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README.md

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| `frai rag index` | Index compliance docs into a local vector store |
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| `frai eval` | Run baseline evaluation metrics and write reports |
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### RAG Indexing
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```bash
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frai rag index --input docs/policies --output .frai/compliance-index.json --chunk-size 400
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```
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- Scans `.md`, `.txt`, `.json`, `.yaml` files recursively.
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- Generates a lightweight JSON vector store consumable by SDKs and future connectors.
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### Evaluation Harness
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```bash
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frai eval --outputs runs/outputs.json --references runs/golden.json --report reports/eval --format markdown
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```
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- Runs baseline metrics (exact match, toxicity keyword scan, length variance).
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- Produces JSON and/or Markdown summaries for CI and governance reviews.
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**Docs generated:**
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- `checklist.md` — Implementation checklist
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- `model_card.md` — Model card
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- **PDF export**: Convert docs to PDF with one command
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- **Codebase scanning**: Detects AI/ML code and generates relevant docs
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- **Easy setup**: One-time API key configuration
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- **Compliance-aware RAG**: Build vector stores from policies for knowledge-grounded guardrails
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- **Evaluation harness**: Run baseline metrics and capture auditable reports
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### Monorepo Layout
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```
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frai/
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├─ packages/
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│ ├─ frai-cli/ # CLI entry point and command wiring
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│ └─ frai-core/ # Reusable services (config, questionnaire, documents, scanners, RAG, eval)
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├─ docs/ # Roadmaps, design notes, and feature backlogs
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└─ examples/ # Sample AI projects used in tests and demos
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```
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## 📖 Learn More
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- [GitHub Repository](https://github.com/sebastianbuzdugan/frai)
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- [NPM Package](https://www.npmjs.com/package/frai)
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- [AI Feature Backlog](docs/ai_feature_backlog.md)
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- [Evaluation Harness Design](docs/eval_harness_design.md)
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