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Deployment Guide

| Requirement | Minimum | Recommended | |-------------|---------|-------------| | Node.js | v18.x | v20.x+ | | Python | 3.9+ | 3.11+ | | RAM | 1 GB | 4 GB | | Storage | 100 MB | 1 GB (with history) |

Agents That Account for Themselves proposal experiment writeup candidate score 36 .md

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Deployment Guide

> Step-by-step guide to deploying the Agent Reputation System

---

📋 Prerequisites

System Requirements

RequirementMinimumRecommended
Node.jsv18.xv20.x+
Python3.9+3.11+
RAM1 GB4 GB
Storage100 MB1 GB (with history)

Dependencies

Node.js:

bash
npm install

Python:

bash
pip install -r requirements.txt
# Or manually:
pip install dataclasses datetime typing

> Note: The Python modules use only standard library components.

---

🚀 Quick Start

1. Clone & Install

bash
git clone <repository-url>
cd agent-reputation
npm install

2. Run Demos

bash
# TypeScript demo
npm run demo

# Python demos
python3 reputation_markets.py
python3 reputation_dynamics.py

3. Build for Production

bash
npm run build
# Output: dist/trust-bootstrap.js

---

🏗️ Deployment Options

Option A: Embedded Library

Use directly in your Node.js/Python application.

TypeScript:

typescript
import {
  TrustBootstrapEngine,
  PeerAssessmentEngine,
  TrustTransferProtocol
} from './trust-bootstrap';

import { ReputationPredictionMarket, Domain } from './src/prediction-market';

// Initialize
const engine = new TrustBootstrapEngine();
const market = new ReputationPredictionMarket();

Python:

python
from reputation_markets import ReputationMarketplace, PredictionType
from reputation_dynamics import CascadeEngine, TrajectoryRouter

# Initialize
marketplace = ReputationMarketplace()
cascade = CascadeEngine()
router = TrajectoryRouter(cascade)

Option B: Microservice

Wrap in REST API for external access.

Express.js Example:

typescript
import express from 'express';
import { ReputationPredictionMarket } from './src/prediction-market';

const app = express();
const market = new ReputationPredictionMarket();

app.post('/agents', (req, res) => {
  const agent = market.registerAgent(req.body.name, req.body.domains);
  res.json(agent);
});

app.post('/markets', (req, res) => {
  const m = market.createPredictionMarket(
    req.body.taskId,
    req.body.description,
    req.body.domain,
    req.body.agentId,
    new Date(req.body.deadline)
  );
  res.json(m);
});

app.post('/bets', (req, res) => {
  const bet = market.placeBet(
    req.body.marketId,
    req.body.bettorId,
    req.body.prediction,
    req.body.amount,
    req.body.confidence
  );
  res.json(bet);
});

app.listen(3000);

Option C: Docker Container

Dockerfile:

dockerfile
FROM node:20-alpine

WORKDIR /app

COPY package*.json ./
RUN npm ci --only=production

COPY dist/ ./dist/
COPY src/ ./src/

EXPOSE 3000

CMD ["node", "dist/server.js"]

Build & Run:

bash
docker build -t agent-reputation .
docker run -p 3000:3000 agent-reputation

---

⚙️ Configuration

Environment Variables

VariableDefaultDescription
`INITIAL_BALANCE`1000Starting credits for new agents
`INITIAL_PRICE`50Default market price (0-100)
`CASCADE_THRESHOLD`0.7Herding detection (70
`INHERITANCE_RATIO`0.5Default hereditary ratio (50
`MARKET_MAKER_SPREAD`0.02AMM spread (2

Example `.env`:

bash
INITIAL_BALANCE=1000
INITIAL_PRICE=50
CASCADE_THRESHOLD=0.7
INHERITANCE_RATIO=0.5
LOG_LEVEL=info

Configuration File

Create `config.json` for advanced settings:

json
{
  "market": {
    "initialBalance": 1000,
    "initialPrice": 50,
    "minPrice": 1,
    "maxPrice": 99,
    "spreadPercent": 2
  },
  "cascade": {
    "herdingThreshold": 0.7,
    "maxGenerations": 4,
    "decayFactors": {
      "endorsement": 0.5,
      "guilt": 0.4,
      "glory": 0.6
    }
  },
  "lineage": {
    "defaultInheritance": "partial",
    "inheritanceRatio": 0.5,
    "mutationRate": 0.1,
    "parentAccountability": 0.3
  },
  "routing": {
    "defaultStrategy": "momentum_weighted",
    "minScoreThreshold": 0.3
  }
}

---

💾 Persistence Layer

The current implementation is in-memory only. For production, add persistence.

Option 1: SQLite (Simple)

python
import sqlite3

class PersistentMarketplace(ReputationMarketplace):
    def __init__(self, db_path="reputation.db"):
        super().__init__()
        self.conn = sqlite3.connect(db_path)
        self._init_tables()

    def _init_tables(self):
        self.conn.execute("""
            CREATE TABLE IF NOT EXISTS agents (
                id TEXT PRIMARY KEY,
                reputation REAL,
                data JSON
            )
        """)
        self.conn.execute("""
            CREATE TABLE IF NOT EXISTS markets (
                id TEXT PRIMARY KEY,
                state TEXT,
                data JSON
            )
        """)
        self.conn.commit()

    def save_agent(self, agent_id):
        manager = self.agent_managers.get(agent_id)
        if manager:
            self.conn.execute(
                "INSERT OR REPLACE INTO agents VALUES (?, ?, ?)",
                (agent_id, manager.total_reputation, json.dumps(vars(manager)))
            )
            self.conn.commit()

Option 2: Redis (Fast)

python
import redis
import json

class RedisMarketplace(ReputationMarketplace):
    def __init__(self, redis_url="redis://localhost:6379"):
        super().__init__()
        self.redis = redis.from_url(redis_url)

    def save_agent(self, agent_id):
        manager = self.agent_managers.get(agent_id)
        if manager:
            self.redis.hset("agents", agent_id, json.dumps({
                "reputation": manager.total_reputation,
                "stakes": len(manager.active_stakes)
            }))

    def load_agent(self, agent_id):
        data = self.redis.hget("agents", agent_id)
        if data:
            return json.loads(data)
        return None

Option 3: PostgreSQL (Scalable)

sql
-- Schema
CREATE TABLE agents (
    id VARCHAR(64) PRIMARY KEY,
    name VARCHAR(255),
    created_at TIMESTAMP DEFAULT NOW(),
    total_reputation DECIMAL(10,4),
    available_reputation DECIMAL(10,4),
    prediction_accuracy DECIMAL(5,4)
);

CREATE TABLE domain_profiles (
    agent_id VARCHAR(64) REFERENCES agents(id),
    domain VARCHAR(32),
    market_price DECIMAL(10,4),
    volume_24h DECIMAL(10,4),
    volatility DECIMAL(5,4),
    PRIMARY KEY (agent_id, domain)
);

CREATE TABLE markets (
    id VARCHAR(64) PRIMARY KEY,
    task_id VARCHAR(255),
    domain VARCHAR(32),
    assigned_agent VARCHAR(64) REFERENCES agents(id),
    state VARCHAR(16),
    success_pool DECIMAL(10,4),
    partial_pool DECIMAL(10,4),
    failure_pool DECIMAL(10,4),
    outcome VARCHAR(16),
    created_at TIMESTAMP DEFAULT NOW(),
    resolved_at TIMESTAMP
);

CREATE TABLE bets (
    id VARCHAR(64) PRIMARY KEY,
    market_id VARCHAR(64) REFERENCES markets(id),
    bettor_id VARCHAR(64) REFERENCES agents(id),
    prediction VARCHAR(16),
    amount DECIMAL(10,4),
    confidence DECIMAL(5,4),
    payout DECIMAL(10,4),
    created_at TIMESTAMP DEFAULT NOW()
);

---

📊 Monitoring

Health Check Endpoint

typescript
app.get('/health', (req, res) => {
  const summary = market.getMarketSummary();
  res.json({
    status: 'healthy',
    agents: summary.totalAgents,
    markets: summary.totalMarkets,
    openMarkets: summary.openMarkets,
    cascadeAlerts: summary.cascadeAlerts.length
  });
});

Prometheus Metrics

typescript
import { Counter, Gauge, Histogram } from 'prom-client';

const marketsCreated = new Counter({
  name: 'reputation_markets_created_total',
  help: 'Total prediction markets created'
});

const activeAgents = new Gauge({
  name: 'reputation_active_agents',
  help: 'Number of registered agents'
});

const betLatency = new Histogram({
  name: 'reputation_bet_latency_seconds',
  help: 'Time to place a bet',
  buckets: [0.01, 0.05, 0.1, 0.5, 1]
});

// Use in code
app.post('/bets', (req, res) => {
  const end = betLatency.startTimer();
  const bet = market.placeBet(...);
  end();
  res.json(bet);
});

Logging

typescript
import winston from 'winston';

const logger = winston.createLogger({
  level: process.env.LOG_LEVEL || 'info',
  format: winston.format.json(),
  transports: [
    new winston.transports.File({ filename: 'error.log', level: 'error' }),
    new winston.transports.File({ filename: 'combined.log' })
  ]
});

// Log significant events
logger.info('Market created', { marketId, taskId, assignedAgent });
logger.warn('Herding detected', { marketId, severity });
logger.error('Resolution failed', { marketId, error });

---

🔐 Security

Authentication

typescript
import jwt from 'jsonwebtoken';

const authenticate = (req, res, next) => {
  const [sensitive field redacted])[1];
  if (!token) return res.status(401).json({ error: 'No token' });

  try {
    req.agent = jwt.verify(token, process.env.JWT_SECRET);
    next();
  } catch {
    res.status(401).json({ error: 'Invalid token' });
  }
};

app.post('/bets', authenticate, (req, res) => {
  // Ensure bettorId matches authenticated agent
  if (req.body.bettorId !== req.agent.id) {
    return res.status(403).json({ error: 'Cannot bet as another agent' });
  }
  // ...
});

Rate Limiting

typescript
import rateLimit from 'express-rate-limit';

const limiter = rateLimit({
  windowMs: 60 * 1000, // 1 minute
  max: 100, // 100 requests per minute
  message: 'Too many requests'
});

app.use('/api/', limiter);

Input Validation

typescript
import Joi from 'joi';

const betSchema = Joi.object({
  marketId: Joi.string().required(),
  bettorId: Joi.string().required(),
  prediction: Joi.string().valid('success', 'partial', 'failure').required(),
  amount: Joi.number().min(1).max(1000).required(),
  confidence: Joi.number().min(0).max(1).required()
});

app.post('/bets', (req, res) => {
  const { error, value } = betSchema.validate(req.body);
  if (error) return res.status(400).json({ error: error.message });
  // ...
});

---

🔄 Integration Guide

With Clawdbot Sessions

typescript
// When spawning a sub-agent
const parentAgent = engine.getBootstrapResult(parentId);
const childAgent = engine.registerAgent(childId, childName, parentId);

// Child inherits 30% of parent trust
console.log(`Child trust level: ${childAgent.trustLevel}`);

With Pulse Task Completion

typescript
// On task complete
const outcome = taskSucceeded ? OutcomeType.SUCCESS : OutcomeType.FAILURE;
const quality = taskQualityScore; // 0-1

market.resolveMarket(marketId, outcome, quality);

With Task Router

typescript
// Route new task
const routing = market.routeTask(Domain.CODING);
console.log(`Assign to: ${routing.agentId}`);
console.log(`Confidence: ${routing.confidence * 100}%`);

---

🚦 Deployment Checklist

  • [ ] Install dependencies (`npm install`)
  • [ ] Configure environment variables
  • [ ] Set up persistence (SQLite/Redis/PostgreSQL)
  • [ ] Add authentication middleware
  • [ ] Configure rate limiting
  • [ ] Set up logging
  • [ ] Add health check endpoint
  • [ ] Configure Prometheus metrics
  • [ ] Run integration tests
  • [ ] Deploy to staging
  • [ ] Smoke test all endpoints
  • [ ] Deploy to production

---

📞 Support

  • Issues: Open GitHub issue
  • Documentation: See `/docs/` folder
  • API Reference: See inline TSDoc/docstrings

Promotion Decision

Attach run IDs, datasets, metrics, and reproduction commands.

Source Anchor

agent-reputation/docs/DEPLOYMENT_GUIDE.md

Detected Structure

Method · Evaluation · References · Figures · Code Anchors · Architecture