Fix indent

Removed unnecessary blank lines in the GPU resource manager script.

GPU Resource Manager Proxy for Ollama (Designed for Proxmox).py

@@ -7,25 +7,22 @@ import time
 import threading
 import subprocess
 from datetime import datetime, time as dt_time
-from urllib.parse import urlparse, parse_qs
 import logging
-
+import socket
-# Configuration
+# ----------------------------------------------------------Host-config--------------------------------------------------------------#
-OLLAMA_HOST = "localhost"  # Your Ollama LXC IP
+OLLAMA_HOST = ""  # Your Ollama LXC IP
 OLLAMA_PORT = 11434  # Your Ollama LXC Port
-PROXY_PORT = 11435 # Port Of This Proxy
+PROXY_PORT = 11435  # Port Of This Proxy
-OLLAMA_BASE_URL = f"http://{OLLAMA_HOST}:{OLLAMA_PORT}" # Don't touch unless you know what you are doing.
+OLLAMA_BASE_URL = f"http://{OLLAMA_HOST}:{OLLAMA_PORT}"
-
 # GPU monitoring
-GPU_CHECK_INTERVAL = 10  # seconds it wait's to check for other process apart from known/compute processes
+GPU_CHECK_INTERVAL = 10  # seconds it waits to check for other process apart from known/compute processes
-
 # process process patterns (from your nvidia-smi output)
 IDLE_NvGPU_PROCESSES = ['t-rex', 'trex', 'miner', 'xmrig', 'lolminer', 'nbminer']
-KNOWN_NvidiaGPU_PROCESSES = ['Xorg']  # Processes that are allowed when "idle" compute process is running
+KNOWN_NvGPU_PROCESSES = ['Xorg']  # Processes that are allowed when "idle" compute process is running
-IDLE_CONTAINER_ID = "" # running Idle GPU Container ID, example: COMPUTE_CONTAINER_ID ="120"
+IDLE_CONTAINER_ID = ""  # running Idle GPU Container ID, example: COMPUTE_CONTAINER_ID ="120"
-Blackout_schedule_Start = 2, 15 #when to start stopping the idle NvGPU container.
+Blackout_schedule_Start = dt_time(2, 15)  # 2:15 AM
-Blackout_schedule_End = 3, 30 #when to allow starting the idle NvGPU container again.
+Blackout_schedule_End = dt_time(3, 30)    # 3:30 AM
-#----------------------------------------------------------active-code--------------------------------------------------------------#
+# ----------------------------------------------------------active-code--------------------------------------------------------------#
 logging.basicConfig(
     level=logging.INFO,
     format='%(asctime)s - %(levelname)s - %(message)s',
@@ -34,7 +31,6 @@ logging.basicConfig(
         logging.StreamHandler()
     ]
 )
-
 class GPUResourceManager:
     def __init__(self):
         self.idle_compute_running = False
@@ -45,7 +41,6 @@ class GPUResourceManager:
         self.gpu_processes = []
         self.lock = threading.Lock()
         self.operation_in_progress = False
-        
     def run_command(self, cmd):
         try:
             result = subprocess.run(cmd, shell=True, capture_output=True, text=True, check=True)
@@ -53,13 +48,11 @@ class GPUResourceManager:
         except subprocess.CalledProcessError as e:
             logging.error(f"Command failed: {cmd}, error: {e.stderr}")
             return None
-
     def is_container_running(self, container_id):
         output = self.run_command(f"pct list | grep \"^{container_id}\"")
         if output and "running" in output:
             return True
         return False
-
     def stop_container(self, container_id):
         if self.is_container_running(container_id):
             logging.info(f"Stopping container {container_id}")
@@ -70,7 +63,6 @@ class GPUResourceManager:
                 while self.is_container_running(container_id) and waited < max_wait:
                     time.sleep(1)
                     waited += 1
-                
                 if not self.is_container_running(container_id):
                     logging.info(f"Container {container_id} stopped successfully")
                     return True
@@ -83,7 +75,6 @@ class GPUResourceManager:
             logging.debug(f"Container {container_id} already stopped, no action needed")
             return True
         return False
-
     def start_container(self, container_id):
         if not self.is_container_running(container_id):
             logging.info(f"Starting container {container_id}")
@@ -94,7 +85,6 @@ class GPUResourceManager:
                 while not self.is_container_running(container_id) and waited < max_wait:
                     time.sleep(1)
                     waited += 1
-                
                 if self.is_container_running(container_id):
                     logging.info(f"Container {container_id} started successfully")
                     return True
@@ -106,10 +96,11 @@ class GPUResourceManager:
             logging.debug(f"Container {container_id} already running, no action needed")
             return True
         return False
-
     def get_gpu_processes(self):
         try:
-            output = self.run_command("nvidia-smi --query-compute-apps=pid,process_name,used_memory --format=csv,noheader,nounits")
+            output = self.run_command(
+                "nvidia-smi --query-compute-apps=pid,process_name,used_memory --format=csv,noheader,nounits"
+            )
             processes = []
             if output:
                 for line in output.split('\n'):
@@ -125,29 +116,23 @@ class GPUResourceManager:
         except Exception as e:
             logging.error(f"Error getting GPU processes: {e}")
             return []
-
     def is_compute_process(self, process_name):
         process_lower = process_name.lower()
         for pattern in IDLE_NvGPU_PROCESSES:
             if pattern in process_lower:
                 return True
         return False
-
     def is_known_system_process(self, process_name):
-        return any(sys_proc in process_name for sys_proc in KNOWN_NvidiaGPU_PROCESSES)
+        return any(sys_proc in process_name for sys_proc in KNOWN_NvGPU_PROCESSES)
-
     def is_gpu_idle(self):
         processes = self.get_gpu_processes()
-
         non_mining_processes = []
         for process in processes:
             if not self.is_compute_process(process['name']) and not self.is_known_system_process(process['name']):
                 memory_usage = int(process['memory'].split()[0])
-                if memory_usage > 100:  # More than 100MB is significant
+                if memory_usage > 100: #MB 
                     non_mining_processes.append(process)
-        
         is_idle = len(non_mining_processes) == 0
-        
         if is_idle:
             mining_count = len([p for p in processes if self.is_compute_process(p['name'])])
             if mining_count > 0:
@@ -156,34 +141,28 @@ class GPUResourceManager:
                 logging.debug("GPU is truly idle (no significant processes)")
         else:
             logging.debug(f"GPU is active with non-mining processes: {[p['name'] for p in non_mining_processes]}")
-            
         return is_idle
-
     def is_Idle_NvGPU_process_active(self):
         processes = self.get_gpu_processes()
         mining_processes = [p for p in processes if self.is_compute_process(p['name'])]
         return len(mining_processes) > 0
-
     def is_ollama_still_active(self):
         if not self.ollama_active:
             return False
         time_since_last_activity = time.time() - self.last_ollama_activity
         return time_since_last_activity < self.ollama_activity_timeout
-
     def should_stop_for_schedule(self):
         now = datetime.now().time()
-        stop_start = dt_time(Blackout_schedule_Start)  # 2:15 AM
+        stop_start = Blackout_schedule_Start 
-        stop_end = dt_time(Blackout_schedule_End)    # 3:30 AM
+        stop_end = Blackout_schedule_End    
         in_window = stop_start <= now <= stop_end
         if in_window:
             logging.debug("Within scheduled maintenance window (2:15am-3:30am)")
         return in_window
-
     def manage_idle_NvGPU_process(self):
         with self.lock:
             if self.operation_in_progress:
-                return  
+                return
-                
             self.operation_in_progress = True
             try:
                 current_idle_NvGPU_process_state = self.is_container_running(IDLE_CONTAINER_ID)
@@ -195,8 +174,7 @@ class GPUResourceManager:
                         self.stop_container(IDLE_CONTAINER_ID)
                         self.idle_compute_running = False
                     return
-                
+
-                
                 ollama_still_active = self.is_ollama_still_active()
                 if ollama_still_active:
                     if current_idle_NvGPU_process_state or mining_active_on_gpu:
@@ -206,11 +184,9 @@ class GPUResourceManager:
                         self.idle_compute_running = False
                     return
                 else:
-                    
                     if self.ollama_active:
                         self.ollama_active = False
                         logging.info("Ollama activity timeout reached")
-                
                 if self.is_gpu_idle():
                     if not current_idle_NvGPU_process_state and not mining_active_on_gpu:
                         logging.info("GPU idle, starting idle NvGPU container")
@@ -226,7 +202,6 @@ class GPUResourceManager:
                         self.idle_compute_running = False
             finally:
                 self.operation_in_progress = False
-
     def force_stop_idle_NvGPU_process_for_ollama(self):
         with self.lock:
             self.ollama_active = True
@@ -247,9 +222,8 @@ class GPUResourceManager:
                         logging.warning("Mining processes still active after container stop")
             else:
                 logging.debug("idle NvGPU container already stopped, no action needed")
-                
-            self.idle_compute_running = False
 
+            self.idle_compute_running = False
     def start_monitoring(self):
         def monitor_loop():
             while True:
@@ -258,48 +232,52 @@ class GPUResourceManager:
                 except Exception as e:
                     logging.error(f"Error in monitor loop: {e}")
                 time.sleep(GPU_CHECK_INTERVAL)
-        
         monitor_thread = threading.Thread(target=monitor_loop, daemon=True)
         monitor_thread.start()
         logging.info("GPU monitoring thread started")
-
 class OllamaProxyHandler(http.server.SimpleHTTPRequestHandler):
     def __init__(self, *args, **kwargs):
         self.gpu_manager = kwargs.pop('gpu_manager')
         super().__init__(*args, **kwargs)
-    
     def do_GET(self):
         if self._is_gpu_intensive_operation(self.path, {}):
             self.gpu_manager.force_stop_idle_NvGPU_process_for_ollama()
-            time.sleep(2) 
+            time.sleep(2)
-        
         self._forward_request('GET')
-    
+    def do_HEAD(self):
+        if self._is_gpu_intensive_operation(self.path, {}):
+            self.gpu_manager.force_stop_idle_NvGPU_process_for_ollama()
+            time.sleep(2)
+        self._forward_request('HEAD')
     def do_POST(self):
         content_length = int(self.headers.get('Content-Length', 0))
         post_data = self.rfile.read(content_length) if content_length > 0 else b''
-        
         try:
-            request_data = json.loads(post_data.decode('utf-8')) if post_data else {}
+            request_data = {}
+            try:
+                request_data = json.loads(post_data.decode('utf-8')) if post_data else {}
+            except Exception:
+                request_data = {}
             is_gpu_intensive = self._is_gpu_intensive_operation(self.path, request_data)
-            
             if is_gpu_intensive:
                 logging.info(f"GPU-intensive operation detected: {self.path}")
                 self.gpu_manager.force_stop_idle_NvGPU_process_for_ollama()
                 time.sleep(3.5)
-
             self._forward_request('POST', post_data)
-            
             if is_gpu_intensive:
                 with self.gpu_manager.lock:
                     self.gpu_manager.last_ollama_activity = time.time()
                 logging.info("Ollama request completed, activity timestamp updated")
-                
         except Exception as e:
             logging.error(f"Error processing request: {e}")
             self.send_error(500, f"Internal server error: {e}")
-    
     def _is_gpu_intensive_operation(self, path, request_data):
+        if path == '/api/generate' and request_data.get('keep_alive') == 0:
+            logging.debug("Detected model unload request via /api/generate")
+            return False
+        if path == '/api/chat' and request_data.get('keep_alive') == 0 and request_data.get('messages') == []:
+            logging.debug("Detected model unload request via /api/chat")
+            return False
         if path in ['/api/generate', '/api/chat', '/api/embeddings']:
             return True
         if path == '/api/load':
@@ -307,71 +285,92 @@ class OllamaProxyHandler(http.server.SimpleHTTPRequestHandler):
         if path == '/api/pull':
             return request_data.get('stream', True)
         return False
-    
     def _forward_request(self, method, data=None):
         url = f"{OLLAMA_BASE_URL}{self.path}"
         headers = {key: value for key, value in self.headers.items()}
-        hop_headers = ['connection', 'keep-alive', 'proxy-authenticate', 
+        hop_headers = {
-                      'proxy-authorization', 'te', 'trailers', 'upgrade']
+            'connection', 'keep-alive', 'proxy-authenticate',
-        for header in hop_headers:
+            'proxy-authorization', 'te', 'trailers', 'upgrade',
-            headers.pop(header, None)
+            'transfer-encoding'
-
+        }
+        for header in list(headers.keys()):
+            if header.lower() in hop_headers:
+                headers.pop(header, None)
+        headers.pop('Host', None)
+        timeout = (10, None)
         try:
-            if method == 'GET':
+            if method.upper() in ('GET', 'HEAD'):
-                response = requests.get(url, headers=headers, timeout=300)
+                resp = requests.request(method, url, headers=headers, stream=True, timeout=timeout)
             else:
-                response = requests.post(url, data=data, headers=headers, timeout=300)
+                resp = requests.request(method, url, headers=headers, data=data, stream=True, timeout=timeout)
-
+            self.send_response(resp.status_code)
-            self.send_response(response.status_code)
+            for key, value in resp.headers.items():
-            for key, value in response.headers.items():
+                k_lower = key.lower()
-                if key.lower() not in ['content-encoding', 'transfer-encoding', 'connection']:
+                if k_lower in hop_headers:
+                    continue
+                try:
                     self.send_header(key, value)
+                except Exception:
+                    logging.debug(f"Skipping header {key} due to send_header error")
             self.end_headers()
-            self.wfile.write(response.content)
+            try:
-            
+                for chunk in resp.iter_content(chunk_size=4096):
+                    if not chunk:
+                        continue
+                    try:
+                        self.wfile.write(chunk)
+                        self.wfile.flush()
+                    except (BrokenPipeError, ConnectionResetError, socket.error) as e:
+                        logging.info(f"Client connection closed during streaming: {e}")
+                        break
+            finally:
+                resp.close()
+
         except requests.exceptions.RequestException as e:
             logging.error(f"Error forwarding to Ollama: {e}")
-            self.send_error(502, f"Bad gateway: {e}")
+            try:
-    
+                if hasattr(self, '_headers_buffer') and getattr(self, 'wfile', None):
+                    try:
+                        err_msg = f"\n\n[proxy error] upstream request failed: {e}\n"
+                        self.wfile.write(err_msg.encode('utf-8'))
+                        self.wfile.flush()
+                    except Exception:
+                        pass
+                else:
+                    self.send_error(502, f"Bad gateway: {e}")
+            except Exception:
+                pass
     def log_message(self, format, *args):
         logging.info(f"{self.address_string()} - {format % args}")
-
+class ThreadedTCPServer(socketserver.ThreadingMixIn, socketserver.TCPServer):
+    daemon_threads = True
+    allow_reuse_address = True
 def main():
     logging.info("Starting GPU Resource Manager Proxy on Proxmox Host")
-
     manager = GPUResourceManager()
     test_output = manager.run_command("pct list > /dev/null && echo 'pct available'")
     if test_output:
         logging.info("pct command available")
     else:
         logging.error("pct command not available! Running on wrong system?")
-        return
-
     gpu_processes = manager.get_gpu_processes()
     logging.info(f"Current GPU processes: {gpu_processes}")
-
     idle_NvGPU_process_status = manager.is_container_running(IDLE_CONTAINER_ID)
     logging.info(f"idle NvGPU {IDLE_CONTAINER_ID} running: {idle_NvGPU_process_status}")
-
     gpu_manager = GPUResourceManager()
-
     gpu_manager.start_monitoring()
-
     handler = lambda *args, **kwargs: OllamaProxyHandler(*args, gpu_manager=gpu_manager, **kwargs)
-    
+    with ThreadedTCPServer(("", PROXY_PORT), handler) as httpd:
-    with socketserver.TCPServer(("", PROXY_PORT), handler) as httpd:
         logging.info(f"Proxy server running on port {PROXY_PORT}")
         logging.info(f"Forwarding to Ollama at {OLLAMA_HOST}:{OLLAMA_PORT}")
         logging.info(f"Managing idle NvGPU process: {IDLE_CONTAINER_ID}")
         logging.info("Monitoring GPU usage and scheduled maintenance windows")
         logging.info(f"Mining process patterns: {IDLE_NvGPU_PROCESSES}")
-        
         try:
             httpd.serve_forever()
         except KeyboardInterrupt:
             logging.info("Shutting down proxy server")
         except Exception as e:
             logging.error(f"Server error: {e}")
-
 if __name__ == "__main__":
-    main()
+    main()

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 mrmarcus007
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,5 +1,5 @@
 # GPU Resource Manager & Proxy for Ollama  
-*A smart GPU-aware proxy for Proxmox VE that dynamically manages GPU resources between Ollama and GPU-intensive background processes.*
+*A smart GPU-aware proxy designed for Proxmox VE that dynamically manages GPU resources between Ollama and GPU-intensive background processes.*
 
 ---
 
@@ -66,7 +66,7 @@ GPU_CHECK_INTERVAL = 10        # Seconds between GPU checks
 
 # GPU Process Management
 IDLE_NvGPU_PROCESSES = ['t-rex', 'trex', 'miner', 'xmrig', 'lolminer', 'nbminer']
-KNOWN_NvidiaGPU_PROCESSES = ['Xorg']  
+KNOWN_NvGPU_PROCESSES = ['Xorg']  
 IDLE_CONTAINER_ID = "120"      # LXC container ID of idle GPU workload
 Blackout_schedule_Start = 2, 15 #when to start stopping the idle NvGPU container. Hour, Minute.
 Blackout_schedule_End = 3, 30 #when to allow starting the idle NvGPU container again. Hour, Minute.