B5: default model auto-pull on first start (v0.19.1)

model_pull.py: ensure_model() checks llama-server availability at
startup, falls back to Ollama pull API if model not found.
Integrated into app.py lifespan after assess_hardware().
11 tests cover all paths: available/unreachable/pull success/fail.

model_pull.py

@@ -0,0 +1,80 @@
+"""
+cAIc — Model pull/download helper.
+
+Uses Ollama's pull API to download models that aren't available on the
+inference server. Runs synchronously during startup.
+"""
+import asyncio
+import json
+import logging
+
+import httpx
+
+from config import DEFAULT_MODEL, LLAMA_SERVER_BASE, OLLAMA_BASE
+
+log = logging.getLogger("caic")
+
+
+async def _model_available_on_llama(model: str) -> bool:
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            resp = await client.get(f"{LLAMA_SERVER_BASE}/v1/models")
+            if resp.status_code == 200:
+                models = resp.json().get("data", [])
+                return any(m.get("id") == model for m in models)
+    except Exception:
+        pass
+    return False
+
+
+async def _model_available_on_ollama(model: str) -> bool:
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            resp = await client.post(f"{OLLAMA_BASE}/api/show", json={"name": model})
+            return resp.status_code == 200
+    except Exception:
+        pass
+    return False
+
+
+async def _pull_via_ollama(model: str) -> bool:
+    try:
+        async with httpx.AsyncClient(timeout=300) as client:
+            async with client.stream("POST", f"{OLLAMA_BASE}/api/pull", json={"name": model}) as resp:
+                if resp.status_code != 200:
+                    log.warning("ollama pull returned %s for %s", resp.status_code, model)
+                    return False
+                async for line in resp.aiter_lines():
+                    if line.strip():
+                        try:
+                            data = json.loads(line)
+                            status = data.get("status", "")
+                            if status:
+                                log.info("ollama pull %s: %s", model, status)
+                        except json.JSONDecodeError:
+                            pass
+                return True
+    except httpx.ConnectError:
+        log.warning("ollama not reachable at %s — cannot pull %s", OLLAMA_BASE, model)
+    except Exception as e:
+        log.warning("ollama pull error for %s: %s", model, e)
+    return False
+
+
+async def ensure_model(model: str = "") -> bool:
+    """Ensure *model* is available for inference. Pull via Ollama if needed."""
+    model = model or DEFAULT_MODEL
+    if await _model_available_on_llama(model):
+        log.info("model %s already available on llama-server", model)
+        return True
+    log.info("model %s not found on llama-server, checking Ollama", model)
+    if await _model_available_on_ollama(model):
+        log.info("model %s found on Ollama (available for embeddings)", model)
+        return True
+    log.info("model %s not found on Ollama either — pulling", model)
+    ok = await _pull_via_ollama(model)
+    if ok:
+        log.info("model %s pulled successfully", model)
+    else:
+        log.warning("model %s could not be pulled", model)
+    return ok