SocialSage AI - Autonomous Trading Agent System

A social-first AI trading analysis platform with autonomous agents that help users make informed trading decisions by analyzing social sentiment and market data.

Project Structure

socialsage-ai/
├── frontend/    # Next.js Frontend Application
├── backend/     # Firebase Functions Backend
└── agent/       # Autonomous Agent System

Architecture

The system consists of several key components:

1. Scout Module: Monitors various data sources for potential opportunities

   • Twitter sentiment analysis
   • DeFi protocol APY tracking
   • On-chain activity monitoring

2. AI Judge: Evaluates opportunities and makes spawning decisions

   • Risk assessment
   • Capital requirement analysis
   • Success probability prediction

3. Agent Factory: Creates and deploys new agent instances

   • Deterministic wallet generation
   • Docker container deployment
   • Initial capital allocation

4. Health Monitor: Manages agent lifecycle

   • Performance tracking
   • Auto-termination conditions
   • Audit trail maintenance

Tech Stack

• Frontend: Next.js, TypeScript, Tailwind CSS
• Backend: Firebase Functions, Firebase Admin SDK
• AI/ML: AWS Bedrock, OpenAI
• Database: Firebase Firestore
• Authentication: Firebase Auth
• Storage: Firebase Storage
• Blockchain: Ethers.js, Uniswap V3 SDK
• Containerization: Docker

Setup Instructions

Prerequisites

• Node.js (v18 or higher)
• pnpm
• Firebase CLI
• AWS Account (for Bedrock)
• Docker

Agent System Setup

1. Install dependencies:

pnpm install

2. Configure environment:

cp .env.example .env
# Edit .env with your configuration

3. Build and run:

# Development mode
pnpm dev

# Production build
pnpm build
pnpm start

Docker Deployment

Build and run the agent system:

# Build image
docker build -t autonomous-agent .

# Run container
docker run -d \
  --name autonomous-agent \
  --env-file .env \
  autonomous-agent

Backend Setup

1. ✅ Initialize Firebase Admin SDK
2. ✅ Set up service account key
3. ✅ Create Firebase Functions:
   • ✅ User Authentication
   • Market Analysis
   • Social Integration
4. 🚧 AWS Bedrock Integration:
   • Set up AWS credentials
   • Configure Bedrock client

Frontend Setup

1. ✅ Initialize Next.js project
2. 🚧 Create Core Components:
   • ✅ Authentication hooks
   • Dashboard
   • Analysis View
   • Social Feed
3. ✅ Firebase Client Integration

Environment Setup

1. Backend Environment Variables (backend/.env):

FIREBASE_PROJECT_ID=your-project-id

2. Frontend Environment Variables (frontend/.env.local):

NEXT_PUBLIC_FIREBASE_API_KEY=your-api-key
NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN=your-auth-domain
NEXT_PUBLIC_FIREBASE_PROJECT_ID=your-project-id
NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET=your-storage-bucket
NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID=your-messaging-sender-id
NEXT_PUBLIC_FIREBASE_APP_ID=your-app-id

Security Considerations

• All spawned agents run in isolated environments
• Multi-sig controlled treasury
• Strict capital allocation limits
• Automated health monitoring and termination
• Comprehensive audit logging

Contributing

This is a hackathon project for ETHGlobal Agents.

License

MIT