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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,120 @@ | ||
| export type GoogleModel = { | ||
| maxTokens: number; | ||
| cost: { | ||
| prompt: number; | ||
| completion: number; | ||
| }; | ||
| displayName: string; | ||
| }; | ||
|
|
||
| export const googleModels = { | ||
| 'gemini-pro': { | ||
| maxTokens: 32760, | ||
| cost: { | ||
| prompt: NaN, | ||
| completion: NaN, | ||
| }, | ||
| displayName: 'Gemini Pro', | ||
| }, | ||
| 'gemini-pro-vision': { | ||
| maxTokens: 16384, | ||
| cost: { | ||
| prompt: NaN, | ||
| completion: NaN, | ||
| }, | ||
| displayName: 'Gemini Pro Vision', | ||
| }, | ||
| } satisfies Record<string, GoogleModel>; | ||
|
|
||
| export type GoogleModels = keyof typeof googleModels; | ||
|
|
||
| export const googleModelOptions = Object.entries(googleModels).map(([id, { displayName }]) => ({ | ||
| value: id, | ||
| label: displayName, | ||
| })); | ||
|
|
||
| export interface GoogleChatMessage { | ||
| role: 'user' | 'assistant'; | ||
| parts: ({ | ||
| text: string; | ||
| } | { | ||
| inline_data: { | ||
| mime_type: string; | ||
| data: string; | ||
| }; | ||
| })[] | ||
| } | ||
|
|
||
| export type ChatCompletionOptions = { | ||
| project: string; | ||
| location: string; | ||
| applicationCredentials: string; | ||
| model: GoogleModels; | ||
| prompt: GoogleChatMessage[]; | ||
| max_output_tokens: number; | ||
| temperature?: number; | ||
| top_p?: number; | ||
| top_k?: number; | ||
| signal?: AbortSignal; | ||
| }; | ||
|
|
||
| export type ChatCompletionChunk = { | ||
| completion: string; | ||
| finish_reason: 'FINISH_REASON_UNSPECIFIED' | 'FINISH_REASON_STOP' | 'FINISH_REASON_MAX_TOKENS' | 'FINISH_REASON_SAFETY' | 'FINISH_REASON_RECITATION' | 'FINISH_REASON_OTHER' | undefined; | ||
| model: string; | ||
| }; | ||
|
|
||
| export async function* streamChatCompletions({ | ||
| project, | ||
| location, | ||
| applicationCredentials, | ||
| model, | ||
| signal, | ||
| max_output_tokens, | ||
| temperature, | ||
| top_p, | ||
| top_k, | ||
| prompt, | ||
| }: ChatCompletionOptions): AsyncGenerator<ChatCompletionChunk> { | ||
| const defaultSignal = new AbortController().signal; | ||
|
|
||
| // If you import normally, the Google auth library throws a fit. | ||
| const { VertexAI } = await import('@google-cloud/vertexai'); | ||
|
|
||
| // Can't find a way to pass the credentials path in | ||
| process.env['GOOGLE_APPLICATION_CREDENTIALS'] = applicationCredentials; | ||
| const vertexAi = new VertexAI({ project, location }); | ||
| const generativeModel = vertexAi.preview.getGenerativeModel({ | ||
| model, | ||
| generation_config: { | ||
| max_output_tokens, | ||
| temperature, | ||
| top_p, | ||
| top_k, | ||
| } | ||
| }); | ||
| const response = await generativeModel.generateContentStream({ | ||
| contents: prompt, | ||
| }); | ||
|
|
||
| let hadChunks = false; | ||
|
|
||
| for await (const chunk of response.stream) { | ||
| console.log('streaming google responses') | ||
| hadChunks = true; | ||
|
|
||
| if (!signal?.aborted && chunk.candidates[0]?.content.parts[0]?.text) { | ||
| yield { | ||
| completion: chunk.candidates[0]?.content.parts[0]?.text, | ||
| finish_reason: chunk.candidates[0]?.finishReason as any, | ||
| model, | ||
| }; | ||
| } else { | ||
| return; | ||
| } | ||
| } | ||
|
|
||
| if (!hadChunks) { | ||
| throw new Error(`No chunks received.`); | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,3 @@ | ||
| import { googlePlugin } from './plugin.js'; | ||
|
|
||
| export default googlePlugin; |
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