feat: add auto-start server fixture (#118)

- turboquant_server_url fixture: auto-starts llama-server if no URL provided
- Finds binary in standard locations or PATH
- Finds GGUF model in standard locations
- Configurable via env vars (port, kv_type, ctx_size, timeout)
- Skips gracefully if binary or model not found
- turboquant_model_name fixture for model discovery

tests/conftest.py

@@ -1,3 +1,85 @@
 """Pytest configuration for turboquant."""
-import sys, os
+import os
+import sys
+import pytest
+from pathlib import Path
+
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
+
+
+@pytest.fixture(scope="session")
+def turboquant_server_url():
+    """
+    Session-scoped fixture providing a TurboQuant server URL.
+    
+    If TURBOQUANT_SERVER_URL is set, uses that directly.
+    Otherwise, auto-starts a llama-server with TurboQuant flags.
+    
+    Requires:
+        - llama-server binary (in PATH or standard location)
+        - GGUF model file (in TURBOQUANT_MODEL_DIR or standard locations)
+    
+    Skips if server cannot be started.
+    """
+    # If URL already provided, use it
+    if os.environ.get("TURBOQUANT_SERVER_URL"):
+        yield os.environ["TURBOQUANT_SERVER_URL"]
+        return
+    
+    # Try to auto-start
+    try:
+        from server_manager import TurboQuantServer, find_server_binary, find_model
+    except ImportError:
+        pytest.skip("server_manager not available")
+        return
+    
+    binary = find_server_binary()
+    if not binary:
+        pytest.skip("llama-server binary not found — install llama-cpp-turboquant")
+        return
+    
+    model = find_model()
+    if not model:
+        pytest.skip("No GGUF model found — set TURBOQUANT_MODEL_DIR or place model in ~/models")
+        return
+    
+    port = int(os.environ.get("TURBOQUANT_TEST_PORT", "18081"))
+    kv_type = os.environ.get("TURBOQUANT_KV_TYPE", "turbo4")
+    ctx_size = int(os.environ.get("TURBOQUANT_CTX_SIZE", "8192"))
+    timeout = float(os.environ.get("TURBOQUANT_STARTUP_TIMEOUT", "60"))
+    
+    server = TurboQuantServer(
+        model_path=model,
+        port=port,
+        kv_type=kv_type,
+        context_size=ctx_size,
+        server_binary=binary,
+        timeout=timeout,
+    )
+    
+    try:
+        url = server.start()
+        yield url
+    except Exception as e:
+        pytest.skip(f"Could not start TurboQuant server: {e}")
+    finally:
+        server.stop()
+
+
+@pytest.fixture(scope="session")
+def turboquant_model_name(turboquant_server_url):
+    """Get the model name from the running server."""
+    import json
+    import urllib.request
+    
+    try:
+        req = urllib.request.Request(f"{turboquant_server_url}/v1/models")
+        resp = urllib.request.urlopen(req, timeout=10)
+        data = json.loads(resp.read())
+        models = data.get("data", [])
+        if models:
+            return models[0].get("id", "unknown")
+    except Exception:
+        pass
+    return "gemma-4"

tests/server_manager.py

@@ -0,0 +1,197 @@
+#!/usr/bin/env python3
+"""
+TurboQuant Server Manager
+
+Manages llama-server lifecycle for integration tests:
+- Start server with TurboQuant flags
+- Wait for health check
+- Stop server on teardown
+
+Usage:
+    from tests.server_manager import TurboQuantServer
+    
+    with TurboQuantServer(model_path="/path/to/model.gguf") as server:
+        url = server.url  # e.g. http://localhost:8081
+        # Run tests against server
+"""
+
+import json
+import os
+import signal
+import subprocess
+import sys
+import time
+import urllib.request
+import urllib.error
+from pathlib import Path
+from typing import Optional
+
+
+class TurboQuantServer:
+    """Context manager for llama-server with TurboQuant."""
+    
+    def __init__(
+        self,
+        model_path: str,
+        port: int = 8081,
+        kv_type: str = "turbo4",
+        context_size: int = 32768,
+        server_binary: Optional[str] = None,
+        timeout: float = 60.0,
+        host: str = "127.0.0.1",
+    ):
+        self.model_path = model_path
+        self.port = port
+        self.kv_type = kv_type
+        self.context_size = context_size
+        self.timeout = timeout
+        self.host = host
+        
+        # Find server binary
+        if server_binary:
+            self.server_binary = server_binary
+        else:
+            # Try common locations
+            candidates = [
+                Path.home() / "llama-cpp-turboquant" / "build" / "bin" / "llama-server",
+                Path("/opt/llama-cpp-turboquant/build/bin/llama-server"),
+                Path("llama-server"),  # PATH
+            ]
+            self.server_binary = None
+            for c in candidates:
+                if c.exists() or c.name == "llama-server":
+                    try:
+                        subprocess.run([str(c), "--help"], capture_output=True, timeout=5)
+                        self.server_binary = str(c)
+                        break
+                    except (FileNotFoundError, subprocess.TimeoutExpired):
+                        continue
+        
+        self.process: Optional[subprocess.Popen] = None
+    
+    @property
+    def url(self) -> str:
+        return f"http://{self.host}:{self.port}"
+    
+    def _build_command(self) -> list:
+        cmd = [
+            self.server_binary,
+            "-m", self.model_path,
+            "--port", str(self.port),
+            "--host", self.host,
+            "-ctk", self.kv_type,
+            "-ctv", self.kv_type,
+            "-c", str(self.context_size),
+        ]
+        return cmd
+    
+    def _check_health(self) -> bool:
+        try:
+            req = urllib.request.Request(f"{self.url}/v1/models")
+            resp = urllib.request.urlopen(req, timeout=5)
+            data = json.loads(resp.read())
+            return "data" in data and len(data.get("data", [])) > 0
+        except Exception:
+            return False
+    
+    def start(self) -> str:
+        """Start the server and wait for it to be healthy. Returns the server URL."""
+        if not self.server_binary:
+            raise RuntimeError(
+                "llama-server binary not found. Set server_binary or install to standard location."
+            )
+        
+        if not Path(self.model_path).exists():
+            raise FileNotFoundError(f"Model not found: {self.model_path}")
+        
+        cmd = self._build_command()
+        
+        # Set TurboQuant env
+        env = os.environ.copy()
+        env["TURBO_LAYER_ADAPTIVE"] = "7"
+        
+        self.process = subprocess.Popen(
+            cmd,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            env=env,
+        )
+        
+        # Wait for health
+        start = time.time()
+        while time.time() - start < self.timeout:
+            if self.process.poll() is not None:
+                stderr = self.process.stderr.read().decode() if self.process.stderr else ""
+                raise RuntimeError(f"Server exited early (code {self.process.returncode}): {stderr[:500]}")
+            
+            if self._check_health():
+                return self.url
+            
+            time.sleep(1.0)
+        
+        self.stop()
+        raise TimeoutError(f"Server did not become healthy within {self.timeout}s")
+    
+    def stop(self):
+        """Stop the server."""
+        if self.process:
+            try:
+                self.process.send_signal(signal.SIGTERM)
+                self.process.wait(timeout=10)
+            except subprocess.TimeoutExpired:
+                self.process.kill()
+                self.process.wait(timeout=5)
+            except Exception:
+                pass
+            self.process = None
+    
+    def __enter__(self) -> "TurboQuantServer":
+        self.start()
+        return self
+    
+    def __exit__(self, *args):
+        self.stop()
+
+
+def find_server_binary() -> Optional[str]:
+    """Find llama-server binary in common locations."""
+    candidates = [
+        Path.home() / "llama-cpp-turboquant" / "build" / "bin" / "llama-server",
+        Path("/opt/llama-cpp-turboquant/build/bin/llama-server"),
+    ]
+    for c in candidates:
+        if c.exists():
+            return str(c)
+    
+    # Try PATH
+    try:
+        result = subprocess.run(["which", "llama-server"], capture_output=True, text=True)
+        if result.returncode == 0:
+            return result.stdout.strip()
+    except Exception:
+        pass
+    
+    return None
+
+
+def find_model(model_dir: Optional[str] = None) -> Optional[str]:
+    """Find a GGUF model file."""
+    search_dirs = [
+        model_dir,
+        os.environ.get("TURBOQUANT_MODEL_DIR"),
+        str(Path.home() / "models"),
+        "/opt/models",
+        "/tmp/models",
+    ]
+    
+    for d in search_dirs:
+        if not d:
+            continue
+        p = Path(d)
+        if p.is_file() and p.suffix == ".gguf":
+            return str(p)
+        if p.is_dir():
+            for f in sorted(p.rglob("*.gguf")):
+                return str(f)
+    
+    return None