@juspay/neurolink
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Universal AI Development Platform with working MCP integration, multi-provider support, voice (TTS/STT/realtime), and professional CLI. 58+ external MCP servers discoverable, multimodal file processing, RAG pipelines. Build, test, and deploy AI applicatio
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JavaScript
/**
* Amazon SageMaker Provider Implementation (Simplified)
*
* This module provides a simplified SageMaker provider that extends BaseProvider
* and integrates with the NeuroLink ecosystem using existing patterns.
*/
import { BaseProvider } from "../core/baseProvider.js";
import { logger } from "../utils/logger.js";
import { withSpan } from "../telemetry/withSpan.js";
import { tracers } from "../telemetry/tracers.js";
// SageMaker-specific imports
import { getDefaultSageMakerEndpoint, getSageMakerConfig, getSageMakerModel, getSageMakerModelConfig, } from "./sagemaker/config.js";
import { handleSageMakerError, SageMakerError } from "./sagemaker/errors.js";
import { SageMakerLanguageModel } from "./sagemaker/language-model.js";
/**
* Amazon SageMaker Provider extending BaseProvider
*/
export class AmazonSageMakerProvider extends BaseProvider {
sagemakerModel;
sagemakerConfig;
modelConfig;
constructor(modelName, endpointName, region, neurolink, credentials) {
super(modelName, "sagemaker", neurolink);
try {
// Load and validate configuration, then overlay per-request credentials
const baseConfig = getSageMakerConfig(credentials?.region ?? region);
this.sagemakerConfig = {
...baseConfig,
...(credentials?.region !== undefined && {
region: credentials.region,
}),
...(credentials?.accessKeyId !== undefined && {
accessKeyId: credentials.accessKeyId,
}),
...(credentials?.secretAccessKey !== undefined && {
secretAccessKey: credentials.secretAccessKey,
}),
...(credentials?.sessionToken !== undefined && {
sessionToken: credentials.sessionToken,
}),
...(credentials?.endpoint !== undefined && {
endpoint: credentials.endpoint,
}),
};
this.modelConfig = getSageMakerModelConfig(endpointName || getDefaultSageMakerEndpoint());
// Create the SageMaker LanguageModel implementation.
// SageMakerLanguageModel implements SageMakerAsLanguageModel which is
// structurally compatible with LanguageModelV2 (specificationVersion "v2",
// modelId, provider, supportedUrls, doGenerate, doStream).
const smModel = new SageMakerLanguageModel(this.modelName, this.sagemakerConfig, this.modelConfig);
this.sagemakerModel = smModel;
logger.debug("Amazon SageMaker Provider initialized", {
modelName: this.modelName,
endpointName: this.modelConfig.endpointName,
region: this.sagemakerConfig.region,
provider: this.providerName,
});
}
catch (error) {
logger.error("Failed to initialize SageMaker provider", {
error: error instanceof Error ? error.message : String(error),
modelName,
endpointName,
});
throw handleSageMakerError(error);
}
}
getProviderName() {
return "sagemaker";
}
getDefaultModel() {
return getSageMakerModel();
}
getAISDKModel() {
return this.sagemakerModel;
}
async executeStream(_options, _analysisSchema) {
return withSpan({
name: "neurolink.provider.sagemaker.stream",
tracer: tracers.stream,
attributes: {
"provider.name": "sagemaker",
"model.name": this.modelName,
"sagemaker.endpoint": this.modelConfig.endpointName,
"sagemaker.region": this.sagemakerConfig.region,
"sagemaker.not_implemented": true,
},
}, async () => {
try {
// For now, throw an error indicating this is not yet implemented
throw new SageMakerError("SageMaker streaming not yet fully implemented. Coming in next phase.", {
code: "MODEL_ERROR",
statusCode: 501,
endpoint: this.modelConfig.endpointName,
});
}
catch (error) {
throw this.handleProviderError(error);
}
});
}
formatProviderError(error) {
if (error instanceof SageMakerError) {
return error;
}
if (error instanceof Error && error.name === "TimeoutError") {
return new SageMakerError(`SageMaker request timed out. Consider increasing timeout.`, {
code: "NETWORK_ERROR",
statusCode: 408,
cause: error,
endpoint: this.modelConfig.endpointName,
});
}
return handleSageMakerError(error, this.modelConfig.endpointName);
}
/**
* Get SageMaker-specific provider information
*/
getSageMakerInfo() {
return {
endpointName: this.modelConfig.endpointName,
modelType: this.modelConfig.modelType || "custom",
region: this.sagemakerConfig.region,
configured: !!(this.sagemakerConfig.accessKeyId && this.sagemakerConfig.secretAccessKey),
};
}
/**
* Test basic configuration
*/
async testConnection() {
try {
// Basic validation test
if (!this.sagemakerConfig.accessKeyId ||
!this.sagemakerConfig.secretAccessKey) {
return {
connected: false,
error: "AWS credentials not configured",
};
}
if (!this.modelConfig.endpointName ||
this.modelConfig.endpointName === "default-endpoint") {
return {
connected: false,
error: "SageMaker endpoint not configured",
};
}
// For now, just return that configuration looks valid
return {
connected: true,
};
}
catch (error) {
return {
connected: false,
error: error instanceof Error ? error.message : String(error),
};
}
}
/**
* Public method to get the AI SDK model for CLI and external usage
*/
async getModel() {
return this.getAISDKModel();
}
/**
* Test connectivity to the SageMaker endpoint
*/
async testConnectivity() {
const model = this.sagemakerModel;
return model.testConnectivity
? await model.testConnectivity()
: { success: false, error: "Test method not available" };
}
/**
* Get model capabilities and information
*/
getModelCapabilities() {
const model = this.sagemakerModel;
return model.getModelCapabilities
? model.getModelCapabilities()
: {
capabilities: {
streaming: true,
toolCalling: true,
structuredOutput: true,
batchInference: true,
supportedResponseFormats: ["text", "json_object"],
supportedToolTypes: ["function"],
maxBatchSize: 10,
},
};
}
}
export default AmazonSageMakerProvider;
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