Aggregators TypeScript ★ 98

juspay/neurolink

Making enterprise AI infrastructure universally accessible. Edge-first platform unifying 12 providers and 100+ models with multi-agent orchestration, HITL workflows, guardrails middleware, and context summarization.

Add to Claude Desktop config.json

{
  "mcpServers": {
    "juspay-neurolink": {
      "command": "node",
      "args": [
        "~/.mcp/neurolink/index.js"
      ]
    }
  }
}

NeuroLink

The pipe layer for the AI nervous system.

AI intelligence flows as streams — tokens, tool calls, memory, voice, documents. NeuroLink is the vascular layer that carries these streams from where they are generated (LLM providers: the neurons) to where they are needed (connectors: the organs).

import { NeuroLink } from "@juspay/neurolink";

const pipe = new NeuroLink();

// Everything is a stream
const result = await pipe.stream({ input: { text: "Hello" } });
for await (const chunk of result.stream) {
  if ("content" in chunk) {
    process.stdout.write(chunk.content);
  }
}

→ Docs · → Quick Start · → npm


NeuroLink is the universal AI integration platform that unifies 21+ AI providers and 100+ models under one consistent API.

Extracted from production systems at Juspay and battle-tested at enterprise scale, NeuroLink provides a production-ready solution for integrating AI into any application. Whether you’re building with OpenAI, Anthropic, Google, AWS Bedrock, Azure, or any of our 21+ supported providers, NeuroLink gives you a single, consistent interface that works everywhere.

Why NeuroLink? Switch providers with a single parameter change, leverage 64+ built-in tools and MCP servers, deploy with confidence using enterprise features like Redis memory and multi-provider failover, and optimize costs automatically with intelligent routing. Use it via our professional CLI or TypeScript SDK—whichever fits your workflow.

Where we’re headed: We’re building for the future of AI—edge-first execution and continuous streaming architectures that make AI practically free and universally available. Read our vision →

Get Started in <5 Minutes →


What’s New (Q1 2026)

FeatureVersionDescriptionGuide
Avatar / Music Modalities + 12 ProvidersnextNew output: { mode: "avatar" | "music" } dispatch with handlers for D-ID, HeyGen, Replicate-MuseTalk (avatar) and Beatoven, ElevenLabs Music, Lyria, Replicate-MusicGen (music). Plus Fish Audio TTS, Kling/Runway/Replicate video, xAI/Groq/Cohere/Together/Fireworks/Perplexity/Cloudflare LLMs, Voyage/Jina embeddings, Stability/Ideogram/Recraft/Replicate image-gen.Provider Integration
Multi-Provider Voice (TTS/STT)v9.62.06 TTS providers (OpenAI TTS, ElevenLabs, Google TTS, Azure TTS, Fish Audio, Cartesia) + 4 STT providers (Whisper, Deepgram, Azure STT, Google STT) + 2 realtime APIs (OpenAI Realtime, Gemini Live).TTS Guide | STT Guide | Realtime Guide
4 New Providersv9.60.0DeepSeek (V3/R1), NVIDIA NIM (400+ catalog), LM Studio (local), llama.cpp (GGUF local).Provider Setup
ModelAccessDeniedErrorv9.59.0Typed ModelAccessDeniedError + sdk.checkCredentials() API for proactive credential validation before first call.Error Reference
Provider Fallback Policyv9.58.0providerFallback callback + modelChain config for centralized multi-provider fallback logic.Advanced Guide
Per-Request Credentialsv9.52.0Pass credentials per-call or per-instance for all providers. Per-call overrides instance; instance overrides env vars.Credentials Guide
AutoResearchv9.53.0Autonomous AI experiment engine: proposes code changes, runs experiments, evaluates metrics — unattended for hours.AutoResearch Guide
Gemini 3 Multi-turn Tool Fixv9.49.0Fixed multi-step agentic tool calling on Vertex AI Gemini 3. Correct thoughtSignature replay, stepIndex grouping, executionId session isolation, 5-min timeout.Vertex AI Guide
MCP Enhancementsv9.16.0Tool routing (6 strategies), result caching (LRU/FIFO/LFU), request batching, annotations, elicitation protocol, multi-server management.MCP Enhancements Guide
Memoryv9.12.0Per-user condensed memory across conversations. LLM-powered condensation with S3, Redis, or SQLite.Memory Guide
Context Window Managementv9.2.04-stage compaction pipeline with budget gate at 80% usage, per-provider token estimation.Context Compaction Guide
Tool Execution Controlv9.3.0prepareStep and toolChoice for per-step tool enforcement in multi-step agentic loops.API Reference
File Processor Systemv9.1.017+ file type processors with ProcessorRegistry, security sanitization, SVG text injection.File Processors Guide
RAG with generate()/stream()v9.2.0Pass rag: { files } for automatic document chunking, embedding, and AI-powered search. 10 chunking strategies, hybrid search, reranking.RAG Guide
// Multi-Provider Voice (v9.62.0) — TTS + STT
// Voice is configured via the `tts` / `stt` options on generate() / stream(),
// not via dedicated synthesizeSpeech / transcribeAudio methods.

// Text in, audio out (TTS)
const result = await neurolink.generate({
  input: { text: "Hello from NeuroLink" },
  provider: "vertex",
  tts: {
    enabled: true,
    voice: "en-US-Neural2-C",
    format: "mp3",
    output: "./output.mp3", // optional: save to disk
    provider: "elevenlabs", // optional override: openai-tts | elevenlabs | google-ai | vertex | azure-tts | fish-audio | cartesia
  },
});
// result.audio: { buffer: Buffer, format: "mp3", ... }

// Audio in (STT), text out
const transcript = await neurolink.generate({
  input: { text: "Transcribe and summarize" },
  provider: "openai",
  stt: {
    enabled: true,
    audio: audioBuffer, // Buffer of the audio file
    provider: "whisper", // whisper | deepgram | google-stt | azure-stt
    language: "en-US",
  },
});

// Real-time bidirectional voice (OpenAI Realtime / Gemini Live)
import { RealtimeProcessor } from "@juspay/neurolink";

await RealtimeProcessor.connect(
  "openai-realtime",
  { provider: "openai-realtime", model: "gpt-4o-realtime-preview" },
  { onAudio, onTranscript, onError, onFunctionCall },
);

// AutoResearch — autonomous experiment loop (v9.53.0)
import { resolveConfig, ResearchWorker } from "@juspay/neurolink/autoresearch";

const config = resolveConfig({
  repoPath: "/path/to/repo",
  mutablePaths: ["train.py"],
  runCommand: "python3 train.py",
  metric: {
    name: "val_bpb",
    direction: "lower",
    pattern: "^val_bpb:\\s+([\\d.]+)",
  },
});
const worker = new ResearchWorker(config);
await worker.initialize("experiment-1");
const result = await worker.runExperimentCycle("Try lower learning rate");

// Provider Fallback Policy (v9.58.0) — fires only on ModelAccessDeniedError
import { NeuroLink, ModelAccessDeniedError } from "@juspay/neurolink";

const neurolink = new NeuroLink({
  // Async callback. Single error arg. Return null to give up,
  // or { provider?, model? } to retry with a substitute.
  providerFallback: async (error) => {
    if (
      error instanceof ModelAccessDeniedError &&
      error.allowedModels?.length
    ) {
      return { model: error.allowedModels[0] };
    }
    return null;
  },
  // Sugar over providerFallback: if no callback is set, NeuroLink walks this list
  // on each access denial. modelChain is `string[]` only (model names; same provider).
  modelChain: ["claude-opus-4-7", "claude-sonnet-4-6", "gpt-4o"],
});

Previous Updates (Q3–Q4 2025)
  • Sharp image compression (v9.50.0) – Automatic image compression for AI providers via the sharp library; reduces upload bandwidth and bypasses provider size limits.
  • Redis URL/TLS (v9.49.0) – Redis URL-based connections with TLS support for secure conversation memory in production.
  • TaskManager (v9.41.0) – Scheduled and self-running AI tasks; cron-style execution with state checkpointing.
  • Multi-user memory retrieval (v9.40.0) – Per-user memory storage and retrieval with customizable prompts.
  • Evaluation Scoring (14 scorers) (v9.37.0) – Modular evaluation system with 14 scorers, pipelines, and CLI for offline quality assessment.
  • Browser-compatible bundle (v9.34.0) – Client-side SDK bundle for browser use; no Node.js dependency for the core API.
  • Per-call memory control (v9.33.0) – Read/write memory control per generate() and stream() call.
  • Server Adapters (v8.43.0) – HTTP server with Hono, Express, Fastify, Koa. Foreground/background modes, route management, OpenAPI generation. → Guide
  • External TracerProvider (v8.43.0) – Integrate NeuroLink with existing OpenTelemetry setups. → Guide
  • Title Generation Events (v8.38.0) – conversation:titleGenerated event + NEUROLINK_TITLE_PROMPT custom titles. → Guide
  • Video Generation with Veo (v8.32.0) – Video generation via Google Veo 3.1 on Vertex AI. 720p/1080p, portrait/landscape. → Guide
  • Image Generation (v8.31.0) – Native image generation with Gemini and Imagen models. → Guide
  • HTTP/Streamable HTTP Transport (v8.29.0) – Remote MCP servers via HTTP with auth headers, retry, rate limiting. → Guide
  • PPT Generation – 35 slide types, 5 themes, optional AI-generated images. Works across all major providers. → Guide
  • Structured Output with Zod – Type-safe JSON via schema + output.format: "json". → Guide
  • CSV & PDF File Support – Attach CSV/PDF with auto-detection. PDF: native visual analysis on Vertex, Anthropic, Bedrock, AI Studio. → CSV | PDF
  • LiteLLM, SageMaker & OpenRouter – 100+ models via LiteLLM, custom endpoints on SageMaker, 300+ via OpenRouter. → LiteLLM | SageMaker
  • HITL & Guardrails – Human-in-the-loop approval workflows and content filtering. → HITL | Guardrails
  • Redis Conversation Export – Export full session history as JSON for analytics and audit. → Guide

Enterprise Security: Human-in-the-Loop (HITL)

NeuroLink includes a production-ready HITL system for regulated industries and high-stakes AI operations:

CapabilityDescriptionUse Case
Tool Approval WorkflowsRequire human approval before AI executes sensitive toolsFinancial transactions, data modifications
Output ValidationRoute AI outputs through human review pipelinesMedical diagnosis, legal documents
Confidence ThresholdsAutomatically trigger human review below confidence levelCritical business decisions
Complete Audit TrailFull audit logging for compliance (HIPAA, SOC2, GDPR)Regulated industries
import { NeuroLink } from "@juspay/neurolink";

const neurolink = new NeuroLink({
  hitl: {
    enabled: true,
    requireApproval: ["writeFile", "executeCode", "sendEmail"],
    confidenceThreshold: 0.85,
    reviewCallback: async (action, context) => {
      // Custom review logic - integrate with your approval system
      return await yourApprovalSystem.requestReview(action);
    },
  },
});

// AI pauses for human approval before executing sensitive tools
const result = await neurolink.generate({
  input: { text: "Send quarterly report to stakeholders" },
});

Enterprise HITL Guide | Quick Start

📚 Quick Start Guide

This guide will have you generating AI responses in under 5 minutes using either the SDK or CLI.

Installation

Choose your preferred package manager:

# npm
npm install @juspay/neurolink

# pnpm (recommended)
pnpm add @juspay/neurolink

# yarn
yarn add @juspay/neurolink

# CLI only (no installation needed)
npx @juspay/neurolink --help

Configuration

NeuroLink works with 21+ AI providers. You’ll need at least one API key to get started:

Option 1: Interactive Setup (Recommended)

# Run the setup wizard to configure providers
pnpm dlx @juspay/neurolink setup

The wizard will guide you through:

  • Selecting your preferred AI providers
  • Validating API keys
  • Setting up configuration files

Option 2: Manual Configuration

Create a .env file in your project root:

# Choose one or more providers
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
GOOGLE_AI_API_KEY=...

Free Tier Options:

Your First API Call (SDK)

Basic Text Generation:

import { NeuroLink } from "@juspay/neurolink";

// Initialize (auto-selects best available provider from your .env)
const neurolink = new NeuroLink();

// Generate a response
const result = await neurolink.generate({
  input: { text: "Explain quantum computing in simple terms" },
});

console.log(result.content);

Streaming Responses:

// Stream tokens in real-time
const stream = await neurolink.stream({
  input: { text: "Write a haiku about code" },
});
for await (const chunk of stream.stream) {
  if ("content" in chunk) process.stdout.write(chunk.content);
}

Multimodal Input (Images + Text):

const result = await neurolink.generate({
  input: {
    text: "What's in this image?",
    images: ["./photo.jpg"],
  },
});

Using Tools:

// Built-in tools are automatically available
const result = await neurolink.generate({
  input: {
    text: "What time is it and what files are in the current directory?",
  },
  // AI can call getCurrentTime and listDirectory tools
});

Your First API Call (CLI)

Basic Generation:

# Simple text generation
npx @juspay/neurolink generate "Explain TypeScript generics"

# Specify provider and model
npx @juspay/neurolink generate "Hello!" --provider openai --model gpt-4o

# Stream responses
npx @juspay/neurolink stream "Write a story about AI" --provider anthropic

Multimodal Input:

# Analyze images
npx @juspay/neurolink generate "Describe this image" --image photo.jpg

# Process PDFs
npx @juspay/neurolink generate "Summarize this document" --pdf report.pdf

# Combine multiple file types
npx @juspay/neurolink generate "Analyze this data" --file data.xlsx --file config.json

Interactive Loop Mode:

# Start an interactive session with persistent context
npx @juspay/neurolink loop

# Inside loop mode:
> set provider anthropic
> set model claude-opus-4
> generate "Hello, Claude!"
> history  # View conversation history
> exit

Common Use Cases

RAG (Retrieval-Augmented Generation):

// Automatically chunk, embed, and search documents
const result = await neurolink.generate({
  input: { text: "What are the key features mentioned in the documentation?" },
  rag: {
    files: ["./docs/guide.md", "./docs/api.md"],
    chunkSize: 512,
    topK: 5,
  },
});

Structured Output with Zod:

import { z } from "zod";

const schema = z.object({
  name: z.string(),
  age: z.number(),
  email: z.string().email(),
});

const result = await neurolink.generate({
  input: {
    text: "Extract user info: John Doe, 30 years old, john@example.com",
  },
  schema,
  output: { format: "json" },
});

// Parse the structured JSON from result.content
const parsed = schema.parse(JSON.parse(result.content));
console.log(parsed); // { name: "John Doe", age: 30, email: "john@example.com" }

External MCP Servers (GitHub, Slack, etc.):

// Connect to GitHub MCP server
await neurolink.addExternalMCPServer("github", {
  command: "npx",
  args: ["-y", "@modelcontextprotocol/server-github"],
  transport: "stdio",
  env: { GITHUB_TOKEN: process.env.GITHUB_TOKEN },
});

// AI can now interact with GitHub
const result = await neurolink.generate({
  input: { text: 'Create an issue titled "Bug: login fails"' },
});

Next Steps

Troubleshooting

Issue: “Provider not configured”

  • Run npx @juspay/neurolink setup or add provider API key to .env

Issue: Rate limit errors

  • Configure multiple providers for redundancy — NeuroLink auto-selects the best available
  • Use provider: "litellm" with LiteLLM to proxy across many providers

Issue: Large context overflows

  • Enable conversation memory with compaction: new NeuroLink({ conversationMemory: { enabled: true } })
  • Use rag option to search documents instead of sending full content

Need help? Check our Troubleshooting Guide or open an issue.


🌟 Complete Feature Set

NeuroLink is a comprehensive AI development platform. Every feature below is production-ready and fully documented.

🤖 AI Provider Integration

33+ providers unified under one API - Switch providers with a single parameter change.

ProviderModelsFree TierTool SupportStatusDocumentation
OpenAIGPT-4o, GPT-4o-mini, o1✅ Full✅ ProductionSetup Guide
AnthropicClaude 4.6 Opus/Sonnet, Claude 4.5 Opus/Sonnet/Haiku, Claude 4 Opus/Sonnet✅ Full✅ ProductionSetup Guide | Subscription Guide
Google AI StudioGemini 3 Flash/Pro, Gemini 2.5 Flash/Pro✅ Free Tier✅ Full✅ ProductionSetup Guide
AWS BedrockClaude, Titan, Llama, Nova✅ Full✅ ProductionSetup Guide
Google VertexGemini 3/2.5 (gemini-3-*-preview)✅ Full✅ ProductionSetup Guide
Azure OpenAIGPT-4, GPT-4o, o1✅ Full✅ ProductionSetup Guide
LiteLLM100+ models unifiedVaries✅ Full✅ ProductionSetup Guide
AWS SageMakerCustom deployed models✅ Full✅ ProductionSetup Guide
Mistral AIMistral Large, Small✅ Free Tier✅ Full✅ ProductionSetup Guide
Hugging Face100,000+ models✅ Free⚠️ Partial✅ ProductionSetup Guide
OllamaLocal models (Llama, Mistral)✅ Free (Local)⚠️ Partial✅ ProductionSetup Guide
OpenAI CompatibleAny OpenAI-compatible endpointVaries✅ Full✅ ProductionSetup Guide
OpenRouter200+ Models via OpenRouterVaries✅ Full✅ ProductionSetup Guide
DeepSeekdeepseek-chat (V3), deepseek-reasoner (R1)✅ Full✅ ProductionSetup Guide
NVIDIA NIMLlama 3.3 70B, 400+ catalog models✅ Full✅ ProductionSetup Guide
LM StudioAny model loaded in LM Studio (local)✅ Free (Local)✅ Full✅ ProductionSetup Guide
llama.cppAny GGUF model served by llama-server (local)✅ Free (Local)✅ Full✅ ProductionSetup Guide
OpenAI TTSTTS-1, TTS-1-HD, GPT-4o AudioN/A✅ ProductionSetup Guide
ElevenLabsMultilingual v2, Turbo v2.5, Flash v2.5✅ Free TierN/A✅ ProductionSetup Guide
DeepgramNova-3, Nova-2, Enhanced, Base (STT)✅ Free TierN/A✅ ProductionSetup Guide
Azure SpeechAzure Cognitive Services TTS + STTN/A✅ ProductionSetup Guide

📖 Provider Comparison Guide - Detailed feature matrix and selection criteria 🔬 Provider Feature Compatibility - Test-based compatibility reference for all 19 features across 21+ providers


🔧 Built-in Tools & MCP Integration

6 Core Tools (work across all providers, zero configuration):

ToolPurposeAuto-AvailableDocumentation
getCurrentTimeReal-time clock accessTool Reference
readFileFile system readingTool Reference
writeFileFile system writingTool Reference
listDirectoryDirectory listingTool Reference
calculateMathMathematical operationsTool Reference
websearchGroundingGoogle Vertex web search⚠️ Requires credentialsTool Reference

58+ External MCP Servers supported (GitHub, PostgreSQL, Google Drive, Slack, and more):

// stdio transport - local MCP servers via command execution
await neurolink.addExternalMCPServer("github", {
  command: "npx",
  args: ["-y", "@modelcontextprotocol/server-github"],
  transport: "stdio",
  env: { GITHUB_TOKEN: process.env.GITHUB_TOKEN },
});

// HTTP transport - remote MCP servers via URL
await neurolink.addExternalMCPServer("github-copilot", {
  transport: "http",
  url: "https://api.githubcopilot.com/mcp",
  headers: { Authorization: "Bearer YOUR_COPILOT_TOKEN" },
  timeout: 15000,
  retries: 5,
});

// Tools automatically available to AI
const result = await neurolink.generate({
  input: { text: 'Create a GitHub issue titled "Bug in auth flow"' },
});

MCP Transport Options:

TransportUse CaseKey Features
stdioLocal serversCommand execution, environment variables
httpRemote serversURL-based, auth headers, retries, rate limiting
sseEvent streamsServer-Sent Events, real-time updates
websocketBi-directionalFull-duplex communication

📖 MCP Integration Guide - Setup external servers 📖 HTTP Transport Guide - Remote MCP server configuration


🔌 MCP Enhancements

Production-grade MCP capabilities for managing tool calls at scale across multi-server environments:

ModulePurpose
Tool RouterIntelligent routing across servers with 6 strategies
Tool CacheResult caching with LRU, FIFO, and LFU eviction
Request BatcherAutomatic batching of tool calls for throughput
Tool AnnotationsSafety metadata and behavior hints for MCP tools
Tool ConverterBidirectional conversion between NeuroLink and MCP formats
Elicitation ProtocolInteractive user input during tool execution (HITL)
Multi-Server ManagerLoad balancing and failover across server groups
MCP Server BaseAbstract base class for building custom MCP servers
Enhanced Tool DiscoveryAdvanced search and filtering across servers
Agent & Workflow ExposureExpose agents and workflows as MCP tools
Server CapabilitiesResource and prompt management per MCP spec
Registry ClientDiscover and connect to MCP servers from registries
Tool IntegrationEnd-to-end tool lifecycle with middleware chain
Elicitation ManagerManages elicitation flows with validation and timeouts
import { ToolRouter, ToolCache, RequestBatcher } from "@juspay/neurolink";

// Route tool calls across multiple MCP servers
const router = new ToolRouter({
  strategy: "capability-based",
  servers: [
    { name: "github", url: "https://mcp-github.example.com" },
    { name: "db", url: "https://mcp-postgres.example.com" },
  ],
});

// Cache repeated tool results (LRU, FIFO, or LFU)
const cache = new ToolCache({ strategy: "lru", maxSize: 500, ttl: 60_000 });

// Batch concurrent tool calls for throughput
const batcher = new RequestBatcher({ maxBatchSize: 10, maxWaitMs: 50 });

📖 MCP Enhancements Guide - Full reference for all 14 modules


💻 Developer Experience Features

SDK-First Design with TypeScript, IntelliSense, and type safety:

FeatureDescriptionDocumentation
Auto Provider SelectionIntelligent provider fallbackSDK Guide
Streaming ResponsesReal-time token streamingStreaming Guide
Conversation MemoryAutomatic context management with embedded per-user memoryMemory Guide
Full Type SafetyComplete TypeScript typesType Reference
Error HandlingGraceful provider fallbackError Guide
Analytics & EvaluationUsage tracking, quality scoresAnalytics Guide
Middleware SystemRequest/response hooksMiddleware Guide
Framework IntegrationNext.js, SvelteKit, ExpressFramework Guides
Extended ThinkingNative thinking/reasoning mode for Gemini 3 and Claude modelsThinking Guide
RAG Document Processingrag: { files } on generate/stream with 10 chunking strategies and hybrid searchRAG Guide

📁 Multimodal & File Processing

17+ file categories supported (50+ total file types including code languages) with intelligent content extraction and provider-agnostic processing:

CategorySupported TypesProcessing
DocumentsExcel (.xlsx, .xls), Word (.docx), RTF, OpenDocumentSheet extraction, text extraction
DataJSON, YAML, XMLValidation, syntax highlighting
MarkupHTML, SVG, Markdown, TextOWASP-compliant sanitization
Code50+ languages (TypeScript, Python, Java, Go, etc.)Language detection, syntax metadata
Config.env, .ini, .toml, .cfgSecure parsing
MediaImages (PNG, JPEG, WebP, GIF), PDFs, CSVProvider-specific formatting
// Process any supported file type
const result = await neurolink.generate({
  input: {
    text: "Analyze this data and code",
    files: [
      "./data.xlsx", // Excel spreadsheet
      "./config.yaml", // YAML configuration
      "./diagram.svg", // SVG (injected as sanitized text)
      "./main.py", // Python source code
    ],
  },
});

// CLI: Use --file for any supported type
// neurolink generate "Analyze this" --file ./report.xlsx --file ./config.json

Key Features:

  • ProcessorRegistry - Priority-based processor selection with fallback
  • OWASP Security - HTML/SVG sanitization prevents XSS attacks
  • Auto-detection - FileDetector identifies file types by extension and content
  • Provider-agnostic - All processors work across all 21+ AI providers

📖 File Processors Guide - Complete reference for all file types


🏢 Enterprise & Production Features

Production-ready capabilities for regulated industries:

FeatureDescriptionUse CaseDocumentation
Enterprise ProxyCorporate proxy supportBehind firewallsProxy Setup
Redis MemoryDistributed conversation stateMulti-instance deploymentRedis Guide
MemoryPer-user condensed memory (S3/Redis/SQLite)Long-term user contextMemory Guide
Cost OptimizationAutomatic cheapest model selectionBudget controlCost Guide
Multi-Provider FailoverAutomatic provider switchingHigh availabilityFailover Guide
Telemetry & MonitoringOpenTelemetry integrationObservabilityTelemetry Guide
Security HardeningCredential management, auditingComplianceSecurity Guide
Custom Model HostingSageMaker integrationPrivate modelsSageMaker Guide
Load BalancingLiteLLM proxy integrationScale & routingLoad Balancing

Security & Compliance:

  • ✅ SOC2 Type II compliant deployments
  • ✅ ISO 27001 certified infrastructure compatible
  • ✅ GDPR-compliant data handling (EU providers available)
  • ✅ HIPAA compatible (with proper configuration)
  • ✅ Hardened OS verified (SELinux, AppArmor)
  • ✅ Zero credential logging
  • ✅ Encrypted configuration storage
  • ✅ Automatic context window management with 4-stage compaction pipeline and 80% budget gate

📖 Enterprise Deployment Guide - Complete production checklist


Enterprise Persistence: Redis Memory

Production-ready distributed conversation state for multi-instance deployments:

Capabilities

FeatureDescriptionBenefit
Distributed MemoryShare conversation context across instancesHorizontal scaling
Session ExportExport full history as JSONAnalytics, debugging, audit
Auto-DetectionAutomatic Redis discovery from environmentZero-config in containers
Graceful FailoverFalls back to in-memory if Redis unavailableHigh availability
TTL ManagementConfigurable session expirationMemory management

Quick Setup

import { NeuroLink } from "@juspay/neurolink";

// Auto-detect Redis from REDIS_URL environment variable
const neurolink = new NeuroLink({
  conversationMemory: {
    enabled: true,
    enableSummarization: true,
  },
});

// Or explicit Redis configuration
const neurolinkExplicit = new NeuroLink({
  conversationMemory: {
    enabled: true,
    redisConfig: {
      host: "redis.example.com",
      port: 6379,
      password: process.env.REDIS_PASSWORD,
      ttl: 86400, // 24-hour session expiration (seconds)
    },
  },
});

// Retrieve conversation history for analytics
const history = await neurolink.getConversationHistory("session-id");
await saveToDataWarehouse(history);

Docker Quick Start

# Start Redis
docker run -d --name neurolink-redis -p 6379:6379 redis:7-alpine

# Configure NeuroLink
export REDIS_URL=redis://localhost:6379

# Start your application
node your-app.js

Redis Setup Guide | Production Configuration | Migration Patterns


🎨 Professional CLI

15+ commands for every workflow:

CommandPurposeExampleDocumentation
setupInteractive provider configurationneurolink setupSetup Guide
generateText generationneurolink gen "Hello"Generate
streamStreaming generationneurolink stream "Story"Stream
statusProvider health checkneurolink statusStatus
loopInteractive sessionneurolink loopLoop
mcpMCP server managementneurolink mcp discoverMCP CLI
modelsModel listingneurolink modelsModels
evalModel evaluationneurolink evalEval
serveStart HTTP server in foreground modeneurolink serveServe
server startStart HTTP server in background modeneurolink server startServer
server stopStop running background serverneurolink server stopServer
server statusShow server status informationneurolink server statusServer
server routesList all registered API routesneurolink server routesServer
server configView or modify server configurationneurolink server configServer
server openapiGenerate OpenAPI specificationneurolink server openapiServer
rag chunkChunk documents for RAGneurolink rag chunk f.mdRAG CLI

RAG flags are available on generate and stream: --rag-files, --rag-strategy, --rag-chunk-size, --rag-chunk-overlap, --rag-top-k

📖 Complete CLI Reference - All commands and options


🤖 GitHub Action

Run AI-powered workflows directly in GitHub Actions with 21+ provider support and automatic PR/issue commenting.

- uses: juspay/neurolink@v1
  with:
    anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
    prompt: "Review this PR for security issues and code quality"
    post_comment: true
FeatureDescription
Multi-Provider21+ providers with unified interface
PR/Issue CommentsAuto-post AI responses with intelligent updates
Multimodal SupportAttach images, PDFs, CSVs, Excel, Word, JSON, YAML, XML, HTML, SVG, code files to prompts
Cost TrackingBuilt-in analytics and quality evaluation
Extended ThinkingDeep reasoning with thinking tokens

📖 GitHub Action Guide - Complete setup and examples


💰 Smart Model Selection

NeuroLink features intelligent model selection and cost optimization:

Cost Optimization Features

  • 💰 Automatic Cost Optimization: Selects cheapest models for simple tasks
  • 🔄 LiteLLM Model Routing: Access 100+ models with automatic load balancing
  • 🔍 Capability-Based Selection: Find models with specific features (vision, function calling)
  • ⚡ Intelligent Fallback: Seamless switching when providers fail
# Cost optimization - automatically use cheapest model
npx @juspay/neurolink generate "Hello" --optimize-cost

# LiteLLM specific model selection
npx @juspay/neurolink generate "Complex analysis" --provider litellm --model "anthropic/claude-sonnet-4-6"

# Auto-select best available provider
npx @juspay/neurolink generate "Write code" # Automatically chooses optimal provider

Revolutionary Interactive CLI

NeuroLink’s CLI goes beyond simple commands - it’s a full AI development environment:

Why Interactive Mode Changes Everything

FeatureTraditional CLINeuroLink Interactive
Session StateNoneFull persistence
MemoryPer-commandConversation-aware
ConfigurationFlags per command/set persists across session
Tool TestingManual per toolLive discovery & testing
StreamingOptionalReal-time default

Live Demo: Development Session

$ npx @juspay/neurolink loop --enable-conversation-memory

neurolink > /set provider vertex
 provider set to vertex (Gemini 3 support enabled)

neurolink > /set model gemini-3-flash-preview
 model set to gemini-3-flash-preview

neurolink > Analyze my project architecture and suggest improvements

 Analyzing your project structure...
[AI provides detailed analysis, remembering context]

neurolink > Now implement the first suggestion
[AI remembers previous context and implements suggestion]

neurolink > /mcp discover
 Discovered 58 MCP tools:
   GitHub: create_issue, list_repos, create_pr...
   PostgreSQL: query, insert, update...
   [full list]

neurolink > Use the GitHub tool to create an issue for this improvement
 Creating issue... (requires HITL approval if configured)

neurolink > /export json > session-2026-01-01.json
 Exported 15 messages to session-2026-01-01.json

neurolink > exit
Session saved. Resume with: neurolink loop --session session-2026-01-01.json

Session Commands Reference

CommandPurpose
/set <key> <value>Persist configuration (provider, model, temperature)
/mcp discoverList all available MCP tools
/export jsonExport conversation to JSON
/historyView conversation history
/clearClear context while keeping settings

Interactive CLI Guide | CLI Reference

Skip the wizard and configure manually? See docs/getting-started/provider-setup.md.

CLI & SDK Essentials

neurolink CLI mirrors the SDK so teams can script experiments and codify them later.

# Discover available providers and models
npx @juspay/neurolink status
npx @juspay/neurolink models list --provider google-ai

# Route to a specific provider/model
npx @juspay/neurolink generate "Summarize customer feedback" \
  --provider azure --model gpt-4o-mini

# Turn on analytics + evaluation for observability
npx @juspay/neurolink generate "Draft release notes" \
  --enable-analytics --enable-evaluation --format json

# RAG: Ask questions about your docs (auto-chunks, embeds, searches)
npx @juspay/neurolink generate "What are the key features?" \
  --rag-files ./docs/guide.md ./docs/api.md --rag-strategy markdown

# Claude proxy + local OpenObserve dashboard
npx @juspay/neurolink proxy setup
npx @juspay/neurolink proxy telemetry setup
npx @juspay/neurolink proxy status --format json
import { NeuroLink } from "@juspay/neurolink";

const neurolink = new NeuroLink({
  conversationMemory: {
    enabled: true,
  },
  enableOrchestration: true,
});

const result = await neurolink.generate({
  input: {
    text: "Create a comprehensive analysis",
    files: [
      "./sales_data.csv", // Auto-detected as CSV
      "examples/data/invoice.pdf", // Auto-detected as PDF
      "./diagrams/architecture.png", // Auto-detected as image
      "./report.xlsx", // Auto-detected as Excel
      "./config.json", // Auto-detected as JSON
      "./diagram.svg", // Auto-detected as SVG (injected as text)
      "./app.ts", // Auto-detected as TypeScript code
    ],
  },
  provider: "vertex", // PDF-capable provider (see docs/features/pdf-support.md)
  enableEvaluation: true,
  region: "us-east-1",
});

console.log(result.content);
console.log(result.evaluation?.overallScore);

// RAG: Ask questions about your documents
const answer = await neurolink.generate({
  input: { text: "What are the main architectural decisions?" },
  rag: {
    files: ["./docs/architecture.md", "./docs/decisions.md"],
    strategy: "markdown",
    topK: 5,
  },
});
console.log(answer.content); // AI searches your docs and answers

Gemini 3 with Extended Thinking

import { NeuroLink } from "@juspay/neurolink";

const neurolink = new NeuroLink();

// Use Gemini 3 with extended thinking for complex reasoning
const result = await neurolink.generate({
  input: {
    text: "Solve this step by step: What is the optimal strategy for...",
  },
  provider: "vertex",
  model: "gemini-3-flash-preview",
  thinkingConfig: {
    thinkingLevel: "medium", // Options: "minimal", "low", "medium", "high"
  },
});

console.log(result.content);

Full command and API breakdown lives in docs/cli/commands.md and docs/sdk/api-reference.md.

Platform Capabilities at a Glance

CapabilityHighlights
Provider unification21+ providers with automatic fallback, cost-aware routing, providerFallback policy, modelChain config.
Multimodal pipelineStream images + CSV data + PDF documents across providers with local/remote assets. Auto-detection for mixed file types.
Voice pipelineTTS (6 providers: Google, OpenAI, ElevenLabs, Azure, Fish Audio, Cartesia) + STT (4 providers) + realtime voice APIs (OpenAI Realtime, Gemini Live).
Quality & governanceAuto-evaluation engine (14 scorers), guardrails middleware, HITL workflows, audit logging.
Memory & contextPer-user condensed memory (S3/Redis/SQLite), Redis session export, 4-stage context compaction.
CLI toolingLoop sessions, setup wizard, config validation, Redis auto-detect, JSON output, TTS/STT flags.
Enterprise opsClaude proxy, OTLP observability, OpenObserve dashboard, regional routing, credential management.
Tool ecosystemMCP auto discovery, HTTP/stdio/SSE/WebSocket transports, LiteLLM hub access, SageMaker custom deployment, web search.

Documentation Map

AreaWhen to UseLink
Getting startedInstall, configure, run first promptdocs/getting-started/index.md
Feature guidesUnderstand new functionality front-to-backdocs/features/index.md
CLI referenceCommand syntax, flags, loop sessionsdocs/cli/index.md
SDK referenceClasses, methods, optionsdocs/sdk/index.md
RAGDocument chunking, hybrid search, reranking, rag:{} APIdocs/features/rag.md
IntegrationsLiteLLM, SageMaker, MCPdocs/litellm-integration.md
AdvancedMiddleware, architecture, streaming patternsdocs/advanced/index.md
CookbookPractical recipes for common patternsdocs/cookbook/index.md
GuidesMigration, Redis, troubleshooting, provider selectiondocs/guides/index.md
OperationsConfiguration, troubleshooting, provider matrixdocs/reference/index.md

New in 2026: Enhanced Documentation

Enterprise Features:

Provider Intelligence:

Middleware System:

Redis & Persistence:

Migration Guides:

Developer Experience:

Integrations

Contributing & Support


NeuroLink is built with ❤️ by Juspay. Contributions, questions, and production feedback are always welcome.

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