@antl3x/toolrag
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Context-aware tool retrieval for language models - unlock the full potential of LLM function calling without context window limitations or constraints.
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TypeScript
import { EmbeddingProvider } from './EmbeddingProvider.js';
import * as aiplatform from '@google-cloud/aiplatform';
import { z } from 'zod';
declare const EmbeddingProviderGoogleConfigSchema: z.ZodDefault<z.ZodObject<{
model: z.ZodDefault<z.ZodString>;
projectId: z.ZodEffects<z.ZodOptional<z.ZodString>, string | undefined, string | undefined>;
location: z.ZodDefault<z.ZodString>;
dimensions: z.ZodDefault<z.ZodNumber>;
taskType: z.ZodDefault<z.ZodString>;
client: z.ZodOptional<z.ZodType<aiplatform.v1.PredictionServiceClient, z.ZodTypeDef, aiplatform.v1.PredictionServiceClient>>;
}, "strip", z.ZodTypeAny, {
model: string;
location: string;
dimensions: number;
taskType: string;
projectId?: string | undefined;
client?: aiplatform.v1.PredictionServiceClient | undefined;
}, {
model?: string | undefined;
projectId?: string | undefined;
location?: string | undefined;
dimensions?: number | undefined;
taskType?: string | undefined;
client?: aiplatform.v1.PredictionServiceClient | undefined;
}>>;
type EmbeddingProviderGoogleConfig = z.infer<typeof EmbeddingProviderGoogleConfigSchema>;
/**
* Google implementation of the EmbeddingProvider
*/
export declare class EmbeddingProviderGoogle implements EmbeddingProvider {
private _config;
private _client;
private _endpoint;
constructor(config?: EmbeddingProviderGoogleConfig);
getEmbedding(text: string): Promise<number[]>;
getDimensions(): number;
getName(): string;
getModel(): string;
}
export {};
//# sourceMappingURL=EmbeddingProviderGoogle.d.ts.map