gpu-program-swapper/vram_arbitrator.py

"""VRAM Arbitrator and High-Speed Switch Manager for Ollama and ComfyUI."""
import time
import httpx
import psutil
import logging
from typing import Dict, List, Any, Optional
from collections import deque

import asyncio
import json
import websockets

import overclock_manager
import ram_optimizer
import telemetry_store

try:
    import pynvml
    pynvml.nvmlInit()
    NVML_AVAILABLE = True
except Exception as e:
    NVML_AVAILABLE = False

logger = logging.getLogger("vram_arbitrator")

OLLAMA_API_BASE = "http://localhost:11434"
COMFY_API_BASE = "http://127.0.0.1:8188"

# Circular buffer for transition events (the durable log lives in telemetry_store)
SWITCH_HISTORY = deque(maxlen=50)

# Bandwidth thresholds used to classify how a model actually got into VRAM.
# PCIe 4.0 x16 tops out near 31.5 GB/s; this NVMe sustains well under 2 GB/s.
RAM_HIT_GBPS = 5.0
PARTIAL_HIT_GBPS = 1.5

# How long Ollama's VRAM may take to actually drain before we stop waiting.
YIELD_CONFIRM_TIMEOUT_S = 3.0
YIELD_CONFIRM_POLL_S = 0.02
YIELD_RESIDUAL_BYTES = 256 * 1024 ** 2  # treat <256 MB as "released"

# Connection-pooled clients. Re-creating an AsyncClient per call meant a fresh TCP
# handshake on every one of the watchdog's polls.
_clients: Dict[str, httpx.AsyncClient] = {}


def _client(base_url: str, timeout: float) -> httpx.AsyncClient:
    key = f"{base_url}|{timeout}"
    c = _clients.get(key)
    if c is None or c.is_closed:
        c = httpx.AsyncClient(
            base_url=base_url,
            timeout=timeout,
            limits=httpx.Limits(max_keepalive_connections=4, max_connections=8),
        )
        _clients[key] = c
    return c


async def close_clients() -> None:
    for c in list(_clients.values()):
        try:
            await c.aclose()
        except Exception:
            pass
    _clients.clear()


# Bit flags from nvmlDeviceGetCurrentClocksThrottleReasons, decoded for the governor.
THROTTLE_REASONS = {
    0x0000000000000001: "gpu_idle",
    0x0000000000000002: "applications_clocks_setting",
    0x0000000000000004: "sw_power_cap",
    0x0000000000000008: "hw_slowdown",
    0x0000000000000010: "sync_boost",
    0x0000000000000020: "sw_thermal_slowdown",
    0x0000000000000040: "hw_thermal_slowdown",
    0x0000000000000080: "hw_power_brake_slowdown",
    0x0000000000000100: "display_clock_setting",
}


def decode_throttle_reasons(bits: int) -> List[str]:
    return [name for mask, name in THROTTLE_REASONS.items() if bits & mask]


def get_process_vram_bytes() -> Dict[str, int]:
    """Fast NVML-only VRAM attribution, used by the yield barrier's tight poll loop.

    Deliberately avoids psutil lookups: this runs every 20 ms while we wait for VRAM
    to actually drain.
    """
    out = {"ollama_bytes": 0, "comfyui_bytes": 0, "other_bytes": 0, "free_bytes": 0}
    if not NVML_AVAILABLE:
        return out
    try:
        handle = pynvml.nvmlDeviceGetHandleByIndex(0)
        out["free_bytes"] = pynvml.nvmlDeviceGetMemoryInfo(handle).free
        procs = list(pynvml.nvmlDeviceGetComputeRunningProcesses(handle))
        try:
            procs += list(pynvml.nvmlDeviceGetGraphicsRunningProcesses(handle))
        except Exception:
            pass
        merged: Dict[int, int] = {}
        for p in procs:
            merged[p.pid] = max(merged.get(p.pid, 0), p.usedGpuMemory or 0)
        for pid, used in merged.items():
            kind = _PID_KIND_CACHE.get(pid)
            if kind is None:
                kind = _classify_pid(pid)
                _PID_KIND_CACHE[pid] = kind
            if kind == "ollama":
                out["ollama_bytes"] += used
            elif kind == "comfy":
                out["comfyui_bytes"] += used
            else:
                out["other_bytes"] += used
    except Exception as e:
        logger.debug(f"get_process_vram_bytes failed: {e}")
    return out


_PID_KIND_CACHE: Dict[int, str] = {}


def _classify_pid(pid: int) -> str:
    try:
        proc = psutil.Process(pid)
        pname = proc.name().lower()
        cmdline = " ".join(proc.cmdline()).lower()
    except Exception:
        return "other"
    if "ollama" in pname or "llama-server" in cmdline:
        return "ollama"
    if "comfy" in cmdline or "main.py" in cmdline:
        return "comfy"
    return "other"


def get_gpu_hardware_stats() -> Dict[str, Any]:
    """Retrieve comprehensive GPU hardware and process metrics via NVML."""
    if not NVML_AVAILABLE:
        return {"available": False, "error": "NVML not initialized"}
    
    try:
        handle = pynvml.nvmlDeviceGetHandleByIndex(0)
        name = pynvml.nvmlDeviceGetName(handle)
        if isinstance(name, bytes):
            name = name.decode("utf-8")
        
        mem_info = pynvml.nvmlDeviceGetMemoryInfo(handle)
        util_rates = pynvml.nvmlDeviceGetUtilizationRates(handle)
        temp_c = pynvml.nvmlDeviceGetTemperature(handle, pynvml.NVML_TEMPERATURE_GPU)
        try:
            power_mw = pynvml.nvmlDeviceGetPowerUsage(handle)
            power_w = round(power_mw / 1000.0, 1)
        except Exception:
            power_w = 0.0
            
        fan_pct = 0
        fans = []
        try:
            num_fans = pynvml.nvmlDeviceGetNumFans(handle)
            for i in range(num_fans):
                try:
                    fans.append(pynvml.nvmlDeviceGetFanSpeed_v2(handle, i))
                except Exception:
                    pass
            if fans:
                fan_pct = max(fans)
            else:
                fan_pct = pynvml.nvmlDeviceGetFanSpeed(handle)
                fans = [fan_pct]
        except Exception:
            try:
                fan_pct = pynvml.nvmlDeviceGetFanSpeed(handle)
                fans = [fan_pct]
            except Exception:
                fan_pct = 0
                fans = []
            
        try:
            clock_graphics = pynvml.nvmlDeviceGetClockInfo(handle, pynvml.NVML_CLOCK_GRAPHICS)
            clock_mem = pynvml.nvmlDeviceGetClockInfo(handle, pynvml.NVML_CLOCK_MEM)
        except Exception:
            clock_graphics = 0
            clock_mem = 0

        # PCIe throughput (KB/s) — TX + RX. Key metric for the RAM-cache
        # PCIe-speed swap thesis (assimilated from pmady/gpu-mcp-server).
        pcie_tx_kbps = 0
        pcie_rx_kbps = 0
        try:
            pcie_tx_kbps = pynvml.nvmlDeviceGetPcieThroughput(handle, pynvml.NVML_PCIE_UTIL_TX_BYTES)
        except Exception:
            pass
        try:
            pcie_rx_kbps = pynvml.nvmlDeviceGetPcieThroughput(handle, pynvml.NVML_PCIE_UTIL_RX_BYTES)
        except Exception:
            pass

        # Why the GPU is not running at full clocks — the thermal governor reads this.
        throttle_bits = 0
        throttle_reasons: List[str] = []
        try:
            throttle_bits = pynvml.nvmlDeviceGetCurrentClocksThrottleReasons(handle)
            throttle_reasons = decode_throttle_reasons(throttle_bits)
        except Exception:
            pass

        # Power management limit (watts) — the OC ceiling.
        power_limit_w = 0.0
        try:
            power_limit_w = round(pynvml.nvmlDeviceGetPowerManagementLimit(handle) / 1000.0, 1)
        except Exception:
            pass

        # Driver + CUDA version (completeness).
        driver_version = ""
        cuda_version = ""
        try:
            dv = pynvml.nvmlSystemGetDriverVersion()
            driver_version = dv.decode("utf-8") if isinstance(dv, bytes) else str(dv)
        except Exception:
            pass
        try:
            cv = pynvml.nvmlSystemGetCudaDriverVersion()
            cuda_version = cv  # int like 12030 == CUDA 12.3
        except Exception:
            pass

        # Discover processes on GPU
        proc_breakdown = {
            "ollama_bytes": 0,
            "comfyui_bytes": 0,
            "system_bytes": 0,
            "processes": []
        }
        
        try:
            procs = pynvml.nvmlDeviceGetComputeRunningProcesses(handle)
            graphics_procs = pynvml.nvmlDeviceGetGraphicsRunningProcesses(handle)
            all_procs = {p.pid: p.usedGpuMemory for p in procs}
            for p in graphics_procs:
                all_procs[p.pid] = max(all_procs.get(p.pid, 0), p.usedGpuMemory or 0)
                
            for pid, used_mem in all_procs.items():
                pname = "Unknown"
                cmdline = ""
                try:
                    proc = psutil.Process(pid)
                    pname = proc.name()
                    cmdline = " ".join(proc.cmdline())
                except Exception:
                    pass
                
                is_ollama = "ollama" in pname.lower() or "llama-server" in cmdline.lower()
                is_comfy = "comfy" in cmdline.lower() or "main.py" in cmdline.lower()
                
                if is_ollama:
                    proc_breakdown["ollama_bytes"] += used_mem
                elif is_comfy:
                    proc_breakdown["comfyui_bytes"] += used_mem
                else:
                    proc_breakdown["system_bytes"] += used_mem
                    
                proc_breakdown["processes"].append({
                    "pid": pid,
                    "name": pname,
                    "cmdline": cmdline[:60],
                    "vram_bytes": used_mem,
                    "vram_mb": round(used_mem / (1024**2), 1),
                    "is_ollama": is_ollama,
                    "is_comfy": is_comfy,
                })
        except Exception as e:
            logger.error(f"Error enumerating GPU processes: {e}")

        total_vram = mem_info.total
        used_vram = mem_info.used
        free_vram = mem_info.free
        
        return {
            "available": True,
            "device_name": name,
            "vram_total_bytes": total_vram,
            "vram_total_gb": round(total_vram / (1024**3), 2),
            "vram_used_bytes": used_vram,
            "vram_used_gb": round(used_vram / (1024**3), 2),
            "vram_free_bytes": free_vram,
            "vram_free_gb": round(free_vram / (1024**3), 2),
            "vram_used_pct": round((used_vram / total_vram * 100) if total_vram > 0 else 0, 1),
            "gpu_util_pct": util_rates.gpu,
            "mem_util_pct": util_rates.memory,
            "temperature_c": temp_c,
            "power_w": power_w,
            "power_limit_w": power_limit_w,
            "pcie_tx_kbps": pcie_tx_kbps,
            "pcie_rx_kbps": pcie_rx_kbps,
            "throttle_bits": throttle_bits,
            "throttle_reasons": throttle_reasons,
            "driver_version": driver_version,
            "cuda_version": cuda_version,
            "fan_pct": fan_pct,
            "fans": fans,
            "num_fans": len(fans),
            "clock_graphics_mhz": clock_graphics,
            "clock_mem_mhz": clock_mem,
            "breakdown": {
                "ollama_mb": round(proc_breakdown["ollama_bytes"] / (1024**2), 1),
                "ollama_gb": round(proc_breakdown["ollama_bytes"] / (1024**3), 2),
                "comfyui_mb": round(proc_breakdown["comfyui_bytes"] / (1024**2), 1),
                "comfyui_gb": round(proc_breakdown["comfyui_bytes"] / (1024**3), 2),
                "system_mb": round(proc_breakdown["system_bytes"] / (1024**2), 1),
                "system_gb": round(proc_breakdown["system_bytes"] / (1024**3), 2),
                "free_mb": round(free_vram / (1024**2), 1),
                "free_gb": round(free_vram / (1024**3), 2),
                "processes": proc_breakdown["processes"],
            }
        }
    except Exception as e:
        return {"available": False, "error": str(e)}

async def get_ollama_live_state() -> Dict[str, Any]:
    """Get active models, running status, and VRAM expiration from Ollama."""
    state = {
        "online": False,
        "loaded_models": [],
        "active_model_name": None,
        "active_model_vram_gb": 0.0,
        "active_context": 0,
        "expires_at": None,
        "installed_models": []
    }
    try:
        client = _client(OLLAMA_API_BASE, 3.0)
        # Check running models (ps)
        ps_resp = await client.get("/api/ps")
        if ps_resp.status_code == 200:
            state["online"] = True
            models = ps_resp.json().get("models", [])
            state["loaded_models"] = models
            if models:
                first = models[0]
                state["active_model_name"] = first.get("name")
                vram_bytes = first.get("size_vram", first.get("size", 0))
                state["active_model_vram_gb"] = round(vram_bytes / (1024**3), 2)
                state["active_context"] = first.get("context_length", 0)
                state["expires_at"] = first.get("expires_at")
        
        # Check all tags
        tags_resp = await client.get("/api/tags")
        if tags_resp.status_code == 200:
            state["installed_models"] = tags_resp.json().get("models", [])
    except Exception as e:
        logger.debug(f"Ollama check error: {e}")
        
    return state

async def get_comfyui_live_state() -> Dict[str, Any]:
    """Get prompt queue, device status, and active execution from ComfyUI."""
    state = {
        "online": False,
        "executing": False,
        "queue_remaining": 0,
        "queue_running": 0,
        "current_node": None,
        "current_prompt_id": None,
        "vram_free_mb": 0,
        "vram_total_mb": 0,
    }
    try:
        client = _client(COMFY_API_BASE, 3.0)
        # Check system stats
        stats_resp = await client.get("/system_stats")
        if stats_resp.status_code == 200:
            state["online"] = True
            data = stats_resp.json()
            devices = data.get("devices", [])
            if devices:
                dev = devices[0]
                state["vram_free_mb"] = round(dev.get("vram_free", 0) / (1024**2), 1)
                state["vram_total_mb"] = round(dev.get("vram_total", 0) / (1024**2), 1)
        
        # Check queue
        queue_resp = await client.get("/queue")
        if queue_resp.status_code == 200:
            qdata = queue_resp.json()
            running = qdata.get("queue_running", [])
            pending = qdata.get("queue_pending", [])
            state["queue_running"] = len(running)
            state["queue_remaining"] = len(pending)
            state["executing"] = len(running) > 0
            if running:
                state["current_prompt_id"] = running[0][1] if len(running[0]) > 1 else str(running[0])
    except Exception as e:
        logger.debug(f"ComfyUI check error: {e}")
        
    return state

async def _await_vram_release(baseline_bytes: int,
                              timeout_s: float = YIELD_CONFIRM_TIMEOUT_S) -> Dict[str, Any]:
    """Block until Ollama's VRAM has actually drained, or we give up.

    Posting keep_alive:0 only *asks* Ollama to unload; the driver frees the allocation
    some milliseconds later. Returning before that happens is how ComfyUI ends up
    allocating into VRAM that is still occupied, which shows up as a CUDA OOM mid-graph.
    """
    t0 = time.perf_counter()
    last = baseline_bytes
    while True:
        snap = get_process_vram_bytes()
        last = snap["ollama_bytes"]
        if last <= YIELD_RESIDUAL_BYTES:
            return {
                "confirmed": True,
                "confirm_ms": round((time.perf_counter() - t0) * 1000, 2),
                "residual_bytes": last,
                "free_bytes": snap["free_bytes"],
            }
        if (time.perf_counter() - t0) >= timeout_s:
            return {
                "confirmed": False,
                "confirm_ms": round((time.perf_counter() - t0) * 1000, 2),
                "residual_bytes": last,
                "free_bytes": snap["free_bytes"],
                "error": f"Ollama still holding {round(last / (1024**3), 2)} GB after {timeout_s}s",
            }
        await asyncio.sleep(YIELD_CONFIRM_POLL_S)


def _record(event: Dict[str, Any]) -> None:
    """Push an event to both the in-memory ring and the durable store."""
    event.setdefault("ts", time.time())
    event.setdefault("timestamp", time.strftime("%H:%M:%S"))
    SWITCH_HISTORY.appendleft(event)
    telemetry_store.record_event(event, profile=overclock_manager.ACTIVE_PROFILE)


async def instant_free_ollama_vram(model_name: Optional[str] = None,
                                   confirm: bool = True) -> Dict[str, Any]:
    """Yield Ollama's VRAM and wait for the driver to actually release it.

    The returned duration_ms is now the real end-to-end release time, not just how long
    the HTTP POST took.
    """
    t0 = time.perf_counter()
    if not model_name:
        ollama_state = await get_ollama_live_state()
        model_name = ollama_state.get("active_model_name")

    if not model_name:
        return {"success": True, "message": "No active Ollama model in VRAM",
                "duration_ms": 0, "confirmed": True}

    baseline = get_process_vram_bytes()["ollama_bytes"]
    try:
        client = _client(OLLAMA_API_BASE, 5.0)
        await client.post("/api/generate", json={"model": model_name, "keep_alive": 0})
        request_ms = round((time.perf_counter() - t0) * 1000, 2)

        barrier = {"confirmed": None, "confirm_ms": 0.0, "residual_bytes": baseline}
        if confirm:
            barrier = await _await_vram_release(baseline)

        duration_ms = round((time.perf_counter() - t0) * 1000, 2)
        freed_gb = round(max(baseline - barrier.get("residual_bytes", 0), 0) / (1024**3), 2)

        _record({
            "event_type": "Ollama VRAM Yield",
            "source": model_name,
            "target": "VRAM 0MB (Kept in RAM)",
            "duration_ms": duration_ms,
            "yield_confirm_ms": barrier.get("confirm_ms"),
            "cache_status": "RAM-Cached" if barrier.get("confirmed") else "Yield Timeout",
            "detail": barrier.get("error"),
        })
        return {
            "success": True,
            "model": model_name,
            "duration_ms": duration_ms,
            "request_ms": request_ms,
            "confirm_ms": barrier.get("confirm_ms"),
            "confirmed": barrier.get("confirmed"),
            "freed_gb": freed_gb,
            "residual_gb": round(barrier.get("residual_bytes", 0) / (1024**3), 2),
            "free_vram_gb": round(barrier.get("free_bytes", 0) / (1024**3), 2),
            "error": barrier.get("error"),
        }
    except Exception as e:
        return {"success": False, "error": str(e),
                "duration_ms": round((time.perf_counter() - t0) * 1000, 2)}


async def instant_free_comfyui_vram() -> Dict[str, Any]:
    """Tell ComfyUI to purge loaded diffusion models from VRAM."""
    t0 = time.perf_counter()
    try:
        client = _client(COMFY_API_BASE, 5.0)
        await client.post("/free", json={"unload_models": True, "free_memory": True})
        duration_ms = round((time.perf_counter() - t0) * 1000, 2)
        snap = get_process_vram_bytes()
        _record({
            "event_type": "ComfyUI VRAM Purge",
            "source": "ComfyUI Pipeline",
            "target": "VRAM Free",
            "duration_ms": duration_ms,
            "cache_status": "Cleaned",
        })
        return {"success": True, "duration_ms": duration_ms,
                "free_vram_gb": round(snap["free_bytes"] / (1024**3), 2)}
    except Exception as e:
        return {"success": False, "error": str(e),
                "duration_ms": round((time.perf_counter() - t0) * 1000, 2)}


_MODEL_SIZE_CACHE: Dict[str, int] = {}


def _model_size_bytes(model_name: str) -> int:
    """On-disk weight size for an Ollama model, used to turn load time into bandwidth."""
    if model_name in _MODEL_SIZE_CACHE:
        return _MODEL_SIZE_CACHE[model_name]
    try:
        for f in ram_optimizer.find_ollama_model_files():
            _MODEL_SIZE_CACHE[f["model"]] = f["size_bytes"]
    except Exception as e:
        logger.debug(f"model size lookup failed: {e}")
    return _MODEL_SIZE_CACHE.get(model_name, 0)


def classify_load(size_bytes: int, load_duration_ms: float) -> Dict[str, Any]:
    """Classify how a model reached VRAM, from achieved bandwidth rather than a constant.

    The old rule was `load_duration_ms < 2500`, which called a 27B Q2_K read from NVMe a
    cache hit and a small model read from RAM a cold load. Bandwidth separates them
    cleanly: page cache feeds PCIe at many GB/s, this NVMe does not.
    """
    if load_duration_ms <= 1.0:
        return {"cache_status": "Already in VRAM", "load_gbps": None, "is_ram_hit": True}
    if not size_bytes:
        # No size on record — fall back to the old heuristic, but say so.
        return {
            "cache_status": "RAM Cache Hit ⚡" if load_duration_ms < 2500 else "Cold Disk Load 💾",
            "load_gbps": None,
            "is_ram_hit": load_duration_ms < 2500,
            "detail": "size unknown, fell back to duration heuristic",
        }
    gbps = (size_bytes / (1024**3)) / (load_duration_ms / 1000.0)
    if gbps >= RAM_HIT_GBPS:
        status = "RAM Cache Hit ⚡"
    elif gbps >= PARTIAL_HIT_GBPS:
        status = "Partial Cache 🌤"
    else:
        status = "Cold Disk Load 💾"
    return {"cache_status": status, "load_gbps": round(gbps, 2), "is_ram_hit": gbps >= RAM_HIT_GBPS}


async def switch_ollama_model(target_model: str, keep_alive: str = "30m") -> Dict[str, Any]:
    """High-speed hot-swap to target Ollama model, tracking swap metrics."""
    t0 = time.perf_counter()
    cur_state = await get_ollama_live_state()
    prev_model = cur_state.get("active_model_name") or "None"

    try:
        client = _client(OLLAMA_API_BASE, 180.0)
        resp = await client.post(
            "/api/generate",
            json={"model": target_model, "prompt": "Ready check", "stream": False,
                  "keep_alive": keep_alive},
        )
        total_duration_ms = round((time.perf_counter() - t0) * 1000, 2)

        if resp.status_code == 200:
            data = resp.json()
            load_dur_ms = round(data.get("load_duration", 0) / 1e6, 2)
            eval_dur_ms = round(data.get("eval_duration", 0) / 1e6, 2)
            eval_count = data.get("eval_count", 0)
            tokens_per_sec = round((eval_count / (eval_dur_ms / 1000)) if eval_dur_ms > 0 else 0, 1)

            size_bytes = _model_size_bytes(target_model)
            cls = classify_load(size_bytes, load_dur_ms)

            _record({
                "event_type": "LLM Model Switch",
                "source": prev_model,
                "target": target_model,
                "duration_ms": total_duration_ms,
                "load_duration_ms": load_dur_ms,
                "tokens_per_sec": tokens_per_sec,
                "bytes_loaded": size_bytes,
                "load_gbps": cls["load_gbps"],
                "cache_status": cls["cache_status"],
                "detail": cls.get("detail"),
            })

            return {
                "success": True,
                "prev_model": prev_model,
                "target_model": target_model,
                "total_duration_ms": total_duration_ms,
                "load_duration_ms": load_dur_ms,
                "tokens_per_sec": tokens_per_sec,
                "model_size_gb": round(size_bytes / (1024**3), 2) if size_bytes else None,
                "load_gbps": cls["load_gbps"],
                "cache_status": cls["cache_status"],
                "is_ram_hit": cls["is_ram_hit"],
                "response": data.get("response", ""),
            }
        return {"success": False, "error": f"HTTP {resp.status_code}: {resp.text}",
                "duration_ms": total_duration_ms}
    except Exception as e:
        return {"success": False, "error": str(e),
                "duration_ms": round((time.perf_counter() - t0) * 1000, 2)}


def get_switch_history() -> List[Dict[str, Any]]:
    return list(SWITCH_HISTORY)


class AutoArbitrator:
    """Real-time bidirectional background arbitrator for seamless Ollama <-> ComfyUI hot-swapping.

    Two behavioural changes worth knowing about:

      * ComfyUI's VRAM is no longer purged 1.5 s after every finished prompt. Iterating on
        a workflow is the common case, and purging between runs forced a full checkpoint
        reload each time. The purge now waits for COMFY_IDLE_PURGE_S of genuinely empty
        queue, and happens immediately only when Ollama actually needs the VRAM.
      * The watchdog no longer polls two ComfyUI endpoints every 300 ms. The WebSocket is
        the primary signal; polling is a fallback that runs at 1 Hz and only hits /queue,
        backing off further while the socket is healthy.
    """

    COMFY_IDLE_PURGE_S = 30.0
    WATCHDOG_INTERVAL_S = 1.0
    WATCHDOG_INTERVAL_WS_OK_S = 3.0

    def __init__(self):
        self.running = False
        self.ws_task: Optional[asyncio.Task] = None
        self.poll_task: Optional[asyncio.Task] = None
        self.idle_task: Optional[asyncio.Task] = None
        self.last_yield_time = 0.0
        self.last_comfy_free_time = 0.0
        self.connected_ws = False
        self.last_action = "Idle"
        self.comfy_was_active = False
        self.comfy_idle_since: Optional[float] = None
        self.oc_profile = None
        self.pending_purge = False
        self.stats = {"yields": 0, "purges": 0, "yield_timeouts": 0, "deferred_purges": 0}

    async def start(self):
        if self.running:
            return
        self.running = True
        self.ws_task = asyncio.create_task(self._ws_listener())
        self.poll_task = asyncio.create_task(self._poll_watchdog())
        self.idle_task = asyncio.create_task(self._idle_purge_loop())
        logger.info("AutoArbitrator background engine started (Bidirectional).")
        try:
            await asyncio.get_running_loop().run_in_executor(
                None, overclock_manager.apply_profile, "balanced")
            self.oc_profile = "balanced"
        except Exception as e:
            logger.warning(f"Startup overclock apply failed: {e}")

    async def stop(self):
        self.running = False
        for task in (self.ws_task, self.poll_task, self.idle_task):
            if task:
                task.cancel()
        await close_clients()
        logger.info("AutoArbitrator background engine stopped.")

    async def trigger_comfy_priority(self, reason: str = "ComfyUI prompt detected"):
        """Yield Ollama's VRAM — and confirm it is gone — before diffusion allocates."""
        self.comfy_was_active = True
        self.comfy_idle_since = None
        self._apply_oc_profile("comfy")
        now = time.time()
        if now - self.last_yield_time < 1.0:
            return

        ollama_state = await get_ollama_live_state()
        if ollama_state.get("active_model_name"):
            model = ollama_state["active_model_name"]
            logger.info(f"⚡ ComfyUI active ({reason}) -> Auto-yielding Ollama model '{model}'...")
            self.last_yield_time = time.time()
            res = await instant_free_ollama_vram(model, confirm=True)
            self.stats["yields"] += 1
            if res.get("confirmed"):
                self.last_action = (f"Yielded '{model}' for ComfyUI in "
                                    f"{res.get('confirm_ms')}ms (confirmed {res.get('freed_gb')}GB free)")
            else:
                self.stats["yield_timeouts"] += 1
                self.last_action = (f"⚠ Yield of '{model}' NOT confirmed: "
                                    f"{res.get('residual_gb')}GB still held")
                logger.warning(f"VRAM yield barrier timed out: {res.get('error')}")
            logger.info(f"Ollama auto-yield completed: {res}")

    async def trigger_comfy_completed(self, immediate: bool = False):
        """Mark the end of a generation. The actual purge is deferred unless forced."""
        self.comfy_was_active = False
        if self.comfy_idle_since is None:
            self.comfy_idle_since = time.time()
        self._apply_oc_profile("ollama")
        if immediate:
            await self._purge_comfy_now("Ollama needs VRAM")
        else:
            self.pending_purge = True
            self.stats["deferred_purges"] += 1
            self.last_action = (f"ComfyUI idle — holding its checkpoints for "
                                f"{int(self.COMFY_IDLE_PURGE_S)}s in case you iterate")

    async def _purge_comfy_now(self, reason: str):
        now = time.time()
        if now - self.last_comfy_free_time < 3.0:
            return
        self.last_comfy_free_time = now
        self.pending_purge = False
        logger.info(f"⚡ Purging ComfyUI VRAM cache ({reason})...")
        res = await instant_free_comfyui_vram()
        self.stats["purges"] += 1
        self.last_action = f"Purged ComfyUI VRAM ({res.get('duration_ms')}ms) — {reason}"
        logger.info(f"ComfyUI purge completed: {res}")

    async def _idle_purge_loop(self):
        """Purge ComfyUI's VRAM only after a real idle gap, not between iterations."""
        while self.running:
            try:
                if self.pending_purge and self.comfy_idle_since and not self.comfy_was_active:
                    idle_for = time.time() - self.comfy_idle_since
                    if idle_for >= self.COMFY_IDLE_PURGE_S:
                        await self._purge_comfy_now(
                            f"idle {int(idle_for)}s")
            except Exception as e:
                logger.debug(f"idle purge loop error: {e}")
            await asyncio.sleep(2.0)

    async def request_vram_for_ollama(self, needed_gb: float = 0.0) -> Dict[str, Any]:
        """Called when Ollama needs VRAM now: purge ComfyUI immediately rather than waiting."""
        snap = get_process_vram_bytes()
        free_gb = snap["free_bytes"] / (1024**3)
        if needed_gb and free_gb >= needed_gb:
            return {"purged": False, "free_gb": round(free_gb, 2), "reason": "enough free VRAM"}
        if snap["comfyui_bytes"] > YIELD_RESIDUAL_BYTES:
            await self._purge_comfy_now(f"Ollama requested {needed_gb or '?'}GB")
            snap = get_process_vram_bytes()
            return {"purged": True, "free_gb": round(snap["free_bytes"] / (1024**3), 2)}
        return {"purged": False, "free_gb": round(free_gb, 2), "reason": "ComfyUI holds no VRAM"}

    async def _ws_listener(self):
        client_id = "hyperswap-arbitrator"
        ws_url = f"ws://127.0.0.1:8188/ws?clientId={client_id}"
        backoff = 2.0

        while self.running:
            try:
                async with websockets.connect(ws_url, ping_interval=10, ping_timeout=10) as ws:
                    self.connected_ws = True
                    backoff = 2.0
                    logger.info("AutoArbitrator connected to ComfyUI WebSocket.")
                    while self.running:
                        msg = await ws.recv()
                        if not isinstance(msg, str):
                            continue
                        try:
                            data = json.loads(msg)
                            msg_type = data.get("type")
                            msg_data = data.get("data", {})

                            if msg_type == "status":
                                queue_rem = (msg_data.get("status", {})
                                             .get("exec_info", {}).get("queue_remaining", 0))
                                if queue_rem > 0:
                                    await self.trigger_comfy_priority(f"Queue remaining: {queue_rem}")
                                elif queue_rem == 0 and self.comfy_was_active:
                                    await self.trigger_comfy_completed()
                            elif msg_type in ("execution_start", "execution_cached"):
                                await self.trigger_comfy_priority(f"Event: {msg_type}")
                            elif msg_type == "executing":
                                node = msg_data.get("node")
                                if node is not None:
                                    await self.trigger_comfy_priority(f"Executing node: {node}")
                                elif self.comfy_was_active:
                                    await self.trigger_comfy_completed()
                            elif msg_type == "execution_success":
                                await self.trigger_comfy_completed()
                            elif msg_type == "execution_error":
                                logger.warning(f"ComfyUI execution error: {msg_data}")
                                await self.trigger_comfy_completed()
                        except Exception as e:
                            logger.debug(f"WS parse error: {e}")
            except (websockets.exceptions.ConnectionClosed, OSError, asyncio.CancelledError):
                self.connected_ws = False
            except Exception as e:
                self.connected_ws = False
                logger.debug(f"WS connection error: {e}")

            await asyncio.sleep(backoff)
            backoff = min(backoff * 1.5, 15.0)

    async def _poll_watchdog(self):
        """Fallback for when the WebSocket is down. One cheap /queue call, 1 Hz.

        The previous version hit /system_stats and /queue every 300 ms on fresh TCP
        connections — roughly 6.6 requests/second against ComfyUI, forever.
        """
        while self.running:
            interval = self.WATCHDOG_INTERVAL_WS_OK_S if self.connected_ws else self.WATCHDOG_INTERVAL_S
            try:
                client = _client(COMFY_API_BASE, 3.0)
                resp = await client.get("/queue")
                if resp.status_code == 200:
                    q = resp.json()
                    busy = len(q.get("queue_running", [])) > 0 or len(q.get("queue_pending", [])) > 0
                    if busy:
                        await self.trigger_comfy_priority("Watchdog saw an active queue")
                    elif self.comfy_was_active:
                        await self.trigger_comfy_completed()
            except Exception:
                pass
            await asyncio.sleep(interval)

    def _apply_oc_profile(self, profile: str):
        """Apply an overclock profile in a background thread; only fire on transition."""
        if self.oc_profile == profile:
            return
        self.oc_profile = profile
        try:
            loop = asyncio.get_running_loop()
            loop.run_in_executor(None, overclock_manager.apply_profile, profile)
            logger.info(f"🎛️ Overclock profile switched -> '{profile}'")
        except Exception as e:
            logger.warning(f"Overclock profile switch failed ({profile}): {e}")

    def get_status(self) -> Dict[str, Any]:
        idle_for = (time.time() - self.comfy_idle_since) if self.comfy_idle_since else None
        return {
            "running": self.running,
            "connected_ws": self.connected_ws,
            "last_action": self.last_action,
            "mode": "Bidirectional Hot-Swap (ComfyUI <-> Ollama)",
            "comfy_active": self.comfy_was_active,
            "pending_purge": self.pending_purge,
            "comfy_idle_s": round(idle_for, 1) if idle_for is not None else None,
            "idle_purge_after_s": self.COMFY_IDLE_PURGE_S,
            "oc_profile": self.oc_profile,
            "counters": dict(self.stats),
        }


arbitrator = AutoArbitrator()