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FRAI · Framework of Responsible Artificial Intelligence

!npm version

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:
``bash
npm install -g frai
`

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

$3

`bash
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.

$3

`bash
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

`
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

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

$3

- Interactive CLI:
`bash
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:

`bash
pnpm install --global ./packages/frai-cli


then:

---

📖 Learn More

---

Generated by FRAI - Responsible AI in Minutes