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chore: import upstream snapshot with attribution
2026-07-13 13:20:55 +08:00

43 lines
1.3 KiB
TypeScript

import { GoogleGenAI } from '@google/genai'
import { createLogger } from '@sim/logger'
import type { StreamingExecution } from '@/executor/types'
import { executeGeminiRequest } from '@/providers/gemini/core'
import { getProviderDefaultModel, getProviderModels } from '@/providers/models'
import type { ProviderConfig, ProviderRequest, ProviderResponse } from '@/providers/types'
const logger = createLogger('GoogleProvider')
/**
* Google Gemini provider
*
* Uses the @google/genai SDK with API key authentication.
* Shares core execution logic with Vertex AI provider.
*/
export const googleProvider: ProviderConfig = {
id: 'google',
name: 'Google',
description: "Google's Gemini models",
version: '1.0.0',
models: getProviderModels('google'),
defaultModel: getProviderDefaultModel('google'),
executeRequest: async (
request: ProviderRequest
): Promise<ProviderResponse | StreamingExecution> => {
if (!request.apiKey) {
throw new Error('API key is required for Google Gemini')
}
logger.info('Creating Google Gemini client', { model: request.model })
const ai = new GoogleGenAI({ apiKey: request.apiKey })
return executeGeminiRequest({
ai,
model: request.model,
request,
providerType: 'google',
})
},
}