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Advanced Research Go Implementation

A comprehensive Go implementation of the Advanced Research framework for symbiotic intelligence with NeuralBlitz integration.

Overview

This Go implementation provides high-performance, production-ready systems for:

  • Learning Record Store (LRS) Integration: Real-time learning analytics
  • Opencode Documentation: Structured research workflow management
  • NeuralBlitz v50: Geometric deep learning and tensor computation
  • Unified API System: Multi-modal research processing
  • Automated Pipeline: Ideas → Synthesis → Implementation workflow

Architecture

cmd/
├── server/          # HTTP/gRPC server
├── cli/            # Command-line interface
└── worker/         # Background workers

pkg/
├── core/           # Core context injection
├── lrs/            # LRS integration
├── opencode/       # Opencode integration  
├── neuralblitz/    # Geometric computation
├── unified/        # Unified API
├── pipeline/       # Research pipeline
└── config/         # Configuration management

internal/
├── storage/        # Database interfaces
├── transport/      # HTTP/gRPC transport
└── utils/          # Internal utilities

api/                # Protocol buffers
web/                # Web frontend (optional)

Quick Start

Prerequisites

  • Go 1.21 or later
  • Git
  • Docker (optional)

Installation

# Clone the repository
git clone https://github.com/advanced-research/go
cd go

# Install dependencies
go mod download

# Build the CLI
make build

# Run the server
make server

# Run the CLI
./bin/advanced-research --help

Development

# Run tests
make test

# Run tests with coverage
make test-coverage

# Format code
make fmt

# Lint code
make lint

# Generate protocol buffers
make generate

# Run development server
make dev

Configuration

The system uses YAML configuration files. See configs/default.yaml for default settings.

server:
  http_port: 8080
  grpc_port: 9090
  
integrations:
  lrs:
    enabled: true
    endpoint: "http://localhost:8080/xapi/"
  opencode:
    enabled: true
    workspace: "advanced-research"
  neuralblitz:
    enabled: true
    backend: "cuda"

Usage

CLI Usage

# Initialize the system
./bin/advanced-research init

# Create a research session
./bin/advanced-research session create --user "researcher@example.com"

# Process a research query
./bin/advanced-research query "Create a geometric deep learning model"

# Run automated pipeline
./bin/advanced-research pipeline run --ideas "Idea 1,Idea 2,Idea 3"

# Check system status
./bin/advanced-research status

HTTP API Usage

# Start the server
./bin/advanced-research server

# Create session
curl -X POST http://localhost:8080/api/v1/sessions \
  -H "Content-Type: application/json" \
  -d '{"user_id": "researcher@example.com", "mode": "research"}'

# Process query
curl -X POST http://localhost:8080/api/v1/query \
  -H "Content-Type: application/json" \
  -d '{"session_id": "session-123", "query": "Analyze this theory"}'

Performance

The Go implementation provides:

  • High Concurrency: Goroutine-based parallel processing
  • Low Latency: Optimized HTTP/gRPC servers
  • Memory Efficiency: Careful memory management
  • Scalability: Horizontal scaling support

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests
  5. Submit a pull request

License

MIT License - see LICENSE file for details.