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web.ts
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web.ts
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import { GoogleVertexAILLMConnection } from "../../utils/googlevertexai-connection.js";
import {
WebGoogleAuthOptions,
WebGoogleAuth,
} from "../../utils/googlevertexai-webauth.js";
import { BaseChatGoogleVertexAI, GoogleVertexAIChatInput } from "./common.js";
/**
* Enables calls to the Google Cloud's Vertex AI API to access
* Large Language Models in a chat-like fashion.
*
* This entrypoint and class are intended to be used in web environments like Edge
* functions where you do not have access to the file system. It supports passing
* service account credentials directly as a "GOOGLE_VERTEX_AI_WEB_CREDENTIALS"
* environment variable or directly as "authOptions.credentials".
* @example
* ```typescript
* const model = new ChatGoogleVertexAI({
* temperature: 0.7,
* });
* const result = await model.invoke(
* "How do I implement a binary search algorithm in Python?",
* );
* ```
*/
export class ChatGoogleVertexAI extends BaseChatGoogleVertexAI<WebGoogleAuthOptions> {
static lc_name() {
return "ChatVertexAI";
}
get lc_secrets(): { [key: string]: string } {
return {
"authOptions.credentials": "GOOGLE_VERTEX_AI_WEB_CREDENTIALS",
};
}
constructor(fields?: GoogleVertexAIChatInput<WebGoogleAuthOptions>) {
super(fields);
const client = new WebGoogleAuth(fields?.authOptions);
this.connection = new GoogleVertexAILLMConnection(
{ ...fields, ...this },
this.caller,
client,
false
);
this.streamedConnection = new GoogleVertexAILLMConnection(
{ ...fields, ...this },
this.caller,
client,
true
);
}
}
export type {
ChatExample,
GoogleVertexAIChatAuthor,
GoogleVertexAIChatInput,
GoogleVertexAIChatInstance,
GoogleVertexAIChatMessage,
GoogleVertexAIChatMessageFields,
GoogleVertexAIChatPrediction,
} from "./common.js";