Add explicit warm-wait before generation starts

Instead of relying solely on retry-on-500, poll /api/ps before starting
any LLM stream so the main model has time to fully load into VRAM.

- llm.py: add wait_for_model_loaded(model, timeout=90s) — polls /api/ps
  every 2s, returns True when model appears in loaded list
- generation_task.py: launch model_load_task in parallel with build_context
  and classify_intent (both use fast/small-model ops that don't need the
  main model); after context is built, await the load task — shows
  "Loading model..." status only if the user actually has to wait;
  logs a warning and proceeds if 90s timeout elapses

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/fabledassistant/services/llm.py

@@ -2,6 +2,7 @@ import asyncio
 import json
 import logging
 import re
+import time
 from collections.abc import AsyncGenerator
 from dataclasses import dataclass, field
 from typing import Literal
@@ -75,6 +76,30 @@ async def ensure_model(model: str) -> None:
         logger.warning("Failed to pull model '%s' — chat may not work", model, exc_info=True)
 
 
+async def wait_for_model_loaded(model: str, timeout: float = 90.0) -> bool:
+    """Poll /api/ps every 2s until the model appears in Ollama's loaded-model list.
+
+    Returns True when the model is loaded, False if timeout elapses first.
+    Used before generation to avoid streaming 500s during cold model loads.
+    """
+    base = model.removesuffix(":latest")
+    deadline = time.monotonic() + timeout
+    while True:
+        try:
+            async with httpx.AsyncClient(timeout=5.0) as client:
+                resp = await client.get(f"{Config.OLLAMA_URL}/api/ps")
+                resp.raise_for_status()
+                loaded = {m["name"] for m in resp.json().get("models", [])}
+                if model in loaded or f"{base}:latest" in loaded or base in loaded:
+                    return True
+        except Exception:
+            pass  # Ollama may still be starting up
+        remaining = deadline - time.monotonic()
+        if remaining <= 0:
+            return False
+        await asyncio.sleep(min(2.0, remaining))
+
+
 async def stream_chat(
     messages: list[dict],
     model: str,