frai

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FRAI · Framework of Responsible Artificial Intelligence

FRAI (Framework of Responsible Artificial Intelligence) is an open-source toolkit that helps any team — from solo developers to compliance officers — ship AI features responsibly. It walks you through quick questions, scans your code, and generates documentation you can actually hand to stakeholders: implementation checklists, model cards, risk files, evaluation reports, and policy-aware RAG indexes.

Think of FRAI as a safety net for AI launches: it collects the right facts, highlights blind spots, and keeps evidence tidy so production reviews stop feeling like guesswork.

🚀 Getting Started

1. Install FRAI globally:

npm install -g frai

2. Set up your OpenAI API key (required for AI-powered tips):

frai --setup

You only need to do this once per machine or project. Your key is stored securely and never shared.

3. Run FRAI in your project:

frai

Tip: frai is available globally after installing the published npm package. If you're working from a local clone, follow the steps in Local Development to run the CLI from source.

🛠️ CLI Commands & Features

Command	Description
frai	Interactive mode for documenting an AI feature (8-question progressive system)
frai --scan	Scan codebase for AI/ML code and generate docs
frai --setup	Set up your OpenAI API key (local/global)
frai --ci	Run in CI mode (non-interactive)
frai --help, -h	Show help and usage info
frai --version, -v	Show current version
frai --update	Check for new versions of FRAI
frai --list-docs	List generated documentation files
frai --clean	Remove generated documentation files
frai --export-pdf	Export documentation markdown files as PDFs
frai --show-config	Show API key config status
frai --key=API_KEY	Provide OpenAI API key directly (one-off use)
frai --global	Use with --setup to save API key globally
frai rag index	Index compliance docs into a local vector store
frai eval	Run baseline evaluation metrics and write reports

RAG Indexing

frai rag index --input docs/policies --output .frai/compliance-index.json --chunk-size 400

• Scans .md, .txt, .json, .yaml files recursively.
• Generates a lightweight JSON vector store consumable by SDKs and future connectors.

Evaluation Harness

frai eval --outputs runs/outputs.json --references runs/golden.json --report reports/eval --format markdown

• Runs baseline metrics (exact match, toxicity keyword scan, length variance).
• Produces JSON and/or Markdown summaries for CI and governance reviews.

Docs generated:

• checklist.md — Implementation checklist
• model_card.md — Model card
• risk_file.md — Risk & compliance

💡 Features

• Progressive 8-question system: Context-aware, fast, and actionable
• AI-powered recommendations: Get tailored tips for responsible AI
• Comprehensive documentation: Checklist, model card, and risk file
• PDF export: Convert docs to PDF with one command
• Codebase scanning: Detects AI/ML code and generates relevant docs
• Easy setup: One-time API key configuration
• Compliance-aware RAG: Build vector stores from policies for knowledge-grounded guardrails
• Evaluation harness: Run baseline metrics and capture auditable reports

Monorepo Layout

frai/
├─ packages/
│  ├─ frai-cli/      # CLI entry point and command wiring
│  └─ frai-core/     # Reusable services (config, questionnaire, documents, scanners, RAG, eval)
├─ docs/             # Roadmaps, design notes, and feature backlogs
└─ examples/         # Sample AI projects used in tests and demos

🔑 API Key Setup

FRAI requires an OpenAI API key for generating AI-powered tips and documentation. Run:

frai --setup

If you skip this step, FRAI will prompt you to set up your key on first use.

🧑‍💻 Local Development

Run FRAI directly from this repository without publishing:

pnpm install
pnpm --filter frai run build
node packages/frai-cli/dist/index.js --help

Configure an OpenAI key from source

• Interactive CLI:

  node packages/frai-cli/dist/index.js --setup YOUR_KEY
  

• Manual .env:

  OPENAI_API_KEY=YOUR_KEY
  

To test the global binary locally (without npm publishing), install the workspace package:

pnpm install --global ./packages/frai-cli
# then:
frai --setup

📖 Learn More

• GitHub Repository
• NPM Package
• AI Feature Backlog
• Evaluation Harness Design

Generated by FRAI - Responsible AI in Minutes