Astraea: WA family-law multi-agent site (Flask + Ollama semantic RAG)

.gitignore

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+venv/
+*.pyc
+__pycache__/

README.md

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+# Astraea ⚖️
+
+A constellation of **Washington State family-law specialist agents**, backed by a local
+Ollama semantic-RAG pipeline. Eight specialists, each grounded in its own cited corpus of
+Washington law (RCW), answer questions with inline citations — never from thin air.
+
+> For educational purposes only — not legal advice.
+
+## The eight specialists
+
+| Agent | Domain | Primary source |
+|---|---|---|
+| 🧭 Navigator | Court process, residency, intake, routing | RCW 26.09 (overview) |
+| ⚖️ Divorce & Dissolution | No-fault dissolution, legal separation, the 90-day wait | RCW 26.09 |
+| 🧒 Child Custody & Parenting | Parenting plans, best-interest factors, relocation | RCW 26.09 / 26.10 |
+| 💵 Child Support | Income-shares model, the economic table | RCW 26.19 |
+| 🕊️ Spousal Maintenance | Maintenance factors & duration | RCW 26.09.090 |
+| 🏠 Property & Debt | Community vs. separate property, division | RCW 26.16 / 26.09.080 |
+| 🛡️ Protection Orders | DV, anti-harassment, ERPO | RCW 7.105 |
+| 🤝 Mediation & ADR | Mandatory mediation, settlement, collaborative law | RCW 26.09.015 |
+
+## Architecture
+
+```
+Flask (gunicorn + nginx)          Ollama host (nightmare, RTX 4080 SUPER)
+  app.py ── /api/chat ──────────► granite4.2 (RAG answer, think:false, num_ctx<=16K)
+  rag.py  ── embed + retrieve ───► nomic-embed-text-v2-moe (semantic embeddings)
+  agents.py (8 specialist defs)
+  books/*.md  (8 cited WA-law corpora, chunked -> embedded -> index.json)
+```
+
+The RAG engine chunks each book on heading + sentence boundaries, embeds every chunk with
+`nomic-embed-text-v2-moe`, and retrieves the top-5 by cosine similarity. The answer model
+(`granite4.2`) is an instruction-follower that answers strictly from the retrieved context
+and says so when the answer isn't in the corpus.
+
+## Deploy (Proxmox LXC)
+
+```bash
+# On CT 150 "astraea" (10.30.20.160)
+/opt/astraea/venv/bin/gunicorn --workers 2 --threads 4 --bind 0.0.0.0:5000 --timeout 240 app:app
+# systemd: astraea.service  ·  nginx: /etc/nginx/sites-enabled/astraea (80 -> 5000)
+```
+
+Redeploy: `tar czf /tmp/a.tar.gz app.py rag.py agents.py templates/ && scp → proxmox → pct push 150 → extract → systemctl restart astraea`.
+
+Reindex (after editing a book): `curl -X POST http://<ct>:5000/api/reindex` (or restart the
+service). The vector index is cached at `/opt/astraea/index.json` and rebuilt only when a
+book changes.
+
+## API
+
+- `GET  /api/agents` — list specialists
+- `POST /api/chat` — `{agent_id, message, history?}` → `{answer, citations, grounded, latency_ms}`
+- `GET  /api/health` — agent count + index status
+- `POST /api/reindex` — rebuild the vector index
+
+## Public
+
+https://astraea.thetempleofdoom.com (Cloudflare fleet tunnel `1aeb1ac0` → 10.30.20.160:80)

agents.py

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+# -*- coding: utf-8 -*-
+"""Astraea — Washington State family-law specialist agents.
+Each agent scopes a domain and pulls from its own set of 'books' (markdown sources).
+"""
+
+# Backend Ollama (nightmare, RTX 4080 SUPER). Renumbers after reboot — .29 as of Sept 2026.
+OLLAMA_URL = "http://10.30.20.29:11434"
+EMBED_MODEL = "nomic-embed-text-v2-moe:latest"   # semantic embeddings (verified on nightmare)
+RAG_MODEL = "granite4.2:latest"                  # grounded-answer RAG lane (num_ctx <= 16384)
+GENERAL_MODEL = "qwen3.8fast:latest"             # fallback / general reasoning
+
+BOOKS_DIR = "/opt/astraea/books"
+
+# Each agent: id, name, emoji, tagline, description, books (list of .md filenames), system prompt.
+AGENTS = [
+    {
+        "id": "navigator",
+        "name": "Navigator",
+        "emoji": "\U0001F9ED",
+        "tagline": "Where to start",
+        "description": "Point you at the right specialist and walk through the Washington family-law process, from residency to final decree.",
+        "books": ["overview-intake.md", "mediation-adr.md"],
+        "accent": "#7dd3fc",
+        "system": (
+            "You are the Navigator, the intake specialist for Astraea, a Washington State "
+            "family-law assistant. Help a person understand the overall WA family-law process: "
+            "residency requirements, the steps of a dissolution (petition, service, the 90-day "
+            "waiting period, temporary orders, settlement, trial), court fees and fee waivers, "
+            "and whether they need a lawyer. Most importantly, identify which specialist they "
+            "should talk to next and tell them so."
+        ),
+    },
+    {
+        "id": "divorce",
+        "name": "Divorce & Dissolution",
+        "emoji": "\u2696\uFE0F",
+        "tagline": "Ending a marriage",
+        "description": "No-fault dissolution, legal separation, the 90-day wait, grounds, residency, and the decree.",
+        "books": ["divorce-dissolution.md"],
+        "accent": "#a5b4fc",
+        "system": (
+            "You are the Divorce & Dissolution specialist for Astraea, a Washington State "
+            "family-law assistant. Washington is a no-fault divorce state. Explain dissolution of "
+            "marriage and legal separation under RCW 26.09: residency requirements, the petition, "
+            "service, the 90-day waiting period, temporary orders, default, and the final decree. "
+            "Be clear about what 'no-fault' means and what the court can and cannot decide."
+        ),
+    },
+    {
+        "id": "custody",
+        "name": "Child Custody & Parenting",
+        "emoji": "\U0001F9D2",
+        "tagline": "Parenting plans",
+        "description": "Residential schedules, best-interest factors, restrictions, relocation, and nonparental custody.",
+        "books": ["custody-parenting.md"],
+        "accent": "#86efac",
+        "system": (
+            "You are the Child Custody & Parenting Plans specialist for Astraea, a Washington "
+            "State family-law assistant. Explain parenting plans and residential schedules under "
+            "RCW 26.09.184-.191: the best-interest-of-the-child factors, restrictions under "
+            "RCW 26.09.191 (domestic violence, abuse, etc.), decision-making, relocation, "
+            "and nonparental custody actions under RCW 26.10. Always center the child's safety "
+            "and best interests."
+        ),
+    },
+    {
+        "id": "child-support",
+        "name": "Child Support",
+        "emoji": "\U0001F4B5",
+        "tagline": "The support schedule",
+        "description": "Income-shares calculation, the WA economic table, deviations, imputed income, and modification.",
+        "books": ["child-support.md"],
+        "accent": "#fcd34d",
+        "system": (
+            "You are the Child Support specialist for Astraea, a Washington State family-law "
+            "assistant. Explain Washington's child support schedule under RCW 26.19: the "
+            "income-shares model, the economic table, how income is combined, standard "
+            "calculations and deviations, imputed income, healthcare and special expenses, and "
+            "how to modify an existing order. Give practical guidance, not a legal ruling."
+        ),
+    },
+    {
+        "id": "maintenance",
+        "name": "Spousal Maintenance",
+        "emoji": "\U0001F54A\uFE0F",
+        "tagline": "Alimony in WA",
+        "description": "Maintenance factors, duration, and when spousal support is ordered or modified.",
+        "books": ["spousal-maintenance.md"],
+        "accent": "#f0abfc",
+        "system": (
+            "You are the Spousal Maintenance (alimony) specialist for Astraea, a Washington State "
+            "family-law assistant. Explain maintenance under RCW 26.09.090: the statutory factors "
+            "(length of marriage, need, ability to pay, age/health, standard of living), how "
+            "duration is typically set, and modification or termination of maintenance awards. "
+            "Be honest that maintenance is fact-specific and discretionary."
+        ),
+    },
+    {
+        "id": "property",
+        "name": "Property & Debt",
+        "emoji": "\U0001F3E0",
+        "tagline": "Community property",
+        "description": "Separate vs. community property, characterization, division, pensions, and marital debt.",
+        "books": ["property-debt.md"],
+        "accent": "#fdba74",
+        "system": (
+            "You are the Property & Debt Division specialist for Astraea, a Washington State "
+            "family-law assistant. Washington is a community property state. Explain the "
+            "difference between separate and community property and debt (RCW 26.16), how assets "
+            "are characterized, the court's 'just and equitable' division standard (RCW 26.09.080), "
+            "pensions/retirement and QDROs, and how marital debt is allocated."
+        ),
+    },
+    {
+        "id": "protection",
+        "name": "Protection Orders",
+        "emoji": "\U0001F6E1\uFE0F",
+        "tagline": "Safety orders",
+        "description": "Domestic violence, anti-harassment, sexual assault, and extreme-risk protection orders (RCW 7.105).",
+        "books": ["protection-orders.md"],
+        "accent": "#fca5a5",
+        "system": (
+            "You are the Protection Orders & Safety specialist for Astraea, a Washington State "
+            "family-law assistant. Washington consolidated protection orders under RCW 7.105 "
+            "(effective July 1, 2022): domestic violence protection orders, civil anti-harassment, "
+            "sexual assault protection orders, stalking, and extreme risk protection orders. "
+            "Explain how to file, what each order does, and safety resources. If someone describes "
+            "immediate danger, tell them to call 911 and offer crisis resources."
+        ),
+    },
+    {
+        "id": "mediation",
+        "name": "Mediation & ADR",
+        "emoji": "\U0001F91D",
+        "tagline": "Settle, don't fight",
+        "description": "Mandatory mediation, settlement conferences, arbitration, collaborative law, and guardians ad litem.",
+        "books": ["mediation-adr.md"],
+        "accent": "#67e8f9",
+        "system": (
+            "You are the Mediation & Alternative Dispute Resolution specialist for Astraea, a "
+            "Washington State family-law assistant. Explain mandatory mediation in WA family law, "
+            "settlement conferences, arbitration, collaborative law, parenting-plan mediation, and "
+            "the role of guardians ad litem. Help people resolve disputes without a contested trial."
+        ),
+    },
+]
+
+AGENT_BY_ID = {a["id"]: a for a in AGENTS}
+
+DISCLAIMER = "Astraea provides general legal information for Washington State, not legal advice. For your specific situation, consult a licensed Washington attorney."

app.py

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+# -*- coding: utf-8 -*-
+"""Astraea — a constellation of Washington State family-law specialist agents.
+
+Flask app + semantic RAG backend. LLM (granite4.2 RAG lane) and embeddings
+(nomic-embed-text-v2-moe) run on the Ollama host (nightmare).
+"""
+import json
+import re
+import time
+import urllib.request
+
+from flask import Flask, jsonify, render_template, request
+
+import rag
+from agents import (
+    AGENTS, AGENT_BY_ID, OLLAMA_URL, RAG_MODEL, GENERAL_MODEL, DISCLAIMER,
+)
+
+app = Flask(__name__)
+
+
+def _ollama_chat(model, messages, num_ctx=16384, num_predict=1024, temperature=0.1, timeout=180):
+    payload = {
+        "model": model,
+        "messages": messages,
+        "stream": False,
+        "think": False,
+        "options": {
+            "temperature": temperature,
+            "num_predict": num_predict,
+            "num_ctx": num_ctx,
+        },
+    }
+    req = urllib.request.Request(
+        f"{OLLAMA_URL}/api/chat",
+        data=json.dumps(payload).encode("utf-8"),
+        headers={"Content-Type": "application/json"},
+    )
+    opener = urllib.request.build_opener(urllib.request.ProxyHandler({}))
+    with opener.open(req, timeout=timeout) as r:
+        d = json.loads(r.read().decode("utf-8"))
+    msg = d.get("message", {})
+    content = msg.get("content") or msg.get("thinking") or ""
+    return content.strip()
+
+
+def _strip_model_sources(text):
+    """Remove a model-written trailing 'Sources:'/'References:' block (defensive)."""
+    text = re.split(r"\n\s*(?:Sources|References|Citations)\s*:\s*\n", text, flags=re.I)[0]
+    text = re.split(r"\n\s*Sources?\s*$", text, flags=re.I)[0]
+    return text.strip()
+
+
+def _build_answer(agent, message, history):
+    top = rag.retrieve(message, agent["id"], top_k=5)
+    if not top:
+        return {
+            "answer": "I couldn't find relevant Washington law on that in my reference "
+                      "library yet. Try rephrasing, or ask the Navigator to point you to "
+                      "the right specialist.",
+            "citations": [],
+            "grounded": False,
+        }
+
+    context_blocks = []
+    citations = []
+    seen = set()
+    for i, (score, c) in enumerate(top, 1):
+        key = (c["source"], c["title"])
+        if key in seen:
+            continue
+        seen.add(key)
+        context_blocks.append(f"[{i}] ({c['source']} — {c['title']})\n{c['text']}")
+        citations.append({
+            "source": c["source"],
+            "title": c["title"],
+            "score": round(score, 3),
+            "snippet": c["text"][:260] + ("…" if len(c["text"]) > 260 else ""),
+        })
+
+    system = (
+        f"{agent['system']}\n\n"
+        "Rules:\n"
+        "- Answer the user's question DIRECTLY and concisely. Begin your answer immediately — "
+        "do NOT restate the question, do NOT narrate your reasoning, and do NOT say what you "
+        "are about to do.\n"
+        "- Answer using ONLY the reference documents provided below.\n"
+        "- Cite the RCW section (or source) inline for every legal claim, e.g. (RCW 26.09.030).\n"
+        "- If the documents do not contain the answer, say so clearly and suggest which "
+        "specialist or official resource to consult.\n"
+        "- Be practical and plain-English, specific to Washington State.\n"
+        "- Do NOT write a 'Sources' list at the end; cite inline only."
+    )
+    user = (
+        "REFERENCE DOCUMENTS:\n\n"
+        + "\n\n".join(context_blocks)
+        + f"\n\nUSER QUESTION: {message}"
+    )
+
+    messages = [{"role": "system", "content": system}]
+    if history:
+        for turn in history[-6:]:
+            if turn.get("role") in ("user", "assistant"):
+                messages.append({"role": turn["role"], "content": turn["content"]})
+    messages.append({"role": "user", "content": user})
+
+    try:
+        answer = _ollama_chat(RAG_MODEL, messages)
+    except Exception as e:
+        # Fall back to the general model if the RAG lane is unavailable.
+        try:
+            answer = _ollama_chat(GENERAL_MODEL, messages, num_ctx=16384)
+        except Exception:
+            return {
+                "answer": "The legal engine is temporarily unavailable. Please try again in a "
+                          "moment. (Backend LLM could not be reached.)",
+                "citations": [],
+                "grounded": False,
+            }
+
+    answer = _strip_model_sources(answer)
+    return {
+        "answer": answer,
+        "citations": citations,
+        "grounded": True,
+        "model": RAG_MODEL,
+    }
+
+
+@app.route("/")
+def index():
+    agents_public = [
+        {k: a[k] for k in ("id", "name", "emoji", "tagline", "description", "accent")}
+        for a in AGENTS
+    ]
+    return render_template("index.html", agents=agents_public, disclaimer=DISCLAIMER)
+
+
+@app.route("/api/agents")
+def api_agents():
+    return jsonify([
+        {k: a[k] for k in ("id", "name", "emoji", "tagline", "description", "accent")}
+        for a in AGENTS
+    ])
+
+
+@app.route("/api/chat", methods=["POST"])
+def api_chat():
+    data = request.get_json(force=True, silent=True) or {}
+    agent_id = (data.get("agent_id") or "navigator").strip()
+    message = (data.get("message") or "").strip()
+    history = data.get("history") or []
+    agent = AGENT_BY_ID.get(agent_id)
+    if not agent:
+        return jsonify({"error": "Unknown agent"}), 400
+    if not message:
+        return jsonify({"error": "Message required"}), 400
+    if len(message) > 4000:
+        message = message[:4000]
+
+    t0 = time.time()
+    result = _build_answer(agent, message, history)
+    result["latency_ms"] = round((time.time() - t0) * 1000)
+    result["agent"] = agent_id
+    return jsonify(result)
+
+
+@app.route("/api/health")
+def health():
+    return jsonify({"ok": True, "agent_count": len(AGENTS), "index": rag.index_status()})
+
+
+@app.route("/api/index/status")
+def index_status():
+    return jsonify(rag.index_status())
+
+
+@app.route("/api/reindex", methods=["POST"])
+def reindex():
+    try:
+        idx = rag.build_index()
+        return jsonify({"ok": True, "chunks": len(idx)})
+    except Exception as e:
+        return jsonify({"ok": False, "error": str(e)}), 500
+
+
+# Kick off the background index build once at import (before serving).
+rag.start_background_index()
+
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5000, threaded=True)

astraea-nginx.conf

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+server {
+    listen 80;
+    server_name _;
+
+    location / {
+        proxy_pass http://127.0.0.1:5000;
+        proxy_set_header Host $host;
+        proxy_set_header X-Real-IP $remote_addr;
+        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+        proxy_set_header X-Forwarded-Proto $scheme;
+        proxy_read_timeout 300;
+        proxy_send_timeout 300;
+    }
+}

astraea.service

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+[Unit]
+Description=Astraea — Washington family-law specialist agents (Flask + RAG)
+After=network.target
+
+[Service]
+WorkingDirectory=/opt/astraea
+ExecStart=/opt/astraea/venv/bin/gunicorn --workers 2 --threads 4 --bind 0.0.0.0:5000 --timeout 240 app:app
+Restart=always
+RestartSec=3
+Environment=PYTHONUNBUFFERED=1
+
+[Install]
+WantedBy=multi-user.target

rag.py

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+# -*- coding: utf-8 -*-
+"""Semantic RAG engine for Astraea — chunk the law 'books', embed, and retrieve.
+
+stdlib-only (urllib + json + math), no numpy needed. Embeddings and generation
+run on the Ollama host (nightmare). The vector index is cached to disk and rebuilt
+incrementally only when a book changes.
+"""
+import json
+import math
+import os
+import re
+import threading
+import urllib.request
+
+from agents import OLLAMA_URL, EMBED_MODEL, BOOKS_DIR, AGENTS
+
+INDEX_PATH = "/opt/astraea/index.json"
+
+
+def _post(url, payload, timeout=120):
+    """POST JSON to Ollama with a no-proxy opener (safe on LAN)."""
+    req = urllib.request.Request(
+        url, data=json.dumps(payload).encode("utf-8"),
+        headers={"Content-Type": "application/json"},
+    )
+    opener = urllib.request.build_opener(urllib.request.ProxyHandler({}))
+    with opener.open(req, timeout=timeout) as r:
+        return json.loads(r.read().decode("utf-8"))
+
+
+def embed(text):
+    """Return a float vector for `text` via the Ollama embeddings endpoint."""
+    d = _post(f"{OLLAMA_URL}/api/embeddings", {"model": EMBED_MODEL, "prompt": text})
+    v = d.get("embedding") or d.get("embeddings")
+    if isinstance(v, list) and v and isinstance(v[0], list):
+        v = v[0]
+    if not v:
+        raise RuntimeError("empty embedding returned")
+    return v
+
+
+def _cosine(a, b):
+    dot = sum(x * y for x, y in zip(a, b))
+    na = math.sqrt(sum(x * x for x in a))
+    nb = math.sqrt(sum(y * y for y in b))
+    return dot / (na * nb) if na and nb else 0.0
+
+
+MAX_CHUNK = 1100  # chars — stay safely under the embedding model's context budget
+
+
+def _split_long(text, limit):
+    """Split text into pieces <= limit chars, preferring sentence boundaries."""
+    if len(text) <= limit:
+        return [text] if text.strip() else []
+    parts = re.split(r"(?<=[.!?])\s+", text)
+    out = []
+    cur = ""
+    for p in parts:
+        if cur and len(cur) + len(p) + 1 > limit:
+            out.append(cur)
+            cur = p
+        else:
+            cur = (cur + " " + p).strip() if cur else p
+        while len(cur) > limit:
+            out.append(cur[:limit])
+            cur = cur[limit:]
+    if cur.strip():
+        out.append(cur)
+    return out
+
+
+def _chunk_markdown(text):
+    """Split markdown into self-contained (title, body) chunks, each <= MAX_CHUNK chars."""
+    lines = text.splitlines()
+    chunks = []
+    cur_title = None
+    cur_buf = []
+
+    def flush():
+        nonlocal cur_title, cur_buf
+        if not cur_buf:
+            return
+        body = "\n".join(cur_buf).strip()
+        cur_buf = []
+        if not body:
+            return
+        for piece in _split_long(body, MAX_CHUNK):
+            chunks.append((cur_title or "Section", piece))
+
+    for line in lines:
+        if re.match(r"^#{1,4}\s+", line):
+            flush()
+            cur_title = re.sub(r"^#{1,4}\s+", "", line).strip()
+        else:
+            cur_buf.append(line)
+    flush()
+    return chunks
+
+
+def build_index():
+    """Build (or load from cache) the vector index. Returns list of chunk dicts."""
+    index = []
+    book_files = []
+    for a in AGENTS:
+        for b in a["books"]:
+            path = os.path.join(BOOKS_DIR, b)
+            if os.path.exists(path):
+                book_files.append((path, a["id"]))
+
+    # Decide whether to reuse cache: index.json exists, embed model matches, and no book changed.
+    if os.path.exists(INDEX_PATH):
+        try:
+            with open(INDEX_PATH) as f:
+                cached = json.load(f)
+            if cached.get("embed_model") == EMBED_MODEL:
+                newest_book = max(os.path.getmtime(p) for p, _ in book_files) if book_files else 0
+                if os.path.getmtime(INDEX_PATH) >= newest_book:
+                    return cached["chunks"]
+        except Exception:
+            pass
+
+    for path, agent_id in book_files:
+        try:
+            with open(path, encoding="utf-8") as f:
+                text = f.read()
+        except Exception:
+            continue
+        base = os.path.basename(path)
+        for title, body in _chunk_markdown(text):
+            # Embed the title + body together for best semantic match.
+            try:
+                vec = embed(f"{title}\n{body}")
+            except Exception:
+                continue  # skip any chunk that fails to embed
+            index.append({
+                "agent": agent_id,
+                "source": base,
+                "title": title,
+                "text": body,
+                "vector": vec,
+            })
+
+    if index:
+        try:
+            with open(INDEX_PATH, "w") as f:
+                json.dump({"embed_model": EMBED_MODEL, "chunks": index}, f)
+        except Exception:
+            pass
+    return index
+
+
+def retrieve(query, agent_id, top_k=5):
+    """Return top-k relevant chunks for `agent_id` via cosine similarity."""
+    qvec = embed(query)
+    scored = []
+    for c in _INDEX:
+        if c["agent"] != agent_id:
+            continue
+        scored.append((_cosine(qvec, c["vector"]), c))
+    scored.sort(key=lambda x: x[0], reverse=True)
+    return [(s, c) for s, c in scored[:top_k]]
+
+
+# Global index, built lazily once in a background thread.
+_INDEX = []
+_index_lock = threading.Lock()
+_index_ready = False
+
+
+def start_background_index():
+    def _run():
+        global _index_ready
+        try:
+            idx = build_index()
+            with _index_lock:
+                _INDEX.clear()
+                _INDEX.extend(idx)
+        finally:
+            _index_ready = True
+    threading.Thread(target=_run, daemon=True).start()
+
+
+def index_status():
+    return {"ready": _index_ready, "chunks": len(_INDEX)}

requirements.txt

@@ -0,0 +1,2 @@
+flask>=3.0
+gunicorn>=21.2

templates/index.html

@@ -0,0 +1,408 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>Astraea — Washington Family Law, Decoded</title>
+<meta name="description" content="A constellation of Washington State family-law specialist agents. Ask about divorce, custody, child support, property, and protection orders.">
+<style>
+  :root {
+    --bg: #070b1a;
+    --bg2: #0b1228;
+    --panel: #101832;
+    --panel2: #141d3d;
+    --line: #233055;
+    --text: #e8edfb;
+    --muted: #8b98c4;
+    --accent: #7dd3fc;
+    --gold: #f5d06f;
+  }
+  * { box-sizing: border-box; margin: 0; padding: 0; }
+  html, body { height: 100%; }
+  body {
+    font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
+    background: radial-gradient(1200px 700px at 50% -10%, #18254f 0%, var(--bg2) 45%, var(--bg) 100%);
+    color: var(--text);
+    overflow-x: hidden;
+    -webkit-font-smoothing: antialiased;
+  }
+  #stars { position: fixed; inset: 0; z-index: 0; pointer-events: none; }
+
+  .wrap { position: relative; z-index: 1; max-width: 1120px; margin: 0 auto; padding: 0 22px 80px; }
+
+  header {
+    padding: 46px 0 8px;
+    display: flex; align-items: center; justify-content: space-between;
+  }
+  .brand { display: flex; align-items: center; gap: 14px; }
+  .logo {
+    width: 46px; height: 46px; border-radius: 13px;
+    background: linear-gradient(135deg, #6ea8ff, #a78bfa);
+    display: grid; place-items: center; font-size: 26px;
+    box-shadow: 0 0 26px rgba(124, 155, 255, .55);
+  }
+  .brand h1 { font-size: 26px; font-weight: 700; letter-spacing: .4px; }
+  .brand h1 span { color: var(--gold); }
+  .brand .sub { color: var(--muted); font-size: 13px; margin-top: 2px; letter-spacing: .3px; }
+  .pill {
+    font-size: 12px; color: var(--muted); border: 1px solid var(--line);
+    padding: 6px 12px; border-radius: 999px; display: inline-flex; align-items: center; gap: 7px;
+  }
+  .dot { width: 8px; height: 8px; border-radius: 50%; background: #4ade80; box-shadow: 0 0 10px #4ade80; }
+
+  .hero { padding: 26px 0 34px; max-width: 720px; }
+  .hero h2 { font-size: clamp(28px, 5vw, 46px); line-height: 1.12; font-weight: 800; letter-spacing: -.5px; }
+  .hero h2 .grad {
+    background: linear-gradient(90deg, #7dd3fc, #a78bfa, #f0abfc);
+    -webkit-background-clip: text; background-clip: text; color: transparent;
+  }
+  .hero p { color: var(--muted); font-size: 16.5px; line-height: 1.6; margin-top: 14px; max-width: 640px; }
+
+  .section-label { font-size: 12px; text-transform: uppercase; letter-spacing: 2px; color: var(--muted); margin: 10px 0 16px; }
+
+  .grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(240px, 1fr)); gap: 14px; }
+  .card {
+    background: linear-gradient(180deg, var(--panel2), var(--panel));
+    border: 1px solid var(--line); border-radius: 16px; padding: 18px 18px 16px;
+    cursor: pointer; transition: transform .18s ease, border-color .18s ease, box-shadow .18s ease;
+    position: relative; overflow: hidden;
+  }
+  .card::before {
+    content: ""; position: absolute; inset: 0 0 auto 0; height: 3px;
+    background: var(--c, var(--accent)); opacity: .85;
+  }
+  .card:hover { transform: translateY(-3px); border-color: var(--c, var(--accent)); box-shadow: 0 14px 34px rgba(0,0,0,.4); }
+  .card.active { border-color: var(--c, var(--accent)); box-shadow: 0 0 0 1px var(--c, var(--accent)), 0 16px 40px rgba(0,0,0,.5); }
+  .card .emoji { font-size: 30px; line-height: 1; }
+  .card h3 { font-size: 16.5px; font-weight: 700; margin: 12px 0 3px; }
+  .card .tag { font-size: 12px; color: var(--c, var(--accent)); font-weight: 600; margin-bottom: 8px; }
+  .card p { font-size: 13px; color: var(--muted); line-height: 1.5; }
+
+  .chat-panel {
+    margin-top: 38px;
+    background: linear-gradient(180deg, var(--panel2), var(--panel));
+    border: 1px solid var(--line); border-radius: 20px;
+    display: flex; flex-direction: column; overflow: hidden;
+    box-shadow: 0 30px 70px rgba(0,0,0,.45);
+  }
+  .chat-head {
+    padding: 16px 20px; border-bottom: 1px solid var(--line);
+    display: flex; align-items: center; gap: 13px;
+  }
+  .chat-head .emoji { font-size: 26px; }
+  .chat-head .who { font-weight: 700; font-size: 15.5px; }
+  .chat-head .who .scope { color: var(--muted); font-weight: 500; font-size: 12.5px; margin-top: 1px; }
+  .chips { margin-left: auto; display: flex; gap: 7px; flex-wrap: wrap; justify-content: flex-end; }
+  .chip {
+    font-size: 12px; padding: 6px 11px; border-radius: 999px; cursor: pointer;
+    border: 1px solid var(--line); color: var(--muted); background: transparent;
+    transition: all .15s ease; white-space: nowrap;
+  }
+  .chip:hover { color: var(--text); border-color: var(--muted); }
+  .chip.on { color: #06121f; background: var(--c, var(--accent)); border-color: var(--c, var(--accent)); font-weight: 700; }
+
+  .messages { padding: 22px; min-height: 240px; max-height: 520px; overflow-y: auto; display: flex; flex-direction: column; gap: 16px; }
+  .msg { max-width: 78%; display: flex; flex-direction: column; }
+  .msg.user { align-self: flex-end; align-items: flex-end; }
+  .msg.agent { align-self: flex-start; align-items: flex-start; }
+  .bubble {
+    padding: 13px 16px; border-radius: 16px; font-size: 15px; line-height: 1.6; white-space: pre-wrap; word-break: break-word;
+  }
+  .msg.user .bubble { background: linear-gradient(135deg, #3b82f6, #6366f1); color: #fff; border-bottom-right-radius: 4px; }
+  .msg.agent .bubble { background: var(--panel2); border: 1px solid var(--line); border-bottom-left-radius: 4px; }
+  .msg .who-label { font-size: 11.5px; color: var(--muted); margin: 0 4px 5px; }
+
+  .citations { margin-top: 10px; width: 100%; }
+  .cite-toggle {
+    font-size: 12px; color: var(--gold); cursor: pointer; border: none; background: none;
+    display: inline-flex; align-items: center; gap: 5px; padding: 4px 2px;
+  }
+  .cite-list { margin-top: 8px; display: none; flex-direction: column; gap: 8px; }
+  .cite-list.open { display: flex; }
+  .cite {
+    background: #0c142e; border: 1px solid var(--line); border-radius: 10px; padding: 10px 12px;
+    font-size: 12.5px; color: var(--muted);
+  }
+  .cite b { color: var(--text); display: block; margin-bottom: 3px; font-size: 13px; }
+  .cite .src { color: var(--gold); font-size: 11px; }
+
+  .typing { display: inline-flex; gap: 5px; align-items: center; padding: 6px 2px; }
+  .typing i { width: 7px; height: 7px; border-radius: 50%; background: var(--muted); animation: blink 1.2s infinite; }
+  .typing i:nth-child(2) { animation-delay: .2s; }
+  .typing i:nth-child(3) { animation-delay: .4s; }
+  @keyframes blink { 0%,100% { opacity: .25; } 50% { opacity: 1; } }
+
+  .composer { border-top: 1px solid var(--line); padding: 14px 16px; display: flex; gap: 10px; align-items: flex-end; }
+  .composer textarea {
+    flex: 1; resize: none; background: #0c142e; border: 1px solid var(--line); color: var(--text);
+    border-radius: 12px; padding: 12px 14px; font-size: 15px; font-family: inherit; line-height: 1.5;
+    max-height: 140px; outline: none; transition: border-color .15s ease;
+  }
+  .composer textarea:focus { border-color: var(--c, var(--accent)); }
+  .send {
+    border: none; border-radius: 12px; padding: 13px 20px; font-size: 15px; font-weight: 700;
+    color: #06121f; background: var(--c, var(--accent)); cursor: pointer; transition: transform .1s ease, opacity .2s;
+  }
+  .send:active { transform: scale(.96); }
+  .send:disabled { opacity: .45; cursor: default; }
+  .hint { font-size: 11.5px; color: var(--muted); text-align: center; padding: 0 22px 14px; }
+
+  .disclaimer {
+    margin-top: 26px; font-size: 12.5px; color: var(--muted); text-align: center; line-height: 1.6;
+    border-top: 1px solid var(--line); padding-top: 20px;
+  }
+  footer { margin-top: 20px; text-align: center; }
+  .bmac {
+    display: inline-flex; align-items: center; gap: 9px; color: var(--text); text-decoration: none;
+    background: var(--panel2); border: 1px solid var(--line); padding: 10px 18px; border-radius: 999px;
+    font-size: 13.5px; font-weight: 600; transition: all .15s ease;
+  }
+  .bmac:hover { border-color: var(--gold); box-shadow: 0 0 18px rgba(245,208,111,.25); }
+  .bmac .cup { font-size: 17px; }
+
+  #mascot {
+    position: fixed; z-index: 2; pointer-events: none; will-change: transform;
+    font-size: 24px; filter: drop-shadow(0 0 8px rgba(255,220,150,.8)); opacity: .9;
+  }
+  @media (max-width: 640px) {
+    .chips { margin-left: 0; width: 100%; justify-content: flex-start; }
+    .chat-head { flex-wrap: wrap; }
+    .msg { max-width: 92%; }
+  }
+</style>
+</head>
+<body>
+<canvas id="stars"></canvas>
+<div id="mascot">✦</div>
+
+<div class="wrap">
+  <header>
+    <div class="brand">
+      <div class="logo">⚖️</div>
+      <div>
+        <h1>ASTRA<span>EA</span></h1>
+        <div class="sub">Washington Family Law, decoded by specialist agents</div>
+      </div>
+    </div>
+    <div class="pill"><span class="dot"></span> <span id="statusText">Engines online</span></div>
+  </header>
+
+  <section class="hero">
+    <h2>Eight specialists.<br>One <span class="grad">constellation</span> of Washington family law.</h2>
+    <p>Ask a divorce, custody, child-support, property, or protection-order question. Each specialist answers from the actual Revised Code of Washington — with citations — not from thin air.</p>
+  </section>
+
+  <div class="section-label">Choose your specialist</div>
+  <div class="grid" id="grid"></div>
+
+  <section class="chat-panel" id="chatPanel">
+    <div class="chat-head">
+      <div class="emoji" id="headEmoji">🧭</div>
+      <div>
+        <div class="who" id="headName">Navigator</div>
+        <div class="who"><div class="scope" id="headScope">Where to start</div></div>
+      </div>
+      <div class="chips" id="chips"></div>
+    </div>
+    <div class="messages" id="messages"></div>
+    <div class="composer">
+      <textarea id="input" rows="1" placeholder="Ask a Washington family-law question…"></textarea>
+      <button class="send" id="sendBtn">Ask</button>
+    </div>
+    <div class="hint">Answers cite the Revised Code of Washington. This is legal information, not advice.</div>
+  </section>
+
+  <div class="disclaimer">{{ disclaimer }}</div>
+  <footer>
+    <a class="bmac" href="https://buymeacoffee.com/r26xrthzttg" target="_blank" rel="noopener">
+      <span class="cup">☕</span> Support Astraea
+    </a>
+  </footer>
+</div>
+
+<script>
+  const AGENTS = {{ agents | tojson }};
+  const DISCLAIMER = {{ disclaimer | tojson }};
+
+  // ---- Starfield + cursor mascot ----
+  const cvs = document.getElementById('stars');
+  const ctx = cvs.getContext('2d');
+  let stars = [];
+  function sizeCanvas() {
+    cvs.width = window.innerWidth; cvs.height = window.innerHeight;
+    stars = Array.from({length: 130}, () => ({
+      x: Math.random() * cvs.width, y: Math.random() * cvs.height,
+      r: Math.random() * 1.4 + .3, tw: Math.random() * Math.PI * 2,
+      sp: Math.random() * .02 + .005
+    }));
+  }
+  sizeCanvas();
+  window.addEventListener('resize', sizeCanvas);
+  function drawStars() {
+    ctx.clearRect(0, 0, cvs.width, cvs.height);
+    for (const s of stars) {
+      s.tw += s.sp;
+      const a = .35 + Math.abs(Math.sin(s.tw)) * .65;
+      ctx.beginPath(); ctx.arc(s.x, s.y, s.r, 0, Math.PI * 2);
+      ctx.fillStyle = `rgba(190,210,255,${a})`; ctx.fill();
+    }
+    requestAnimationFrame(drawStars);
+  }
+  drawStars();
+
+  const mascot = document.getElementById('mascot');
+  let mx = innerWidth/2, my = innerHeight/3, cx = mx, cy = my;
+  addEventListener('mousemove', e => { mx = e.clientX; my = e.clientY; });
+  (function follow() {
+    cx += (mx - cx) * .08; cy += (my - cy) * .08;
+    mascot.style.transform = `translate(${cx - 8}px, ${cy - 30}px) rotate(${Math.sin(Date.now()/700)*20}deg)`;
+    requestAnimationFrame(follow);
+  })();
+
+  // ---- App state ----
+  const grid = document.getElementById('grid');
+  const chips = document.getElementById('chips');
+  const messages = document.getElementById('messages');
+  const input = document.getElementById('input');
+  const sendBtn = document.getElementById('sendBtn');
+  const statusText = document.getElementById('statusText');
+  let active = AGENTS[0].id;
+  const history = {};       // per-agent turn history
+  AGENTS.forEach(a => history[a.id] = []);
+
+  function accent(id) { const a = AGENTS.find(x => x.id === id); return a ? a.accent : '#7dd3fc'; }
+
+  function renderGrid() {
+    grid.innerHTML = '';
+    AGENTS.forEach(a => {
+      const c = document.createElement('div');
+      c.className = 'card' + (a.id === active ? ' active' : '');
+      c.style.setProperty('--c', a.accent);
+      c.innerHTML = `<div class="emoji">${a.emoji}</div><h3>${a.name}</h3>
+        <div class="tag">${a.tagline}</div><p>${a.description}</p>`;
+      c.onclick = () => selectAgent(a.id, true);
+      grid.appendChild(c);
+    });
+  }
+
+  function renderChips() {
+    chips.innerHTML = '';
+    AGENTS.forEach(a => {
+      const b = document.createElement('button');
+      b.className = 'chip' + (a.id === active ? ' on' : '');
+      b.style.setProperty('--c', a.accent);
+      b.textContent = a.emoji + ' ' + a.name.split(' & ')[0].split(' ')[0];
+      b.onclick = () => selectAgent(a.id, false);
+      chips.appendChild(b);
+    });
+  }
+
+  function selectAgent(id, scroll) {
+    active = id;
+    const a = AGENTS.find(x => x.id === id);
+    document.getElementById('headEmoji').textContent = a.emoji;
+    document.getElementById('headName').textContent = a.name;
+    document.getElementById('headScope').textContent = a.tagline;
+    document.getElementById('chatPanel').style.setProperty('--c', a.accent);
+    document.getElementById('chatPanel').style.borderColor = a.accent + '55';
+    renderGrid(); renderChips();
+    messages.innerHTML = '';
+    renderHistory();
+    if (scroll) document.getElementById('chatPanel').scrollIntoView({behavior: 'smooth', block: 'start'});
+    input.focus();
+  }
+
+  function renderHistory() {
+    const h = history[active] || [];
+    h.forEach(t => addBubble(t.role, t.content, t.citations));
+  }
+
+  function addBubble(role, text, citations) {
+    const m = document.createElement('div');
+    m.className = 'msg ' + role;
+    const label = document.createElement('div');
+    label.className = 'who-label';
+    label.textContent = role === 'user' ? 'You' : (AGENTS.find(x => x.id === active)?.name || 'Agent');
+    const b = document.createElement('div');
+    b.className = 'bubble';
+    b.textContent = text;
+    m.appendChild(label); m.appendChild(b);
+    if (role === 'assistant' && citations && citations.length) {
+      const cw = document.createElement('div'); cw.className = 'citations';
+      const t = document.createElement('button'); t.className = 'cite-toggle';
+      t.innerHTML = '🔗 ' + citations.length + ' source' + (citations.length > 1 ? 's' : '');
+      const list = document.createElement('div'); list.className = 'cite-list';
+      citations.forEach(c => {
+        const item = document.createElement('div'); item.className = 'cite';
+        item.innerHTML = `<b>${c.title}</b><div>${c.snippet}</div><div class="src">${c.source}</div>`;
+        list.appendChild(item);
+      });
+      t.onclick = () => list.classList.toggle('open');
+      cw.appendChild(t); cw.appendChild(list);
+      m.appendChild(cw);
+    }
+    messages.appendChild(m);
+    messages.scrollTop = messages.scrollHeight;
+  }
+
+  function typingIndicator(on) {
+    document.querySelectorAll('.typing').forEach(e => e.remove());
+    if (!on) return;
+    const m = document.createElement('div'); m.className = 'msg agent';
+    const t = document.createElement('div'); t.className = 'typing';
+    t.innerHTML = '<i></i><i></i><i></i>';
+    m.appendChild(t); messages.appendChild(m);
+    messages.scrollTop = messages.scrollHeight;
+  }
+
+  async function send() {
+    const text = input.value.trim();
+    if (!text) return;
+    input.value = ''; input.style.height = 'auto';
+    addBubble('user', text);
+    history[active].push({role: 'user', content: text});
+    typingIndicator(true); sendBtn.disabled = true;
+    try {
+      const r = await fetch('/api/chat', {
+        method: 'POST', headers: {'Content-Type': 'application/json'},
+        body: JSON.stringify({agent_id: active, message: text, history: history[active].slice(0, -1)})
+      });
+      const d = await r.json();
+      typingIndicator(false);
+      if (d.answer) {
+        addBubble('assistant', d.answer, d.citations);
+        history[active].push({role: 'assistant', content: d.answer, citations: d.citations});
+      } else {
+        addBubble('assistant', d.error || 'Something went wrong. Please try again.', null);
+      }
+    } catch (e) {
+      typingIndicator(false);
+      addBubble('assistant', 'Could not reach the legal engine. Please try again.', null);
+    } finally {
+      sendBtn.disabled = false; input.focus();
+    }
+  }
+
+  sendBtn.onclick = send;
+  input.addEventListener('keydown', e => {
+    if (e.key === 'Enter' && !e.shiftKey) { e.preventDefault(); send(); }
+  });
+  input.addEventListener('input', () => {
+    input.style.height = 'auto'; input.style.height = Math.min(input.scrollHeight, 140) + 'px';
+  });
+
+  // ---- Boot ----
+  renderGrid(); renderChips(); selectAgent(active, false);
+  fetch('/api/health').then(r => r.json()).then(d => {
+    if (d.ok) {
+      statusText.textContent = d.index.ready
+        ? `${d.agent_count} agents · ${d.index.chunks} law passages indexed`
+        : 'Indexing law library…';
+    }
+  }).catch(() => { statusText.textContent = 'Engine warming up'; });
+</script>
+
+<!-- Umami analytics beacon -->
+<script async src="https://analytics.thetempleofdoom.com/script.js" data-website-id="c8c2f69c-4448-40ab-9848-02179f10c001"></script>
+</body>
+</html>