@ai-sdk/google
Version:
The **[Google Generative AI provider](https://ai-sdk.dev/providers/ai-sdk-providers/google-generative-ai)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the [Google Generative AI](https://ai.google/discover/generativeai/)
859 lines (852 loc) • 27.7 kB
JavaScript
// src/google-generative-ai-language-model.ts
import {
combineHeaders,
createEventSourceResponseHandler,
createJsonResponseHandler,
parseProviderOptions,
postJsonToApi,
resolve
} from "@ai-sdk/provider-utils";
import { z as z2 } from "zod";
// src/convert-json-schema-to-openapi-schema.ts
function convertJSONSchemaToOpenAPISchema(jsonSchema) {
if (isEmptyObjectSchema(jsonSchema)) {
return void 0;
}
if (typeof jsonSchema === "boolean") {
return { type: "boolean", properties: {} };
}
const {
type,
description,
required,
properties,
items,
allOf,
anyOf,
oneOf,
format,
const: constValue,
minLength,
enum: enumValues
} = jsonSchema;
const result = {};
if (description)
result.description = description;
if (required)
result.required = required;
if (format)
result.format = format;
if (constValue !== void 0) {
result.enum = [constValue];
}
if (type) {
if (Array.isArray(type)) {
if (type.includes("null")) {
result.type = type.filter((t) => t !== "null")[0];
result.nullable = true;
} else {
result.type = type;
}
} else if (type === "null") {
result.type = "null";
} else {
result.type = type;
}
}
if (enumValues !== void 0) {
result.enum = enumValues;
}
if (properties != null) {
result.properties = Object.entries(properties).reduce(
(acc, [key, value]) => {
acc[key] = convertJSONSchemaToOpenAPISchema(value);
return acc;
},
{}
);
}
if (items) {
result.items = Array.isArray(items) ? items.map(convertJSONSchemaToOpenAPISchema) : convertJSONSchemaToOpenAPISchema(items);
}
if (allOf) {
result.allOf = allOf.map(convertJSONSchemaToOpenAPISchema);
}
if (anyOf) {
if (anyOf.some(
(schema) => typeof schema === "object" && (schema == null ? void 0 : schema.type) === "null"
)) {
const nonNullSchemas = anyOf.filter(
(schema) => !(typeof schema === "object" && (schema == null ? void 0 : schema.type) === "null")
);
if (nonNullSchemas.length === 1) {
const converted = convertJSONSchemaToOpenAPISchema(nonNullSchemas[0]);
if (typeof converted === "object") {
result.nullable = true;
Object.assign(result, converted);
}
} else {
result.anyOf = nonNullSchemas.map(convertJSONSchemaToOpenAPISchema);
result.nullable = true;
}
} else {
result.anyOf = anyOf.map(convertJSONSchemaToOpenAPISchema);
}
}
if (oneOf) {
result.oneOf = oneOf.map(convertJSONSchemaToOpenAPISchema);
}
if (minLength !== void 0) {
result.minLength = minLength;
}
return result;
}
function isEmptyObjectSchema(jsonSchema) {
return jsonSchema != null && typeof jsonSchema === "object" && jsonSchema.type === "object" && (jsonSchema.properties == null || Object.keys(jsonSchema.properties).length === 0);
}
// src/convert-to-google-generative-ai-messages.ts
import {
UnsupportedFunctionalityError
} from "@ai-sdk/provider";
import { convertUint8ArrayToBase64 } from "@ai-sdk/provider-utils";
function convertToGoogleGenerativeAIMessages(prompt) {
var _a, _b;
const systemInstructionParts = [];
const contents = [];
let systemMessagesAllowed = true;
for (const { role, content } of prompt) {
switch (role) {
case "system": {
if (!systemMessagesAllowed) {
throw new UnsupportedFunctionalityError({
functionality: "system messages are only supported at the beginning of the conversation"
});
}
systemInstructionParts.push({ text: content });
break;
}
case "user": {
systemMessagesAllowed = false;
const parts = [];
for (const part of content) {
switch (part.type) {
case "text": {
parts.push({ text: part.text });
break;
}
case "image": {
parts.push(
part.image instanceof URL ? {
fileData: {
mimeType: (_a = part.mimeType) != null ? _a : "image/jpeg",
fileUri: part.image.toString()
}
} : {
inlineData: {
mimeType: (_b = part.mimeType) != null ? _b : "image/jpeg",
data: convertUint8ArrayToBase64(part.image)
}
}
);
break;
}
case "file": {
parts.push(
part.data instanceof URL ? {
fileData: {
mimeType: part.mimeType,
fileUri: part.data.toString()
}
} : {
inlineData: {
mimeType: part.mimeType,
data: part.data
}
}
);
break;
}
}
}
contents.push({ role: "user", parts });
break;
}
case "assistant": {
systemMessagesAllowed = false;
contents.push({
role: "model",
parts: content.map((part) => {
switch (part.type) {
case "text": {
return part.text.length === 0 ? void 0 : { text: part.text };
}
case "file": {
if (part.mimeType !== "image/png") {
throw new UnsupportedFunctionalityError({
functionality: "Only PNG images are supported in assistant messages"
});
}
if (part.data instanceof URL) {
throw new UnsupportedFunctionalityError({
functionality: "File data URLs in assistant messages are not supported"
});
}
return {
inlineData: {
mimeType: part.mimeType,
data: part.data
}
};
}
case "tool-call": {
return {
functionCall: {
name: part.toolName,
args: part.args
}
};
}
}
}).filter((part) => part !== void 0)
});
break;
}
case "tool": {
systemMessagesAllowed = false;
contents.push({
role: "user",
parts: content.map((part) => ({
functionResponse: {
name: part.toolName,
response: {
name: part.toolName,
content: part.result
}
}
}))
});
break;
}
}
}
return {
systemInstruction: systemInstructionParts.length > 0 ? { parts: systemInstructionParts } : void 0,
contents
};
}
// src/get-model-path.ts
function getModelPath(modelId) {
return modelId.includes("/") ? modelId : `models/${modelId}`;
}
// src/google-error.ts
import { createJsonErrorResponseHandler } from "@ai-sdk/provider-utils";
import { z } from "zod";
var googleErrorDataSchema = z.object({
error: z.object({
code: z.number().nullable(),
message: z.string(),
status: z.string()
})
});
var googleFailedResponseHandler = createJsonErrorResponseHandler({
errorSchema: googleErrorDataSchema,
errorToMessage: (data) => data.error.message
});
// src/google-prepare-tools.ts
import {
UnsupportedFunctionalityError as UnsupportedFunctionalityError2
} from "@ai-sdk/provider";
function prepareTools(mode, useSearchGrounding, dynamicRetrievalConfig, modelId) {
var _a, _b;
const tools = ((_a = mode.tools) == null ? void 0 : _a.length) ? mode.tools : void 0;
const toolWarnings = [];
const isGemini2 = modelId.includes("gemini-2");
const supportsDynamicRetrieval = modelId.includes("gemini-1.5-flash") && !modelId.includes("-8b");
if (useSearchGrounding) {
return {
tools: isGemini2 ? { googleSearch: {} } : {
googleSearchRetrieval: !supportsDynamicRetrieval || !dynamicRetrievalConfig ? {} : { dynamicRetrievalConfig }
},
toolConfig: void 0,
toolWarnings
};
}
if (tools == null) {
return { tools: void 0, toolConfig: void 0, toolWarnings };
}
const functionDeclarations = [];
for (const tool of tools) {
if (tool.type === "provider-defined") {
toolWarnings.push({ type: "unsupported-tool", tool });
} else {
functionDeclarations.push({
name: tool.name,
description: (_b = tool.description) != null ? _b : "",
parameters: convertJSONSchemaToOpenAPISchema(tool.parameters)
});
}
}
const toolChoice = mode.toolChoice;
if (toolChoice == null) {
return {
tools: { functionDeclarations },
toolConfig: void 0,
toolWarnings
};
}
const type = toolChoice.type;
switch (type) {
case "auto":
return {
tools: { functionDeclarations },
toolConfig: { functionCallingConfig: { mode: "AUTO" } },
toolWarnings
};
case "none":
return {
tools: { functionDeclarations },
toolConfig: { functionCallingConfig: { mode: "NONE" } },
toolWarnings
};
case "required":
return {
tools: { functionDeclarations },
toolConfig: { functionCallingConfig: { mode: "ANY" } },
toolWarnings
};
case "tool":
return {
tools: { functionDeclarations },
toolConfig: {
functionCallingConfig: {
mode: "ANY",
allowedFunctionNames: [toolChoice.toolName]
}
},
toolWarnings
};
default: {
const _exhaustiveCheck = type;
throw new UnsupportedFunctionalityError2({
functionality: `Unsupported tool choice type: ${_exhaustiveCheck}`
});
}
}
}
// src/map-google-generative-ai-finish-reason.ts
function mapGoogleGenerativeAIFinishReason({
finishReason,
hasToolCalls
}) {
switch (finishReason) {
case "STOP":
return hasToolCalls ? "tool-calls" : "stop";
case "MAX_TOKENS":
return "length";
case "IMAGE_SAFETY":
case "RECITATION":
case "SAFETY":
case "BLOCKLIST":
case "PROHIBITED_CONTENT":
case "SPII":
return "content-filter";
case "FINISH_REASON_UNSPECIFIED":
case "OTHER":
return "other";
case "MALFORMED_FUNCTION_CALL":
return "error";
default:
return "unknown";
}
}
// src/google-generative-ai-language-model.ts
var GoogleGenerativeAILanguageModel = class {
constructor(modelId, settings, config) {
this.specificationVersion = "v1";
this.defaultObjectGenerationMode = "json";
this.supportsImageUrls = false;
this.modelId = modelId;
this.settings = settings;
this.config = config;
}
get supportsStructuredOutputs() {
var _a;
return (_a = this.settings.structuredOutputs) != null ? _a : true;
}
get provider() {
return this.config.provider;
}
async getArgs({
mode,
prompt,
maxTokens,
temperature,
topP,
topK,
frequencyPenalty,
presencePenalty,
stopSequences,
responseFormat,
seed,
providerMetadata
}) {
var _a, _b, _c;
const type = mode.type;
const warnings = [];
const googleOptions = parseProviderOptions({
provider: "google",
providerOptions: providerMetadata,
schema: googleGenerativeAIProviderOptionsSchema
});
if (((_a = googleOptions == null ? void 0 : googleOptions.thinkingConfig) == null ? void 0 : _a.includeThoughts) === true && !this.config.provider.startsWith("google.vertex.")) {
warnings.push({
type: "other",
message: `The 'includeThoughts' option is only supported with the Google Vertex provider and might not be supported or could behave unexpectedly with the current Google provider (${this.config.provider}).`
});
}
const generationConfig = {
// standardized settings:
maxOutputTokens: maxTokens,
temperature,
topK,
topP,
frequencyPenalty,
presencePenalty,
stopSequences,
seed,
// response format:
responseMimeType: (responseFormat == null ? void 0 : responseFormat.type) === "json" ? "application/json" : void 0,
responseSchema: (responseFormat == null ? void 0 : responseFormat.type) === "json" && responseFormat.schema != null && // Google GenAI does not support all OpenAPI Schema features,
// so this is needed as an escape hatch:
this.supportsStructuredOutputs ? convertJSONSchemaToOpenAPISchema(responseFormat.schema) : void 0,
...this.settings.audioTimestamp && {
audioTimestamp: this.settings.audioTimestamp
},
// provider options:
responseModalities: googleOptions == null ? void 0 : googleOptions.responseModalities,
thinkingConfig: googleOptions == null ? void 0 : googleOptions.thinkingConfig
};
const { contents, systemInstruction } = convertToGoogleGenerativeAIMessages(prompt);
switch (type) {
case "regular": {
const { tools, toolConfig, toolWarnings } = prepareTools(
mode,
(_b = this.settings.useSearchGrounding) != null ? _b : false,
this.settings.dynamicRetrievalConfig,
this.modelId
);
return {
args: {
generationConfig,
contents,
systemInstruction,
safetySettings: this.settings.safetySettings,
tools,
toolConfig,
cachedContent: this.settings.cachedContent
},
warnings: [...warnings, ...toolWarnings]
};
}
case "object-json": {
return {
args: {
generationConfig: {
...generationConfig,
responseMimeType: "application/json",
responseSchema: mode.schema != null && // Google GenAI does not support all OpenAPI Schema features,
// so this is needed as an escape hatch:
this.supportsStructuredOutputs ? convertJSONSchemaToOpenAPISchema(mode.schema) : void 0
},
contents,
systemInstruction,
safetySettings: this.settings.safetySettings,
cachedContent: this.settings.cachedContent
},
warnings
};
}
case "object-tool": {
return {
args: {
generationConfig,
contents,
tools: {
functionDeclarations: [
{
name: mode.tool.name,
description: (_c = mode.tool.description) != null ? _c : "",
parameters: convertJSONSchemaToOpenAPISchema(
mode.tool.parameters
)
}
]
},
toolConfig: { functionCallingConfig: { mode: "ANY" } },
safetySettings: this.settings.safetySettings,
cachedContent: this.settings.cachedContent
},
warnings
};
}
default: {
const _exhaustiveCheck = type;
throw new Error(`Unsupported type: ${_exhaustiveCheck}`);
}
}
}
supportsUrl(url) {
return this.config.isSupportedUrl(url);
}
async doGenerate(options) {
var _a, _b, _c, _d, _e;
const { args, warnings } = await this.getArgs(options);
const body = JSON.stringify(args);
const mergedHeaders = combineHeaders(
await resolve(this.config.headers),
options.headers
);
const {
responseHeaders,
value: response,
rawValue: rawResponse
} = await postJsonToApi({
url: `${this.config.baseURL}/${getModelPath(
this.modelId
)}:generateContent`,
headers: mergedHeaders,
body: args,
failedResponseHandler: googleFailedResponseHandler,
successfulResponseHandler: createJsonResponseHandler(responseSchema),
abortSignal: options.abortSignal,
fetch: this.config.fetch
});
const { contents: rawPrompt, ...rawSettings } = args;
const candidate = response.candidates[0];
const parts = candidate.content == null || typeof candidate.content !== "object" || !("parts" in candidate.content) ? [] : candidate.content.parts;
const toolCalls = getToolCallsFromParts({
parts,
// Use candidateParts
generateId: this.config.generateId
});
const usageMetadata = response.usageMetadata;
return {
text: getTextFromParts(parts),
reasoning: getReasoningDetailsFromParts(parts),
files: (_a = getInlineDataParts(parts)) == null ? void 0 : _a.map((part) => ({
data: part.inlineData.data,
mimeType: part.inlineData.mimeType
})),
toolCalls,
finishReason: mapGoogleGenerativeAIFinishReason({
finishReason: candidate.finishReason,
hasToolCalls: toolCalls != null && toolCalls.length > 0
}),
usage: {
promptTokens: (_b = usageMetadata == null ? void 0 : usageMetadata.promptTokenCount) != null ? _b : NaN,
completionTokens: (_c = usageMetadata == null ? void 0 : usageMetadata.candidatesTokenCount) != null ? _c : NaN
},
rawCall: { rawPrompt, rawSettings },
rawResponse: { headers: responseHeaders, body: rawResponse },
warnings,
providerMetadata: {
google: {
groundingMetadata: (_d = candidate.groundingMetadata) != null ? _d : null,
safetyRatings: (_e = candidate.safetyRatings) != null ? _e : null
}
},
sources: extractSources({
groundingMetadata: candidate.groundingMetadata,
generateId: this.config.generateId
}),
request: { body }
};
}
async doStream(options) {
const { args, warnings } = await this.getArgs(options);
const body = JSON.stringify(args);
const headers = combineHeaders(
await resolve(this.config.headers),
options.headers
);
const { responseHeaders, value: response } = await postJsonToApi({
url: `${this.config.baseURL}/${getModelPath(
this.modelId
)}:streamGenerateContent?alt=sse`,
headers,
body: args,
failedResponseHandler: googleFailedResponseHandler,
successfulResponseHandler: createEventSourceResponseHandler(chunkSchema),
abortSignal: options.abortSignal,
fetch: this.config.fetch
});
const { contents: rawPrompt, ...rawSettings } = args;
let finishReason = "unknown";
let usage = {
promptTokens: Number.NaN,
completionTokens: Number.NaN
};
let providerMetadata = void 0;
const generateId = this.config.generateId;
let hasToolCalls = false;
return {
stream: response.pipeThrough(
new TransformStream({
transform(chunk, controller) {
var _a, _b, _c, _d, _e, _f;
if (!chunk.success) {
controller.enqueue({ type: "error", error: chunk.error });
return;
}
const value = chunk.value;
const usageMetadata = value.usageMetadata;
if (usageMetadata != null) {
usage = {
promptTokens: (_a = usageMetadata.promptTokenCount) != null ? _a : NaN,
completionTokens: (_b = usageMetadata.candidatesTokenCount) != null ? _b : NaN
};
}
const candidate = (_c = value.candidates) == null ? void 0 : _c[0];
if (candidate == null) {
return;
}
const content = candidate.content;
if (content != null) {
const deltaText = getTextFromParts(content.parts);
if (deltaText != null) {
controller.enqueue({
type: "text-delta",
textDelta: deltaText
});
}
const reasoningDeltaText = getReasoningDetailsFromParts(
content.parts
);
if (reasoningDeltaText != null) {
for (const part of reasoningDeltaText) {
controller.enqueue({
type: "reasoning",
textDelta: part.text
});
}
}
const inlineDataParts = getInlineDataParts(content.parts);
if (inlineDataParts != null) {
for (const part of inlineDataParts) {
controller.enqueue({
type: "file",
mimeType: part.inlineData.mimeType,
data: part.inlineData.data
});
}
}
const toolCallDeltas = getToolCallsFromParts({
parts: content.parts,
generateId
});
if (toolCallDeltas != null) {
for (const toolCall of toolCallDeltas) {
controller.enqueue({
type: "tool-call-delta",
toolCallType: "function",
toolCallId: toolCall.toolCallId,
toolName: toolCall.toolName,
argsTextDelta: toolCall.args
});
controller.enqueue({
type: "tool-call",
toolCallType: "function",
toolCallId: toolCall.toolCallId,
toolName: toolCall.toolName,
args: toolCall.args
});
hasToolCalls = true;
}
}
}
if (candidate.finishReason != null) {
finishReason = mapGoogleGenerativeAIFinishReason({
finishReason: candidate.finishReason,
hasToolCalls
});
const sources = (_d = extractSources({
groundingMetadata: candidate.groundingMetadata,
generateId
})) != null ? _d : [];
for (const source of sources) {
controller.enqueue({ type: "source", source });
}
providerMetadata = {
google: {
groundingMetadata: (_e = candidate.groundingMetadata) != null ? _e : null,
safetyRatings: (_f = candidate.safetyRatings) != null ? _f : null
}
};
}
},
flush(controller) {
controller.enqueue({
type: "finish",
finishReason,
usage,
providerMetadata
});
}
})
),
rawCall: { rawPrompt, rawSettings },
rawResponse: { headers: responseHeaders },
warnings,
request: { body }
};
}
};
function getToolCallsFromParts({
parts,
generateId
}) {
const functionCallParts = parts == null ? void 0 : parts.filter(
(part) => "functionCall" in part
);
return functionCallParts == null || functionCallParts.length === 0 ? void 0 : functionCallParts.map((part) => ({
toolCallType: "function",
toolCallId: generateId(),
toolName: part.functionCall.name,
args: JSON.stringify(part.functionCall.args)
}));
}
function getTextFromParts(parts) {
const textParts = parts == null ? void 0 : parts.filter(
(part) => "text" in part && part.thought !== true
);
return textParts == null || textParts.length === 0 ? void 0 : textParts.map((part) => part.text).join("");
}
function getReasoningDetailsFromParts(parts) {
const reasoningParts = parts == null ? void 0 : parts.filter(
(part) => "text" in part && part.thought === true && part.text != null
);
return reasoningParts == null || reasoningParts.length === 0 ? void 0 : reasoningParts.map((part) => ({ type: "text", text: part.text }));
}
function getInlineDataParts(parts) {
return parts == null ? void 0 : parts.filter(
(part) => "inlineData" in part
);
}
function extractSources({
groundingMetadata,
generateId
}) {
var _a;
return (_a = groundingMetadata == null ? void 0 : groundingMetadata.groundingChunks) == null ? void 0 : _a.filter(
(chunk) => chunk.web != null
).map((chunk) => ({
sourceType: "url",
id: generateId(),
url: chunk.web.uri,
title: chunk.web.title
}));
}
var contentSchema = z2.object({
parts: z2.array(
z2.union([
// note: order matters since text can be fully empty
z2.object({
functionCall: z2.object({
name: z2.string(),
args: z2.unknown()
})
}),
z2.object({
inlineData: z2.object({
mimeType: z2.string(),
data: z2.string()
})
}),
z2.object({
text: z2.string().nullish(),
thought: z2.boolean().nullish()
})
])
).nullish()
});
var groundingChunkSchema = z2.object({
web: z2.object({ uri: z2.string(), title: z2.string() }).nullish(),
retrievedContext: z2.object({ uri: z2.string(), title: z2.string() }).nullish()
});
var groundingMetadataSchema = z2.object({
webSearchQueries: z2.array(z2.string()).nullish(),
retrievalQueries: z2.array(z2.string()).nullish(),
searchEntryPoint: z2.object({ renderedContent: z2.string() }).nullish(),
groundingChunks: z2.array(groundingChunkSchema).nullish(),
groundingSupports: z2.array(
z2.object({
segment: z2.object({
startIndex: z2.number().nullish(),
endIndex: z2.number().nullish(),
text: z2.string().nullish()
}),
segment_text: z2.string().nullish(),
groundingChunkIndices: z2.array(z2.number()).nullish(),
supportChunkIndices: z2.array(z2.number()).nullish(),
confidenceScores: z2.array(z2.number()).nullish(),
confidenceScore: z2.array(z2.number()).nullish()
})
).nullish(),
retrievalMetadata: z2.union([
z2.object({
webDynamicRetrievalScore: z2.number()
}),
z2.object({})
]).nullish()
});
var safetyRatingSchema = z2.object({
category: z2.string().nullish(),
probability: z2.string().nullish(),
probabilityScore: z2.number().nullish(),
severity: z2.string().nullish(),
severityScore: z2.number().nullish(),
blocked: z2.boolean().nullish()
});
var responseSchema = z2.object({
candidates: z2.array(
z2.object({
content: contentSchema.nullish().or(z2.object({}).strict()),
finishReason: z2.string().nullish(),
safetyRatings: z2.array(safetyRatingSchema).nullish(),
groundingMetadata: groundingMetadataSchema.nullish()
})
),
usageMetadata: z2.object({
promptTokenCount: z2.number().nullish(),
candidatesTokenCount: z2.number().nullish(),
totalTokenCount: z2.number().nullish()
}).nullish()
});
var chunkSchema = z2.object({
candidates: z2.array(
z2.object({
content: contentSchema.nullish(),
finishReason: z2.string().nullish(),
safetyRatings: z2.array(safetyRatingSchema).nullish(),
groundingMetadata: groundingMetadataSchema.nullish()
})
).nullish(),
usageMetadata: z2.object({
promptTokenCount: z2.number().nullish(),
candidatesTokenCount: z2.number().nullish(),
totalTokenCount: z2.number().nullish()
}).nullish()
});
var googleGenerativeAIProviderOptionsSchema = z2.object({
responseModalities: z2.array(z2.enum(["TEXT", "IMAGE"])).nullish(),
thinkingConfig: z2.object({
thinkingBudget: z2.number().nullish(),
includeThoughts: z2.boolean().nullish()
}).nullish()
});
export {
GoogleGenerativeAILanguageModel,
groundingMetadataSchema,
safetyRatingSchema
};
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