { AIService } from './service';\nimport { AI, AIOptions } from './public-types';\nimport {\n ImagenModelParams,\n HybridParams,\n ModelParams,\n RequestOptions,\n AIErrorCode,\n LiveModelParams\n} from './types';\nimport { AIError } from './errors';\nimport {\n AIModel,\n GenerativeModel,\n LiveGenerativeModel,\n ImagenModel\n} from './models';\nimport { encodeInstanceIdentifier } from './helpers';\nimport { GoogleAIBackend } from './backend';\nimport { WebSocketHandlerImpl } from './websocket';\nimport { TemplateGenerativeModel } from './models/template-generative-model';\nimport { TemplateImagenModel } from './models/template-imagen-model';\n\nexport { ChatSession } from './methods/chat-session';\nexport { LiveSession } from './methods/live-session';\nexport * from './requests/schema-builder';\nexport { ImagenImageFormat } from './requests/imagen-image-format';\nexport {\n AIModel,\n GenerativeModel,\n LiveGenerativeModel,\n ImagenModel,\n TemplateGenerativeModel,\n TemplateImagenModel,\n AIError\n};\nexport { Backend, VertexAIBackend, GoogleAIBackend } from './backend';\nexport {\n startAudioConversation,\n AudioConversationController,\n StartAudioConversationOptions\n} from './methods/live-session-helpers';\n\ndeclare module '@firebase/component' {\n interface NameServiceMapping {\n [AI_TYPE]: AIService;\n }\n}\n\n/**\n * Returns the default {@link AI} instance that is associated with the provided\n * {@link @firebase/app#FirebaseApp}. If no instance exists, initializes a new instance with the\n * default settings.\n *\n * @example\n * ```javascript\n * const ai = getAI(app);\n * ```\n *\n * @example\n * ```javascript\n * // Get an AI instance configured to use the Gemini Developer API (via Google AI).\n * const ai = getAI(app, { backend: new GoogleAIBackend() });\n * ```\n *\n * @example\n * ```javascript\n * // Get an AI instance configured to use the Vertex AI Gemini API.\n * const ai = getAI(app, { backend: new VertexAIBackend() });\n * ```\n *\n * @param app - The {@link @firebase/app#FirebaseApp} to use.\n * @param options - {@link AIOptions} that configure the AI instance.\n * @returns The default {@link AI} instance for the given {@link @firebase/app#FirebaseApp}.\n *\n * @public\n */\nexport function getAI(app: FirebaseApp = getApp(), options?: AIOptions): AI {\n app = getModularInstance(app);\n // Dependencies\n const AIProvider: Provider<'AI'> = _getProvider(app, AI_TYPE);\n\n const backend = options?.backend ?? new GoogleAIBackend();\n\n const finalOptions: Omit<AIOptions, 'backend'> = {\n useLimitedUseAppCheckTokens: options?.useLimitedUseAppCheckTokens ?? false\n };\n\n const identifier = encodeInstanceIdentifier(backend);\n const aiInstance = AIProvider.getImmediate({\n identifier\n });\n\n aiInstance.options = finalOptions;\n\n return aiInstance;\n}\n\n/**\n * Returns a {@link GenerativeModel} class with methods for inference\n * and other functionality.\n *\n * @public\n */\nexport function getGenerativeModel(\n ai: AI,\n modelParams: ModelParams | HybridParams,\n requestOptions?: RequestOptions\n): GenerativeModel {\n // Uses the existence of HybridParams.mode to clarify the type of the modelParams input.\n const hybridParams = modelParams as HybridParams;\n let inCloudParams: ModelParams;\n if (hybridParams.mode) {\n inCloudParams = hybridParams.inCloudParams || {\n model: DEFAULT_HYBRID_IN_CLOUD_MODEL\n };\n } else {\n inCloudParams = modelParams as ModelParams;\n }\n\n if (!inCloudParams.model) {\n throw new AIError(\n AIErrorCode.NO_MODEL,\n `Must provide a model name. Example: getGenerativeModel({ model: 'my-model-name' })`\n );\n }\n\n /**\n * An AIService registered by index.node.ts will not have a\n * chromeAdapterFactory() method.\n */\n const chromeAdapter = (ai as AIService).chromeAdapterFactory?.(\n hybridParams.mode,\n typeof window === 'undefined' ? undefined : window,\n hybridParams.onDeviceParams\n );\n\n const generativeModel = new GenerativeModel(\n ai,\n inCloudParams,\n requestOptions,\n chromeAdapter\n );\n\n generativeModel._apiSettings.inferenceMode = hybridParams.mode;\n return generativeModel;\n}\n\n/**\n * Returns an {@link ImagenModel} class with methods for using Imagen.\n *\n * Only Imagen 3 models (named `imagen-3.0-*`) are supported.\n *\n * @param ai - An {@link AI} instance.\n * @param modelParams - Parameters to use when making Imagen requests.\n * @param requestOptions - Additional options to use when making requests.\n *\n * @throws If the `apiKey` or `projectId` fields are missing in your\n * Firebase config.\n *\n * @public\n */\nexport function getImagenModel(\n ai: AI,\n modelParams: ImagenModelParams,\n requestOptions?: RequestOptions\n): ImagenModel {\n if (!modelParams.model) {\n throw new AIError(\n AIErrorCode.NO_MODEL,\n `Must provide a model name. Example: getImagenModel({ model: 'my-model-name' })`\n );\n }\n return new ImagenModel(ai, modelParams, requestOptions);\n}\n\n/**\n * Returns a {@link LiveGenerativeModel} class for real-time, bidirectional communication.\n *\n * The Live API is only supported in modern browser windows and Node >= 22.\n *\n * @param ai - An {@link AI} instance.\n * @param modelParams - Parameters to use when setting up a {@link LiveSession}.\n * @throws If the `apiKey` or `projectId` fields are missing in your\n * Firebase config.\n *\n * @beta\n */\nexport function getLiveGenerativeModel(\n ai: AI,\n modelParams: LiveModelParams\n): LiveGenerativeModel {\n if (!modelParams.model) {\n throw new AIError(\n AIErrorCode.NO_MODEL,\n `Must provide a model name for getLiveGenerativeModel. Example: getLiveGenerativeModel(ai, { model: 'my-model-name' })`\n );\n }\n const webSocketHandler = new WebSocketHandlerImpl();\n return new LiveGenerativeModel(ai, modelParams, webSocketHandler);\n}\n\n/**\n * Returns a {@link TemplateGenerativeModel} class for executing server-side\n * templates.\n *\n * @param ai - An {@link AI} instance.\n * @param requestOptions - Additional options to use when making requests.\n *\n * @beta\n */\nexport function getTemplateGenerativeModel(\n ai: AI,\n requestOptions?: RequestOptions\n): TemplateGenerativeModel {\n return new TemplateGenerativeModel(ai, requestOptions);\n}\n\n/**\n * Returns a {@link TemplateImagenModel} class for executing server-side\n * Imagen templates.\n *\n * @param ai - An {@link AI} instance.\n * @param requestOptions - Additional options to use when making requests.\n *\n * @beta\n */\nexport function getTemplateImagenModel(\n ai: AI,\n requestOptions?: RequestOptions\n): TemplateImagenModel {\n return new TemplateImagenModel(ai, requestOptions);\n}\n","/**\n * The Firebase AI Web SDK.\n *\n * @packageDocumentation\n */\n\n/**\n * @license\n * Copyright 2025 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 { registerVersion, _registerComponent } from '@firebase/app';\nimport { AI_TYPE } from './constants';\nimport { Component, ComponentType } from '@firebase/component';\nimport { name, version } from '../package.json';\nimport { factory } from './factory-node';\n\nfunction registerAI(): void {\n _registerComponent(\n new Component(AI_TYPE, factory, ComponentType.PUBLIC).setMultipleInstances(\n true\n )\n );\n\n registerVersion(name, version, 'node');\n // BUILD_TARGET will be replaced by values like esm, cjs, etc during the compilation\n registerVersion(name, version, '__BUILD_TARGET__');\n}\n\nregisterAI();\n\nexport * from './api';\nexport * from 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