@juspay/neurolink/dist/providers/amazonBedrock/client.d.ts

The pipe layer of an AI nervous system: one interface connecting provider neurons to your application, across three inference types — generate, stream and decide. `decide` returns typed, calibrated judgements from a non-generative model (~400ms, ~$0.00002

import { BedrockRuntimeClient } from "@aws-sdk/client-bedrock-runtime";
import type { AIProviderName } from "../../constants/enums.js";
import { BaseProvider } from "../../core/baseProvider.js";
import type { NeuroLink } from "../../neurolink.js";
import type { EmbedInput, StreamOptions, StreamResult, EnhancedGenerateResult, TextGenerationOptions } from "../../types/index.js";
export declare class AmazonBedrockProvider extends BaseProvider {
    private bedrockClient;
    private conversationHistory;
    private region;
    /**
     * Parse the region segment from a Bedrock ARN.
     * Returns null when the input is not an ARN.
     *
     * Supports all AWS partitions:
     * - `arn:aws:bedrock:…`        (commercial)
     * - `arn:aws-cn:bedrock:…`     (China)
     * - `arn:aws-us-gov:bedrock:…` (GovCloud)
     */
    private static extractRegionFromArn;
    constructor(modelName?: string, neurolink?: NeuroLink, region?: string, credentials?: {
        accessKeyId?: string;
        secretAccessKey?: string;
        sessionToken?: string;
        region?: string;
    });
    /**
     * Perform initial health check to catch credential/connectivity issues early
     * This prevents the health check failure we saw in production logs
     */
    private performInitialHealthCheck;
    getAISDKModel(): never;
    getProviderName(): AIProviderName;
    getDefaultModel(): string;
    /**
     * Get the default embedding model for Amazon Bedrock
     * @returns The default Bedrock embedding model name
     */
    protected getDefaultEmbeddingModel(): string;
    generate(optionsOrPrompt: TextGenerationOptions | string): Promise<EnhancedGenerateResult | null>;
    private conversationLoop;
    private convertToAWSMessages;
    /**
     * `tools` is passed in rather than re-resolved from `getAllTools()`. That
     * call returns only the provider's own registry, so resolving here meant a
     * tool the caller passed to generate/stream could never execute — the
     * streaming path advertised it to the model and then failed every call to
     * it with "Tool not found", and the generate path never advertised it at
     * all. The turn's full merged tool set is resolved once by the caller and
     * handed down.
     */
    private executeSingleTool;
    /**
     * Resolve the turn's tools once: whatever the caller passed, else the
     * provider's own registry. `BaseProvider.stream()` has already merged base
     * tools into `options.tools` by the time it reaches the streaming path;
     * the generate path has no such pre-merge, so it falls back here.
     */
    private resolveTurnTools;
    /**
     * Present the resolved tools in the shape `runAgenticLoop` dispatches
     * through. Execution still goes through `executeSingleTool`, so the tool
     * span, the parameter defaults and the ToolResult unwrapping are unchanged
     * — only which tools are reachable changes.
     */
    private toEngineTools;
    private convertAISDKToolsToToolDefinitions;
    private formatToolsForBedrock;
    private convertToBedrockMessages;
    getBedrockClient(): BedrockRuntimeClient;
    protected executeStream(options: StreamOptions): Promise<StreamResult>;
    /**
     * A multimodal turn skips model middleware (see modelBridge.ts's header).
     * WARN when middleware was configured, per request or on the provider,
     * since it silently did not run; multimodal turns alone are unremarkable,
     * so stay at debug otherwise.
     */
    private logMultimodalMiddlewareSkip;
    /**
     * `inferenceConfig` carries `maxTokens` and `temperature` only, so any other
     * sampling option a middleware sets would be dropped without a trace.
     * `tools` is reported where it is compared, at each call site.
     */
    private warnOnUnsentMiddlewareOptions;
    /**
     * Runs the turn behind `streamingConversationLoop`: the model-middleware
     * path for a text-only starting turn, or the direct fallback for a
     * multimodal one. Extracted only to keep `streamingConversationLoop`
     * readable — the branching logic itself is unchanged from what it
     * replaced.
     */
    private buildBedrockStreamTurn;
    /**
     * Turns a settled loop outcome's usage into the shape both the analytics
     * resolution and the stream's own `finally` block report. Shared so the
     * two call sites in `streamingConversationLoop` can't drift.
     */
    private summarizeBedrockStreamUsage;
    private streamingConversationLoop;
    /**
     * Health check for Amazon Bedrock service
     * Uses ListFoundationModels API to validate connectivity and permissions
     */
    checkBedrockHealth(): Promise<void>;
    protected formatProviderError(error: unknown): Error;
    /**
     * Generate embeddings for text or multi-modal input using Amazon Bedrock.
     * Supports both text-only models (Titan Embed Text) and multi-modal models
     * (Titan Embed Image, Nova Multimodal Embeddings).
     *
     * @param input - Text string or EmbedInput with text/image/mimeType
     * @param modelName - The embedding model to use (default: amazon.titan-embed-text-v2:0)
     * @returns Promise resolving to the embedding vector
     */
    embed(input: string | EmbedInput, modelName?: string): Promise<number[]>;
    /**
     * Generate embeddings for multiple texts in a single batch
     * @param texts - The texts to embed
     * @param modelName - The embedding model to use (default: amazon.titan-embed-text-v2:0)
     * @returns Promise resolving to an array of embedding vectors
     */
    embedMany(texts: string[], modelName?: string): Promise<number[][]>;
}