Removed unused imports and cleaned up code for size.
This commit is contained in:
mrmarcus007
@@ -7,26 +7,21 @@ import time
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import threading
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import subprocess
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from datetime import datetime, time as dt_time
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from urllib.parse import urlparse, parse_qs
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import logging
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import socket
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# Configuration
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# ----------------------------------------------------------Host-config--------------------------------------------------------------#
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OLLAMA_HOST = "" # Your Ollama LXC IP
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OLLAMA_PORT = 11434 # Your Ollama LXC Port
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PROXY_PORT = 11435 # Port Of This Proxy
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OLLAMA_BASE_URL = f"http://{OLLAMA_HOST}:{OLLAMA_PORT}" # Fixed formatting
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OLLAMA_BASE_URL = f"http://{OLLAMA_HOST}:{OLLAMA_PORT}"
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# GPU monitoring
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GPU_CHECK_INTERVAL = 10 # seconds it waits to check for other process apart from known/compute processes
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# process process patterns (from your nvidia-smi output)
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IDLE_NvGPU_PROCESSES = ['t-rex', 'trex', 'miner', 'xmrig', 'lolminer', 'nbminer']
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KNOWN_NvGPU_PROCESSES = ['Xorg'] # Processes that are allowed when "idle" compute process is running
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IDLE_CONTAINER_ID = "" # running Idle GPU Container ID, example: COMPUTE_CONTAINER_ID ="120"
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Blackout_schedule_Start = dt_time(2, 15) # 2:15 AM
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Blackout_schedule_End = dt_time(3, 30) # 3:30 AM
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# ----------------------------------------------------------active-code--------------------------------------------------------------#
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logging.basicConfig(
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level=logging.INFO,
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@@ -36,7 +31,6 @@ logging.basicConfig(
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logging.StreamHandler()
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]
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)
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class GPUResourceManager:
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def __init__(self):
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self.idle_compute_running = False
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@@ -47,7 +41,6 @@ class GPUResourceManager:
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self.gpu_processes = []
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self.lock = threading.Lock()
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self.operation_in_progress = False
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def run_command(self, cmd):
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try:
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result = subprocess.run(cmd, shell=True, capture_output=True, text=True, check=True)
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@@ -55,13 +48,11 @@ class GPUResourceManager:
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except subprocess.CalledProcessError as e:
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logging.error(f"Command failed: {cmd}, error: {e.stderr}")
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return None
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def is_container_running(self, container_id):
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output = self.run_command(f"pct list | grep \"^{container_id}\"")
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if output and "running" in output:
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return True
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return False
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def stop_container(self, container_id):
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if self.is_container_running(container_id):
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logging.info(f"Stopping container {container_id}")
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@@ -85,7 +76,6 @@ class GPUResourceManager:
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logging.debug(f"Container {container_id} already stopped, no action needed")
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return True
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return False
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def start_container(self, container_id):
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if not self.is_container_running(container_id):
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logging.info(f"Starting container {container_id}")
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@@ -108,7 +98,6 @@ class GPUResourceManager:
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logging.debug(f"Container {container_id} already running, no action needed")
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return True
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return False
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def get_gpu_processes(self):
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try:
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output = self.run_command(
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@@ -129,29 +118,23 @@ class GPUResourceManager:
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except Exception as e:
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logging.error(f"Error getting GPU processes: {e}")
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return []
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def is_compute_process(self, process_name):
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process_lower = process_name.lower()
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for pattern in IDLE_NvGPU_PROCESSES:
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if pattern in process_lower:
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return True
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return False
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def is_known_system_process(self, process_name):
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return any(sys_proc in process_name for sys_proc in KNOWN_NvGPU_PROCESSES)
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def is_gpu_idle(self):
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processes = self.get_gpu_processes()
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non_mining_processes = []
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for process in processes:
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if not self.is_compute_process(process['name']) and not self.is_known_system_process(process['name']):
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memory_usage = int(process['memory'].split()[0])
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if memory_usage > 100: #MB
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non_mining_processes.append(process)
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is_idle = len(non_mining_processes) == 0
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if is_idle:
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mining_count = len([p for p in processes if self.is_compute_process(p['name'])])
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if mining_count > 0:
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@@ -160,20 +143,16 @@ class GPUResourceManager:
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logging.debug("GPU is truly idle (no significant processes)")
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else:
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logging.debug(f"GPU is active with non-mining processes: {[p['name'] for p in non_mining_processes]}")
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return is_idle
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def is_Idle_NvGPU_process_active(self):
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processes = self.get_gpu_processes()
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mining_processes = [p for p in processes if self.is_compute_process(p['name'])]
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return len(mining_processes) > 0
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def is_ollama_still_active(self):
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if not self.ollama_active:
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return False
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time_since_last_activity = time.time() - self.last_ollama_activity
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return time_since_last_activity < self.ollama_activity_timeout
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def should_stop_for_schedule(self):
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now = datetime.now().time()
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stop_start = Blackout_schedule_Start
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@@ -182,12 +161,10 @@ class GPUResourceManager:
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if in_window:
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logging.debug("Within scheduled maintenance window (2:15am-3:30am)")
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return in_window
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def manage_idle_NvGPU_process(self):
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with self.lock:
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if self.operation_in_progress:
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return
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self.operation_in_progress = True
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try:
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current_idle_NvGPU_process_state = self.is_container_running(IDLE_CONTAINER_ID)
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@@ -212,7 +189,6 @@ class GPUResourceManager:
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if self.ollama_active:
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self.ollama_active = False
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logging.info("Ollama activity timeout reached")
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if self.is_gpu_idle():
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if not current_idle_NvGPU_process_state and not mining_active_on_gpu:
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logging.info("GPU idle, starting idle NvGPU container")
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@@ -228,7 +204,6 @@ class GPUResourceManager:
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self.idle_compute_running = False
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finally:
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self.operation_in_progress = False
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def force_stop_idle_NvGPU_process_for_ollama(self):
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with self.lock:
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self.ollama_active = True
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@@ -251,7 +226,6 @@ class GPUResourceManager:
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logging.debug("idle NvGPU container already stopped, no action needed")
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self.idle_compute_running = False
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def start_monitoring(self):
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def monitor_loop():
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while True:
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@@ -264,54 +238,42 @@ class GPUResourceManager:
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monitor_thread = threading.Thread(target=monitor_loop, daemon=True)
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monitor_thread.start()
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logging.info("GPU monitoring thread started")
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class OllamaProxyHandler(http.server.SimpleHTTPRequestHandler):
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def __init__(self, *args, **kwargs):
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self.gpu_manager = kwargs.pop('gpu_manager')
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super().__init__(*args, **kwargs)
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def do_GET(self):
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if self._is_gpu_intensive_operation(self.path, {}):
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self.gpu_manager.force_stop_idle_NvGPU_process_for_ollama()
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time.sleep(2)
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self._forward_request('GET')
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def do_HEAD(self):
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if self._is_gpu_intensive_operation(self.path, {}):
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self.gpu_manager.force_stop_idle_NvGPU_process_for_ollama()
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time.sleep(2)
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self._forward_request('HEAD')
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def do_POST(self):
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content_length = int(self.headers.get('Content-Length', 0))
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post_data = self.rfile.read(content_length) if content_length > 0 else b''
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try:
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request_data = {}
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try:
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request_data = json.loads(post_data.decode('utf-8')) if post_data else {}
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except Exception:
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request_data = {}
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is_gpu_intensive = self._is_gpu_intensive_operation(self.path, request_data)
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if is_gpu_intensive:
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logging.info(f"GPU-intensive operation detected: {self.path}")
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self.gpu_manager.force_stop_idle_NvGPU_process_for_ollama()
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time.sleep(3.5)
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self._forward_request('POST', post_data)
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if is_gpu_intensive:
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with self.gpu_manager.lock:
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self.gpu_manager.last_ollama_activity = time.time()
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logging.info("Ollama request completed, activity timestamp updated")
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except Exception as e:
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logging.error(f"Error processing request: {e}")
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self.send_error(500, f"Internal server error: {e}")
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def _is_gpu_intensive_operation(self, path, request_data):
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if path == '/api/generate' and request_data.get('keep_alive') == 0:
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logging.debug("Detected model unload request via /api/generate")
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@@ -326,11 +288,9 @@ class OllamaProxyHandler(http.server.SimpleHTTPRequestHandler):
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if path == '/api/pull':
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return request_data.get('stream', True)
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return False
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def _forward_request(self, method, data=None):
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url = f"{OLLAMA_BASE_URL}{self.path}"
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headers = {key: value for key, value in self.headers.items()}
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hop_headers = {
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'connection', 'keep-alive', 'proxy-authenticate',
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'proxy-authorization', 'te', 'trailers', 'upgrade',
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@@ -341,17 +301,13 @@ class OllamaProxyHandler(http.server.SimpleHTTPRequestHandler):
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headers.pop(header, None)
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headers.pop('Host', None)
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timeout = (10, None)
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try:
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if method.upper() in ('GET', 'HEAD'):
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resp = requests.request(method, url, headers=headers, stream=True, timeout=timeout)
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else:
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resp = requests.request(method, url, headers=headers, data=data, stream=True, timeout=timeout)
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self.send_response(resp.status_code)
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for key, value in resp.headers.items():
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k_lower = key.lower()
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if k_lower in hop_headers:
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@@ -361,7 +317,6 @@ class OllamaProxyHandler(http.server.SimpleHTTPRequestHandler):
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except Exception:
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logging.debug(f"Skipping header {key} due to send_header error")
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self.end_headers()
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try:
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for chunk in resp.iter_content(chunk_size=4096):
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if not chunk:
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@@ -392,47 +347,35 @@ class OllamaProxyHandler(http.server.SimpleHTTPRequestHandler):
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def log_message(self, format, *args):
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logging.info(f"{self.address_string()} - {format % args}")
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class ThreadedTCPServer(socketserver.ThreadingMixIn, socketserver.TCPServer):
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daemon_threads = True
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allow_reuse_address = True
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def main():
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logging.info("Starting GPU Resource Manager Proxy on Proxmox Host")
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manager = GPUResourceManager()
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test_output = manager.run_command("pct list > /dev/null && echo 'pct available'")
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if test_output:
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logging.info("pct command available")
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else:
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logging.error("pct command not available! Running on wrong system?")
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gpu_processes = manager.get_gpu_processes()
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logging.info(f"Current GPU processes: {gpu_processes}")
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idle_NvGPU_process_status = manager.is_container_running(IDLE_CONTAINER_ID)
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logging.info(f"idle NvGPU {IDLE_CONTAINER_ID} running: {idle_NvGPU_process_status}")
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gpu_manager = GPUResourceManager()
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gpu_manager.start_monitoring()
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handler = lambda *args, **kwargs: OllamaProxyHandler(*args, gpu_manager=gpu_manager, **kwargs)
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with ThreadedTCPServer(("", PROXY_PORT), handler) as httpd:
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logging.info(f"Proxy server running on port {PROXY_PORT}")
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logging.info(f"Forwarding to Ollama at {OLLAMA_HOST}:{OLLAMA_PORT}")
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logging.info(f"Managing idle NvGPU process: {IDLE_CONTAINER_ID}")
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logging.info("Monitoring GPU usage and scheduled maintenance windows")
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logging.info(f"Mining process patterns: {IDLE_NvGPU_PROCESSES}")
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try:
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httpd.serve_forever()
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except KeyboardInterrupt:
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logging.info("Shutting down proxy server")
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except Exception as e:
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logging.error(f"Server error: {e}")
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if __name__ == "__main__":
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main()
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