# ⚖️ Astraea — Self-Hosted AI Family-Law Assistant for Washington State

> **Eight specialist AI agents. Grounded in verified Washington law. Your documents never leave your network.**

Astraea is a self-hosted, multi-agent legal information assistant focused on Washington State family law: divorce, custody, child support, maintenance, property division, protection orders, and mediation. It combines retrieval-augmented generation (RAG) over a curated library of state-specific legal references with tool-calling LLM agents, PDF form auto-fill, per-user document vaults, and optional Twilio/SMTP communications — all running on your own hardware with your own models.

**Live instance:** https://astraea.thetempleofdoom.com

---

## Why Astraea

People going through divorce or custody battles face three problems: lawyers are expensive, court forms are intimidating, and generic chatbots hallucinate the law. Astraea attacks all three:

1. **Grounded answers, not vibes.** Every agent answers from a curated book library (185KB of verified WA-law reference material citing RCW chapters, controlling case law like *In re Marriage of Littlefield*, and WashingtonLawHelp.org). Responses carry citations back to the source chunks.
2. **Specialists, not one generic bot.** Eight agents, each with its own system prompt, book subset, and focus — from the intake Navigator to the Protection Orders specialist with built-in DV-safety guardrails.
3. **Self-hosted and private.** Runs on a Proxmox LXC container, talks to a LAN Ollama server, and stores everything in a local SQLite database. No cloud APIs, no data leaving your network.

> ⚠️ **Not legal advice.** Astraea is an educational and organizational tool. It does not replace a licensed Washington attorney. This notice is embedded in the product, the agents' system prompts, and every source book.

## The Eight Specialists

| Agent | Focus |
|---|---|
| 🧭 **Navigator** | Intake — where to start, which specialist next, the overall WA process |
| ⚖️ **Divorce & Dissolution** | No-fault dissolution, legal separation, the 90-day wait, decrees |
| 🧒 **Child Custody & Parenting** | Parenting plans, best-interest factors, relocation, nonparental custody |
| 💰 **Child Support** | Washington's economic table, imputation, deviations |
| 🤝 **Spousal Maintenance** | Alimony factors, duration, modification |
| 🏠 **Property & Debt** | Characterization, fair-and-equitable division, QDROs |
| 🛡️ **Protection** | Protection orders, no-contact orders, DV safety planning |
| 🕊️ **Mediation & ADR** | Mediation, arbitration, collaborative law, settlement strategy |

## Feature Highlights

- **Multi-agent RAG chat** — stdlib-only vector engine (embeddings via Ollama, cosine retrieval, cached disk index, incremental rebuild when a book changes)
- **Per-user document vault** — upload filings/correspondence/evidence; text extracted (PDF/DOCX/TXT), chunked, embedded, and retrieved as `[USER DOC]` context in chats
- **PDF form auto-fill** — 10+ Washington court form packets (FL All-Cases series) with field detection (`detect_fields.py` + `pymupdf` overlay) and LLM-assisted mapping from your case facts
- **Document generation** — declarations, letters, timelines generated from your case context
- **Comms missions with DV safety guard** — Twilio SMS/voice + SMTP email with a hard block on contacting anyone protected by a no-contact/protection order, plus formal message templates
- **No-KYC auth** — username/password only, per-user profiles with an "About Me" context system, 12 professional avatars
- **Text-to-speech** — every answer speakable via edge-tts
- **Conversation memory** — per-agent persisted history in SQLite
- **Zero cloud dependencies** — Flask + SQLite + Ollama; the RAG engine is pure stdlib (urllib + json + math)

## Architecture

```
                    ┌─────────────────────────────────────────┐
  Browser ──HTTPS──▶│  nginx (TLS termination, fleet tunnel)  │
                    └───────────────┬─────────────────────────┘
                                    │ :5000
                    ┌───────────────▼───────────────┐
                    │  Astraea (Flask + gunicorn)   │
                    │  ├─ agents.py   8 specialists │
                    │  ├─ rag.py      vector engine │
                    │  ├─ store.py    SQLite DAL    │
                    │  ├─ userdocs.py doc vault     │
                    │  ├─ forms.py    PDF autofill  │
                    │  ├─ comms.py    Twilio/SMTP   │
                    │  └─ tts.py      edge-tts      │
                    └───────────────┬───────────────┘
                                    │ LAN
                    ┌───────────────▼───────────────┐
                    │  Ollama host (GPU)            │
                    │  ├─ qwen3.8fast  orchestrator │
                    │  ├─ ornith-1.5:9b fallback    │
                    │  └─ nomic-embed  embeddings   │
                    └───────────────────────────────┘
```

**Repo layout**

```
├── app.py              # Flask app: routes, chat orchestration, uploads (757 lines)
├── agents.py           # The 8 specialist definitions (system prompts, book subsets)
├── rag.py              # Stdlib-only RAG: chunk → embed → cosine retrieve → cite
├── store.py            # SQLite: users, sessions, profiles, settings, messages, files
├── documents.py        # Generated-document engine
├── detect_fields.py    # PDF form field detection (pymupdf)
├── forms.py            # Court-form fill + overlay endpoints
├── comms.py            # Twilio SMS/voice + SMTP, no-contact safety guard
├── tts.py              # edge-tts speech synthesis
├── userdocs.py         # Per-user document vault ingestion
├── books/              # 16 curated WA family-law reference books (the RAG corpus)
├── templates/          # Landing page + app SPA (vanilla JS, no build step)
├── static/             # Assets
├── astraea.service     # systemd unit (gunicorn, 2 workers × 4 threads)
├── astraea-nginx.conf  # nginx site config
└── benchmark_models.py # Model-selection benchmark harness
```

## Quick Start

### Requirements
- Python 3.11+ (3.9 works with minor tweaks — stdlib-only core)
- An [Ollama](https://ollama.com) server reachable on your LAN with:
  - `qwen3.8fast` (or any tool-calling model) — orchestrator
  - `ornith-1.5:9b` (or any reliable instruct model) — fallback
  - `nomic-embed-text-v2-moe` — embeddings
- Optional: `pymupdf` for PDF form filling, `edge-tts` for speech

### Install

```bash
git clone http://10.30.20.149:3000/drjones/astraea.git
cd astraea
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt
pip install pymupdf edge-tts   # optional features
```

### Configure

Point the agents at your Ollama host in `agents.py`:

```python
OLLAMA_URL    = "http://your-ollama-host:11434"
RAG_MODEL     = "qwen3.8fast"       # tool-calling orchestrator
GENERAL_MODEL = "ornith-1.5:9b"     # fallback
EMBED_MODEL   = "nomic-embed-text-v2-moe"
```

The vector index builds on first boot (background thread) and caches to `index.json`.

### Run

```bash
python app.py                       # dev, port 5000
# or production:
gunicorn --workers 2 --threads 4 --bind 0.0.0.0:5000 --timeout 240 app:app
```

Register a user, answer the About-Me prompts (this becomes silent context for every agent), and start with the **Navigator**.

### Deploy on Proxmox LXC (how we run it)

```bash
pct create 150 local:vztmpl/debian-12-standard_12.12-1_amd64.tar.zst \
  --hostname astraea --memory 2048 --cores 2 \
  --net0 name=eth0,bridge=vmbr0,ip=10.30.20.160/24,gw=10.30.20.1 \
  --rootfs poolmaster:8 --unprivileged 1
pct start 150
# then: install python3-venv, clone, pip install, cp astraea.service /etc/systemd/system/
systemctl enable --now astraea
```

nginx TLS termination + Cloudflare Tunnel gives the public URL. See `astraea-nginx.conf`.

## The RAG Corpus

`books/` contains 16 reference books (~185KB) written as structured Markdown, each with inline citations to RCW statutes, Washington case law, and WashingtonLawHelp.org:

- `divorce-dissolution.md` + 3 case-law companions (characterization, division, maintenance)
- `custody-parenting.md`, `parentage.md`, `guardianship.md`
- `child-support.md`, `spousal-maintenance.md`, `property-debt.md`
- `protection-orders.md`, `mediation-adr.md`, `modification-enforcement.md`
- `overview-intake.md`, `committed-relationships.md`, `adoption.md`

The index is chunked at ~1200 chars, embedded once, and rebuilt incrementally per-book on change. Retrieval returns top-k chunks as `[SOURCE n]` blocks the agent must cite.

## Safety Design

- **Not-legal-advice notice** in the product UI, agent system prompts, and every book header
- **No-contact safety guard** (`comms.py`): if a user's profile indicates a protection/no-contact order is in effect, outbound Twilio/SMTP actions toward the protected party are hard-blocked with a safety message
- **No-KYC by design**: no emails, no phone numbers required at signup; users stay anonymous
- **Local-only data**: uploads, chats, and profiles live in one SQLite file on your container

## Known Limitations & Roadmap

- [ ] **Password hashing is unsalted SHA-256** — needs bcrypt/argon2 with a transparent re-hash-on-login migration (next security release)
- [ ] Session tokens don't expire — add TTL + refresh
- [ ] No rate limiting on auth/chat endpoints
- [ ] Single-node SQLite — Postgres adapter for multi-user scale
- [ ] Books cover WA only — contributions for other states welcome (keep the citation format!)
- [ ] Streaming responses (currently full-answer)

## Operations

```bash
systemctl status astraea          # service health
curl localhost:5000/api/health    # app health + index status
curl -X POST localhost:5000/api/reindex   # force full RAG rebuild
```

Database backup: `cp astraea.db astraea.db.bak-$(date +%F)` — everything (users, chats, vault metadata) is in that one file. Uploads live in `uploads/`.

## Credits

Built by [drjones](https://github.com/drjonesxxx1) on a Proxmox homelab with local Ollama models — no cloud APIs were harmed.

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*Licensed under MIT — see [LICENSE](LICENSE). Legal reference material is educational, cites public sources, and is not legal advice.*