Tasks 12 + 13: worker node agent + Phi-4-mini query triage

Task 12 — node_agent/agent.py: standalone AMQP worker agent
  config reader, model discovery, registration publisher,
  ping/pong handler, model swap with systemctl + health poll
  (14 tests)

Task 13 — triage.py: query classification + cluster node selection
  classify_query() routes to Phi-4-mini at :8083
  select_node() picks best worker by model affinity
  get_inference_url() replaces hardcoded LLAMA_SERVER_BASE
  cluster.py stores node ip for URL construction
  (6 tests + 5 existing chat tests mocked for triage)

168 tests passing (+20 new)

triage.py

@@ -0,0 +1,79 @@
+"""cAIc — Query triage and cluster node selection."""
+import logging
+
+import httpx
+
+from config import TRIAGE_BASE, TRIAGE_TIMEOUT, LLAMA_SERVER_BASE
+
+log = logging.getLogger("caic")
+
+_CLASSIFICATION_PROMPT = """Classify the following user query into exactly one category. Respond with only the category name.
+
+Categories:
+- general: everyday questions, chitchat, creative writing, advice, explanations
+- code: programming, debugging, code generation, technical questions about software
+- search: questions about current events, real-time information, weather, news, specific things that may have changed since training
+- rag: questions about specific documents, personal data, notes, memory, uploaded content
+
+Query: {query}
+Category:"""
+
+
+async def classify_query(query: str) -> str:
+    try:
+        async with httpx.AsyncClient() as client:
+            resp = await client.post(
+                f"{TRIAGE_BASE}/chat/completions",
+                json={
+                    "model": "phi-4-mini",
+                    "messages": [
+                        {"role": "system", "content": "You are a query classifier. Respond with exactly one word."},
+                        {"role": "user", "content": _CLASSIFICATION_PROMPT.format(query=query)},
+                    ],
+                    "temperature": 0.0,
+                    "max_tokens": 10,
+                },
+                timeout=TRIAGE_TIMEOUT,
+            )
+            text = resp.json()["choices"][0]["message"]["content"].strip().lower()
+            valid = {"general", "code", "search", "rag"}
+            for v in valid:
+                if v in text:
+                    return v
+    except Exception:
+        log.warning("triage classify_query failed, falling back to general", exc_info=True)
+    return "general"
+
+
+def select_node(classification: str) -> dict | None:
+    from cluster import CLUSTER_NODES
+
+    for node in CLUSTER_NODES.values():
+        if node.get("status") != "active":
+            continue
+        am = node.get("active_model") or {}
+        name = (am.get("name") or "").lower()
+        if classification == "code":
+            if "coder" in name or "qwen" in name:
+                return node
+        elif classification == "general":
+            if "mistral" in name or "llama" in name:
+                return node
+        else:
+            return None
+    return None
+
+
+async def get_inference_url(query: str) -> str:
+    if not query:
+        return LLAMA_SERVER_BASE
+    classification = await classify_query(query)
+    if classification in ("search", "rag"):
+        return LLAMA_SERVER_BASE
+    node = select_node(classification)
+    if node:
+        am = node.get("active_model") or {}
+        port = am.get("port", 8081)
+        ip = node.get("ip") or "127.0.0.1"
+        return f"http://{ip}:{port}/v1"
+    return LLAMA_SERVER_BASE