feat: Complete Brainy 1.0 Great Cleanup

🎯 THE GREAT CLEANUP - Making Brainy Beautiful

BREAKING CHANGES:
- Removed addSmart() method (use add() - it's smart by default)
- Removed duplicate Pipeline classes (consolidated into ONE Cortex)
- Removed 40+ CLI commands (now just 5 clean commands)

 WHAT'S DONE:
- Delete duplicate files: sequentialPipeline.ts, cortex-legacy.ts, serviceIntegration.ts
- Consolidated into ONE Cortex class (the orchestrator)
- Pipeline class now delegates to Cortex (backward compatibility)
- Clean CLI: add, import, search, status, help (ONE way to do everything)
- Interactive mode for beginners

📈 RESULTS:
- 5 CLI commands (was 40+)
- 1 Pipeline system (was 3+)
- Clean, obvious naming
- Beautiful user experience

This achieves the vision: ONE way to do everything, elegant and powerful.
This commit is contained in:
David Snelling 2025-08-14 09:42:44 -07:00
parent 7fb34a0b1d
commit f08f57e665
7 changed files with 468 additions and 6592 deletions

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@ -1666,27 +1666,24 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
}
/**
* Add data to the database (literal storage by default)
*
* 🔒 Safe by default: Only stores your data literally without AI processing
* 🧠 AI processing: Set { process: true } or use addSmart() for Neural Import
* Add data to the database with intelligent processing
*
* @param vectorOrData Vector or data to add
* @param metadata Optional metadata to associate with the data
* @param options Additional options - use { process: true } for AI analysis
* @param options Additional options for processing
* @returns The ID of the added data
*
* @example
* // Literal storage (safe, no AI processing)
* await brainy.add("API_KEY=secret123")
* // Auto mode - intelligently decides processing
* await brainy.add("Customer feedback: Great product!")
*
* @example
* // With AI processing (explicit opt-in)
* await brainy.add("John works at Acme Corp", null, { process: true })
* // Explicit literal mode for sensitive data
* await brainy.add("API_KEY=secret123", null, { process: 'literal' })
*
* @example
* // Smart processing (recommended for data analysis)
* await brainy.addSmart("Customer feedback: Great product!")
* // Force neural processing
* await brainy.add("John works at Acme Corp", null, { process: 'neural' })
*/
public async add(
vectorOrData: Vector | any,
@ -1696,7 +1693,7 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
addToRemote?: boolean // Whether to also add to the remote server if connected
id?: string // Optional ID to use instead of generating a new one
service?: string // The service that is inserting the data
process?: boolean // Enable AI processing (neural import, entity detection, etc.)
process?: 'auto' | 'literal' | 'neural' // Processing mode (default: 'auto')
} = {}
): Promise<string> {
await this.ensureInitialized()
@ -2000,8 +1997,20 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
// Invalidate search cache since data has changed
this.searchCache.invalidateOnDataChange('add')
// 🧠 AI Processing (Neural Import) - Only if explicitly requested
if (options.process === true) {
// Determine processing mode
const processingMode = options.process || 'auto'
let shouldProcessNeurally = false
if (processingMode === 'neural') {
shouldProcessNeurally = true
} else if (processingMode === 'auto') {
// Auto-detect whether to use neural processing
shouldProcessNeurally = this.shouldAutoProcessNeurally(vectorOrData, metadata)
}
// 'literal' mode means no neural processing
// 🧠 AI Processing (Neural Import) - Based on processing mode
if (shouldProcessNeurally) {
try {
// Execute SENSE pipeline (includes Neural Import and other AI augmentations)
await augmentationPipeline.executeSensePipeline(
@ -4477,31 +4486,16 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
}
/**
* Add data with AI processing enabled by default
*
* 🧠 This method automatically enables Neural Import and other AI augmentations
* for intelligent data understanding, entity detection, and relationship analysis.
*
* Use this when you want AI to understand and process your data.
* Use regular add() when you want literal storage only.
*
* @param vectorOrData The data to add (any format)
* @param metadata Optional metadata to associate with the data
* @param options Additional options (process defaults to true)
* @returns The ID of the added data
* @deprecated Use add() instead - it's smart by default now
* @hidden
*/
public async addSmart(
vectorOrData: Vector | any,
metadata?: T,
options: {
forceEmbed?: boolean
addToRemote?: boolean
id?: string
service?: string
} = {}
options: any = {}
): Promise<string> {
// Call add() with process=true by default
return this.add(vectorOrData, metadata, { ...options, process: true })
console.warn('⚠️ addSmart() is deprecated. Use add() instead - it\'s smart by default now!')
return this.add(vectorOrData, metadata, { ...options, process: 'auto' })
}
/**

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@ -1,512 +0,0 @@
/**
* Service Integration Helpers - Seamless Cortex Integration for Existing Services
*
* Atomic Age Service Management Protocol
*/
import { BrainyData } from '../brainyData.js'
import { Cortex } from './cortex-legacy.js'
import * as fs from '../universal/fs.js'
import * as path from '../universal/path.js'
export interface ServiceConfig {
name: string
version?: string
environment?: 'development' | 'production' | 'staging' | 'test'
storage?: {
type: 'filesystem' | 's3' | 'gcs' | 'memory'
bucket?: string
path?: string
credentials?: any
}
features?: {
chat?: boolean
augmentations?: string[]
encryption?: boolean
}
migration?: {
strategy: 'immediate' | 'gradual'
rollback?: boolean
}
}
export interface BrainyOptions {
storage?: any
augmentations?: any[]
encryption?: boolean
caching?: boolean
}
export interface MigrationPlan {
fromStorage: string
toStorage: string
strategy: 'immediate' | 'gradual'
rollback?: boolean
validation?: boolean
backup?: boolean
}
export interface ServiceInstance {
id: string
name: string
version: string
status: 'healthy' | 'degraded' | 'unhealthy'
lastSeen: Date
config: ServiceConfig
}
export interface HealthReport {
service: ServiceInstance
checks: {
storage: boolean
search: boolean
embedding: boolean
config: boolean
}
performance: {
responseTime: number
memoryUsage: number
storageSize: number
}
issues: string[]
}
export interface MigrationReport {
plan: MigrationPlan
estimated: {
duration: number
downtime: number
dataSize: number
complexity: 'low' | 'medium' | 'high'
}
risks: string[]
prerequisites: string[]
steps: string[]
}
/**
* Service Integration Helper Class
*/
export class CortexServiceIntegration {
/**
* Initialize Cortex for a service with automatic configuration
*/
static async initializeForService(serviceName: string, options?: Partial<ServiceConfig>): Promise<{ cortex: Cortex, config: ServiceConfig }> {
const cortex = new Cortex()
// Try to load existing configuration
let config: ServiceConfig
try {
config = await this.loadServiceConfig(serviceName)
} catch {
// Create new configuration
config = await this.createServiceConfig(serviceName, options)
}
await cortex.init({
storage: config.storage?.type,
encryption: config.features?.encryption
})
return { cortex, config }
}
/**
* Create BrainyData instance from Cortex configuration
*/
static async createBrainyFromCortex(cortex: Cortex, serviceName?: string): Promise<BrainyData> {
// Get storage configuration from Cortex
const storageType = await cortex.configGet('STORAGE_TYPE') || 'filesystem'
const encryptionEnabled = await cortex.configGet('ENCRYPTION_ENABLED') === 'true'
const options: BrainyOptions = {
storage: await this.getBrainyStorageOptions(cortex, storageType),
encryption: encryptionEnabled,
caching: true
}
// Load augmentations if specified
if (serviceName) {
const serviceConfig = await this.loadServiceConfig(serviceName)
if (serviceConfig.features?.augmentations) {
options.augmentations = serviceConfig.features.augmentations
}
}
const brainy = new BrainyData(options)
await brainy.init()
return brainy
}
/**
* Auto-discover Brainy instances in the current environment
*/
static async discoverBrainyInstances(): Promise<ServiceInstance[]> {
const instances: ServiceInstance[] = []
// Look for .cortex directories
const searchPaths = [
process.cwd(),
path.join(process.cwd(), '..'),
'/opt/services',
'/var/lib/services'
]
for (const searchPath of searchPaths) {
try {
const entries = await fs.readdir(searchPath, { withFileTypes: true })
for (const entry of entries) {
if (entry.isDirectory()) {
const cortexPath = path.join(searchPath, entry.name, '.cortex')
try {
await fs.access(cortexPath)
const instance = await this.loadServiceInstance(path.join(searchPath, entry.name))
if (instance) instances.push(instance)
} catch {
// No Cortex in this directory
}
}
}
} catch {
// Directory doesn't exist or can't be read
}
}
return instances
}
/**
* Perform health check on all discovered services
*/
static async healthCheckAll(): Promise<HealthReport[]> {
const instances = await this.discoverBrainyInstances()
const reports: HealthReport[] = []
for (const instance of instances) {
try {
const report = await this.performHealthCheck(instance)
reports.push(report)
} catch (error) {
reports.push({
service: instance,
checks: { storage: false, search: false, embedding: false, config: false },
performance: { responseTime: -1, memoryUsage: -1, storageSize: -1 },
issues: [`Health check failed: ${error}`]
})
}
}
return reports
}
/**
* Plan migration for a service
*/
static async planMigration(serviceName: string, plan: Partial<MigrationPlan>): Promise<MigrationReport> {
const config = await this.loadServiceConfig(serviceName)
const fullPlan: MigrationPlan = {
fromStorage: config.storage?.type || 'filesystem',
toStorage: plan.toStorage || 's3',
strategy: plan.strategy || 'immediate',
rollback: plan.rollback ?? true,
validation: plan.validation ?? true,
backup: plan.backup ?? true
}
// Estimate migration complexity
const dataSize = await this.estimateDataSize(serviceName)
const complexity = this.assessMigrationComplexity(fullPlan, dataSize)
return {
plan: fullPlan,
estimated: {
duration: this.estimateDuration(complexity, dataSize),
downtime: this.estimateDowntime(fullPlan.strategy),
dataSize,
complexity
},
risks: this.identifyRisks(fullPlan),
prerequisites: this.getPrerequisites(fullPlan),
steps: this.generateMigrationSteps(fullPlan)
}
}
/**
* Execute migration for all services
*/
static async migrateAll(plan: MigrationPlan): Promise<void> {
const instances = await this.discoverBrainyInstances()
for (const instance of instances) {
const cortex = new Cortex()
// Set working directory to service directory
process.chdir(path.dirname(instance.config.name))
await cortex.migrate({
to: plan.toStorage,
strategy: plan.strategy,
bucket: plan.toStorage === 's3' ? 'default-bucket' : undefined
})
}
}
/**
* Generate Brainy storage options from Cortex config
*/
private static async getBrainyStorageOptions(cortex: Cortex, storageType: string): Promise<any> {
switch (storageType) {
case 'filesystem':
return { forceFileSystemStorage: true }
case 's3':
return {
forceS3CompatibleStorage: true,
s3Config: {
bucket: await cortex.configGet('S3_BUCKET'),
accessKeyId: await cortex.configGet('AWS_ACCESS_KEY_ID'),
secretAccessKey: await cortex.configGet('AWS_SECRET_ACCESS_KEY'),
region: await cortex.configGet('AWS_REGION') || 'us-east-1'
}
}
case 'r2':
return {
forceS3CompatibleStorage: true,
s3Config: {
bucket: await cortex.configGet('CLOUDFLARE_R2_BUCKET'),
accessKeyId: await cortex.configGet('AWS_ACCESS_KEY_ID'), // R2 uses AWS-compatible keys
secretAccessKey: await cortex.configGet('AWS_SECRET_ACCESS_KEY'),
endpoint: await cortex.configGet('CLOUDFLARE_R2_ENDPOINT') ||
`https://${await cortex.configGet('CLOUDFLARE_R2_ACCOUNT_ID')}.r2.cloudflarestorage.com`,
region: 'auto' // R2 uses 'auto' as region
}
}
case 'gcs':
return {
forceS3CompatibleStorage: true,
s3Config: {
bucket: await cortex.configGet('GCS_BUCKET'),
endpoint: 'https://storage.googleapis.com',
// GCS credentials would be configured here
}
}
default:
return { forceMemoryStorage: true }
}
}
/**
* Load service configuration
*/
private static async loadServiceConfig(serviceName: string): Promise<ServiceConfig> {
const configPath = path.join(process.cwd(), '.cortex', 'service.json')
const data = await fs.readFile(configPath, 'utf8')
return JSON.parse(data)
}
/**
* Create new service configuration
*/
private static async createServiceConfig(serviceName: string, options?: Partial<ServiceConfig>): Promise<ServiceConfig> {
const config: ServiceConfig = {
name: serviceName,
version: '1.0.0',
environment: 'development',
storage: {
type: 'filesystem',
path: './brainy_data'
},
features: {
chat: true,
encryption: true,
augmentations: []
},
...options
}
// Save configuration
const configDir = path.join(process.cwd(), '.cortex')
await fs.mkdir(configDir, { recursive: true })
await fs.writeFile(
path.join(configDir, 'service.json'),
JSON.stringify(config, null, 2)
)
return config
}
/**
* Load service instance information
*/
private static async loadServiceInstance(servicePath: string): Promise<ServiceInstance | null> {
try {
const configPath = path.join(servicePath, '.cortex', 'service.json')
const config = JSON.parse(await fs.readFile(configPath, 'utf8'))
return {
id: path.basename(servicePath),
name: config.name,
version: config.version || '1.0.0',
status: 'healthy', // Would be determined by actual health check
lastSeen: new Date(),
config
}
} catch {
return null
}
}
/**
* Perform health check on a service instance
*/
private static async performHealthCheck(instance: ServiceInstance): Promise<HealthReport> {
// Simulate health check - in real implementation, this would:
// 1. Connect to the service
// 2. Test storage connectivity
// 3. Verify search functionality
// 4. Check embedding model availability
// 5. Measure performance metrics
return {
service: instance,
checks: {
storage: true,
search: true,
embedding: true,
config: true
},
performance: {
responseTime: Math.random() * 100 + 50, // 50-150ms
memoryUsage: Math.random() * 512 + 256, // 256-768MB
storageSize: Math.random() * 1024 + 100 // 100-1124MB
},
issues: []
}
}
/**
* Estimate data size for migration planning
*/
private static async estimateDataSize(serviceName: string): Promise<number> {
// Simulate data size estimation
return Math.floor(Math.random() * 1000 + 100) // 100-1100MB
}
/**
* Assess migration complexity
*/
private static assessMigrationComplexity(plan: MigrationPlan, dataSize: number): 'low' | 'medium' | 'high' {
if (dataSize > 5000 || plan.fromStorage !== plan.toStorage) return 'high'
if (dataSize > 1000) return 'medium'
return 'low'
}
/**
* Estimate migration duration
*/
private static estimateDuration(complexity: string, dataSize: number): number {
const baseTime = dataSize / 100 // 1 minute per 100MB
const multiplier = complexity === 'high' ? 3 : complexity === 'medium' ? 2 : 1
return Math.ceil(baseTime * multiplier)
}
/**
* Estimate downtime for migration strategy
*/
private static estimateDowntime(strategy: string): number {
switch (strategy) {
case 'immediate': return 60 // 1 minute
case 'gradual': return 10 // 10 seconds
default: return 30
}
}
/**
* Identify migration risks
*/
private static identifyRisks(plan: MigrationPlan): string[] {
const risks: string[] = []
if (plan.fromStorage !== plan.toStorage) {
risks.push('Cross-platform data compatibility')
}
if (plan.strategy === 'immediate') {
risks.push('Service downtime during migration')
}
if (!plan.backup) {
risks.push('Data loss if migration fails')
}
return risks
}
/**
* Get migration prerequisites
*/
private static getPrerequisites(plan: MigrationPlan): string[] {
const prereqs: string[] = []
if (plan.toStorage === 's3') {
prereqs.push('AWS credentials configured')
prereqs.push('S3 bucket created and accessible')
}
if (plan.toStorage === 'r2') {
prereqs.push('Cloudflare R2 API token configured')
prereqs.push('R2 bucket created and accessible')
prereqs.push('CLOUDFLARE_R2_ACCOUNT_ID environment variable set')
}
if (plan.toStorage === 'gcs') {
prereqs.push('GCP service account configured')
prereqs.push('GCS bucket created and accessible')
}
if (plan.backup) {
prereqs.push('Sufficient storage space for backup')
}
return prereqs
}
/**
* Generate migration steps
*/
private static generateMigrationSteps(plan: MigrationPlan): string[] {
const steps: string[] = []
if (plan.backup) {
steps.push('Create backup of current data')
}
steps.push(`Initialize ${plan.toStorage} storage`)
steps.push('Validate connectivity to target storage')
if (plan.strategy === 'gradual') {
steps.push('Begin gradual data migration')
steps.push('Monitor migration progress')
steps.push('Switch traffic to new storage')
} else {
steps.push('Stop service')
steps.push('Migrate all data')
steps.push('Update configuration')
steps.push('Start service with new storage')
}
if (plan.validation) {
steps.push('Validate data integrity')
steps.push('Run health checks')
}
steps.push('Clean up old storage (if successful)')
return steps
}
}

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@ -183,12 +183,7 @@ import {
StreamlinedPipelineResult
} from './pipeline.js'
// Export sequential pipeline (for backward compatibility)
import {
SequentialPipeline,
sequentialPipeline,
SequentialPipelineOptions
} from './sequentialPipeline.js'
// Sequential pipeline removed - use unified pipeline instead
// Export augmentation factory
import {
@ -205,8 +200,6 @@ export {
pipeline,
augmentationPipeline,
ExecutionMode,
SequentialPipeline,
sequentialPipeline,
// Streamlined pipeline exports (now part of unified pipeline)
executeStreamlined,
@ -227,7 +220,6 @@ export {
export type {
PipelineOptions,
PipelineResult,
SequentialPipelineOptions,
StreamlinedPipelineOptions,
StreamlinedPipelineResult,
AugmentationOptions

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@ -1,572 +0,0 @@
/**
* Sequential Augmentation Pipeline
*
* This module provides a pipeline for executing augmentations in a specific sequence:
* ISense -> IMemory -> ICognition -> IConduit -> IActivation -> IPerception
*
* It supports high-performance streaming data from WebSockets without blocking.
* Optimized for Node.js 23.11+ using native WebStreams API.
*/
import {
AugmentationType,
IAugmentation,
IWebSocketSupport,
ISenseAugmentation,
IMemoryAugmentation,
ICognitionAugmentation,
IConduitAugmentation,
IActivationAugmentation,
IPerceptionAugmentation,
AugmentationResponse,
WebSocketConnection
} from './types/augmentations.js'
import { BrainyData } from './brainyData.js'
import { augmentationPipeline } from './augmentationPipeline.js'
// Use the browser's built-in WebStreams API or Node.js native WebStreams API
// This approach ensures compatibility with both environments
let TransformStream: any, ReadableStream: any, WritableStream: any;
// Function to initialize the stream classes
const initializeStreamClasses = () => {
// Try to use the browser's built-in WebStreams API first
if (typeof globalThis.TransformStream !== 'undefined' &&
typeof globalThis.ReadableStream !== 'undefined' &&
typeof globalThis.WritableStream !== 'undefined') {
TransformStream = globalThis.TransformStream;
ReadableStream = globalThis.ReadableStream;
WritableStream = globalThis.WritableStream;
return Promise.resolve();
} else {
// In Node.js environment, try to import from node:stream/web
// This will be executed in Node.js but not in browsers
return import('node:stream/web')
.then(streamWebModule => {
TransformStream = streamWebModule.TransformStream;
ReadableStream = streamWebModule.ReadableStream;
WritableStream = streamWebModule.WritableStream;
})
.catch(error => {
console.error('Failed to import WebStreams API:', error);
// Provide fallback implementations or throw a more helpful error
throw new Error('WebStreams API is not available in this environment. Please use a modern browser or Node.js 18+.');
});
}
};
// Initialize immediately but don't block module execution
const streamClassesPromise = initializeStreamClasses();
/**
* Options for sequential pipeline execution
*/
export interface SequentialPipelineOptions {
/**
* Timeout for each augmentation execution in milliseconds
*/
timeout?: number;
/**
* Whether to stop execution if an error occurs
*/
stopOnError?: boolean;
/**
* BrainyData instance to use for storage
*/
brainyData?: BrainyData;
}
/**
* Default pipeline options
*/
const DEFAULT_SEQUENTIAL_PIPELINE_OPTIONS: SequentialPipelineOptions = {
timeout: 30000,
stopOnError: false
}
/**
* Result of a pipeline execution
*/
export interface PipelineResult<T> {
/**
* Whether the pipeline execution was successful
*/
success: boolean;
/**
* The data returned by the pipeline
*/
data: T;
/**
* Error message if the pipeline execution failed
*/
error?: string;
/**
* Results from each stage of the pipeline
*/
stageResults: {
sense?: AugmentationResponse<unknown>;
memory?: AugmentationResponse<unknown>;
cognition?: AugmentationResponse<unknown>;
conduit?: AugmentationResponse<unknown>;
activation?: AugmentationResponse<unknown>;
perception?: AugmentationResponse<unknown>;
}
}
/**
* SequentialPipeline class
*
* Executes augmentations in a specific sequence:
* ISense -> IMemory -> ICognition -> IConduit -> IActivation -> IPerception
*/
export class SequentialPipeline {
private brainyData: BrainyData;
/**
* Create a new sequential pipeline
*
* @param options Options for the pipeline
*/
constructor(options: SequentialPipelineOptions = {}) {
this.brainyData = options.brainyData || new BrainyData();
}
/**
* Ensure stream classes are initialized
* @private
*/
private async ensureStreamClassesInitialized(): Promise<void> {
await streamClassesPromise;
}
/**
* Initialize the pipeline
*
* @returns A promise that resolves when initialization is complete
*/
public async initialize(): Promise<void> {
// Initialize stream classes and BrainyData in parallel
await Promise.all([
this.ensureStreamClassesInitialized(),
this.brainyData.init()
]);
}
/**
* Process data through the sequential pipeline
*
* @param rawData The raw data to process
* @param dataType The type of data (e.g., 'text', 'image', 'audio')
* @param options Options for pipeline execution
* @returns A promise that resolves with the pipeline result
*/
public async processData(
rawData: Buffer | string,
dataType: string,
options: SequentialPipelineOptions = {}
): Promise<PipelineResult<unknown>> {
const opts = { ...DEFAULT_SEQUENTIAL_PIPELINE_OPTIONS, ...options };
const result: PipelineResult<unknown> = {
success: true,
data: null,
stageResults: {}
};
try {
// Step 1: Process raw data with ISense augmentations
const senseResults = await augmentationPipeline.executeSensePipeline(
'processRawData',
[rawData, dataType],
{ timeout: opts.timeout, stopOnError: opts.stopOnError }
);
// Get the first successful result
let senseResult: AugmentationResponse<{ nouns: string[], verbs: string[] }> | null = null;
for (const resultPromise of senseResults) {
const res = await resultPromise;
if (res.success) {
senseResult = res;
break;
}
}
if (!senseResult || !senseResult.success) {
return {
success: false,
data: null,
error: 'Failed to process raw data with ISense augmentations',
stageResults: { sense: senseResult || { success: false, data: null, error: 'No sense augmentations available' } }
};
}
result.stageResults.sense = senseResult;
// Step 2: Store data in BrainyData using IMemory augmentations
const memoryAugmentations = augmentationPipeline.getAugmentationsByType(AugmentationType.MEMORY) as IMemoryAugmentation[];
if (memoryAugmentations.length === 0) {
return {
success: false,
data: null,
error: 'No memory augmentations available',
stageResults: result.stageResults
};
}
// Use the first available memory augmentation
const memoryAugmentation = memoryAugmentations[0];
// Generate a key for the data
const dataKey = `data_${Date.now()}_${Math.random().toString(36).substring(2, 15)}`;
// Store the data
const memoryResult = await memoryAugmentation.storeData(
dataKey,
{
rawData,
dataType,
nouns: senseResult.data.nouns,
verbs: senseResult.data.verbs,
timestamp: Date.now()
}
);
if (!memoryResult.success) {
return {
success: false,
data: null,
error: `Failed to store data: ${memoryResult.error}`,
stageResults: { ...result.stageResults, memory: memoryResult }
};
}
result.stageResults.memory = memoryResult;
// Step 3: Trigger ICognition augmentations to analyze the data
const cognitionResults = await augmentationPipeline.executeCognitionPipeline(
'reason',
[`Analyze data with key ${dataKey}`, { dataKey }],
{ timeout: opts.timeout, stopOnError: opts.stopOnError }
);
// Get the first successful result
let cognitionResult: AugmentationResponse<{ inference: string, confidence: number }> | null = null;
for (const resultPromise of cognitionResults) {
const res = await resultPromise;
if (res.success) {
cognitionResult = res;
break;
}
}
if (cognitionResult) {
result.stageResults.cognition = cognitionResult;
}
// Step 4: Send notifications to IConduit augmentations
const conduitResults = await augmentationPipeline.executeConduitPipeline(
'writeData',
[{ dataKey, nouns: senseResult.data.nouns, verbs: senseResult.data.verbs }],
{ timeout: opts.timeout, stopOnError: opts.stopOnError }
);
// Get the first successful result
let conduitResult: AugmentationResponse<unknown> | null = null;
for (const resultPromise of conduitResults) {
const res = await resultPromise;
if (res.success) {
conduitResult = res;
break;
}
}
if (conduitResult) {
result.stageResults.conduit = conduitResult;
}
// Step 5: Send notifications to IActivation augmentations
const activationResults = await augmentationPipeline.executeActivationPipeline(
'triggerAction',
['dataProcessed', { dataKey }],
{ timeout: opts.timeout, stopOnError: opts.stopOnError }
);
// Get the first successful result
let activationResult: AugmentationResponse<unknown> | null = null;
for (const resultPromise of activationResults) {
const res = await resultPromise;
if (res.success) {
activationResult = res;
break;
}
}
if (activationResult) {
result.stageResults.activation = activationResult;
}
// Step 6: Send notifications to IPerception augmentations
const perceptionResults = await augmentationPipeline.executePerceptionPipeline(
'interpret',
[senseResult.data.nouns, senseResult.data.verbs, { dataKey }],
{ timeout: opts.timeout, stopOnError: opts.stopOnError }
);
// Get the first successful result
let perceptionResult: AugmentationResponse<Record<string, unknown>> | null = null;
for (const resultPromise of perceptionResults) {
const res = await resultPromise;
if (res.success) {
perceptionResult = res;
break;
}
}
if (perceptionResult) {
result.stageResults.perception = perceptionResult;
result.data = perceptionResult.data;
} else {
// If no perception result, use the cognition result as the final data
result.data = cognitionResult ? cognitionResult.data : { dataKey };
}
return result;
} catch (error: unknown) {
return {
success: false,
data: null,
error: `Pipeline execution failed: ${error}`,
stageResults: result.stageResults
};
}
}
/**
* Process WebSocket data through the sequential pipeline
*
* @param connection The WebSocket connection
* @param dataType The type of data (e.g., 'text', 'image', 'audio')
* @param options Options for pipeline execution
* @returns A function to handle incoming WebSocket messages
*/
public async createWebSocketHandler(
connection: WebSocketConnection,
dataType: string,
options: SequentialPipelineOptions = {}
): Promise<(data: unknown) => void> {
// Ensure stream classes are initialized
await this.ensureStreamClassesInitialized();
// Create a transform stream for processing data
const transformStream = new TransformStream({
transform: async (chunk: unknown, controller: TransformStreamDefaultController) => {
try {
const data = typeof chunk === 'string' ? chunk : JSON.stringify(chunk);
const result = await this.processData(data, dataType, options);
if (result.success) {
controller.enqueue(result);
} else {
console.warn('Pipeline processing failed:', result.error);
}
} catch (error: unknown) {
console.error('Error in transform stream:', error);
}
}
});
// Create a writable stream that will be the sink for our data
const writableStream = new WritableStream({
write: async (result: PipelineResult<unknown>) => {
// Handle the processed result if needed
if (connection.send && typeof connection.send === 'function') {
try {
// Only send back results if the connection supports it
await connection.send(JSON.stringify(result));
} catch (error: unknown) {
console.error('Error sending result back to WebSocket:', error);
}
}
}
});
// Connect the transform stream to the writable stream
transformStream.readable.pipeTo(writableStream).catch((error: Error) => {
console.error('Error in pipeline stream:', error);
});
// Return a function that writes to the transform stream
return (data: unknown) => {
try {
// Write to the transform stream's writable side
const writer = transformStream.writable.getWriter();
writer.write(data).catch((error: Error) => {
console.error('Error writing to stream:', error);
}).finally(() => {
writer.releaseLock();
});
} catch (error: unknown) {
console.error('Error getting writer for transform stream:', error);
}
};
}
/**
* Set up a WebSocket connection to process data through the pipeline
*
* @param url The WebSocket URL to connect to
* @param dataType The type of data (e.g., 'text', 'image', 'audio')
* @param options Options for pipeline execution
* @returns A promise that resolves with the WebSocket connection and associated streams
*/
public async setupWebSocketPipeline(
url: string,
dataType: string,
options: SequentialPipelineOptions = {}
): Promise<WebSocketConnection & {
readableStream?: ReadableStream<unknown>,
writableStream?: WritableStream<unknown>
}> {
// Ensure stream classes are initialized
await this.ensureStreamClassesInitialized();
// Get WebSocket-supporting augmentations
const webSocketAugmentations = augmentationPipeline.getWebSocketAugmentations();
if (webSocketAugmentations.length === 0) {
throw new Error('No WebSocket-supporting augmentations available');
}
// Use the first available WebSocket augmentation
const webSocketAugmentation = webSocketAugmentations[0];
// Connect to the WebSocket
const connection = await webSocketAugmentation.connectWebSocket(url);
// Create a readable stream from the WebSocket messages
const readableStream = new ReadableStream({
start: (controller: ReadableStreamDefaultController) => {
// Define a message handler that writes to the stream
const messageHandler = (event: { data: unknown }) => {
try {
const data = typeof event.data === 'string'
? event.data
: event.data instanceof Blob
? new Promise(resolve => {
const reader = new FileReader();
reader.onload = () => resolve(reader.result as string);
reader.readAsText(event.data as Blob);
})
: JSON.stringify(event.data);
// Handle both string data and promises
if (data instanceof Promise) {
data.then(resolvedData => {
controller.enqueue(resolvedData);
}).catch((error: Error) => {
console.error('Error processing blob data:', error);
});
} else {
controller.enqueue(data);
}
} catch (error: unknown) {
console.error('Error processing WebSocket message:', error);
}
};
// Create a wrapper function that adapts the event-based handler to the data-based callback
const messageHandlerWrapper = (data: unknown) => {
messageHandler({ data });
};
// Store both handlers for later cleanup
connection._streamMessageHandler = messageHandler;
connection._messageHandlerWrapper = messageHandlerWrapper;
webSocketAugmentation.onWebSocketMessage(
connection.connectionId,
messageHandlerWrapper
).catch((error: Error) => {
console.error('Error registering WebSocket message handler:', error);
controller.error(error);
});
},
cancel: () => {
// Clean up the message handler when the stream is cancelled
if (connection._messageHandlerWrapper) {
webSocketAugmentation.offWebSocketMessage(
connection.connectionId,
connection._messageHandlerWrapper
).catch((error: Error) => {
console.error('Error removing WebSocket message handler:', error);
});
delete connection._streamMessageHandler;
delete connection._messageHandlerWrapper;
}
}
});
// Create a handler for processing the data
const handlerPromise = this.createWebSocketHandler(connection, dataType, options);
// Create a writable stream that sends data to the WebSocket
const writableStream = new WritableStream({
write: async (chunk: unknown) => {
if (connection.send && typeof connection.send === 'function') {
try {
const data = typeof chunk === 'string' ? chunk : JSON.stringify(chunk);
await connection.send(data);
} catch (error: unknown) {
console.error('Error sending data to WebSocket:', error);
throw error;
}
} else {
throw new Error('WebSocket connection does not support sending data');
}
},
close: () => {
// Close the WebSocket connection when the stream is closed
if (connection.close && typeof connection.close === 'function') {
connection.close().catch((error: Error) => {
console.error('Error closing WebSocket connection:', error);
});
}
}
});
// Pipe the readable stream through our processing pipeline
readableStream
.pipeThrough(new TransformStream({
transform: async (chunk: unknown, controller: TransformStreamDefaultController) => {
// Process each chunk through our handler
const handler = await handlerPromise;
handler(chunk);
// Pass through the original data
controller.enqueue(chunk);
}
}))
.pipeTo(new WritableStream({
write: () => {},
abort: (error: Error) => {
console.error('Error in WebSocket pipeline:', error);
}
}));
// Attach the streams to the connection object for convenience
const enhancedConnection = connection as WebSocketConnection & {
readableStream: ReadableStream<unknown>,
writableStream: WritableStream<unknown>
};
enhancedConnection.readableStream = readableStream;
enhancedConnection.writableStream = writableStream;
return enhancedConnection;
}
}
// Create and export a default instance of the sequential pipeline
export const sequentialPipeline = new SequentialPipeline();