feat(setup): dynamic model discovery for local providers in wizard

Replace the static model text prompt with live API queries:
- _fetch_local_models(): queries /v1/models (LM Studio, llama.cpp) or
  /api/tags (Ollama) and returns a questionary.select list
- _fetch_lmstudio_available_models(): queries LM Studio's beta
  /api/v0/models to list downloaded-but-not-loaded models
- _load_lmstudio_model(): tries /api/v0/models/load to load a model
  in-place; falls back to telling the user to load manually
- Cloud providers keep the existing text-input behaviour

Also replace hardcoded LMSTUDIO_MODEL in integration tests with a
lmstudio_model fixture that queries the API at runtime and uses
whichever model is currently loaded (skips if none).

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

src/pyra/setup/wizard.py

@@ -153,11 +153,95 @@ def _check_local_server(provider: Provider) -> None:
         )
 
 
+def _fetch_local_models(provider: Provider) -> list[str]:
+    """Return currently loaded/available models from a local provider's API."""
+    if not provider.base_url:
+        return []
+    try:
+        if provider.id == "ollama":
+            resp = httpx.get(f"{provider.base_url}/api/tags", timeout=3.0)
+            resp.raise_for_status()
+            return [m["name"] for m in resp.json().get("models", [])]
+        else:
+            resp = httpx.get(f"{provider.base_url}/models", timeout=3.0)
+            resp.raise_for_status()
+            return [m["id"] for m in resp.json().get("data", [])]
+    except Exception:
+        return []
+
+
+def _fetch_lmstudio_available_models() -> list[str]:
+    """Return all downloaded (not necessarily loaded) models from LM Studio's beta API."""
+    try:
+        resp = httpx.get("http://localhost:1234/api/v0/models", timeout=3.0)
+        resp.raise_for_status()
+        return [m["id"] for m in resp.json().get("data", [])]
+    except Exception:
+        return []
+
+
+def _load_lmstudio_model(model_id: str) -> bool:
+    """Attempt to load a model via LM Studio's beta API. Returns True on success."""
+    try:
+        resp = httpx.post(
+            "http://localhost:1234/api/v0/models/load",
+            json={"identifier": model_id},
+            timeout=60.0,
+        )
+        return resp.is_success
+    except Exception:
+        return False
+
+
 def _choose_model(provider: Provider) -> str:
-    model = questionary.text(
-        "Model name:",
-        default=provider.default_model,
-    ).ask()
+    if provider.group != "Local":
+        model = questionary.text("Model name:", default=provider.default_model).ask()
+        if model is None:
+            raise SystemExit(0)
+        return model.strip()
+
+    _MANUAL = "__manual__"
+    loaded = _fetch_local_models(provider)
+
+    if loaded:
+        choices = loaded + [questionary.Choice("── Enter manually ──", value=_MANUAL)]
+        selected = questionary.select("Select model:", choices=choices).ask()
+        if selected is None:
+            raise SystemExit(0)
+        if selected != _MANUAL:
+            return selected
+
+    elif provider.id == "lmstudio":
+        console.print("  [yellow]No model currently loaded in LM Studio.[/yellow]")
+        available = _fetch_lmstudio_available_models()
+        if available:
+            choices = available + [questionary.Choice("── Enter manually ──", value=_MANUAL)]
+            selected = questionary.select(
+                "Select a downloaded model to load:", choices=choices
+            ).ask()
+            if selected is None:
+                raise SystemExit(0)
+            if selected != _MANUAL:
+                console.print(f"  Loading [bold]{selected}[/bold]...", end=" ")
+                if _load_lmstudio_model(selected):
+                    console.print("[green]✓ Loaded[/green]")
+                else:
+                    console.print(
+                        "[yellow]Could not load via API — "
+                        "please load the model manually in LM Studio.[/yellow]"
+                    )
+                return selected
+        else:
+            console.print(Panel(
+                "No models are loaded or downloaded in LM Studio.\n"
+                "Open LM Studio → Local Server tab → load a model, then re-run setup.",
+                border_style="yellow",
+            ))
+
+    else:
+        console.print(f"  [yellow]No models found at {provider.base_url}.[/yellow]")
+
+    model = questionary.text("Model name:", default=provider.default_model).ask()
     if model is None:
         raise SystemExit(0)
     return model.strip()