Getting Started

Getting Started

Requirements

• Python 3.11 or 3.12
• pip 23+

---

Install

# Governance platform + REST API (minimum)
pip install "rai-governance-platform[dashboard]"

# Add PostgreSQL driver
pip install "rai-governance-platform[dashboard,postgres]"

# Add Redis (distributed rate limiting)
pip install "rai-governance-platform[dashboard,redis]"

# Add OpenTelemetry
pip install "rai-governance-platform[dashboard,telemetry]"

# Add LLM providers (for bias evaluation)
pip install "rai-governance-platform[dashboard,openai,anthropic]"

# Everything
pip install "rai-governance-platform[all]"

---

5-minute quickstart

1. Start the dashboard

# No auth, SQLite in-memory (dev mode)
RAI_AUTH_ENABLED=false \
uvicorn responsibleai.dashboard.app:app --port 8765

Open http://localhost:8765 — live dark-mode dashboard.
API docs: http://localhost:8765/api/docs

2. Evaluate a model

curl -s -X POST http://localhost:8765/api/evaluate \
  -H "Content-Type: application/json" \
  -d '{
    "model_name": "gpt-4o",
    "provider": "openai",
    "fairness": 0.80,
    "privacy": 0.85,
    "security": 0.82,
    "robustness": 0.78,
    "compliance": 0.90,
    "authenticity": 0.88
  }' | python3 -m json.tool

3. Scan for PII

curl -s -X POST http://localhost:8765/api/scan \
  -H "Content-Type: application/json" \
  -d '{"text": "Call me at 555-123-4567 or user@company.com. My SSN is 123-45-6789."}' \
  | python3 -m json.tool

4. Check compliance

curl -s http://localhost:8765/api/health | python3 -m json.tool

---

Production setup

# Generate an API key
python3 -c "import secrets; print(secrets.token_urlsafe(32))"
# → example: abc123xyz...

# Start with auth and persistent SQLite
RAI_API_KEYS=abc123xyz \
RAI_DB_PATH=/var/lib/rai/governance.db \
uvicorn responsibleai.dashboard.app:app \
  --host 0.0.0.0 --port 8765 --workers 4

Run Alembic before first production start:

RAI_DB_PATH=/var/lib/rai/governance.db alembic upgrade head

---

Python SDK

from responsibleai import (
    TrustScoreEngine,
    ComplianceEngine,
    GuardrailsEngine,
    HallucinationDetector,
    RedTeamSimulator,
    CostTracker,
    ModelRouter,
    TrustDriftMonitor,
    PassportGenerator,
)

engine = TrustScoreEngine()
score = engine.compute(
    fairness=0.80, privacy=0.85, security=0.82,
    robustness=0.78, compliance=0.90, authenticity=0.88,
)
print(f"{score.overall:.1f}/100  Grade: {score.grade}  Risk: {score.risk_level}")

---

MCP Server (Claude Code)

pip install "rai-governance-platform[mcp]"

Add to ~/.claude/claude_desktop_config.json:

{
  "mcpServers": {
    "responsibleai": {
      "command": "responsibleai-mcp",
      "env": {
        "RAI_API_URL": "http://localhost:8765",
        "RAI_API_KEY": "your-key"
      }
    }
  }
}

Now Claude Code has 10 governance tools available. See MCP Server for full reference.

---

Docker

git clone https://github.com/Guruprasath-Annadurai/ResponsibleAi.git
cd ResponsibleAi
cp .env.example .env
# Edit .env — set RAI_API_KEYS
docker compose up -d