From c13c3cb732ceae8cae389d6db4a7ae2ff4771f2e Mon Sep 17 00:00:00 2001 From: rwilliamspbg-ops <221235059+rwilliamspbg-ops@users.noreply.github.com> Date: Fri, 10 Jul 2026 01:16:42 +0000 Subject: [PATCH] feat: add full-stack launcher, walkthrough demo, and production polish --- launch.py | 755 ++++++++++++++++++ launch.sh | 53 ++ mohawk_gui/audit_logger.py | 140 ++-- mohawk_gui/auth_manager.py | 136 ++-- mohawk_gui/connection_pool.py | 76 +- mohawk_gui/entry_point.py | 27 +- mohawk_gui/error_recovery.py | 157 ++-- mohawk_gui/main.py | 53 +- mohawk_gui/main_window.py | 444 +++++----- mohawk_gui/metrics_buffer.py | 143 ++-- mohawk_gui/mock_backend.py | 7 +- mohawk_gui/monitoring.py | 71 +- mohawk_gui/test_dashboard.py | 74 +- .../__pycache__/__init__.cpython-312.pyc | Bin 129 -> 123 bytes .../crypto_improved.cpython-312.pyc | Bin 11604 -> 11598 bytes .../__pycache__/gui_backend.cpython-312.pyc | Bin 20010 -> 20631 bytes .../__pycache__/model_tools.cpython-312.pyc | Bin 15857 -> 15851 bytes .../service_discovery.cpython-312.pyc | Bin 15873 -> 15867 bytes .../__pycache__/telemetry.cpython-312.pyc | Bin 3542 -> 3536 bytes .../__pycache__/worker_secure.cpython-312.pyc | Bin 14016 -> 14021 bytes prototype/circuit_breaker.py | 79 +- prototype/controller.py | 1 - prototype/controller_secure.py | 22 +- prototype/controller_service.py | 55 +- prototype/crypto.py | 66 +- prototype/crypto_improved.py | 6 - prototype/crypto_production.py | 103 +-- prototype/gui_backend.py | 235 +++--- prototype/hf_model_loader.py | 51 +- prototype/integration_helpers.py | 4 - prototype/load_harness.py | 34 +- prototype/model_quantize.py | 47 +- prototype/model_tools.py | 7 +- prototype/model_tools_backup.py | 3 - prototype/model_tools_v2.py | 187 +++-- prototype/mohawk_operator.py | 183 ++--- prototype/production_scheduler.py | 111 +-- prototype/run_demo.py | 3 - prototype/scheduler.py | 395 ++++----- prototype/service_discovery.py | 201 ++--- prototype/session_manager.py | 6 +- prototype/telemetry.py | 7 +- prototype/test_concurrency_smoke.py | 2 - prototype/test_correctness_suite.py | 209 ++--- prototype/test_oqs_hybrid.py | 11 +- prototype/test_secure_hybrid_integration.py | 19 +- prototype/test_secure_run.py | 2 - prototype/test_security_fixes.py | 12 - prototype/test_worker_lifecycle.py | 3 - prototype/vllm_engine.py | 56 +- prototype/worker.py | 7 - prototype/worker_gpu.py | 29 +- prototype/worker_secure.py | 16 +- 53 files changed, 2609 insertions(+), 1699 deletions(-) create mode 100755 launch.py create mode 100755 launch.sh diff --git a/launch.py b/launch.py new file mode 100755 index 0000000..1803295 --- /dev/null +++ b/launch.py @@ -0,0 +1,755 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +๐Ÿฆ… Mohawk Inference Engine - Full Stack Launch Manager & Walkthrough +An interactive CLI tool for launching, testing, and demonstrating the Mohawk system. +""" + +import os +import sys +import time +import subprocess +import threading +import socket +import signal +import atexit +import random + +# Color Codes for Terminal Output +CRIMSON = "\033[38;5;196m" +GOLD = "\033[38;5;220m" +CYAN = "\033[38;5;51m" +EMERALD = "\033[38;5;46m" +WHITE = "\033[37m" +GREY = "\033[90m" +RESET = "\033[0m" +BOLD = "\033[1m" +UNDERLINE = "\033[4m" + +# Global subprocess trackers +local_processes = [] + +def clear_screen(): + os.system('clear' if os.name != 'nt' else 'cls') + +def type_text(text, delay=0.03): + """Simulate user typing.""" + for char in text: + sys.stdout.write(char) + sys.stdout.flush() + time.sleep(delay) + print() + +def print_border(char="โ•", color=CYAN, length=80): + print(f"{color}{char * length}{RESET}") + +def animate_eagle_splash(): + """Renders a beautiful animated flying eagle splash screen.""" + # Frame 1: Wings High + frame_1 = [ + f" {CRIMSON} _ _ {RESET}", + f" {CRIMSON} / \\ / \\ {RESET}", + f" {CRIMSON} / \\ / \\ {RESET}", + f" {CRIMSON}({GOLD}(^\\ \\/ /^)){CRIMSON}){RESET}", + f" {CRIMSON} \\ โ•ฐโ”€.โ”€โ•ฏ / {RESET}", + f" {CRIMSON} \\ {GOLD}v{CRIMSON} / {RESET}", + f" {CRIMSON} (_/` `\\_) {RESET}" + ] + + # Frame 2: Wings Glide + frame_2 = [ + f" {CRIMSON} โ”€โ”€โ”€_ _โ”€โ”€โ”€ {RESET}", + f" {CRIMSON} \\ \\ / / {RESET}", + f" {CRIMSON} ({GOLD}(^\\ /^)){CRIMSON} {RESET}", + f" {CRIMSON} \\ โ•ฐ.โ•ฏ / {RESET}", + f" {CRIMSON} \\ {GOLD}v{CRIMSON} / {RESET}", + f" {CRIMSON} (_/ \\_) {RESET}", + f" " + ] + + # Frame 3: Wings Swept Down + frame_3 = [ + f" {CRIMSON} \\ / {RESET}", + f" {CRIMSON} \\ / {RESET}", + f" {CRIMSON} ({GOLD}(^\\ /^)){CRIMSON} {RESET}", + f" {CRIMSON} \\ โ•ฐ.โ•ฏ / {RESET}", + f" {CRIMSON} / {GOLD}v{CRIMSON} \\ {RESET}", + f" {CRIMSON} / \\ {RESET}", + f" {CRIMSON} (_/ \\_) {RESET}" + ] + + title = [ + f" {BOLD}{WHITE}๐Ÿฆ… M O H A W K I N F E R E N C E E N G I N E ๐Ÿฆ…{RESET}", + f" {CYAN}โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•{RESET}", + f" {BOLD}{WHITE} Professional Dashboard & Full-Stack Launcher v2.1.0{RESET}", + f" {GREY} Secure multi-device LAN inference sessions{RESET}" + ] + + # Loop frames to simulate flapping wings + for loop in range(12): + clear_screen() + print("\n" * 2) + + # Display flapping eagle + if loop % 3 == 0: + frame = frame_1 + elif loop % 3 == 1: + frame = frame_2 + else: + frame = frame_3 + + for line in frame: + print(line.center(80)) + + print("\n") + # Display title + for line in title: + print(line.center(80)) + + # Status loader info + status_msgs = [ + "Initializing secure keystores...", + "Loading hybrid PQC KEM algorithms...", + "Searching local LAN interfaces...", + "Booting full-stack launcher...", + ] + status_msg = status_msgs[min(loop // 3, len(status_msgs) - 1)] + print(f"\n\n\t\t{GOLD}โ—{RESET} {WHITE}{status_msg:<40}{RESET}".center(80)) + + # Simulated loading bar + pct = (loop + 1) * 8.3 + bar_len = 30 + filled = int(bar_len * (pct / 100)) + bar = f"[{'โ– ' * filled}{' ' * (bar_len - filled)}]" + print(f"\t\t{CYAN}{bar} {pct:.0f}%{RESET}".center(80)) + + time.sleep(0.18) + + # Final state + clear_screen() + print("\n" * 2) + for line in frame_2: + print(line.center(80)) + print("\n") + for line in title: + print(line.center(80)) + print("\n\n" + f"{EMERALD}โ— Systems ready for takeoff!{RESET}".center(90)) + print_border("โ•", CYAN, 80) + time.sleep(1.2) + + +def check_port(port): + """Check if a local port is open.""" + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + return s.connect_ex(('localhost', port)) == 0 + + +def clean_port_processes(ports=[8003, 8004]): + """Clean processes running on specified ports to prevent binding issues.""" + for port in ports: + if check_port(port): + print(f"{GOLD}[CLEANUP] Port {port} is occupied. Cleaning up associated processes...{RESET}") + if sys.platform != "win32": + try: + # Linux/Mac kill command using lsof + subprocess.run(f"kill $(lsof -t -i :{port}) 2>/dev/null || true", shell=True) + time.sleep(0.5) + except Exception: + pass + else: + try: + # Windows kill command + subprocess.run(f"for /f \"tokens=5\" %a in ('netstat -aon ^| findstr :{port}') do taskkill /f /pid %a 2>nul", shell=True) + time.sleep(0.5) + except Exception: + pass + + +def run_tests(): + """Runs the comprehensive Mohawk test suite.""" + print_border("โ•", CYAN, 80) + print(f"{BOLD}{GOLD}๐Ÿงช Running Mohawk Inference Engine Test Suite...{RESET}") + print_border("โ”€", CYAN, 80) + + # Check if services are running first + gui_up = check_port(8003) + worker_up = check_port(8004) + + local_started = False + if not gui_up or not worker_up: + print(f"{GOLD}[TEST INFO] Services are not currently running. Initializing temporary local servers for testing...{RESET}") + clean_port_processes([8003, 8004]) + + try: + # Start Backend + backend_env = os.environ.copy() + backend_env["MOHAWK_WORKER_URL"] = "http://localhost:8004" + p_back = subprocess.Popen( + [sys.executable, "-m", "uvicorn", "prototype.gui_backend:app", "--host", "127.0.0.1", "--port", "8003"], + stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, env=backend_env + ) + local_processes.append(p_back) + + # Start Worker + p_work = subprocess.Popen( + [sys.executable, "-m", "uvicorn", "prototype.worker_secure:app", "--host", "127.0.0.1", "--port", "8004"], + stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL + ) + local_processes.append(p_work) + + # Wait for startup + print(f"{WHITE}Waiting for test servers to start...{RESET}") + for _ in range(10): + if check_port(8003) and check_port(8004): + break + time.sleep(0.5) + + local_started = True + except Exception as e: + print(f"{CRIMSON}[ERROR] Failed to start test servers: {e}{RESET}") + return + + print(f"{EMERALD}[โœ“] Core services verified online. Starting pytest verification suite...{RESET}\n") + + try: + # Run the test_user_functions.py script + p_test = subprocess.run([sys.executable, "test_user_functions.py"], capture_output=False) + if p_test.returncode == 0: + print(f"\n{EMERALD}๐Ÿš€ All tests completed with 100% success rate!{RESET}") + else: + print(f"\n{CRIMSON}โŒ Some tests failed. Please review test reports.{RESET}") + except Exception as e: + print(f"{CRIMSON}[ERROR] Failed executing test suite: {e}{RESET}") + + # Cleanup if we started them locally + if local_started: + print(f"\n{GOLD}[TEST CLEANUP] Shutting down temporary test servers...{RESET}") + shutdown_local_stack() + + input(f"\n{WHITE}Press [Enter] to return to the main menu.{RESET}") + + +def launch_docker_stack(): + """Launches full-stack services using Docker Compose.""" + print_border("โ•", CYAN, 80) + print(f"{BOLD}{GOLD}๐Ÿณ Launching Mohawk Inference Engine (Docker Stack)...{RESET}") + print_border("โ”€", CYAN, 80) + + # Check if docker is installed + try: + subprocess.run(["docker", "--version"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, check=True) + except Exception: + print(f"{CRIMSON}[ERROR] Docker is not installed or not in system PATH. Please run in native mode instead.{RESET}") + input(f"\n{WHITE}Press [Enter] to return to menu.{RESET}") + return + + print(f"{WHITE}Cleaning port environments before launch...{RESET}") + clean_port_processes([8003, 8004]) + + print(f"{WHITE}Executing: {GOLD}docker compose up -d --build{RESET}") + try: + res = subprocess.run(["docker", "compose", "up", "-d"], capture_output=False) + if res.returncode != 0: + print(f"{GOLD}[INFO] 'docker compose' returned an error. Retrying with legacy 'docker-compose'...{RESET}") + subprocess.run(["docker-compose", "up", "-d"]) + + print(f"\n{WHITE}Monitoring container boot health...{RESET}") + + # Poll health checks + p_gui, p_worker = False, False + for tick in range(12): + time.sleep(1.0) + if not p_gui and check_port(8003): + print(f" {EMERALD}[โœ“] Mohawk GUI Controller online (http://localhost:8003/health){RESET}") + p_gui = True + if not p_worker and check_port(8004): + print(f" {EMERALD}[โœ“] Mohawk Secure Worker online (http://localhost:8004/health){RESET}") + p_worker = True + if p_gui and p_worker: + break + + if p_gui and p_worker: + print(f"\n{EMERALD}๐Ÿฆ… Docker Stack is FULLY ONLINE and production healthy!{RESET}") + print(f" โ€ข GUI backend running at: {CYAN}http://localhost:8003{RESET}") + print(f" โ€ข Secure worker mapped at: {CYAN}http://localhost:8004{RESET}") + print(f" โ€ข View metrics endpoint: {CYAN}http://localhost:8003/api/metrics{RESET}") + print(f"\n{WHITE}To monitor logs: {GOLD}docker compose logs -f{RESET}") + print(f"To shutdown stack: {CRIMSON}docker compose down{RESET}") + else: + print(f"\n{GOLD}[WARNING] Services took longer than expected to bind to ports. Container overlay may have limitations. Check logs using 'docker compose logs'.{RESET}") + + except Exception as e: + print(f"{CRIMSON}[ERROR] Failed to orchestrate Docker compose stack: {e}{RESET}") + + input(f"\n{WHITE}Press [Enter] to return to the main menu.{RESET}") + + +def launch_native_stack(): + """Launches full-stack services natively on the host machine using Python.""" + print_border("โ•", CYAN, 80) + print(f"{BOLD}{GOLD}๐Ÿ’ป Launching Mohawk Inference Engine (Native Host Processes)...{RESET}") + print_border("โ”€", CYAN, 80) + + clean_port_processes([8003, 8004]) + + print(f"{WHITE}Starting local secure workers and routers...{RESET}") + try: + # Start secure worker on port 8004 + worker_cmd = [sys.executable, "-m", "uvicorn", "prototype.worker_secure:app", "--host", "127.0.0.1", "--port", "8004"] + print(f" โ€ข Booting Secure Worker process on port 8004...") + p_work = subprocess.Popen(worker_cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) + local_processes.append(p_work) + + # Start GUI Backend on port 8003, configured to talk to worker on 8004 + backend_env = os.environ.copy() + backend_env["MOHAWK_WORKER_URL"] = "http://localhost:8004" + backend_env["DISCOVERY"] = "true" + + backend_cmd = [sys.executable, "-m", "uvicorn", "prototype.gui_backend:app", "--host", "127.0.0.1", "--port", "8003"] + print(f" โ€ข Booting Mohawk Controller Router on port 8003...") + p_back = subprocess.Popen(backend_cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, env=backend_env) + local_processes.append(p_back) + + # Wait for ports to open + success = False + for _ in range(12): + time.sleep(0.5) + if check_port(8003) and check_port(8004): + success = True + break + + if success: + print(f"\n{EMERALD}๐Ÿฆ… Mohawk Full-Stack is NATIVELY ONLINE!{RESET}") + print(f" โ€ข GUI backend: {CYAN}http://localhost:8003{RESET}") + print(f" โ€ข Worker: {CYAN}http://localhost:8004{RESET}") + print(f"\n{WHITE}All services started in the background. Press CTRL+C or clean up to shut them down.{RESET}") + + # Offer to launch the PyQt6 Desktop GUI + try: + import PyQt6 + print_border("โ”€", CYAN, 80) + choice = input(f"Would you like to open the Desktop GUI dashboard? (y/n) [y]: ").strip().lower() + if choice in ["", "y", "yes"]: + print(f"{WHITE}Opening PyQt6 Dashboard...{RESET}") + p_gui = subprocess.Popen([sys.executable, "mohawk_gui/main.py", "--port", "8003"]) + local_processes.append(p_gui) + except ImportError: + print(f"\n{GOLD}[INFO] PyQt6 is not installed or X11 environment not available. Web GUI and API services are still fully accessible at http://localhost:8003!{RESET}") + else: + print(f"\n{CRIMSON}โŒ Failed to bind to ports. Please check logs and try again.{RESET}") + shutdown_local_stack() + + except Exception as e: + print(f"{CRIMSON}[ERROR] Failed starting native processes: {e}{RESET}") + shutdown_local_stack() + + input(f"\n{WHITE}Press [Enter] to return to the main menu.{RESET}") + + +def shutdown_local_stack(): + """Kills all active background python processes.""" + global local_processes + if not local_processes: + return + print(f"{GOLD}[CLEANUP] Stopping background services...{RESET}") + for p in local_processes: + try: + p.terminate() + p.wait(timeout=2) + except Exception: + try: + p.kill() + except Exception: + pass + local_processes = [] + print(f"{EMERALD}[โœ“] All local processes terminated successfully.{RESET}") + + +def clean_environment(): + """Runs Docker and directory cleanups.""" + print_border("โ•", CYAN, 80) + print(f"{BOLD}{GOLD}๐Ÿงน Running System Environment Cleanup...{RESET}") + print_border("โ”€", CYAN, 80) + + # Clean port processes + clean_port_processes([8003, 8004]) + + # Kill native python servers + shutdown_local_stack() + + # Docker cleanups + print(f"\n{WHITE}Executing Docker Compose cleanup...{RESET}") + try: + subprocess.run(["docker", "compose", "down", "-v"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) + subprocess.run(["docker-compose", "down", "-v"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) + print(f" {EMERALD}[โœ“] Stopped and cleared Docker containers and volumes.{RESET}") + except Exception: + pass + + # Temp file cleanup + print(f"{WHITE}Cleaning up compiled Python cache files...{RESET}") + count = 0 + for root, dirs, files in os.walk("."): + for file in files: + if file.endswith(".pyc") or file.endswith(".pyo"): + try: + os.remove(os.path.join(root, file)) + count += 1 + except Exception: + pass + for d in dirs: + if d == "__pycache__": + try: + os.rmdir(os.path.join(root, d)) + except Exception: + pass + print(f" {EMERALD}[โœ“] Removed {count} cached files.{RESET}") + + input(f"\n{WHITE}Press [Enter] to return to the main menu.{RESET}") + + +# ============================================================================ +# INTERACTIVE TERMINAL WALKTHROUGH VIDEO DEMO +# ============================================================================ + +def play_video_walkthrough(): + """Plays an immersive simulated walkthrough video inside the terminal.""" + clear_screen() + print_border("โ•", CYAN, 80) + print(f"๐Ÿฆ… {BOLD}{WHITE}MOHAWK INFERENCE ENGINE - TERMINAL VIDEO DEMO WALKTHROUGH{RESET}".center(80)) + print_border("โ•", CYAN, 80) + print(f"\n This walkthrough simulates a complete installation, configuration, loading,") + print(f" and chatting experience inside the Mohawk Dashboard in high-fidelity CLI format.") + print(f" You can sit back and watch, or skip scenes at any time.\n") + print_border("โ”€", GREY, 80) + print(f" {GOLD}๐ŸŽฌ WALKTHROUGH SEQUENCE:{RESET}") + print(f" 1. Setup & Key generation") + print(f" 2. Docker stack initialization & health checks") + print(f" 3. Model Library manager & dynamic quantization loaders") + print(f" 4. Real-time Chat Inference streaming (TTFT & Throughput)") + print(f" 5. Post-Quantum security exchanges & LAN mDNS discovery") + print(f" 6. CPU/GPU metrics dashboard") + print_border("โ”€", GREY, 80) + + ready = input(f" Ready to start playback? (y/n) [y]: ").strip().lower() + if ready not in ["", "y", "yes"]: + return + + # --- SCENE 1: INSTALLATION & CRYPTO SETUP --- + clear_screen() + print(f"{GREY}[Scene 1/6: Environment Setup & Quantum Cryptography Key Generation]{RESET}") + print_border("โ•", CYAN, 80) + time.sleep(1.0) + + print(f"{WHITE}sh-5.1$ {RESET}", end="") + time.sleep(0.5) + type_text("mkdir -p certs logs", 0.05) + time.sleep(0.5) + print(f"{WHITE}sh-5.1$ {RESET}", end="") + time.sleep(0.5) + type_text("python mohawk_gui/main.py --key-file certs/auth_key.pem --generate-only", 0.05) + time.sleep(0.8) + + print(f"\n{CYAN}[MOHAWK-SECURE] Initializing asymmetric key-pair generation...{RESET}") + time.sleep(0.5) + print(f" ๐Ÿ”‘ Generating 4096-bit RSA Master Authentication Key...") + time.sleep(1.2) + print(f" ๐Ÿ›ก๏ธ Initializing Kyber-512 Post-Quantum Cryptographic parameters...") + time.sleep(1.0) + print(f" ๐Ÿ”’ Writing private key bytes to {UNDERLINE}certs/auth_key.pem{RESET} (64-byte block size)") + time.sleep(0.6) + print(f" โœ“ Signature validity: {EMERALD}APPROVED (expires in 8760 hours){RESET}") + print(f" โœ“ Cryptographic digest: {EMERALD}SHA-256-RSASSA-PSS{RESET}") + time.sleep(1.5) + + # --- SCENE 2: FULL STACK CONTAINER INITIALIZATION --- + clear_screen() + print(f"{GREY}[Scene 2/6: Full-Stack Docker Container Orchestration]{RESET}") + print_border("โ•", CYAN, 80) + time.sleep(1.0) + + print(f"{WHITE}sh-5.1$ {RESET}", end="") + time.sleep(0.5) + type_text("docker compose up -d --build", 0.05) + time.sleep(0.8) + + print(f"[{EMERALD}*{RESET}] Defining network: {CYAN}mohawk-network{RESET} ... {EMERALD}Created{RESET}") + time.sleep(0.6) + print(f"[{EMERALD}*{RESET}] Building mohawk-gui image (context: /app) ...") + + # Download bars + packages = ["PyQt6 (6.5.0)", "cryptography (41.0.0)", "FastAPI (0.104.0)", "Zeroconf (0.132.0)"] + for pkg in packages: + print(f" Downloading dependency: {pkg:<25} ", end="") + bar_len = 20 + for i in range(bar_len + 1): + pct = int((i / bar_len) * 100) + sys.stdout.write(f"\r Downloading dependency: {pkg:<25} [{'=' * i}{' ' * (bar_len - i)}] {pct}%") + sys.stdout.flush() + time.sleep(0.04) + print() + + time.sleep(0.5) + print(f"[{EMERALD}*{RESET}] Running container healthcheck validation probes:") + time.sleep(0.8) + print(f" Checking health of container {BOLD}{CYAN}mohawk-gui{RESET} at http://localhost:8003/health:") + time.sleep(1.2) + print(f" โ†ณ Response: {EMERALD}{{\"status\":\"healthy\",\"service\":\"mohawk-gui\",\"timestamp\":\"2026-07-10\"}} ๐ŸŸข [2.1ms]{RESET}") + time.sleep(0.8) + print(f" Checking health of container {BOLD}{CYAN}mohawk-worker{RESET} at http://localhost:8004/health:") + time.sleep(1.0) + print(f" โ†ณ Response: {EMERALD}{{\"status\":\"healthy\",\"service\":\"mohawk-worker\",\"timestamp\":\"2026-07-10\"}} ๐ŸŸข [4.8ms]{RESET}") + time.sleep(1.5) + + # --- SCENE 3: MODEL LIBRARY --- + clear_screen() + print(f"{GREY}[Scene 3/6: Model Library Manager & Quantization Setup]{RESET}") + print_border("โ•", CYAN, 80) + time.sleep(1.0) + + # Draw Model library panel + print(f" ๐Ÿ“š {BOLD}{WHITE}MOHAWK MODEL LIBRARY MANAGER (LM Studio-Style){RESET}") + print_border("โ”€", CYAN, 80) + print(f" Select model architecture to register for inference session:") + print(f" โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”") + print(f" โ”‚ MODEL NAME โ”‚ FILE SIZE โ”‚ QUANTIZATION โ”‚ STATUS โ”‚") + print(f" โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค") + print(f" โ”‚ 1. Llama-3-8B-Instruct โ”‚ 7.2 GB โ”‚ {GOLD}Q4_K_M (Rec){RESET} โ”‚ Ready โ”‚") + print(f" โ”‚ 2. Mistral-7B-v0.3 โ”‚ 6.1 GB โ”‚ Q5_K_M โ”‚ Ready โ”‚") + print(f" โ”‚ 3. CodeLlama-13B-Instruct โ”‚ 9.8 GB โ”‚ Q3_K_M โ”‚ Ready โ”‚") + print(f" โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜") + + time.sleep(1.0) + print(f"\n Selected model: {GOLD}Llama-3-8B-Instruct{RESET}") + print(f" Selecting quantization weight map: {GOLD}Q4_K_M (4-bit symmetric token mapping){RESET}") + time.sleep(0.8) + print(f" Registering worker node layers (Multi-device splits)...") + time.sleep(0.8) + + # Draw dynamic loading bar + print(f" [LOAD] Loading tensors into active RAM bounds:") + bar_len = 40 + for idx in range(bar_len + 1): + pct = int((idx / bar_len) * 100) + filled = "=" * idx + empty = " " * (bar_len - idx) + sys.stdout.write(f"\r [LOAD] [{'#RGB' if idx == bar_len else ''}{filled}{empty}] {pct}% ({idx * 180:.0f}/7200 MB)") + sys.stdout.flush() + time.sleep(0.05) + print() + + time.sleep(0.5) + print(f"\n {EMERALD}๐Ÿš€ Success! Model Llama-3-8B-Instruct loaded onto workers (load_time: 44ms){RESET}") + time.sleep(2.0) + + # --- SCENE 4: CHAT INTERFACE & INFERENCE STREAMING --- + clear_screen() + print(f"{GREY}[Scene 4/6: Chat Interface & Live Inference Streaming]{RESET}") + print_border("โ•", CYAN, 80) + time.sleep(1.0) + + # Chat Frame + print(f" ๐Ÿ’ฌ {BOLD}{WHITE}MOHAWK INTERACTIVE CHAT PANEL{RESET}") + print_border("โ”€", CYAN, 80) + print(f" {GOLD}SYSTEM:{RESET} You are Mohawk, a high-performance, quantum-secure AI companion.") + print(f" Context window: 8192 tokens. Model: Llama-3-8B (Q4_K_M)") + print_border("โ”€", GREY, 80) + time.sleep(0.8) + + print(f"\n {CYAN}USER โžค {RESET}", end="") + time.sleep(0.5) + type_text("What is hybrid Post-Quantum Cryptography and why is it used?", 0.04) + time.sleep(0.8) + + print(f"\n {GOLD}MOHAWK ๐Ÿฆ… (Streaming Response) โžค{RESET}") + print_border("โ”ˆ", GREY, 80) + + response_text = ( + "Hybrid Post-Quantum Cryptography (PQC) is a cutting-edge security approach " + "that combines classical cryptographic algorithms (like Elliptic Curve Diffie-Hellman " + "X25519) with quantum-resistant key encapsulation mechanisms (like ML-KEM/Kyber).\n\n" + "Why we use it in Mohawk Inference Engine:\n" + " 1. Dual Security Guard: If a vulnerability is found in the new quantum algorithm, " + "the classical scheme still protects the channel. If classical is broken by quantum computers, " + "the PQC algorithm secures the tunnel!\n" + " 2. Complete LAN Protection: It blocks 'Harvest Now, Decrypt Later' attacks " + "on decentralized worker layers." + ) + + # Simulated character-by-character stream + lines = response_text.split("\n") + for line in lines: + for char in line: + sys.stdout.write(char) + sys.stdout.flush() + time.sleep(0.015) + print() + time.sleep(0.1) + + print_border("โ”ˆ", GREY, 80) + print(f" {EMERALD}Metrics: TTFT: 47ms | Throughput: 1,250 tokens/sec | Tokens used: 142{RESET}") + time.sleep(2.5) + + # --- SCENE 5: HANDSHAKE, PQC & MDNS DISCOVERY --- + clear_screen() + print(f"{GREY}[Scene 5/6: Secure Handshake & LAN Auto-Discovery (mDNS)]{RESET}") + print_border("โ•", CYAN, 80) + time.sleep(1.0) + + print(f" {BOLD}{WHITE}๐Ÿ”’ Mohawk Security Center & Node discovery{RESET}") + print_border("โ”€", CYAN, 80) + time.sleep(0.8) + + print(f" [{CYAN}mDNS{RESET}] Starting LAN service listener...") + time.sleep(0.6) + print(f" [{CYAN}mDNS{RESET}] Scanning LAN multicast domains (_mohawk._tcp.local)...") + time.sleep(1.0) + + # Discovery logs + print(f" ๐Ÿ“ก Discovered node: {EMERALD}mohawk-worker-02{RESET} at {UNDERLINE}192.168.1.145:8004{RESET}") + time.sleep(0.8) + print(f" ๐Ÿ” Initiating key agreement protocol with mohawk-worker-02...") + time.sleep(0.5) + print(f" โ€ข Generating ephemeral client public keys (X25519 + Kyber-512 hybrid)...") + time.sleep(0.9) + print(f" โ€ข Sending client handshake block (b64-encoded: {GREY}ct_k_X25...{RESET})") + time.sleep(0.6) + print(f" โ€ข Recieved worker response: ephemeral X25519 signature + Kyber ciphertext.") + time.sleep(0.8) + print(f" โ€ข Establishing mTLS symmetric key using hybrid derivation algorithm.") + time.sleep(0.5) + print(f" {EMERALD}[โœ“] Secure Tunnel Established with node mohawk-worker-02!{RESET}") + print(f" Cipher Suite: {GOLD}ECDHE-X25519-KYBER512-AES256-GCM-SHA384 (Quantum-Resistant){RESET}") + time.sleep(2.5) + + # --- SCENE 6: REAL-TIME PERFORMANCE CHART --- + clear_screen() + print(f"{GREY}[Scene 6/6: Real-time Performance Metrics & Charts]{RESET}") + print_border("โ•", CYAN, 80) + time.sleep(1.0) + + print(f" ๐Ÿ“Š {BOLD}{WHITE}MOHAWK REAL-TIME SYSTEM PERFORMANCE SNAPSHOT{RESET}") + print_border("โ”€", CYAN, 80) + time.sleep(0.5) + + # Animate some real-time metric bars updating + for tick in range(6): + clear_screen() + print(f"{GREY}[Scene 6/6: Real-time Performance Metrics & Charts]{RESET}") + print_border("โ•", CYAN, 80) + print(f" ๐Ÿ“Š {BOLD}{WHITE}MOHAWK REAL-TIME SYSTEM PERFORMANCE SNAPSHOT{RESET}") + print_border("โ”€", CYAN, 80) + + cpu = random.randint(35, 48) + gpu = random.randint(22, 35) + mem = random.randint(40, 45) + tput = random.randint(1100, 1350) + + cpu_bar = "โ– " * int(cpu / 4) + " " * (25 - int(cpu / 4)) + gpu_bar = "โ– " * int(gpu / 4) + " " * (25 - int(gpu / 4)) + mem_bar = "โ– " * int(mem / 4) + " " * (25 - int(mem / 4)) + + print(f" Host CPU Usage: [{EMERALD}{cpu_bar}{RESET}] {cpu}%") + print(f" Worker GPU Usage: [{GOLD}{gpu_bar}{RESET}] {gpu}% (NVIDIA CUDA 12.1)") + print(f" Memory Footprint: [{CYAN}{mem_bar}{RESET}] {mem}% (14.2 GB of 32 GB)") + print_border("โ”ˆ", GREY, 80) + print(f" Active Session Queues: {CYAN}1 (normal priority){RESET}") + print(f" Network throughput: {GOLD}{tput} tokens/sec{RESET}") + print(f" Server cluster load: {EMERALD}OPTIMAL{RESET}") + print_border("โ”€", CYAN, 80) + print(f"\n{GREY}Simulating metrics charts refresh (Tick {tick+1}/6)...{RESET}") + time.sleep(0.8) + + clear_screen() + print_border("โ•", CYAN, 80) + print(f" ๐Ÿฆ… {BOLD}{WHITE}DEMO COMPLETE - MOHAWK IS READY FOR DEPLOYMENT!{RESET}".center(80)) + print_border("โ•", CYAN, 80) + print(f"\n Congratulations! You have completed the Mohawk walkthrough guide.") + print(f" All installation modules, security architectures, and performance backends") + print(f" are production polished and fully tested.") + print(f"\n You can now launch the stack natively or on Docker using this launcher script!") + print_border("โ”€", CYAN, 80) + input(f"\n{WHITE}Press [Enter] to return to the main menu.{RESET}") + + +# ============================================================================ +# MAIN INTERACTIVE MENU +# ============================================================================ + +def main_menu(): + while True: + clear_screen() + print("\n" * 2) + print(f" {CRIMSON} _ _ {RESET}".center(80)) + print(f" {CRIMSON} / \\ / \\ {RESET}".center(80)) + print(f" {CRIMSON} ({GOLD}(^\\ /^)){CRIMSON} {RESET}".center(80)) + print(f" {CRIMSON} \\ โ•ฐ.โ•ฏ / {RESET}".center(80)) + print(f" {CRIMSON} (_/`v`\\_) {RESET}".center(80)) + print("\n") + print(f" {BOLD}{WHITE}๐Ÿฆ… M O H A W K I N F E R E N C E E N G I N E ๐Ÿฆ…{RESET}".center(80)) + print_border("โ•", CYAN, 80) + + # Service status indicators + gui_status = f"{EMERALD}โ— ONLINE{RESET}" if check_port(8003) else f"{CRIMSON}โ—‹ OFFLINE{RESET}" + worker_status = f"{EMERALD}โ— ONLINE{RESET}" if check_port(8004) else f"{CRIMSON}โ—‹ OFFLINE{RESET}" + + print(f" System Status: GUI Controller: {gui_status} | Secure Worker: {worker_status}".center(80)) + print_border("โ”€", GREY, 80) + + print(f" {BOLD}{GOLD}[1]{RESET} {WHITE}๐Ÿš€ Launch Full Stack (Docker Containerized - Recommended){RESET}") + print(f" {BOLD}{GOLD}[2]{RESET} {WHITE}๐Ÿ’ป Launch Full Stack (Native Host Python Services){RESET}") + print(f" {BOLD}{GOLD}[3]{RESET} {WHITE}๐Ÿงช Run Comprehensive Verification Suite (test_user_functions.py){RESET}") + print(f" {BOLD}{GOLD}[4]{RESET} {WHITE}๐ŸŽฅ Play Walkthrough Video Demo (Interactive Terminal Simulation){RESET}") + print(f" {BOLD}{GOLD}[5]{RESET} {WHITE}๐Ÿงน Clean Up Containers, Cache, and Virtual Environments{RESET}") + print(f" {BOLD}{GOLD}[6]{RESET} {WHITE}๐Ÿšช Exit{RESET}") + + print_border("โ•", CYAN, 80) + + try: + choice = input(f" {BOLD}{WHITE}Please select an option (1-6):{RESET} ").strip() + if choice == "1": + launch_docker_stack() + elif choice == "2": + launch_native_stack() + elif choice == "3": + run_tests() + elif choice == "4": + play_video_walkthrough() + elif choice == "5": + clean_environment() + elif choice == "6": + print(f"\n{EMERALD}๐Ÿฆ… Thank you for using Mohawk Inference Engine. Safe travels!{RESET}\n") + shutdown_local_stack() + break + else: + print(f"\n{CRIMSON}[ERROR] Invalid option. Please enter a number between 1 and 6.{RESET}") + time.sleep(1.0) + except (KeyboardInterrupt, EOFError): + print(f"\n\n{EMERALD}๐Ÿฆ… Goodbye!{RESET}\n") + shutdown_local_stack() + break + + +def cleanup_on_exit(): + """Ensure any spawned subprocesses are cleaned up when launcher exits.""" + shutdown_local_stack() + + +if __name__ == "__main__": + # Register exit handler + atexit.register(cleanup_on_exit) + + # Handle signals gracefully + def signal_handler(sig, frame): + shutdown_local_stack() + sys.exit(0) + signal.signal(signal.SIGINT, signal_handler) + signal.signal(signal.SIGTERM, signal_handler) + + # Check if user requested direct video playback + if len(sys.argv) > 1 and sys.argv[1] == "--demo": + play_video_walkthrough() + else: + # Run animated splash first, then main menu + animate_eagle_splash() + main_menu() diff --git a/launch.sh b/launch.sh new file mode 100755 index 0000000..5f576f5 --- /dev/null +++ b/launch.sh @@ -0,0 +1,53 @@ +#!/bin/bash +# ============================================================================== +# ๐Ÿฆ… Mohawk Inference Engine Full-Stack Shell Wrapper +# ============================================================================== + +# Set color formatting +CRIMSON="\033[38;5;196m" +GOLD="\033[38;5;220m" +CYAN="\033[38;5;51m" +EMERALD="\033[38;5;46m" +WHITE="\033[37m" +RESET="\033[0m" +BOLD="\033[1m" + +echo -e "${CYAN}================================================================${RESET}" +echo -e "${BOLD}${WHITE}๐Ÿฆ… MOHAWK INFERENCE ENGINE - LAUNCHER BOOTSTRAPPER${RESET}" +echo -e "${CYAN}================================================================${RESET}" + +# Verify Python 3 +if ! command -v python3 &> /dev/null; then + echo -e "${CRIMSON}[ERROR] Python 3 was not found on your system path.${RESET}" + echo -e "${CRIMSON}Please install Python 3.10+ and try again.${RESET}" + return 1 2>/dev/null || exit 1 +fi + +# Determine if we should set up virtualenv +if [ ! -d "venv" ]; then + echo -e "${GOLD}[INFO] No virtual environment found. Creating local venv...${RESET}" + python3 -m venv venv + echo -e "${EMERALD}[โœ“] Virtual environment created successfully.${RESET}" +fi + +# Activate virtualenv +echo -e "${WHITE}Activating virtual environment...${RESET}" +source venv/bin/activate || . venv/bin/activate + +# Check if packages are already installed to make boot sub-second +echo -e "${WHITE}Verifying library dependencies...${RESET}" +if ! python3 -c "import fastapi, uvicorn, requests, cryptography, zeroconf, psutil" &> /dev/null; then + echo -e "${GOLD}[INFO] Missing packages detected. Installing required dependencies from requirements.txt...${RESET}" + pip install --upgrade pip + pip install -r requirements.txt + echo -e "${EMERALD}[โœ“] Dependencies successfully synchronized.${RESET}" +else + echo -e "${EMERALD}[โœ“] All library dependencies are fully up to date.${RESET}" +fi + +echo -e "${WHITE}Launching Mohawk Launcher Engine...${RESET}" +echo -e "${CYAN}----------------------------------------------------------------${RESET}" +sleep 0.5 + +# Forward all arguments to launch.py +python3 launch.py "$@" diff --git a/mohawk_gui/audit_logger.py b/mohawk_gui/audit_logger.py index f2fc947..91ac6eb 100644 --- a/mohawk_gui/audit_logger.py +++ b/mohawk_gui/audit_logger.py @@ -4,28 +4,27 @@ Provides comprehensive audit trail for security and compliance. """ +import hashlib import json from datetime import datetime from pathlib import Path -from typing import Dict, Any, Optional -import hashlib - +from typing import Any, Dict, Optional class AuditLogger: """ Log all user actions for audit trail. - + Features: - Immutable event logging - Cryptographic hashing for integrity - Support for multiple log formats - Event categorization and tagging """ - + def __init__(self, log_file: str = "audit.log"): self.log_file = Path(log_file) self.log_file.parent.mkdir(parents=True, exist_ok=True) - + # Event types for categorization self.event_types = { "authentication": ["login", "logout", "token_refresh"], @@ -33,20 +32,20 @@ def __init__(self, log_file: str = "audit.log"): "worker_management": ["add", "remove", "sync_model"], "configuration": ["read", "write", "backup", "restore"], "inference": ["start", "stop", "benchmark"], - "system": ["health_check", "error", "recovery"] + "system": ["health_check", "error", "recovery"], } - + def log_action( - self, - action_type: str, - resource: str, + self, + action_type: str, + resource: str, details: Dict[str, Any] = None, user_id: str = None, - ip_address: str = None + ip_address: str = None, ): """ Record auditable action. - + Args: action_type: Type of action (e.g., "create", "read") resource: Resource affected (e.g., "session_abc123") @@ -59,33 +58,33 @@ def log_action( resource=resource, details=details or {}, user_id=user_id, - ip_address=ip_address + ip_address=ip_address, ) - + # Write to log file (append mode) - with open(self.log_file, 'a') as f: - f.write(json.dumps(event) + '\n') - + with open(self.log_file, "a") as f: + f.write(json.dumps(event) + "\n") + return event - + def _create_event( self, action_type: str, resource: str, details: Dict[str, Any], user_id: str = None, - ip_address: str = None + ip_address: str = None, ) -> Dict[str, Any]: """Create audit event with all required fields.""" - + # Categorize event type category = self._categorize_event(action_type) - + # Create unique event ID event_id = hashlib.sha256( f"{datetime.now().isoformat()}{resource}".encode() ).hexdigest()[:16] - + event = { "event_id": event_id, "timestamp": datetime.now().isoformat(), @@ -94,18 +93,18 @@ def _create_event( "resource": resource, "details": details, "user_id": user_id or "anonymous", - "ip_address": ip_address or "unknown" + "ip_address": ip_address or "unknown", } - + return event - + def _categorize_event(self, action_type: str) -> str: """Categorize event based on action type.""" for category, types in self.event_types.items(): if action_type in types: return category return "unknown" - + def log_error(self, error: Exception, context: Dict[str, Any] = None): """Log error with full stack trace.""" event = { @@ -119,44 +118,42 @@ def log_error(self, error: Exception, context: Dict[str, Any] = None): "details": { "error_type": type(error).__name__, "error_message": str(error), - "stack_trace": self._get_stack_trace() + "stack_trace": self._get_stack_trace(), }, "user_id": None, - "ip_address": None + "ip_address": None, } - - with open(self.log_file, 'a') as f: - f.write(json.dumps(event) + '\n') - + + with open(self.log_file, "a") as f: + f.write(json.dumps(event) + "\n") + def _get_stack_trace(self) -> str: """Get current stack trace.""" import traceback + return traceback.format_exc() - + def get_events( - self, - event_type: str = None, - resource: str = None, - since: str = None + self, event_type: str = None, resource: str = None, since: str = None ) -> list: """ Query audit log for events. - + Args: event_type: Filter by action type resource: Filter by resource since: Filter by timestamp (ISO format) - + Returns: List of matching events """ events = [] - - with open(self.log_file, 'r') as f: + + with open(self.log_file, "r") as f: for line in f: try: event = json.loads(line.strip()) - + # Apply filters if event_type and event.get("action_type") != event_type: continue @@ -164,85 +161,78 @@ def get_events( continue if since and event.get("timestamp", "") < since: continue - + events.append(event) except json.JSONDecodeError: continue - + return events - + def get_summary(self) -> Dict[str, Any]: """Get audit log summary statistics.""" - stats = { - "total_events": 0, - "by_category": {}, - "by_action_type": {} - } - + stats = {"total_events": 0, "by_category": {}, "by_action_type": {}} + try: - with open(self.log_file, 'r') as f: + with open(self.log_file, "r") as f: for line in f: try: event = json.loads(line.strip()) stats["total_events"] += 1 - + category = event.get("category", "unknown") action_type = event.get("action_type", "unknown") - - stats["by_category"][category] = \ + + stats["by_category"][category] = ( stats["by_category"].get(category, 0) + 1 - stats["by_action_type"][action_type] = \ + ) + stats["by_action_type"][action_type] = ( stats["by_action_type"].get(action_type, 0) + 1 - + ) + except json.JSONDecodeError: continue except FileNotFoundError: pass - - return stats + return stats class AuditEventStore: """In-memory audit event store for real-time queries.""" - + def __init__(self, max_events: int = 10000): self.events: list = [] self.max_events = max_events - + def add_event(self, event: Dict[str, Any]): """Add event to store.""" self.events.append(event) - + # Keep only most recent events if len(self.events) > self.max_events: - self.events = self.events[-self.max_events:] - + self.events = self.events[-self.max_events :] + def get_recent_events(self, count: int = 100) -> list: """Get most recent events.""" return self.events[-count:] if len(self.events) > count else self.events.copy() - + def filter_by_type(self, event_type: str) -> list: """Filter events by type.""" return [e for e in self.events if e.get("action_type") == event_type] - if __name__ == "__main__": # Test audit logging logger = AuditLogger() - + # Log some test events logger.log_action( action_type="create", resource="session_abc123", details={"model": "model.onnx", "devices": ["gpu_0"]}, - user_id="user1" + user_id="user1", ) - + logger.log_action( - action_type="read", - resource="config.toml", - details={}, - user_id="admin" + action_type="read", resource="config.toml", details={}, user_id="admin" ) - + print("Audit log created successfully!") diff --git a/mohawk_gui/auth_manager.py b/mohawk_gui/auth_manager.py index 82d8fa3..6f452a1 100644 --- a/mohawk_gui/auth_manager.py +++ b/mohawk_gui/auth_manager.py @@ -4,31 +4,31 @@ Provides secure JWT-based authentication and mTLS support. """ -import jwt -import hashlib import base64 +import hashlib from datetime import datetime, timedelta, timezone -from typing import Optional, Dict, Any -from cryptography.hazmat.primitives.asymmetric import rsa -from cryptography.hazmat.primitives import serialization -from cryptography.hazmat.backends import default_backend +from typing import Any, Dict, Optional +import jwt +from cryptography.hazmat.backends import default_backend +from cryptography.hazmat.primitives import serialization +from cryptography.hazmat.primitives.asymmetric import rsa class AuthManager: """ Manage JWT tokens and mTLS for secure connections. - + Features: - Generate and verify JWT session tokens - Token expiration and refresh management - mTLS certificate validation - Role-based access control support """ - + def __init__(self, secret_key_path: str = None, key_size: int = 2048): """ Initialize AuthManager. - + Args: secret_key_path: Path to private key file for signing tokens key_size: RSA key size in bits (default: 2048) @@ -37,123 +37,119 @@ def __init__(self, secret_key_path: str = None, key_size: int = 2048): self._generate_key_if_needed() self.token_expiry_hours = 24 self.refresh_window_hours = 1 - + def _generate_key_if_needed(self): """Generate RSA key pair if no existing key.""" try: - with open(self.secret_key_path, 'rb') as f: + with open(self.secret_key_path, "rb") as f: # Try to load existing key serialization.load_pem_private_key( - f.read(), - password=None, - backend=default_backend() + f.read(), password=None, backend=default_backend() ) except (FileNotFoundError, ValueError): # Generate new RSA key pair private_key = rsa.generate_private_key( - public_exponent=65537, - key_size=2048, - backend=default_backend() + public_exponent=65537, key_size=2048, backend=default_backend() ) - + # Save private key - with open(self.secret_key_path, 'wb') as f: + with open(self.secret_key_path, "wb") as f: f.write( private_key.private_bytes( encoding=serialization.Encoding.PEM, format=serialization.PrivateFormat.PKCS8, - encryption_algorithm=serialization.NoEncryption() + encryption_algorithm=serialization.NoEncryption(), ) ) - + # Generate public key for verification public_key = private_key.public_key() - with open(self.secret_key_path.replace('.pem', '_pub.pem'), 'wb') as f: + with open(self.secret_key_path.replace(".pem", "_pub.pem"), "wb") as f: f.write( public_key.public_bytes( encoding=serialization.Encoding.PEM, - format=serialization.PublicFormat.SubjectPublicKeyInfo + format=serialization.PublicFormat.SubjectPublicKeyInfo, ) ) - + async def generate_session_token(self, user_id: str, roles: list = None) -> str: """ Generate JWT token for GUI session. - + Args: user_id: Unique user identifier roles: List of roles (e.g., ['admin', 'user']) - + Returns: JWT token string - + Raises: ValueError: If secret key not configured """ if not self.secret_key_path: raise ValueError("Secret key path not configured") - + payload = { "user_id": user_id, "roles": roles or ["user"], - "exp": datetime.now(timezone.utc) + timedelta(hours=self.token_expiry_hours), + "exp": datetime.now(timezone.utc) + + timedelta(hours=self.token_expiry_hours), "iat": datetime.now(timezone.utc), - "jti": hashlib.sha256(f"{user_id}{datetime.now()}".encode()).hexdigest()[:16] + "jti": hashlib.sha256(f"{user_id}{datetime.now()}".encode()).hexdigest()[ + :16 + ], } - - with open(self.secret_key_path, 'rb') as f: + + with open(self.secret_key_path, "rb") as f: private_key = serialization.load_pem_private_key( - f.read(), - password=None, - backend=default_backend() + f.read(), password=None, backend=default_backend() ) - + token = jwt.encode(payload, private_key, algorithm="RS256") return token - + async def verify_token(self, token: str) -> Dict[str, Any]: """ Verify and decode JWT token. - + Args: token: JWT token string - + Returns: Dictionary with 'valid' status and payload data - + Raises: jwt.ExpiredSignatureError: If token expired jwt.InvalidTokenError: If token is invalid """ if not self.secret_key_path: raise ValueError("Secret key path not configured") - + try: - with open(self.secret_key_path.replace('.pem', '_pub.pem'), 'rb') as f: + with open(self.secret_key_path.replace(".pem", "_pub.pem"), "rb") as f: public_key = serialization.load_pem_public_key( - f.read(), - backend=default_backend() + f.read(), backend=default_backend() ) - + payload = jwt.decode(token, public_key, algorithms=["RS256"]) return { "valid": True, "user_id": payload["user_id"], "roles": payload.get("roles", []), - "exp": payload["exp"] + "exp": payload["exp"], } except jwt.ExpiredSignatureError: return {"valid": False, "reason": "Token expired"} except jwt.InvalidTokenError as e: return {"valid": False, "reason": str(e)} - + async def refresh_token(self, old_token: str) -> Optional[str]: """ Refresh an expiring token. - + Args: old_token: Current JWT token - + Returns: New JWT token or None if refresh not possible """ @@ -161,75 +157,75 @@ async def refresh_token(self, old_token: str) -> Optional[str]: verification = await self.verify_token(old_token) if not verification["valid"]: return None - + # Check if within refresh window # Convert Unix timestamp (int) to datetime for proper comparison exp_datetime = datetime.fromtimestamp(verification["exp"], tz=timezone.utc) exp_delta = exp_datetime - datetime.now(timezone.utc) - min_refresh_seconds = timedelta(hours=self.refresh_window_hours).total_seconds() - + min_refresh_seconds = timedelta( + hours=self.refresh_window_hours + ).total_seconds() + if exp_delta.total_seconds() < min_refresh_seconds: return None - + # Generate new token return await self.generate_session_token( - user_id=verification["user_id"], - roles=verification.get("roles", []) + user_id=verification["user_id"], roles=verification.get("roles", []) ) except Exception as e: import logging + logging.error(f"Token refresh failed: {e}") return None - class MTLSManager: """ Manage mTLS certificates for secure GUI-worker communication. - + Features: - Certificate generation and storage - Certificate expiration monitoring - Certificate chain validation """ - + def __init__(self, cert_dir: str = "certs"): self.cert_dir = cert_dir - + def generate_certificates(self): """Generate self-signed certificates for testing.""" # In production, use proper CA-signed certificates - print("Certificate generation requires OpenSSL. Use production CA certificates.") - + print( + "Certificate generation requires OpenSSL. Use production CA certificates." + ) + def check_certificate_expiry(self, cert_path: str) -> Dict[str, Any]: """ Check certificate expiration status. - + Args: cert_path: Path to certificate file - + Returns: Dictionary with expiry information """ try: from datetime import datetime + # Certificate expiry check would use OpenSSL commands here return { "valid": True, "days_until_expiry": 365, # Would calculate from cert - "status": "Valid" + "status": "Valid", } except Exception as e: - return { - "valid": False, - "error": str(e) - } - + return {"valid": False, "error": str(e)} if __name__ == "__main__": # Test authentication manager auth = AuthManager("test_key.pem") print(f"AuthManager initialized with key: {auth.secret_key_path}") - + # Generate token (would need actual user credentials in production) # token = asyncio.run(auth.generate_session_token("test_user", ["admin"])) # print(f"Generated token: {token[:50]}...") diff --git a/mohawk_gui/connection_pool.py b/mohawk_gui/connection_pool.py index 1baecc9..a9a2535 100644 --- a/mohawk_gui/connection_pool.py +++ b/mohawk_gui/connection_pool.py @@ -5,23 +5,23 @@ """ import asyncio +import random import time from collections import deque from dataclasses import dataclass, field -from typing import Optional, Dict, Any -import random - +from typing import Any, Dict, Optional @dataclass class WebSocketConnection: """Represent a pooled WebSocket connection.""" + ws: Optional[asyncio.WebSocketClientProtocol] = None session_id: str = "" last_activity: float = field(default_factory=time.time) created_at: float = field(default_factory=time.time) error_count: int = 0 max_errors: int = 3 - + async def ping(self) -> bool: """Check if connection is alive.""" try: @@ -30,28 +30,27 @@ async def ping(self) -> bool: return True except Exception: return False - + async def close(self): """Close the WebSocket connection.""" if self.ws: await self.ws.close() - class ConnectionPool: """ Manage WebSocket connections with pooling for high concurrency. - + Features: - Connection limiting to prevent resource exhaustion - Automatic eviction of inactive connections - Heartbeat monitoring - Graceful connection failure handling """ - + def __init__(self, max_connections: int = 100, ping_interval: float = 30.0): """ Initialize connection pool. - + Args: max_connections: Maximum concurrent connections allowed ping_interval: Seconds between heartbeat pings @@ -61,63 +60,63 @@ def __init__(self, max_connections: int = 100, ping_interval: float = 30.0): self.active_connections: deque = deque() self.ping_interval = ping_interval self._connection_history: Dict[str, float] = {} - + async def acquire(self, session_id: str) -> WebSocketConnection: """ Acquire connection from pool or create new one. - + Args: session_id: Unique session identifier - + Returns: WebSocketConnection instance - + Raises: ConnectionPoolExhaustedError: If no connections available """ # Check if we need to evict inactive connections first await self._evict_inactive() - + # Try to acquire from pool async with self.pool: conn = WebSocketConnection( ws=None, # Would initialize with actual WebSocket connection session_id=session_id, last_activity=time.time(), - created_at=time.time() + created_at=time.time(), ) self.active_connections.append(conn) - + # Track creation time for eviction self._connection_history[session_id] = time.time() - + return conn - + async def release(self, connection: WebSocketConnection): """ Return connection to pool. - + Args: connection: Connection to release """ if connection in self.active_connections: self.active_connections.remove(connection) - + async def _evict_inactive(self): """Remove connections that haven't pinged recently.""" now = time.time() eviction_threshold = self.ping_interval * 2 - + while len(self.active_connections) >= self.max_connections: oldest = self.active_connections.popleft() - + # Check if connection is inactive if now - oldest.last_activity > eviction_threshold: await self._close_connection(oldest) else: # Put back at front of queue self.active_connections.appendleft(oldest) - + async def _close_connection(self, connection: WebSocketConnection): """Close a connection gracefully.""" try: @@ -125,20 +124,20 @@ async def _close_connection(self, connection: WebSocketConnection): await connection.ws.close(code=1000) # Normal closure except Exception as e: print(f"Error closing connection {connection.session_id}: {e}") - + async def health_check(self): """Perform health check on all active connections.""" now = time.time() healthy_connections = [] - + for conn in self.active_connections: is_healthy = await conn.ping() - + if is_healthy: healthy_connections.append(conn) else: conn.error_count += 1 - + # Close connection if too many errors if conn.error_count >= conn.max_errors: await self._close_connection(conn) @@ -146,33 +145,38 @@ async def health_check(self): # Put back in queue with reset error count conn.error_count = 0 self.active_connections.appendleft(conn) - + self.active_connections = deque(healthy_connections) - + def get_stats(self) -> Dict[str, Any]: """Get pool statistics.""" return { "active_connections": len(self.active_connections), "max_connections": self.max_connections, - "utilization": len(self.active_connections) / self.max_connections if self.max_connections > 0 else 0, - "pool_semaphore_value": self.pool._value if hasattr(self.pool, '_value') else None + "utilization": ( + len(self.active_connections) / self.max_connections + if self.max_connections > 0 + else 0 + ), + "pool_semaphore_value": ( + self.pool._value if hasattr(self.pool, "_value") else None + ), } - class ConnectionPoolExhaustedError(Exception): """Raised when connection pool is exhausted.""" - pass + pass if __name__ == "__main__": # Test connection pool pool = ConnectionPool(max_connections=10) - + async def test_pool(): conn = await pool.acquire("test_session") print(f"Acquired connection for session: {conn.session_id}") - + stats = pool.get_stats() print(f"Pool stats: {stats}") - + asyncio.run(test_pool()) diff --git a/mohawk_gui/entry_point.py b/mohawk_gui/entry_point.py index 5706aae..597d10d 100644 --- a/mohawk_gui/entry_point.py +++ b/mohawk_gui/entry_point.py @@ -7,8 +7,8 @@ or embedded in the PyInstaller executable. """ -import sys import os +import sys # Add project root to path project_root = Path(__file__).parent.parent @@ -24,38 +24,31 @@ def main(): print("โ•‘ Production-Ready Multi-Device Inference Management โ•‘") print("โ•šโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•") print() - + # Parse command line arguments import argparse - + parser = argparse.ArgumentParser( description="Mohawk Inference Engine GUI - Production Ready" ) parser.add_argument( - "--host", - default="localhost", - help="Worker host (default: localhost)" + "--host", default="localhost", help="Worker host (default: localhost)" ) parser.add_argument( - "--port", - type=int, - default=8003, - help="Worker port (default: 8003)" + "--port", type=int, default=8003, help="Worker port (default: 8003)" ) parser.add_argument( - "--config", - default="config.toml", - help="Configuration file path" + "--config", default="config.toml", help="Configuration file path" ) - + args = parser.parse_args() - + # Initialize and run GUI from mohawk_gui.main_window import MohawkGUI - + gui = MohawkGUI() gui.show() - + return gui.exec() if __name__ == "__main__": diff --git a/mohawk_gui/error_recovery.py b/mohawk_gui/error_recovery.py index ef75fe2..9e8bf0c 100644 --- a/mohawk_gui/error_recovery.py +++ b/mohawk_gui/error_recovery.py @@ -5,43 +5,42 @@ """ import asyncio -from typing import Optional, Callable, Dict, Any from dataclasses import dataclass, field from enum import Enum - +from typing import Any, Callable, Dict, Optional class RecoveryAction(Enum): """Recovery action types.""" + RETRY = "retry" DEGRADE = "degrade" ALERT = "alert" ABORT = "abort" IGNORE = "ignore" - @dataclass class RecoveryStrategy: """Define how to handle specific error types.""" + error_type: str action: RecoveryAction parameters: Dict[str, Any] = field(default_factory=dict) - class ErrorRecoveryManager: """ Handle errors gracefully with fallback strategies. - + Features: - Automatic retry with exponential backoff - Graceful degradation to fallback modes - Alert generation for critical failures - Transaction rollback support """ - + def __init__(self, alert_callback: Callable = None): """ Initialize error recovery manager. - + Args: alert_callback: Optional callback for alert notifications """ @@ -52,82 +51,75 @@ def __init__(self, alert_callback: Callable = None): parameters={ "max_retries": 5, "initial_backoff_seconds": 1, - "max_backoff_seconds": 30 - } + "max_backoff_seconds": 30, + }, ), "WorkerOffline": RecoveryStrategy( error_type="WorkerOffline", action=RecoveryAction.DEGRADE, - parameters={ - "fallback_mode": "single_worker", - "alert_users": True - } + parameters={"fallback_mode": "single_worker", "alert_users": True}, ), "SSLValidationError": RecoveryStrategy( error_type="SSLValidationError", action=RecoveryAction.ALERT, parameters={ "severity": "high", - "message": "SSL certificate validation failed" - } + "message": "SSL certificate validation failed", + }, ), "MemoryPressure": RecoveryStrategy( error_type="MemoryPressure", action=RecoveryAction.DEGRADE, - parameters={ - "threshold_mb": 80, - "action": "reduce_batch_size" - } + parameters={"threshold_mb": 80, "action": "reduce_batch_size"}, ), "ModelLoadingError": RecoveryStrategy( error_type="ModelLoadingError", action=RecoveryAction.ABORT, - parameters={ - "rollback_transaction": True - } - ) + parameters={"rollback_transaction": True}, + ), } self.alert_callback = alert_callback self._recovery_count: Dict[str, int] = {} - - async def handle_error(self, error: Exception, context: Dict[str, Any]) -> Optional[Any]: + + async def handle_error( + self, error: Exception, context: Dict[str, Any] + ) -> Optional[Any]: """ Handle error with appropriate recovery strategy. - + Args: error: Exception that occurred context: Context information for recovery decisions - + Returns: Result of recovery action or original result if no error """ try: error_type = type(error).__name__ strategy = self.strategies.get(error_type) - + if not strategy: # No specific strategy, use default (alert and ignore) await self._default_error_handler(error, context) return None - + result = await self._execute_recovery_strategy(strategy, error, context) return result - + except Exception as recovery_error: # Recovery itself failed, log and alert print(f"Recovery failed for {error_type}: {recovery_error}") if self.alert_callback: - await self.alert_callback("Recovery failed", str(error), str(recovery_error)) + await self.alert_callback( + "Recovery failed", str(error), str(recovery_error) + ) return None - + async def _execute_recovery_strategy( - self, - strategy: RecoveryStrategy, - error: Exception, - context: Dict[str, Any] + self, strategy: RecoveryStrategy, error: Exception, context: Dict[str, Any] ) -> Optional[Any]: """Execute recovery strategy.""" - + if strategy.action == RecoveryAction.RETRY: return await self._retry_operation(strategy, error, context) elif strategy.action == RecoveryAction.DEGRADE: @@ -139,140 +131,143 @@ async def _execute_recovery_strategy( return await self._abort_operation(strategy, error, context) else: return None - - async def _retry_operation(self, strategy: RecoveryStrategy, error: Exception, context: Dict[str, Any]): + + async def _retry_operation( + self, strategy: RecoveryStrategy, error: Exception, context: Dict[str, Any] + ): """Retry operation with exponential backoff.""" params = strategy.parameters max_retries = params.get("max_retries", 5) initial_backoff = params.get("initial_backoff_seconds", 1) max_backoff = params.get("max_backoff_seconds", 30) - + for attempt in range(max_retries): try: # Wait with exponential backoff if attempt > 0: - wait_time = min(initial_backoff * (2 ** attempt), max_backoff) + wait_time = min(initial_backoff * (2**attempt), max_backoff) await asyncio.sleep(wait_time) - + # Retry the operation result = await self._execute_with_context(context) return result - + except Exception as retry_error: if attempt == max_retries - 1: # Last attempt failed, raise original error raise error from retry_error else: continue - + return None - - async def _degrade_operation(self, strategy: RecoveryStrategy, error: Exception, context: Dict[str, Any]): + + async def _degrade_operation( + self, strategy: RecoveryStrategy, error: Exception, context: Dict[str, Any] + ): """Degraded operation with fallback.""" params = strategy.parameters fallback_mode = params.get("fallback_mode", "single_worker") - + # Log degradation event print(f"Degraded to {fallback_mode} mode due to: {error}") - + # Execute in fallback mode return await self._execute_with_context(context, fallback_mode=fallback_mode) - - async def _abort_operation(self, strategy: RecoveryStrategy, error: Exception, context: Dict[str, Any]): + + async def _abort_operation( + self, strategy: RecoveryStrategy, error: Exception, context: Dict[str, Any] + ): """Abort operation and rollback if needed.""" params = strategy.parameters - + if params.get("rollback_transaction", False): await self._rollback_transaction() - + print(f"Aborted operation due to: {error}") return None - - async def _handle_alert(self, error: Exception, context: Dict[str, Any], params: Dict[str, Any]): + + async def _handle_alert( + self, error: Exception, context: Dict[str, Any], params: Dict[str, Any] + ): """Handle alert notification.""" severity = params.get("severity", "medium") message = params.get("message", str(error)) - + alert_data = { "error_type": type(error).__name__, "severity": severity, "message": message, - "timestamp": __import__('datetime').datetime.now().isoformat() + "timestamp": __import__("datetime").datetime.now().isoformat(), } - + if self.alert_callback: await self.alert_callback(severity, message, str(error)) - + async def _default_error_handler(self, error: Exception, context: Dict[str, Any]): """Handle errors without specific strategy.""" print(f"Unhandled error type: {type(error).__name__}: {error}") - + if self.alert_callback: - await self.alert_callback("warning", f"Unhandled error: {type(error).__name__}", str(error)) - + await self.alert_callback( + "warning", f"Unhandled error: {type(error).__name__}", str(error) + ) + async def _rollback_transaction(self): """Rollback any in-flight transactions.""" print("Rolling back transaction...") # Implementation depends on your transaction system - + async def _execute_with_context( - self, - context: Dict[str, Any], - fallback_mode: str = None + self, context: Dict[str, Any], fallback_mode: str = None ) -> Any: """Execute operation with context.""" # This would contain the actual operation logic # For example: await worker.process_request(request) return {"status": "success", "context": context} - + def get_recovery_stats(self) -> Dict[str, Any]: """Get recovery statistics.""" total = sum(self._recovery_count.values()) - return { - "total_recoveries": total, - "by_type": self._recovery_count - } - + return {"total_recoveries": total, "by_type": self._recovery_count} class DegradedModeManager: """Manage degraded operation modes.""" - + def __init__(self): self.current_mode = "full" self.modes = { "full": {"batch_size": 32, "concurrency": 10}, "single_worker": {"batch_size": 8, "concurrency": 2}, - "minimal": {"batch_size": 1, "concurrency": 1} + "minimal": {"batch_size": 1, "concurrency": 1}, } - + def enter_degraded_mode(self, mode: str): """Enter degraded operation mode.""" if mode in self.modes: self.current_mode = mode print(f"Entered degraded mode: {mode}") - + def get_current_config(self) -> Dict[str, Any]: """Get current operational configuration.""" return { "mode": self.current_mode, - "config": self.modes.get(self.current_mode, {}) + "config": self.modes.get(self.current_mode, {}), } - if __name__ == "__main__": import asyncio - + async def test_recovery(): recovery = ErrorRecoveryManager() - + # Simulate error handling try: raise ConnectionTimeout("Connection timed out") except Exception as e: result = await recovery.handle_error(e, {"operation": "infer"}) print(f"Recovery result: {result}") - + class ConnectionTimeout(Exception): pass - + asyncio.run(test_recovery()) diff --git a/mohawk_gui/main.py b/mohawk_gui/main.py index 26c4472..8a19dc4 100644 --- a/mohawk_gui/main.py +++ b/mohawk_gui/main.py @@ -13,15 +13,14 @@ - System Health Monitor """ -import sys import argparse import os +import sys from pathlib import Path # Add parent directory to path for imports sys.path.insert(0, str(Path(__file__).parent.parent)) - def main(): """Main application entry point.""" parser = argparse.ArgumentParser( @@ -42,43 +41,34 @@ def main(): - Worker Configuration - Security Center (PQC + mTLS) - Conversation History - """ + """, ) - + parser.add_argument( - "--host", - default="localhost", - help="Host to bind to (default: localhost)" + "--host", default="localhost", help="Host to bind to (default: localhost)" ) - + parser.add_argument( - "--port", - type=int, - default=8003, - help="Port to listen on (default: 8003)" + "--port", type=int, default=8003, help="Port to listen on (default: 8003)" ) - + parser.add_argument( - "--key-file", - default=None, - help="Path to authentication key file" + "--key-file", default=None, help="Path to authentication key file" ) - + parser.add_argument( - "--ssl-enabled", - action="store_true", - help="Enable SSL/TLS for connections" + "--ssl-enabled", action="store_true", help="Enable SSL/TLS for connections" ) - + parser.add_argument( "--metrics-interval", type=int, default=1000, - help="Metrics update interval in ms (default: 1000)" + help="Metrics update interval in ms (default: 1000)", ) - + args = parser.parse_args() - + print("=" * 60) print("[MOHAWK] Inference Engine GUI v2.1.0") print("=" * 60) @@ -87,35 +77,36 @@ def main(): if args.key_file: print(f"Auth Key: {args.key_file}") print("=" * 60) - + try: # CRITICAL: Create QApplication FIRST before any QWidgets from PyQt6.QtWidgets import QApplication + app = QApplication(sys.argv) - + # NOW create and show the main window from main_window import MohawkGUI - + window = MohawkGUI() window.show() print("\n[INFO] GUI window opened successfully") print("[INFO] Connecting to Docker backend services...") - + # Run event loop sys.exit(app.exec()) - + except ImportError as e: print(f"\n[ERROR] Import error: {e}") print("\nPlease install dependencies:") print(" pip install PyQt6") sys.exit(1) - + except Exception as e: print(f"\n[ERROR] Error starting application: {e}") import traceback + traceback.print_exc() sys.exit(1) - if __name__ == "__main__": main() diff --git a/mohawk_gui/main_window.py b/mohawk_gui/main_window.py index 9721ab3..35a793b 100644 --- a/mohawk_gui/main_window.py +++ b/mohawk_gui/main_window.py @@ -2,31 +2,51 @@ # -*- coding: utf-8 -*- """Mohawk Inference Engine - Live Wired GUI""" -import sys -import requests import json +import sys from datetime import datetime + +import requests +from PyQt6.QtCore import Qt, QThread, QTimer, pyqtSignal +from PyQt6.QtGui import QColor, QFont from PyQt6.QtWidgets import ( - QApplication, QMainWindow, QWidget, QVBoxLayout, QHBoxLayout, - QLabel, QPushButton, QTabWidget, QStatusBar, QMessageBox, QGroupBox, - QTableWidget, QTableWidgetItem, QTextEdit, QLineEdit, QComboBox, - QSpinBox, QDoubleSpinBox, QProgressBar, QHeaderView, QScrollArea, - QGridLayout, QFormLayout, QCheckBox + QApplication, + QCheckBox, + QComboBox, + QDoubleSpinBox, + QFormLayout, + QGridLayout, + QGroupBox, + QHBoxLayout, + QHeaderView, + QInputDialog, + QLabel, + QLineEdit, + QMainWindow, + QMessageBox, + QProgressBar, + QPushButton, + QScrollArea, + QSpinBox, + QStatusBar, + QTableWidget, + QTableWidgetItem, + QTabWidget, + QTextEdit, + QVBoxLayout, + QWidget, ) -from PyQt6.QtWidgets import QInputDialog -from PyQt6.QtCore import Qt, QTimer, QThread, pyqtSignal -from PyQt6.QtGui import QFont, QColor - class WorkerHealthCheck(QThread): """Background thread for health checks.""" + health_updated = pyqtSignal(dict) - + def __init__(self, base_url="http://localhost:8003"): super().__init__() self.base_url = base_url self.running = True - + def run(self): """Check health periodically.""" while self.running: @@ -35,81 +55,84 @@ def run(self): if response.status_code == 200: self.health_updated.emit({"status": "healthy", "code": 200}) else: - self.health_updated.emit({"status": "degraded", "code": response.status_code}) + self.health_updated.emit( + {"status": "degraded", "code": response.status_code} + ) except requests.ConnectionError: - self.health_updated.emit({"status": "disconnected", "error": "Connection refused"}) + self.health_updated.emit( + {"status": "disconnected", "error": "Connection refused"} + ) except Exception as e: self.health_updated.emit({"status": "error", "error": str(e)}) - + self.msleep(3000) # Check every 3 seconds - + def stop(self): """Stop the health check thread.""" self.running = False - class MohawkGUI(QMainWindow): """Main window for Mohawk Inference Engine GUI with live wiring.""" - + def __init__(self): super().__init__() self.setWindowTitle("Mohawk Inference Engine - Professional Dashboard") self.setGeometry(100, 100, 1400, 900) - + # API endpoints self.gui_service_url = "http://localhost:8003" self.worker_service_url = "http://localhost:8004" - + # Health check thread self.health_thread = WorkerHealthCheck(self.gui_service_url) self.health_thread.health_updated.connect(self.on_health_update) self.health_thread.start() - + # Central widget central_widget = QWidget() self.setCentralWidget(central_widget) layout = QVBoxLayout(central_widget) - + # Title title_label = QLabel("Mohawk Inference Engine v2.1.0") title_label.setFont(QFont("Segoe UI", 16, QFont.Weight.Bold)) layout.addWidget(title_label) - + # Status group status_group = QGroupBox("System Status") status_layout = QHBoxLayout(status_group) - + self.health_label = QLabel("Status: Connecting...") self.health_label.setFont(QFont("Segoe UI", 10)) self.health_label.setStyleSheet("color: orange; font-weight: bold;") status_layout.addWidget(self.health_label) - + self.worker_count_label = QLabel("Workers: 0/2") status_layout.addWidget(self.worker_count_label) - + connect_btn = QPushButton("Connect to Workers") connect_btn.clicked.connect(self.connect_workers) status_layout.addWidget(connect_btn) - + self.throughput_label = QLabel("Throughput: 0 req/s") status_layout.addWidget(self.throughput_label) - + refresh_btn = QPushButton("Refresh") refresh_btn.clicked.connect(self.refresh_all) status_layout.addWidget(refresh_btn) - + status_layout.addStretch() layout.addWidget(status_group) - + # Store references for live updates (BEFORE creating tabs) self.metrics_bars = {} self.sessions_table = None self.workers_table = None - + # Tabs self.tabs = QTabWidget() layout.addWidget(self.tabs) - + # Create tabs self.model_library_widget = self.create_model_library_tab() self.chat_widget = self.create_chat_interface_tab() @@ -118,7 +141,7 @@ def __init__(self): self.workers_widget = self.create_workers_tab() self.security_widget = self.create_security_tab() self.history_widget = self.create_history_tab() - + self.tabs.addTab(self.model_library_widget, "Model Library") self.tabs.addTab(self.chat_widget, "Chat Interface") self.tabs.addTab(self.metrics_widget, "Performance Metrics") @@ -126,21 +149,21 @@ def __init__(self): self.tabs.addTab(self.workers_widget, "Worker Config") self.tabs.addTab(self.security_widget, "Security Center") self.tabs.addTab(self.history_widget, "History") - + # Status bar self.status_bar = QStatusBar() self.setStatusBar(self.status_bar) self.status_bar.showMessage("Ready - Connecting to Docker backend services...") - + # Timer for periodic updates self.update_timer = QTimer() self.update_timer.timeout.connect(self.periodic_update) self.update_timer.start(5000) # Update every 5 seconds - + def on_health_update(self, health_info): """Handle health check updates.""" status = health_info.get("status") - + if status == "healthy": self.health_label.setText("Status: Connected") self.health_label.setStyleSheet("color: green; font-weight: bold;") @@ -151,12 +174,12 @@ def on_health_update(self, health_info): else: self.health_label.setText(f"Status: {status}") self.health_label.setStyleSheet("color: red; font-weight: bold;") - + def api_call(self, endpoint, method="GET", data=None): """Make API call to backend service.""" try: url = f"{self.gui_service_url}{endpoint}" - + if method == "GET": response = requests.get(url, timeout=5) elif method == "POST": @@ -165,7 +188,7 @@ def api_call(self, endpoint, method="GET", data=None): response = requests.put(url, json=data, timeout=5) else: return None - + if response.status_code in [200, 201]: try: return response.json() @@ -182,52 +205,56 @@ def api_call(self, endpoint, method="GET", data=None): if detail: return {"error": f"HTTP {response.status_code}: {detail}"} return {"error": f"HTTP {response.status_code}"} - + except requests.ConnectionError: return {"error": "Connection refused - is the service running?"} except requests.Timeout: return {"error": "Request timeout"} except Exception as e: return {"error": str(e)} - + def create_model_library_tab(self): """Create model library management tab.""" widget = QWidget() layout = QVBoxLayout(widget) - + # Search and filter search_layout = QHBoxLayout() search_input = QLineEdit() search_input.setPlaceholderText("Search models...") search_layout.addWidget(QLabel("Search:")) search_layout.addWidget(search_input) - + filter_combo = QComboBox() filter_combo.addItems(["All", "LLM", "Embedding", "Chat"]) search_layout.addWidget(QLabel("Type:")) search_layout.addWidget(filter_combo) - + download_btn = QPushButton("Download Model") download_btn.clicked.connect(self.download_model) search_layout.addWidget(download_btn) - + refresh_btn = QPushButton("Refresh") refresh_btn.clicked.connect(self.refresh_models) search_layout.addWidget(refresh_btn) - + layout.addLayout(search_layout) - + # Models table self.models_table = QTableWidget() self.models_table.setColumnCount(6) - self.models_table.setHorizontalHeaderLabels(["Name", "Size (GB)", "Type", "Quantization", "Status", "Action"]) - self.models_table.horizontalHeader().setSectionResizeMode(QHeaderView.ResizeMode.Stretch) - + self.models_table.setHorizontalHeaderLabels( + ["Name", "Size (GB)", "Type", "Quantization", "Status", "Action"] + ) + self.models_table.horizontalHeader().setSectionResizeMode( + QHeaderView.ResizeMode.Stretch + ) + # Load sample models self.refresh_models() - + layout.addWidget(self.models_table) - + # Model details details_group = QGroupBox("Model Details") details_layout = QFormLayout(details_group) @@ -237,9 +264,9 @@ def create_model_library_tab(self): details_layout.addRow("Quantization:", QComboBox()) details_layout.addRow("Device Split:", QLineEdit("auto")) layout.addWidget(details_group) - + return widget - + def refresh_models(self): """Refresh model list from controller API.""" result = self.api_call("/api/models") @@ -265,27 +292,29 @@ def refresh_models(self): self.models_table.setItem(i, 1, QTableWidgetItem(str(size))) self.models_table.setItem(i, 2, QTableWidgetItem(mtype)) self.models_table.setItem(i, 3, QTableWidgetItem(quant)) - + status_item = QTableWidgetItem(status) status_color = "green" if status in {"Ready", "Loaded"} else "orange" status_item.setForeground(QColor(status_color)) self.models_table.setItem(i, 4, status_item) - + load_btn = QPushButton("Load") load_btn.clicked.connect(lambda checked, n=name: self.load_model_api(n)) self.models_table.setCellWidget(i, 5, load_btn) - + def load_model_api(self, model_name): """Load model via API call.""" result = self.api_call("/api/models/load", "POST", {"model": model_name}) - + if "error" in result: - QMessageBox.warning(self, "Load Error", f"Failed to load model:\n{result['error']}") + QMessageBox.warning( + self, "Load Error", f"Failed to load model:\n{result['error']}" + ) else: self.selected_model_label.setText(model_name) QMessageBox.information(self, "Success", f"Model loaded: {model_name}") self.status_bar.showMessage(f"Loaded model: {model_name}") - + def download_model(self): """Download a model.""" model_id, accepted = QInputDialog.getText( @@ -308,28 +337,30 @@ def download_model(self): self.refresh_models() QMessageBox.information(self, "Download", f"Model available: {model_id}") - + def create_chat_interface_tab(self): """Create chat interface tab.""" widget = QWidget() layout = QHBoxLayout(widget) - + # Chat area chat_layout = QVBoxLayout() self.chat_display = QTextEdit() self.chat_display.setReadOnly(True) - self.chat_display.setPlainText("Chat Interface - Connected to inference backend\n" + "="*50 + "\n") + self.chat_display.setPlainText( + "Chat Interface - Connected to inference backend\n" + "=" * 50 + "\n" + ) chat_layout.addWidget(self.chat_display) - + # Input area input_group = QGroupBox("Send Message") input_layout = QVBoxLayout(input_group) - + self.message_input = QTextEdit() self.message_input.setMaximumHeight(80) self.message_input.setPlaceholderText("Type your message here...") input_layout.addWidget(self.message_input) - + # Controls controls_layout = QHBoxLayout() controls_layout.addWidget(QLabel("Temperature:")) @@ -337,80 +368,80 @@ def create_chat_interface_tab(self): self.temp_spin.setValue(0.7) self.temp_spin.setRange(0, 2) controls_layout.addWidget(self.temp_spin) - + controls_layout.addWidget(QLabel("Top-p:")) self.topp_spin = QDoubleSpinBox() self.topp_spin.setValue(0.9) self.topp_spin.setRange(0, 1) controls_layout.addWidget(self.topp_spin) - + send_btn = QPushButton("Send Message") send_btn.clicked.connect(self.send_message) controls_layout.addWidget(send_btn) - + input_layout.addLayout(controls_layout) chat_layout.addWidget(input_group) layout.addLayout(chat_layout) - + # Settings panel settings_layout = QVBoxLayout() settings_group = QGroupBox("Chat Settings") form = QFormLayout(settings_group) - + self.max_tokens_spin = QSpinBox() self.max_tokens_spin.setValue(2048) self.max_tokens_spin.setRange(1, 8192) form.addRow("Max Tokens:", self.max_tokens_spin) - + self.system_prompt = QTextEdit() self.system_prompt.setMaximumHeight(100) self.system_prompt.setPlainText("You are a helpful AI assistant.") form.addRow("System Prompt:", self.system_prompt) - + settings_layout.addWidget(settings_group) settings_layout.addStretch() layout.addLayout(settings_layout) - + return widget - + def send_message(self): """Send message to inference backend.""" message = self.message_input.toPlainText().strip() if not message: return - + # Add to chat display self.chat_display.append(f"\nYou: {message}\n") self.message_input.clear() - + # Call inference API payload = { "message": message, "temperature": self.temp_spin.value(), "top_p": self.topp_spin.value(), "max_tokens": self.max_tokens_spin.value(), - "system_prompt": self.system_prompt.toPlainText() + "system_prompt": self.system_prompt.toPlainText(), } - + result = self.api_call("/api/inference/chat", "POST", payload) - + if "error" in result: self.chat_display.append(f"[ERROR] {result['error']}\n") else: response = result.get("response", "No response received") self.chat_display.append(f"Assistant: {response}\n") - + self.status_bar.showMessage("Message processed") - + def create_metrics_tab(self): """Create performance metrics tab.""" widget = QWidget() layout = QVBoxLayout(widget) - + # Metrics grid metrics_group = QGroupBox("Real-time Metrics") metrics_layout = QGridLayout(metrics_group) - + # Throughput metrics_layout.addWidget(QLabel("Throughput (req/s):"), 0, 0) self.throughput_bar = QProgressBar() @@ -418,8 +449,11 @@ def create_metrics_tab(self): metrics_layout.addWidget(self.throughput_bar, 0, 1) self.throughput_value_label = QLabel("0") metrics_layout.addWidget(self.throughput_value_label, 0, 2) - self.metrics_bars["throughput"] = (self.throughput_bar, self.throughput_value_label) - + self.metrics_bars["throughput"] = ( + self.throughput_bar, + self.throughput_value_label, + ) + # Latency p50 metrics_layout.addWidget(QLabel("Latency p50 (ms):"), 1, 0) latency_bar = QProgressBar() @@ -428,7 +462,7 @@ def create_metrics_tab(self): latency_value = QLabel("0") metrics_layout.addWidget(latency_value, 1, 2) self.metrics_bars["latency_p50"] = (latency_bar, latency_value) - + # Latency p95 metrics_layout.addWidget(QLabel("Latency p95 (ms):"), 2, 0) latency95_bar = QProgressBar() @@ -437,7 +471,7 @@ def create_metrics_tab(self): latency95_value = QLabel("0") metrics_layout.addWidget(latency95_value, 2, 2) self.metrics_bars["latency_p95"] = (latency95_bar, latency95_value) - + # Latency p99 metrics_layout.addWidget(QLabel("Latency p99 (ms):"), 3, 0) latency99_bar = QProgressBar() @@ -446,36 +480,36 @@ def create_metrics_tab(self): latency99_value = QLabel("0") metrics_layout.addWidget(latency99_value, 3, 2) self.metrics_bars["latency_p99"] = (latency99_bar, latency99_value) - + layout.addWidget(metrics_group) - + # Resource usage resource_group = QGroupBox("Resource Usage") resource_layout = QGridLayout(resource_group) - + # CPU resource_layout.addWidget(QLabel("CPU Usage:"), 0, 0) self.cpu_bar = QProgressBar() resource_layout.addWidget(self.cpu_bar, 0, 1) self.cpu_value = QLabel("0%") resource_layout.addWidget(self.cpu_value, 0, 2) - + # Memory resource_layout.addWidget(QLabel("Memory Usage:"), 1, 0) self.mem_bar = QProgressBar() resource_layout.addWidget(self.mem_bar, 1, 1) self.mem_value = QLabel("0%") resource_layout.addWidget(self.mem_value, 1, 2) - + # GPU resource_layout.addWidget(QLabel("GPU Usage:"), 2, 0) self.gpu_bar = QProgressBar() resource_layout.addWidget(self.gpu_bar, 2, 1) self.gpu_value = QLabel("0%") resource_layout.addWidget(self.gpu_value, 2, 2) - + layout.addWidget(resource_group) - + # Statistics self.stats_group = QGroupBox("Statistics Summary") self.stats_layout = QFormLayout(self.stats_group) @@ -485,47 +519,59 @@ def create_metrics_tab(self): self.stats_layout.addRow("Error Rate:", QLabel("0%")) self.stats_layout.addRow("Active Sessions:", QLabel("0")) layout.addWidget(self.stats_group) - + layout.addStretch() return widget - + def create_sessions_tab(self): """Create sessions manager tab.""" widget = QWidget() layout = QVBoxLayout(widget) - + # Controls controls_layout = QHBoxLayout() controls_layout.addWidget(QLabel("Max Queue Size:")) self.queue_spin = QSpinBox() self.queue_spin.setValue(50) controls_layout.addWidget(self.queue_spin) - + high_priority_btn = QPushButton("Queue High Priority") high_priority_btn.clicked.connect(self.queue_high_priority) controls_layout.addWidget(high_priority_btn) - + normal_priority_btn = QPushButton("Queue Normal Priority") normal_priority_btn.clicked.connect(self.queue_normal_priority) controls_layout.addWidget(normal_priority_btn) - + refresh_btn = QPushButton("Refresh") refresh_btn.clicked.connect(self.refresh_sessions) controls_layout.addWidget(refresh_btn) - + layout.addLayout(controls_layout) - + # Sessions table self.sessions_table = QTableWidget() self.sessions_table.setColumnCount(7) - self.sessions_table.setHorizontalHeaderLabels(["Session ID", "Model", "Status", "Throughput", "Latency", "Tokens/sec", "Actions"]) - self.sessions_table.horizontalHeader().setSectionResizeMode(QHeaderView.ResizeMode.Stretch) - + self.sessions_table.setHorizontalHeaderLabels( + [ + "Session ID", + "Model", + "Status", + "Throughput", + "Latency", + "Tokens/sec", + "Actions", + ] + ) + self.sessions_table.horizontalHeader().setSectionResizeMode( + QHeaderView.ResizeMode.Stretch + ) + self.refresh_sessions() layout.addWidget(self.sessions_table) - + return widget - + def refresh_sessions(self): """Refresh sessions from API.""" result = self.api_call("/api/sessions") @@ -534,26 +580,36 @@ def refresh_sessions(self): sessions = [] else: sessions = result.get("sessions", []) - + self.sessions_table.setRowCount(len(sessions)) for i, session in enumerate(sessions): - self.sessions_table.setItem(i, 0, QTableWidgetItem(session.get("id", f"sess_{i:03d}"))) - self.sessions_table.setItem(i, 1, QTableWidgetItem(session.get("model", "Unknown"))) - + self.sessions_table.setItem( + i, 0, QTableWidgetItem(session.get("id", f"sess_{i:03d}")) + ) + self.sessions_table.setItem( + i, 1, QTableWidgetItem(session.get("model", "Unknown")) + ) + status = session.get("status", "Unknown") status_item = QTableWidgetItem(status) status_color = "green" if status == "Running" else "blue" status_item.setForeground(QColor(status_color)) self.sessions_table.setItem(i, 2, status_item) - - self.sessions_table.setItem(i, 3, QTableWidgetItem(str(session.get("throughput", 0)))) - self.sessions_table.setItem(i, 4, QTableWidgetItem(f"{session.get('latency', 0)}ms")) - self.sessions_table.setItem(i, 5, QTableWidgetItem(str(session.get("tokens", 0)))) - + + self.sessions_table.setItem( + i, 3, QTableWidgetItem(str(session.get("throughput", 0))) + ) + self.sessions_table.setItem( + i, 4, QTableWidgetItem(f"{session.get('latency', 0)}ms") + ) + self.sessions_table.setItem( + i, 5, QTableWidgetItem(str(session.get("tokens", 0))) + ) + cancel_btn = QPushButton("Cancel") cancel_btn.clicked.connect(lambda checked, idx=i: self.cancel_session(idx)) self.sessions_table.setCellWidget(i, 6, cancel_btn) - + def queue_high_priority(self): """Queue a job with high priority.""" result = self.api_call("/api/queue", "POST", {"priority": "high"}) @@ -561,7 +617,7 @@ def queue_high_priority(self): QMessageBox.warning(self, "Queue Error", result["error"]) else: QMessageBox.information(self, "Queued", "Job queued with high priority") - + def queue_normal_priority(self): """Queue a job with normal priority.""" result = self.api_call("/api/queue", "POST", {"priority": "normal"}) @@ -569,7 +625,7 @@ def queue_normal_priority(self): QMessageBox.warning(self, "Queue Error", result["error"]) else: QMessageBox.information(self, "Queued", "Job queued with normal priority") - + def cancel_session(self, session_idx): """Cancel a session.""" reply = QMessageBox.question(self, "Cancel Session", "Are you sure?") @@ -581,47 +637,59 @@ def cancel_session(self, session_idx): return QMessageBox.information(self, "Cancelled", "Session cancelled") self.refresh_sessions() - + def create_workers_tab(self): """Create workers configuration tab.""" widget = QWidget() layout = QVBoxLayout(widget) - + # Add worker controls add_layout = QHBoxLayout() add_layout.addWidget(QLabel("Host:")) self.worker_host_input = QLineEdit() self.worker_host_input.setText("localhost") add_layout.addWidget(self.worker_host_input) - + add_layout.addWidget(QLabel("Port:")) self.worker_port_spin = QSpinBox() self.worker_port_spin.setValue(8005) self.worker_port_spin.setRange(1, 65535) add_layout.addWidget(self.worker_port_spin) - + add_btn = QPushButton("Add Worker") add_btn.clicked.connect(self.add_worker) add_layout.addWidget(add_btn) - + refresh_btn = QPushButton("Refresh") refresh_btn.clicked.connect(self.refresh_workers) add_layout.addWidget(refresh_btn) - + add_layout.addStretch() layout.addLayout(add_layout) - + # Workers table self.workers_table = QTableWidget() self.workers_table.setColumnCount(7) - self.workers_table.setHorizontalHeaderLabels(["Worker ID", "Host:Port", "Status", "Model", "GPU Threads", "Load", "Actions"]) - self.workers_table.horizontalHeader().setSectionResizeMode(QHeaderView.ResizeMode.Stretch) - + self.workers_table.setHorizontalHeaderLabels( + [ + "Worker ID", + "Host:Port", + "Status", + "Model", + "GPU Threads", + "Load", + "Actions", + ] + ) + self.workers_table.horizontalHeader().setSectionResizeMode( + QHeaderView.ResizeMode.Stretch + ) + self.refresh_workers() layout.addWidget(self.workers_table) - + return widget - + def refresh_workers(self): """Refresh workers from API.""" result = self.api_call("/api/workers") @@ -633,31 +701,39 @@ def refresh_workers(self): connected = sum(1 for w in workers if w.get("status") == "Connected") self.worker_count_label.setText(f"Workers: {connected}/{len(workers)}") - + self.workers_table.setRowCount(len(workers)) for i, worker in enumerate(workers): - self.workers_table.setItem(i, 0, QTableWidgetItem(worker.get("id", f"worker_{i}"))) + self.workers_table.setItem( + i, 0, QTableWidgetItem(worker.get("id", f"worker_{i}")) + ) host_port = f"{worker.get('host', 'localhost')}:{worker.get('port', 8000)}" self.workers_table.setItem(i, 1, QTableWidgetItem(host_port)) - + status = worker.get("status", "Unknown") status_item = QTableWidgetItem(status) status_color = "green" if status == "Connected" else "orange" status_item.setForeground(QColor(status_color)) self.workers_table.setItem(i, 2, status_item) - - self.workers_table.setItem(i, 3, QTableWidgetItem(worker.get("model", "None"))) - self.workers_table.setItem(i, 4, QTableWidgetItem(str(worker.get("threads", 0)))) - + + self.workers_table.setItem( + i, 3, QTableWidgetItem(worker.get("model", "None")) + ) + self.workers_table.setItem( + i, 4, QTableWidgetItem(str(worker.get("threads", 0))) + ) + load = worker.get("load", 0) load_bar = QProgressBar() load_bar.setValue(load) self.workers_table.setCellWidget(i, 5, load_bar) - - action_btn = QPushButton("Connected" if status == "Connected" else "Unavailable") + + action_btn = QPushButton( + "Connected" if status == "Connected" else "Unavailable" + ) action_btn.setEnabled(False) self.workers_table.setCellWidget(i, 6, action_btn) - + def add_worker(self): """Add a new worker.""" host = self.worker_host_input.text().strip() @@ -674,12 +750,12 @@ def add_worker(self): self.refresh_workers() QMessageBox.information(self, "Worker Added", f"Worker added: {host}:{port}") - + def create_security_tab(self): """Create security center tab.""" widget = QWidget() layout = QVBoxLayout(widget) - + # JWT jwt_group = QGroupBox("JWT Authentication") jwt_layout = QFormLayout(jwt_group) @@ -688,10 +764,12 @@ def create_security_tab(self): jwt_layout.addRow("Status:", jwt_status) jwt_layout.addRow("Expiry:", QLabel("24 hours")) refresh_btn = QPushButton("Refresh Token") - refresh_btn.clicked.connect(lambda: self.api_call("/api/security/jwt/refresh", "POST")) + refresh_btn.clicked.connect( + lambda: self.api_call("/api/security/jwt/refresh", "POST") + ) jwt_layout.addRow("Action:", refresh_btn) layout.addWidget(jwt_group) - + # mTLS mtls_group = QGroupBox("mTLS Configuration") mtls_layout = QFormLayout(mtls_group) @@ -701,7 +779,7 @@ def create_security_tab(self): mtls_layout.addRow("Certificate:", QLabel("Valid until 2025-12-31")) mtls_layout.addRow("Client Key:", QLabel("Encrypted (Fernet)")) layout.addWidget(mtls_group) - + # PQC pqc_group = QGroupBox("Post-Quantum Cryptography") pqc_layout = QFormLayout(pqc_group) @@ -710,10 +788,12 @@ def create_security_tab(self): pqc_layout.addRow("Status:", pqc_status) pqc_layout.addRow("liboqs:", QLabel("Not installed (optional)")) enable_pqc_btn = QPushButton("Enable Hybrid KEM") - enable_pqc_btn.clicked.connect(lambda: self.api_call("/api/security/pqc/enable", "POST")) + enable_pqc_btn.clicked.connect( + lambda: self.api_call("/api/security/pqc/enable", "POST") + ) pqc_layout.addRow("Action:", enable_pqc_btn) layout.addWidget(pqc_group) - + # Security logs logs_group = QGroupBox("Security Event Log") logs_layout = QVBoxLayout(logs_group) @@ -727,42 +807,50 @@ def create_security_tab(self): ) logs_layout.addWidget(security_log) layout.addWidget(logs_group) - + return widget - + def create_history_tab(self): """Create conversation history tab.""" widget = QWidget() layout = QVBoxLayout(widget) - + # History table table = QTableWidget() table.setColumnCount(6) - table.setHorizontalHeaderLabels(["Timestamp", "Model", "Tokens Used", "Duration", "Status", "Actions"]) + table.setHorizontalHeaderLabels( + ["Timestamp", "Model", "Tokens Used", "Duration", "Status", "Actions"] + ) table.horizontalHeader().setSectionResizeMode(QHeaderView.ResizeMode.Stretch) - + history = [ - (datetime.now().strftime('%Y-%m-%d %H:%M'), "Llama-3-8B-Instruct-Q4_K_M", 1250, "12s", "Completed"), + ( + datetime.now().strftime("%Y-%m-%d %H:%M"), + "Llama-3-8B-Instruct-Q4_K_M", + 1250, + "12s", + "Completed", + ), ("2024-01-15 14:25", "Llama-3-8B-Instruct-Q4_K_M", 890, "8s", "Completed"), ("2024-01-15 14:20", "Mistral-7B-v0.3-Q5_K_M", 2100, "18s", "Completed"), ] - + table.setRowCount(len(history)) for i, (timestamp, model, tokens, duration, status) in enumerate(history): table.setItem(i, 0, QTableWidgetItem(timestamp)) table.setItem(i, 1, QTableWidgetItem(model)) table.setItem(i, 2, QTableWidgetItem(str(tokens))) table.setItem(i, 3, QTableWidgetItem(duration)) - + status_item = QTableWidgetItem(status) status_item.setForeground(QColor("green")) table.setItem(i, 4, status_item) - + view_btn = QPushButton("View") table.setCellWidget(i, 5, view_btn) - + layout.addWidget(table) - + # Statistics stats_group = QGroupBox("Usage Statistics") stats_layout = QFormLayout(stats_group) @@ -771,42 +859,44 @@ def create_history_tab(self): stats_layout.addRow("Models Used:", QLabel("3")) stats_layout.addRow("Total Sessions:", QLabel("247")) layout.addWidget(stats_group) - + return widget - + def connect_workers(self): """Connect to worker services.""" result = self.api_call("/api/workers/connect", "POST") - + if "error" in result: QMessageBox.warning(self, "Connection Error", result["error"]) else: connected = result.get("connected", 0) total = result.get("total", connected) self.worker_count_label.setText(f"Workers: {connected}/{total}") - QMessageBox.information(self, "Workers Connected", f"Connected workers: {connected}/{total}") + QMessageBox.information( + self, "Workers Connected", f"Connected workers: {connected}/{total}" + ) self.refresh_workers() - + def periodic_update(self): """Periodic updates for live data.""" result = self.api_call("/api/metrics") - + if "error" not in result: metrics = result.get("metrics", {}) - + # Update throughput throughput = metrics.get("throughput", 0) self.throughput_bar.setValue(int(throughput)) self.throughput_value_label.setText(str(int(throughput))) self.throughput_label.setText(f"Throughput: {int(throughput)} req/s") - + # Update CPU/Memory/GPU self.cpu_bar.setValue(metrics.get("cpu", 0)) self.cpu_value.setText(f"{metrics.get('cpu', 0)}%") - + self.mem_bar.setValue(metrics.get("memory", 0)) self.mem_value.setText(f"{metrics.get('memory', 0)}%") - + self.gpu_bar.setValue(metrics.get("gpu", 0)) self.gpu_value.setText(f"{metrics.get('gpu', 0)}%") @@ -823,7 +913,7 @@ def periodic_update(self): bar, label = self.metrics_bars["latency_p99"] bar.setValue(int(metrics.get("latency_p99", 0))) label.setText(str(int(metrics.get("latency_p99", 0)))) - + def refresh_all(self): """Refresh all tabs.""" self.refresh_models() @@ -831,13 +921,12 @@ def refresh_all(self): self.refresh_workers() self.periodic_update() self.status_bar.showMessage("Refreshed all data") - + def closeEvent(self, event): """Handle window close.""" self.health_thread.stop() event.accept() - def main(): """Main entry point.""" print("=" * 60) @@ -848,13 +937,12 @@ def main(): print("=" * 60) print("\n[INFO] GUI window opened successfully") print("[INFO] Connecting to Docker backend services...") - + app = QApplication(sys.argv) window = MohawkGUI() window.show() - - sys.exit(app.exec()) + sys.exit(app.exec()) if __name__ == "__main__": main() diff --git a/mohawk_gui/metrics_buffer.py b/mohawk_gui/metrics_buffer.py index b1bfd61..28550c6 100644 --- a/mohawk_gui/metrics_buffer.py +++ b/mohawk_gui/metrics_buffer.py @@ -4,17 +4,17 @@ Provides efficient metrics buffering and downsampling for real-time visualization. """ -from collections import deque -from dataclasses import dataclass, field import random import statistics import time -from typing import Dict, Any, Optional - +from collections import deque +from dataclasses import dataclass, field +from typing import Any, Dict, Optional @dataclass class BufferedMetrics: """Aggregated metrics over time window.""" + timestamp: float latency_p50: float latency_p95: float @@ -23,39 +23,44 @@ class BufferedMetrics: gpu_utilization: float memory_mb: float = 0.0 active_requests: int = 0 - + def __add__(self, other): """Weighted average for aggregation.""" # Weight new data less than existing buffer - weight_new = 1 / (len(self.buffer) + 1) if hasattr(self, 'buffer') else 0.1 - + weight_new = 1 / (len(self.buffer) + 1) if hasattr(self, "buffer") else 0.1 + return BufferedMetrics( timestamp=self.timestamp, - latency_p50=(self.latency_p50 * (1 - weight_new) + other.latency_p50 * weight_new), - latency_p95=(self.latency_p95 * (1 - weight_new) + other.latency_p95 * weight_new), - latency_p99=(self.latency_p99 * (1 - weight_new) + other.latency_p99 * weight_new), + latency_p50=( + self.latency_p50 * (1 - weight_new) + other.latency_p50 * weight_new + ), + latency_p95=( + self.latency_p95 * (1 - weight_new) + other.latency_p95 * weight_new + ), + latency_p99=( + self.latency_p99 * (1 - weight_new) + other.latency_p99 * weight_new + ), throughput_rps=(self.throughput_rps + other.throughput_rps) / 2, gpu_utilization=(self.gpu_utilization + other.gpu_utilization) / 2, memory_mb=(self.memory_mb + other.memory_mb) / 2, - active_requests=(self.active_requests + other.active_requests) / 2 + active_requests=(self.active_requests + other.active_requests) / 2, ) - class MetricsBuffer: """ Buffer and downsample metrics efficiently. - + Features: - Configurable window size for time-based aggregation - Sample rate control for high-frequency updates - Statistical summaries (percentiles, averages) - Memory-efficient deque with maxlen """ - + def __init__(self, window_size: int = 1000, sample_rate: float = 0.1): """ Initialize metrics buffer. - + Args: window_size: Maximum number of metrics to keep in buffer sample_rate: Probability of storing each metric (0.0-1.0) @@ -64,14 +69,14 @@ def __init__(self, window_size: int = 1000, sample_rate: float = 0.1): self.sample_rate = sample_rate self._latency_history: deque = deque(maxlen=1000) self._throughput_history: deque = deque(maxlen=1000) - + async def add(self, metrics: Dict[str, Any]): """ Add metrics with optional downsampling. - + Args: metrics: Dictionary of metric values - + Example: await buffer.add({ "latency_p50_ms": 12.5, @@ -89,20 +94,20 @@ async def add(self, metrics: Dict[str, Any]): throughput_rps=metrics.get("throughput_rps", 0), gpu_utilization=metrics.get("gpu_utilization", 0), memory_mb=metrics.get("memory_mb", 0), - active_requests=metrics.get("active_requests", 0) + active_requests=metrics.get("active_requests", 0), ) self.buffer.append(buffered) - + # Track latency and throughput separately for statistics if buffered.latency_p50 > 0: self._latency_history.append(buffered.latency_p50) if buffered.throughput_rps > 0: self._throughput_history.append(buffered.throughput_rps) - + def get_summary(self) -> Dict[str, Any]: """ Return aggregated statistics. - + Returns: Dictionary with statistical summaries """ @@ -113,129 +118,139 @@ def get_summary(self) -> Dict[str, Any]: "min_latency_p50_ms": 0, "max_latency_p50_ms": 0, "throughput_rps": 0, - "buffer_utilization": 0 + "buffer_utilization": 0, } - + data = list(self.buffer) latencies = [m.latency_p50 for m in data if m.latency_p50 > 0] throughputs = [m.throughput_rps for m in data if m.throughput_rps > 0] - + return { "count": len(data), "avg_latency_p50_ms": statistics.mean(latencies) if latencies else 0, "min_latency_p50_ms": min(latencies) if latencies else 0, "max_latency_p50_ms": max(latencies) if latencies else 0, - "p95_latency_ms": self._calculate_percentile(latencies, 0.95) if latencies else 0, - "p99_latency_ms": self._calculate_percentile(latencies, 0.99) if latencies else 0, + "p95_latency_ms": ( + self._calculate_percentile(latencies, 0.95) if latencies else 0 + ), + "p99_latency_ms": ( + self._calculate_percentile(latencies, 0.99) if latencies else 0 + ), "avg_throughput_rps": statistics.mean(throughputs) if throughputs else 0, "min_throughput_rps": min(throughputs) if throughputs else 0, "max_throughput_rps": max(throughputs) if throughputs else 0, - "buffer_utilization": len(self.buffer) / self.buffer.maxlen if self.buffer.maxlen > 0 else 0 + "buffer_utilization": ( + len(self.buffer) / self.buffer.maxlen if self.buffer.maxlen > 0 else 0 + ), } - + def _calculate_percentile(self, data: list, percentile: float) -> float: """Calculate percentile from sorted data.""" if not data: return 0 - + if not (0 <= percentile <= 1): raise ValueError(f"Percentile must be between 0 and 1, got {percentile}") - + sorted_data = sorted(data) - + # Proper percentile calculation: map percentile to array index # For n items, index should range from 0 to n-1 index = int((len(sorted_data) - 1) * percentile) - + # Explicit bounds checking index = max(0, min(index, len(sorted_data) - 1)) - + return sorted_data[index] - + def get_time_series(self, window_size: int = None) -> list: """ Get recent metrics as time series. - + Args: window_size: Number of recent entries to return (None for all) - + Returns: List of BufferedMetrics objects """ if window_size is None: return list(self.buffer) - + return list(self.buffer)[-window_size:] - + def clear(self): """Clear the buffer.""" self.buffer.clear() self._latency_history.clear() self._throughput_history.clear() - + def get_memory_usage(self) -> int: """Get approximate memory usage of buffer in bytes.""" return len(self.buffer) * 1024 # Rough estimate - class MetricsAggregator: """Aggregate metrics across multiple sessions/workers.""" - + def __init__(self): self.session_buffers: Dict[str, MetricsBuffer] = {} - + def get_or_create_buffer(self, session_id: str) -> MetricsBuffer: """Get existing buffer or create new one for session.""" if session_id not in self.session_buffers: # Aggregation should be deterministic across sessions; avoid sampling loss. self.session_buffers[session_id] = MetricsBuffer(sample_rate=1.0) return self.session_buffers[session_id] - + async def add_metrics(self, session_id: str, metrics: Dict[str, Any]): """Add metrics to appropriate session buffer.""" buffer = self.get_or_create_buffer(session_id) await buffer.add(metrics) - + def get_global_summary(self) -> Dict[str, Any]: """Get aggregated summary across all sessions.""" all_latencies = [] all_throughputs = [] - + for buffer in self.session_buffers.values(): summary = buffer.get_summary() if summary["count"] > 0: all_latencies.append(summary["avg_latency_p50_ms"]) all_throughputs.append(summary["avg_throughput_rps"]) - + return { "total_sessions": len(self.session_buffers), "active_sessions_with_metrics": len(all_latencies), - "global_avg_latency_p50_ms": statistics.mean(all_latencies) if all_latencies else 0, - "global_avg_throughput_rps": statistics.mean(all_throughputs) if all_throughputs else 0 + "global_avg_latency_p50_ms": ( + statistics.mean(all_latencies) if all_latencies else 0 + ), + "global_avg_throughput_rps": ( + statistics.mean(all_throughputs) if all_throughputs else 0 + ), } - if __name__ == "__main__": # Test metrics buffer import asyncio - + async def test_buffer(): buffer = MetricsBuffer(window_size=100, sample_rate=1.0) - + # Add some sample metrics for i in range(150): - await buffer.add({ - "timestamp": time.time(), - "latency_p50_ms": 10 + random.random() * 20, - "latency_p95_ms": 40 + random.random() * 30, - "latency_p99_ms": 60 + random.random() * 40, - "throughput_rps": 1000 + random.random() * 500, - "gpu_utilization": 50 + random.random() * 30, - "memory_mb": 2000 + random.random() * 1000, - "active_requests": 10 + random.randint(0, 50) - }) - + await buffer.add( + { + "timestamp": time.time(), + "latency_p50_ms": 10 + random.random() * 20, + "latency_p95_ms": 40 + random.random() * 30, + "latency_p99_ms": 60 + random.random() * 40, + "throughput_rps": 1000 + random.random() * 500, + "gpu_utilization": 50 + random.random() * 30, + "memory_mb": 2000 + random.random() * 1000, + "active_requests": 10 + random.randint(0, 50), + } + ) + summary = buffer.get_summary() print(f"Buffer summary: {summary}") - + asyncio.run(test_buffer()) diff --git a/mohawk_gui/mock_backend.py b/mohawk_gui/mock_backend.py index 24995ce..3261bf8 100644 --- a/mohawk_gui/mock_backend.py +++ b/mohawk_gui/mock_backend.py @@ -1,16 +1,15 @@ """Lightweight backend API used by docker-compose for local GUI verification.""" from datetime import datetime + from fastapi import FastAPI app = FastAPI(title="Mohawk GUI Mock Backend", version="1.0.0") - @app.get("/health") async def health() -> dict: return {"status": "healthy", "service": "mohawk-gui-backend"} - @app.get("/api/workers") async def list_workers() -> dict: return { @@ -36,12 +35,10 @@ async def list_workers() -> dict: ] } - @app.post("/api/workers/connect") async def connect_workers() -> dict: return {"status": "ok", "connected": 2} - @app.get("/api/metrics") async def metrics() -> dict: # Keep values in GUI progress bar ranges. @@ -55,7 +52,6 @@ async def metrics() -> dict: } } - @app.get("/api/sessions") async def sessions() -> dict: return { @@ -71,7 +67,6 @@ async def sessions() -> dict: ] } - @app.post("/api/sessions/{session_id}/cancel") async def cancel_session(session_id: str) -> dict: return {"status": "ok", "cancelled": session_id} diff --git a/mohawk_gui/monitoring.py b/mohawk_gui/monitoring.py index 2f79f31..365c181 100644 --- a/mohawk_gui/monitoring.py +++ b/mohawk_gui/monitoring.py @@ -4,16 +4,17 @@ Provides self-monitoring and performance tracking. """ -import psutil +import json import time from dataclasses import dataclass, field -from typing import Dict, Any, Optional -import json +from typing import Any, Dict, Optional +import psutil @dataclass class Guimetrics: """Metrics about GUI health.""" + timestamp: float uptime_seconds: float memory_usage_mb: float @@ -21,29 +22,28 @@ class Guimetrics: active_connections: int = 0 ui_thread_blocked: bool = False gpu_utilization: float = 0.0 - + def to_dict(self) -> Dict[str, Any]: """Convert to dictionary for JSON serialization.""" - return {k: v for k, v in self.__dict__.items() if not k.startswith('_')} - + return {k: v for k, v in self.__dict__.items() if not k.startswith("_")} class GuimetricsCollector: """ Monitor GUI health and performance. - + Features: - Process memory and CPU monitoring - UI thread responsiveness tracking - Connection count monitoring - GPU utilization tracking """ - + def __init__(self): self.start_time = time.time() self.process = psutil.Process() self._last_check_time: float = time.time() self._blocked_count: int = 0 - + def collect(self) -> Dict[str, Any]: """Collect current metrics.""" return Guimetrics( @@ -53,53 +53,52 @@ def collect(self) -> Dict[str, Any]: cpu_percent=self.process.cpu_percent(), active_connections=0, # Would count actual WebSocket connections ui_thread_blocked=False, # Would detect if main thread blocked - gpu_utilization=0.0 # Would query GPU metrics + gpu_utilization=0.0, # Would query GPU metrics ).to_dict() - + def check_ui_responsiveness(self, threshold_seconds: float = 1.0) -> bool: """Check if UI thread is responsive.""" now = time.time() elapsed = now - self._last_check_time - + if elapsed > threshold_seconds: self._blocked_count += 1 return False - + self._last_check_time = now return True - + def get_blocked_stats(self) -> Dict[str, Any]: """Get UI blocking statistics.""" return { "total_blocks": self._blocked_count, - "avg_block_duration_s": 0.5 # Would calculate from logs + "avg_block_duration_s": 0.5, # Would calculate from logs } - class PerformanceTracker: """Track application performance metrics.""" - + def __init__(self): self.operation_times: Dict[str, list] = {} self.request_count: int = 0 - + def record_operation(self, operation_name: str, duration_ms: float): """Record operation duration.""" if operation_name not in self.operation_times: self.operation_times[operation_name] = [] - + self.operation_times[operation_name].append(duration_ms) - + def get_operation_stats(self, operation_name: str) -> Dict[str, Any]: """Get statistics for specific operation.""" times = self.operation_times.get(operation_name, []) - + if not times: return {"count": 0} - + sorted_times = sorted(times) n = len(sorted_times) - + return { "count": n, "avg_ms": sum(times) / n, @@ -107,32 +106,31 @@ def get_operation_stats(self, operation_name: str) -> Dict[str, Any]: "max_ms": max(times), "p50_ms": sorted_times[int(n * 0.5)], "p95_ms": sorted_times[int(n * 0.95)] if n > 20 else sorted_times[-1], - "p99_ms": sorted_times[int(n * 0.99)] if n > 100 else sorted_times[-1] + "p99_ms": sorted_times[int(n * 0.99)] if n > 100 else sorted_times[-1], } - class SystemMonitor: """Monitor system resources.""" - + def __init__(self): self.process = psutil.Process() - + def get_memory_info(self) -> Dict[str, Any]: """Get memory usage information.""" mem = self.process.memory_info() return { "rss_mb": mem.rss / 1024 / 1024, "vms_mb": mem.vms / 1024 / 1024, - "percent": self.process.memory_percent() + "percent": self.process.memory_percent(), } - + def get_cpu_info(self) -> Dict[str, Any]: """Get CPU usage information.""" return { "percent": self.process.cpu_percent(), - "times": dict(self.process.cpu_times()) + "times": dict(self.process.cpu_times()), } - + def get_disk_usage(self, path: str = "/") -> Dict[str, Any]: """Get disk usage for specified path.""" usage = psutil.disk_usage(path) @@ -140,17 +138,18 @@ def get_disk_usage(self, path: str = "/") -> Dict[str, Any]: "total_gb": usage.total / 1024 / 1024 / 1024, "used_gb": usage.used / 1024 / 1024 / 1024, "free_gb": usage.free / 1024 / 1024 / 1024, - "percent": usage.percent + "percent": usage.percent, } - if __name__ == "__main__": import asyncio - + # Test monitoring collector = GuimetricsCollector() - + for _ in range(5): metrics = collector.collect() - print(f"Uptime: {metrics['uptime_seconds']:.1f}s, Memory: {metrics['memory_usage_mb']:.1f}MB") + print( + f"Uptime: {metrics['uptime_seconds']:.1f}s, Memory: {metrics['memory_usage_mb']:.1f}MB" + ) time.sleep(0.5) diff --git a/mohawk_gui/test_dashboard.py b/mohawk_gui/test_dashboard.py index 90ee4bb..a69b63e 100644 --- a/mohawk_gui/test_dashboard.py +++ b/mohawk_gui/test_dashboard.py @@ -9,97 +9,98 @@ import sys from pathlib import Path - def test_imports(): """Test that all imports work correctly.""" print("=" * 60) print("๐Ÿงช Testing Dashboard Imports...") print("=" * 60) - + try: - from PyQt6.QtWidgets import QMainWindow, QWidget, QVBoxLayout + from PyQt6.QtWidgets import QMainWindow, QVBoxLayout, QWidget + print("โœ… PyQt6 imports successful") except ImportError as e: print(f"โŒ PyQt6 import failed: {e}") print("\nInstall PyQt6 with:") print(" pip install PyQt6 pyqtgraph") return False - + try: - from main_window import MohawkGUI, ModelsLibraryPage, ChatInterfacePage + from main_window import ChatInterfacePage, ModelsLibraryPage, MohawkGUI + print("โœ… Dashboard components import successful") except ImportError as e: print(f"โŒ Dashboard component import failed: {e}") print("\nCheck mohawk_gui/main_window.py for errors") return False - - return True + return True def test_ui_components(): """Test that UI components can be created.""" print("\n" + "=" * 60) print("๐Ÿงช Testing UI Component Creation...") print("=" * 60) - + try: from main_window import MohawkGUI - + # Create QApplication (needed for GUI testing) from PyQt6.QtWidgets import QApplication + app = QApplication(sys.argv) - + # Test MohawkGUI initialization print("โœ… Creating MohawkGUI instance...") gui = MohawkGUI() print("โœ… MohawkGUI created successfully") - + # Test that all tabs are initialized print("\n๐Ÿ“‹ Checking tab initialization:") - + tabs = [ "Models Library", - "Chat Interface", + "Chat Interface", "Performance Metrics", "Session Manager", "Worker Configuration", "Security Center", - "Conversation History" + "Conversation History", ] - + for i in range(gui.tabs.count()): widget = gui.tabs.widget(i) - tab_name = widget.title() if hasattr(widget, 'title') else f"Tab {i+1}" + tab_name = widget.title() if hasattr(widget, "title") else f"Tab {i+1}" print(f" โœ… {tab_name}") - + print("\nโœ… All UI components initialized successfully!") - + # Test that navigation buttons are created print("\n๐Ÿ“‹ Checking navigation buttons:") for name, btn in gui.nav_buttons.items(): print(f" โœ… {name} button") - + return True - + except Exception as e: print(f"\nโŒ UI component test failed: {e}") import traceback + traceback.print_exc() return False - def test_dashboard_features(): """Test that all dashboard features are present.""" print("\n" + "=" * 60) print("๐Ÿงช Testing Dashboard Features...") print("=" * 60) - + try: from main_window import MohawkGUI - + app = QApplication(sys.argv) gui = MohawkGUI() - + features = { "Model Library": ["download_model", "upload_model", "load_selected_model"], "Chat Interface": ["send_message", "clear_history"], @@ -108,7 +109,7 @@ def test_dashboard_features(): "Worker Configuration": ["add_worker", "_toggle_worker_connection"], "Security Center": ["refresh_token", "enable_pqc"], } - + all_ok = True for feature_name, methods in features.items(): print(f"\n{feature_name}:") @@ -117,55 +118,55 @@ def test_dashboard_features(): print(f" โœ… {method}() method exists") else: print(f" โš ๏ธ {method}() not found (may be on different tab)") - + print("\nโœ… All dashboard features present!") return True - + except Exception as e: print(f"\nโŒ Dashboard feature test failed: {e}") import traceback + traceback.print_exc() return False - def main(): """Run all tests.""" print("\n" + "=" * 60) print("๐Ÿฆ… Mohawk Inference Engine Dashboard - Test Suite") print("=" * 60 + "\n") - + results = [] - + # Test imports if test_imports(): results.append(("Imports", "โœ… PASSED")) else: results.append(("Imports", "โŒ FAILED")) - + # Test UI components if test_ui_components(): results.append(("UI Components", "โœ… PASSED")) else: results.append(("UI Components", "โŒ FAILED")) - + # Test dashboard features if test_dashboard_features(): results.append(("Dashboard Features", "โœ… PASSED")) else: results.append(("Dashboard Features", "โŒ FAILED")) - + # Summary print("\n" + "=" * 60) print("๐Ÿ“Š Test Summary") print("=" * 60) - + passed = sum(1 for _, status in results if status == "โœ… PASSED") total = len(results) - + for test_name, result in results: status_icon = "โœ…" if result == "โœ… PASSED" else "โŒ" print(f"{status_icon} {test_name}: {result}") - + print("\n" + "=" * 60) if passed == total: print("๐ŸŽ‰ All tests PASSED! Dashboard is ready to run.") @@ -178,6 +179,5 @@ def main(): print("=" * 60) return 1 - if __name__ == "__main__": sys.exit(main()) diff --git a/prototype/__pycache__/__init__.cpython-312.pyc b/prototype/__pycache__/__init__.cpython-312.pyc index 1829f278b5a09b6562f2b36234c6d8c641899fbe..86e7c2088971a3b374714293272691e7e6ab62ab 100644 GIT binary patch delta 27 hcmZo^#n2dMx6 delta 37 rcmX>XbtQ`XG%qg~0}w2^;J=YupM_gpzdXMvySN}RId!u=3%@1+-{K2l diff --git a/prototype/__pycache__/gui_backend.cpython-312.pyc b/prototype/__pycache__/gui_backend.cpython-312.pyc index fadbca3143b874e2bc592a3f302174eb65524270..771d3f2aa9aeb900040c95ef4cfa97cd14329663 100644 GIT binary patch delta 3522 zcmdT`dr(x@8NcV=y?5U(k6qRUc3D^Z&@7_X zRH$iU=Gd`mbga`cjZr(=&D1nbGX+fqooQg0RJuOublTC5wngKF7Sp8PcVVk_oXOw4 zJNvu8?{U6!?{~iMocrDZvi~rdbzG=j_cvsiFB7C#J|nS+Jk(EW3eSxwmvpN6XKd<*pB&D zzB!JaN{hGY4rpZkal{_hd=$Llr zxaLH3e!?uziq5UfJOjtcmU3`Y9`%ipV;|!i_gLR}+4>k?+v9xg39|h$zOz}o&1wi~ 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+from typing import Any, Callable, Optional class CircuitBreaker: """ Circuit breaker for worker calls. - + States: - CLOSED: Normal operation, allow requests - OPEN: Too many failures, reject requests - HALF-OPEN: Testing if service recovered - + Args: failure_threshold: Number of consecutive failures before opening circuit recovery_timeout: Seconds to wait before trying again (half-open state) success_threshold: Successful calls needed to close circuit from half-open """ - + def __init__( self, failure_threshold: int = 5, recovery_timeout: float = 30.0, - success_threshold: int = 1 + success_threshold: int = 1, ): self.failure_threshold = failure_threshold self.recovery_timeout = recovery_timeout self.success_threshold = success_threshold - + self.failures = 0 self.last_failure_time: Optional[float] = None - self.state = 'CLOSED' # CLOSED, OPEN, HALF-OPEN - + self.state = "CLOSED" # CLOSED, OPEN, HALF-OPEN + @property def is_open(self) -> bool: """Check if circuit is open (rejecting requests).""" - return self.state == 'OPEN' - + return self.state == "OPEN" + @property def is_closed(self) -> bool: """Check if circuit is closed (allowing requests).""" - return self.state == 'CLOSED' - + return self.state == "CLOSED" + @property def is_half_open(self) -> bool: """Check if circuit is half-open (testing recovery).""" - return self.state == 'HALF-OPEN' - + return self.state == "HALF-OPEN" + def _check_timeout(self): """Check if recovery timeout has elapsed.""" - if self.state == 'OPEN' and self.last_failure_time: + if self.state == "OPEN" and self.last_failure_time: elapsed = time.time() - self.last_failure_time return elapsed >= self.recovery_timeout return False - + def _on_success(self): """Handle successful call.""" self.failures = 0 - if self.state == 'HALF-OPEN': - self.state = 'CLOSED' - + if self.state == "HALF-OPEN": + self.state = "CLOSED" + def _on_failure(self): """Handle failed call.""" self.failures += 1 self.last_failure_time = time.time() - + if self.failures >= self.failure_threshold: - self.state = 'OPEN' - + self.state = "OPEN" + def call(self, func: Callable) -> Any: """ Execute function with circuit breaker protection. - + Args: func: Function to execute - + Returns: Function result - + Raises: CircuitBreakerOpenError: If circuit is open Exception: Any exception from function execution """ if self._check_timeout(): - self.state = 'HALF-OPEN' - + self.state = "HALF-OPEN" + try: result = func() self._on_success() @@ -98,43 +97,45 @@ def call(self, func: Callable) -> Any: except Exception as e: self._on_failure() raise - + def __call__(self, func: Callable) -> Callable: """Decorator syntax.""" + @wraps(func) def wrapper(*args, **kwargs): return self.call(func)(*args, **kwargs) - return wrapper + return wrapper class CircuitBreakerOpenError(Exception): """Raised when circuit breaker is open.""" - pass + pass def circuit_breaker( failure_threshold: int = 5, recovery_timeout: float = 30.0, - success_threshold: int = 1 + success_threshold: int = 1, ) -> Callable: """ Decorator for adding circuit breaker to functions. - + Args: failure_threshold: Number of failures before opening recovery_timeout: Seconds before retrying success_threshold: Successes needed to close circuit - + Returns: Decorated function """ + def decorator(func: Callable) -> Callable: cb = CircuitBreaker( failure_threshold=failure_threshold, recovery_timeout=recovery_timeout, - success_threshold=success_threshold + success_threshold=success_threshold, ) - + @wraps(func) def wrapper(*args, **kwargs): if cb.is_open: @@ -143,13 +144,13 @@ def wrapper(*args, **kwargs): f"Last failure: {cb.last_failure_time}, " f"Timeout: {cb.recovery_timeout}s" ) - + try: return func(*args, **kwargs) except Exception as e: cb._on_failure() raise - + return wrapper - + return decorator diff --git a/prototype/controller.py b/prototype/controller.py index c921dfc..529be40 100644 --- a/prototype/controller.py +++ b/prototype/controller.py @@ -7,7 +7,6 @@ from prototype.model_tools import ToyModel, WeightSlice - class Controller: """ Model partitioning controller with safe serialization. diff --git a/prototype/controller_secure.py b/prototype/controller_secure.py index 75d5943..42eae8c 100644 --- a/prototype/controller_secure.py +++ b/prototype/controller_secure.py @@ -9,7 +9,6 @@ from prototype.crypto_improved import AEAD, PQCAdapter, ReplayProtectedAEAD, b64, ub64 from prototype.model_tools import ToyModel, WeightSlice - class SecureController: """ Secure controller with replay-protected encryption. @@ -143,7 +142,14 @@ def reconnect_worker(self, worker_url: str) -> bool: self.kems.pop(worker_url, None) return self.handshake_with_worker(worker_url) - def _post_with_retry(self, worker_url: str, path: str, payload: dict, timeout: int, max_attempts: int = 3): + def _post_with_retry( + self, + worker_url: str, + path: str, + payload: dict, + timeout: int, + max_attempts: int = 3, + ): """POST helper with exponential backoff for transient worker failures.""" backoff_base = 0.1 @@ -160,7 +166,9 @@ def _post_with_retry(self, worker_url: str, path: str, payload: dict, timeout: i ) time.sleep(sleep_t) - def _ensure_slice_on_worker(self, slice_id: str, worker_url: str, encrypt: bool = False) -> None: + def _ensure_slice_on_worker( + self, slice_id: str, worker_url: str, encrypt: bool = False + ) -> None: """Ensure a slice is present on a specific worker, used for failover/reconnect.""" if slice_id not in self.slice_cache: raise ValueError(f"slice cache miss for {slice_id}") @@ -267,7 +275,9 @@ def run_distributed(self, assigned, x_blob, encrypt=False): payload = { "slice_id": slice_id, "encrypted": True, - "manifest": {"client_id": self._client_id_for_worker(candidate)}, + "manifest": { + "client_id": self._client_id_for_worker(candidate) + }, "input_b64": b64(ct), "nonce_b64": b64(nonce), } @@ -277,7 +287,9 @@ def run_distributed(self, assigned, x_blob, encrypt=False): "input_b64": base64.b64encode(current).decode("ascii"), } - response = self._post_with_retry(candidate, "/execute", payload, timeout=30) + response = self._post_with_retry( + candidate, "/execute", payload, timeout=30 + ) used_worker = candidate break except Exception as exc: diff --git a/prototype/controller_service.py b/prototype/controller_service.py index 3f7c90d..d16312e 100644 --- a/prototype/controller_service.py +++ b/prototype/controller_service.py @@ -3,8 +3,8 @@ from __future__ import annotations import os -import uuid import threading +import uuid from datetime import datetime, timezone from typing import Literal from urllib.parse import urlparse @@ -15,11 +15,9 @@ app = FastAPI(title="Mohawk Controller Service", version="1.0.0") - class LoadModelRequest(BaseModel): model: str - class ChatRequest(BaseModel): message: str temperature: float = 0.7 @@ -27,20 +25,16 @@ class ChatRequest(BaseModel): max_tokens: int = 2048 system_prompt: str = "You are a helpful AI assistant." - class QueueRequest(BaseModel): priority: Literal["high", "normal"] = "normal" - class AddWorkerRequest(BaseModel): host: str = Field(min_length=1) port: int = Field(ge=1, le=65535) - class DownloadModelRequest(BaseModel): model_id: str - STATE = { "workers": [], "models": [ @@ -70,19 +64,16 @@ class DownloadModelRequest(BaseModel): STATE_LOCK = threading.RLock() - def _worker_urls() -> list[str]: raw = os.getenv("WORKER_URLS", "") return [item.strip() for item in raw.split(",") if item.strip()] - def _worker_host_port(worker_url: str) -> tuple[str, int]: parsed = urlparse(worker_url) host = parsed.hostname or worker_url.split("://", 1)[-1].split(":", 1)[0] port = parsed.port or 8000 return host, port - def _worker_entries_from_env() -> list[dict]: with STATE_LOCK: current_model = STATE["current_model"] @@ -103,7 +94,6 @@ def _worker_entries_from_env() -> list[dict]: ) return workers - def _merged_workers() -> list[dict]: env_workers = _worker_entries_from_env() with STATE_LOCK: @@ -116,12 +106,10 @@ def _merged_workers() -> list[dict]: merged.append(worker) return merged - def _session_status() -> str: with STATE_LOCK: return "Running" if STATE["current_model"] else "Idle" - def _synthesize_sessions() -> list[dict]: with STATE_LOCK: sessions = list(STATE["sessions"]) @@ -141,7 +129,6 @@ def _synthesize_sessions() -> list[dict]: } ] - def _check_worker_health(host: str, port: int) -> str: try: r = requests.get(f"http://{host}:{port}/health", timeout=1) @@ -149,12 +136,10 @@ def _check_worker_health(host: str, port: int) -> str: except Exception: return "Disconnected" - @app.get("/health") async def health() -> dict: return {"status": "healthy", "service": "controller"} - @app.get("/api/models") async def list_models() -> dict: with STATE_LOCK: @@ -166,20 +151,20 @@ async def list_models() -> dict: "current_model": current_model, } - @app.post("/api/models/load") async def load_model(request: LoadModelRequest) -> dict: with STATE_LOCK: names = {m["name"] for m in STATE["models"]} if request.model not in names: - raise HTTPException(status_code=404, detail=f"model not found: {request.model}") + raise HTTPException( + status_code=404, detail=f"model not found: {request.model}" + ) STATE["current_model"] = request.model for model in STATE["models"]: model["status"] = "Loaded" if model["name"] == request.model else "Ready" return {"status": "ok", "model": request.model} - @app.post("/api/models/download") async def download_model(request: DownloadModelRequest) -> dict: model_name = request.model_id.strip() @@ -189,7 +174,11 @@ async def download_model(request: DownloadModelRequest) -> dict: with STATE_LOCK: for model in STATE["models"]: if model["name"] == model_name: - return {"status": "ok", "model": model_name, "message": "Model already exists"} + return { + "status": "ok", + "model": model_name, + "message": "Model already exists", + } STATE["models"].append( { @@ -202,7 +191,6 @@ async def download_model(request: DownloadModelRequest) -> dict: ) return {"status": "ok", "model": model_name} - @app.get("/api/workers") async def list_workers() -> dict: workers = _merged_workers() @@ -214,16 +202,16 @@ async def list_workers() -> dict: return {"workers": workers} - @app.post("/api/workers/connect") async def connect_workers() -> dict: workers = _merged_workers() connected = sum( - 1 for worker in workers if _check_worker_health(worker["host"], worker["port"]) == "Connected" + 1 + for worker in workers + if _check_worker_health(worker["host"], worker["port"]) == "Connected" ) return {"status": "ok", "connected": connected, "total": len(workers)} - @app.post("/api/workers/add") async def add_worker(request: AddWorkerRequest) -> dict: host = request.host.strip() @@ -234,7 +222,9 @@ async def add_worker(request: AddWorkerRequest) -> dict: current_model = STATE["current_model"] existing = {(w["host"], w["port"]) for w in _merged_workers()} if (host, request.port) in existing: - raise HTTPException(status_code=409, detail=f"worker already exists: {host}:{request.port}") + raise HTTPException( + status_code=409, detail=f"worker already exists: {host}:{request.port}" + ) worker = { "id": f"worker_custom_{len(STATE['workers']) + 1}", @@ -249,7 +239,6 @@ async def add_worker(request: AddWorkerRequest) -> dict: STATE["workers"].append(worker) return {"status": "ok", "worker": worker} - @app.post("/api/queue") async def queue_job(request: QueueRequest) -> dict: job = { @@ -261,7 +250,6 @@ async def queue_job(request: QueueRequest) -> dict: STATE["queue"].append(job) return {"status": "ok", "job": job} - @app.post("/api/inference/chat") async def chat_inference(request: ChatRequest) -> dict: truncated = request.message.strip()[:240] @@ -271,17 +259,16 @@ async def chat_inference(request: ChatRequest) -> dict: with STATE_LOCK: model = STATE["current_model"] or "No model loaded" - response = ( - f"[{model}] {truncated}" - ) + response = f"[{model}] {truncated}" return {"status": "ok", "response": response} - @app.get("/api/metrics") async def metrics() -> dict: workers = _merged_workers() connected = sum( - 1 for worker in workers if _check_worker_health(worker["host"], worker["port"]) == "Connected" + 1 + for worker in workers + if _check_worker_health(worker["host"], worker["port"]) == "Connected" ) worker_count = max(len(workers), 1) return { @@ -298,19 +285,16 @@ async def metrics() -> dict: } } - @app.get("/api/sessions") async def sessions() -> dict: return {"sessions": _synthesize_sessions()} - @app.post("/api/sessions/{session_id}/cancel") async def cancel_session(session_id: str) -> dict: with STATE_LOCK: STATE["sessions"] = [s for s in STATE["sessions"] if s.get("id") != session_id] return {"status": "ok", "cancelled": session_id} - @app.post("/api/security/jwt/refresh") async def refresh_jwt() -> dict: with STATE_LOCK: @@ -321,7 +305,6 @@ async def refresh_jwt() -> dict: "refresh_count": refresh_count, } - @app.post("/api/security/pqc/enable") async def enable_pqc() -> dict: with STATE_LOCK: diff --git a/prototype/crypto.py b/prototype/crypto.py index cb7a0ae..16c6f8d 100644 --- a/prototype/crypto.py +++ b/prototype/crypto.py @@ -1,10 +1,10 @@ +import base64 +import os + +from cryptography.hazmat.primitives import hashes, serialization from cryptography.hazmat.primitives.asymmetric import x25519 from cryptography.hazmat.primitives.ciphers.aead import ChaCha20Poly1305 -from cryptography.hazmat.primitives import hashes from cryptography.hazmat.primitives.kdf.hkdf import HKDF -import os -import base64 -from cryptography.hazmat.primitives import serialization # Try to detect liboqs / pyOQS availability. If present, we'll expose # scaffolding for a PQC KEM; if not present, we gracefully fall back @@ -13,11 +13,11 @@ _oqs = None try: import oqs as _oqs # type: ignore + OQS_AVAILABLE = True except Exception: OQS_AVAILABLE = False - class PQCAdapter: """Hybrid PQC adapter scaffold. @@ -32,19 +32,19 @@ class PQCAdapter: implement a full liboqs hybrid KEM without large protocol changes. """ - def __init__(self, oqs_alg: str = 'Kyber512'): + def __init__(self, oqs_alg: str = "Kyber512"): self._priv = x25519.X25519PrivateKey.generate() self.pub = self._priv.public_key() self.oqs_supported = False self.oqs_alg = oqs_alg - self.oqs_public = b'' + self.oqs_public = b"" if OQS_AVAILABLE: try: - kem_cls = getattr(_oqs, 'KeyEncapsulation', None) + kem_cls = getattr(_oqs, "KeyEncapsulation", None) if kem_cls is None: - kem_cls = getattr(_oqs, 'KEM', None) + kem_cls = getattr(_oqs, "KEM", None) if kem_cls is None: - raise RuntimeError('No OQS KEM class available') + raise RuntimeError("No OQS KEM class available") self.kem = kem_cls(self.oqs_alg) pub = self.kem.generate_keypair() if isinstance(pub, tuple): @@ -53,7 +53,7 @@ def __init__(self, oqs_alg: str = 'Kyber512'): self.oqs_supported = True except Exception: self.kem = None - self.oqs_public = b'' + self.oqs_public = b"" self.oqs_supported = False def public_bytes(self) -> bytes: @@ -83,7 +83,7 @@ def derive_shared(self, peer_public_bytes: bytes) -> bytes: algorithm=hashes.SHA256(), length=32, salt=None, - info=b'mohawk-aead-key', + info=b"mohawk-aead-key", ) key = hkdf.derive(shared) return key @@ -93,75 +93,71 @@ def encap(self, peer_oqs_pub: bytes): """Encapsulate to `peer_oqs_pub` using the pyOQS KEM if available. Returns (ct, shared) or raises RuntimeError if not supported. """ - if not self.oqs_supported or not getattr(self, 'kem', None): - raise RuntimeError('OQS not available') + if not self.oqs_supported or not getattr(self, "kem", None): + raise RuntimeError("OQS not available") # Try common pyOQS method names defensively try: # pyOQS KeyEncapsulation API: kem.encap_secret(pub) or kem.encapsulate(pub) - if hasattr(self.kem, 'encap_secret'): + if hasattr(self.kem, "encap_secret"): ct, ss = self.kem.encap_secret(peer_oqs_pub) return ct, ss - if hasattr(self.kem, 'encapsulate'): + if hasattr(self.kem, "encapsulate"): ct, ss = self.kem.encapsulate(peer_oqs_pub) return ct, ss - if hasattr(self.kem, 'encap'): + if hasattr(self.kem, "encap"): ct, ss = self.kem.encap(peer_oqs_pub) return ct, ss except Exception as e: - raise RuntimeError('OQS encapsulation failed: %s' % e) - raise RuntimeError('OQS encapsulation not supported by this pyOQS build') + raise RuntimeError("OQS encapsulation failed: %s" % e) + raise RuntimeError("OQS encapsulation not supported by this pyOQS build") def decap(self, ct: bytes): """Decapsulate ciphertext `ct` using stored private key. Returns shared secret.""" - if not self.oqs_supported or not getattr(self, 'kem', None): - raise RuntimeError('OQS not available') + if not self.oqs_supported or not getattr(self, "kem", None): + raise RuntimeError("OQS not available") try: - if hasattr(self.kem, 'decap_secret'): + if hasattr(self.kem, "decap_secret"): ss = self.kem.decap_secret(ct) return ss - if hasattr(self.kem, 'decapsulate'): + if hasattr(self.kem, "decapsulate"): ss = self.kem.decapsulate(ct) return ss - if hasattr(self.kem, 'decap'): + if hasattr(self.kem, "decap"): ss = self.kem.decap(ct) return ss except Exception as e: - raise RuntimeError('OQS decapsulation failed: %s' % e) - raise RuntimeError('OQS decapsulation not supported by this pyOQS build') - + raise RuntimeError("OQS decapsulation failed: %s" % e) + raise RuntimeError("OQS decapsulation not supported by this pyOQS build") def derive_hybrid_key(shared_x25519: bytes, shared_oqs: bytes) -> bytes: """Derive a single AEAD key from two raw shared secrets (concatenate and run HKDF). This produces a 32-byte AEAD key. """ - combined = (shared_x25519 or b'') + (shared_oqs or b'') + combined = (shared_x25519 or b"") + (shared_oqs or b"") hkdf = HKDF( algorithm=hashes.SHA256(), length=32, salt=None, - info=b'mohawk-hybrid-aead-key', + info=b"mohawk-hybrid-aead-key", ) return hkdf.derive(combined) - class AEAD: def __init__(self, key: bytes): self.key = key self.aead = ChaCha20Poly1305(key) - def encrypt(self, plaintext: bytes, aad: bytes = b''): + def encrypt(self, plaintext: bytes, aad: bytes = b""): nonce = os.urandom(12) ct = self.aead.encrypt(nonce, plaintext, aad) return nonce, ct - def decrypt(self, nonce: bytes, ciphertext: bytes, aad: bytes = b''): + def decrypt(self, nonce: bytes, ciphertext: bytes, aad: bytes = b""): return self.aead.decrypt(nonce, ciphertext, aad) - # helpers def b64(x: bytes) -> str: - return base64.b64encode(x).decode('ascii') - + return base64.b64encode(x).decode("ascii") def ub64(s: str) -> bytes: return base64.b64decode(s) diff --git a/prototype/crypto_improved.py b/prototype/crypto_improved.py index 84966ba..7ee5aaa 100644 --- a/prototype/crypto_improved.py +++ b/prototype/crypto_improved.py @@ -22,7 +22,6 @@ except Exception: OQS_AVAILABLE = False - class ReplayProtectedAEAD: """ AEAD encryption with replay protection. @@ -118,7 +117,6 @@ def decrypt(self, nonce: bytes, ciphertext: bytes, aad: bytes = b"") -> bytes: # The AEAD authentication will still prevent tampering return self.aead.decrypt(nonce, ciphertext, aad) - class PQCAdapter: """Hybrid PQC adapter with improved key management.""" @@ -213,7 +211,6 @@ def decap(self, ct: bytes): raise RuntimeError("OQS decapsulation not supported") - def derive_hybrid_key(shared_x25519: bytes, shared_oqs: bytes) -> bytes: """Derive a single AEAD key from two raw shared secrets.""" combined = (shared_x25519 or b"") + (shared_oqs or b"") @@ -226,7 +223,6 @@ def derive_hybrid_key(shared_x25519: bytes, shared_oqs: bytes) -> bytes: ) return hkdf.derive(combined) - class AEAD: """ Basic AEAD encryption (without replay protection). @@ -246,11 +242,9 @@ def encrypt(self, plaintext: bytes, aad: bytes = b"") -> tuple: def decrypt(self, nonce: bytes, ciphertext: bytes, aad: bytes = b"") -> bytes: return self.aead.decrypt(nonce, ciphertext, aad) - # Helper functions def b64(x: bytes) -> str: return base64.b64encode(x).decode("ascii") - def ub64(s: str) -> bytes: return base64.b64decode(s) diff --git a/prototype/crypto_production.py b/prototype/crypto_production.py index f24076c..abbee26 100644 --- a/prototype/crypto_production.py +++ b/prototype/crypto_production.py @@ -1,33 +1,35 @@ # prototype/crypto_production.py (ENHANCED) -from typing import Optional, Tuple import os +from typing import Optional, Tuple + +from cryptography.hazmat.primitives import hashes from cryptography.hazmat.primitives.asymmetric import x25519 from cryptography.hazmat.primitives.ciphers.aead import ChaCha20Poly1305 from cryptography.hazmat.primitives.kdf.hkdf import HKDF -from cryptography.hazmat.primitives import hashes OQS_AVAILABLE = False try: import oqs as _oqs + OQS_AVAILABLE = True except Exception: pass - class ProductionPQCAdapter: """Production-ready PQC adapter with full hybrid KEM support.""" - - def __init__(self, oqs_alg: str = 'Kyber768'): + + def __init__(self, oqs_alg: str = "Kyber768"): self._priv_x25519 = x25519.X25519PrivateKey.generate() self.pub_x25519 = self._priv_x25519.public_key() - + self.oqs_supported = False self.oqs_alg = oqs_alg - + if OQS_AVAILABLE: try: - kem_cls = getattr(_oqs, 'KeyEncapsulation', None) or \ - getattr(_oqs, 'KEM', None) + kem_cls = getattr(_oqs, "KeyEncapsulation", None) or getattr( + _oqs, "KEM", None + ) if kem_cls: self.kem = kem_cls(oqs_alg) pub = self.kem.generate_keypair() @@ -37,90 +39,91 @@ def __init__(self, oqs_alg: str = 'Kyber768'): self.oqs_supported = True except Exception: pass - + def public_bytes(self) -> bytes: """Return X25519 public key.""" return self.pub_x25519.public_bytes( encoding=x25519.Encoding.Raw, format=x25519.PublicFormat.Raw, ) - + def get_oqs_public(self) -> Optional[bytes]: """Return OQS public key if available.""" return self.oqs_public if self.oqs_supported else None - + def derive_shared(self, peer_public_bytes: bytes) -> bytes: """Derive symmetric AEAD key from X25519 DH.""" peer_pub = x25519.X25519PublicKey.from_public_bytes(peer_public_bytes) shared = self._priv_x25519.exchange(peer_pub) - + hkdf = HKDF( algorithm=hashes.SHA384(), # Use SHA-384 for stronger security length=48, # 48 bytes: 32 for AEAD key + 16 for nonce IV - salt=b'mohawk-hybrid-key-salt', - info=b'hybrid-key-derivation-v2', + salt=b"mohawk-hybrid-key-salt", + info=b"hybrid-key-derivation-v2", ) - + return hkdf.derive(shared) - + def encap(self, peer_oqs_pub: bytes) -> Tuple[bytes, bytes]: """Encapsulate to peer's OQS public key.""" - if not self.oqs_supported or not getattr(self, 'kem', None): - raise RuntimeError('OQS not available') - + if not self.oqs_supported or not getattr(self, "kem", None): + raise RuntimeError("OQS not available") + # Use correct API method based on pyOQS version - if hasattr(self.kem, 'encapsulate'): + if hasattr(self.kem, "encapsulate"): ct, ss = self.kem.encapsulate(peer_oqs_pub) - elif hasattr(self.kem, 'encap_secret'): + elif hasattr(self.kem, "encap_secret"): ct, ss = self.kem.encap_secret(peer_oqs_pub) else: - raise AttributeError('Unsupported OQS encapsulation method') - + raise AttributeError("Unsupported OQS encapsulation method") + return ct, ss - + def decap(self, ct: bytes) -> bytes: """Decapsulate ciphertext to retrieve shared secret.""" - if not self.oqs_supported or not getattr(self, 'kem', None): - raise RuntimeError('OQS not available') - - if hasattr(self.kem, 'decapsulate'): + if not self.oqs_supported or not getattr(self, "kem", None): + raise RuntimeError("OQS not available") + + if hasattr(self.kem, "decapsulate"): ss = self.kem.decapsulate(ct) - elif hasattr(self.kem, 'decap_secret'): + elif hasattr(self.kem, "decap_secret"): ss = self.kem.decap_secret(ct) else: - raise AttributeError('Unsupported OQS decapsulation method') - - return ss + raise AttributeError("Unsupported OQS decapsulation method") + return ss class ReplayProtectedAEAD: """Production AEAD with replay protection.""" - + def __init__( - self, + self, key: bytes, expected_sender_id: str, nonce_expiry_seconds: int = 3600, - max_nonces_per_window: int = 1000 + max_nonces_per_window: int = 1000, ): self.key = key self.sender_id = expected_sender_id self.nonce_expiry = nonce_expiry_seconds self.max_nonces = max_nonces_per_window - + # Nonce tracking with time windows - self.seen_nonces: Dict[str, Tuple[float, int]] = {} # nonce_hex -> (timestamp, usage_count) - + self.seen_nonces: Dict[str, Tuple[float, int]] = ( + {} + ) # nonce_hex -> (timestamp, usage_count) + self.aead = ChaCha20Poly1305(key) - + def is_nonce_fresh(self, nonce: bytes) -> bool: """Check if nonce hasn't been used recently.""" nonce_str = nonce.hex() - + if nonce_str in self.seen_nonces: last_seen, usage_count = self.seen_nonces[nonce_str] time_diff = time.time() - last_seen - + # Check if within expiry window if time_diff < self.nonce_expiry: # Count usages in current window @@ -129,23 +132,23 @@ def is_nonce_fresh(self, nonce: bytes) -> bool: else: # First time seeing this nonce self.seen_nonces[nonce_str] = (time.time(), 1) - + return True - - def encrypt(self, plaintext: bytes, aad: bytes = b'') -> Tuple[bytes, bytes]: + + def encrypt(self, plaintext: bytes, aad: bytes = b"") -> Tuple[bytes, bytes]: """Encrypt with replay protection.""" nonce = os.urandom(12) - + # Check for replay before encryption if not self.is_nonce_fresh(nonce): raise ReplayError(f"Nonce {nonce.hex()} is stale") - + nonce, ct = self.aead.encrypt(nonce, plaintext, aad) return nonce, ct - - def decrypt(self, nonce: bytes, ciphertext: bytes, aad: bytes = b'') -> bytes: + + def decrypt(self, nonce: bytes, ciphertext: bytes, aad: bytes = b"") -> bytes: """Decrypt with replay protection.""" if not self.is_nonce_fresh(nonce): raise ReplayError(f"Nonce {nonce.hex()} is stale") - + return self.aead.decrypt(nonce, ciphertext, aad) diff --git a/prototype/gui_backend.py b/prototype/gui_backend.py index 1375226..89f9782 100644 --- a/prototype/gui_backend.py +++ b/prototype/gui_backend.py @@ -1,26 +1,30 @@ #!/usr/bin/env python3 """Mohawk GUI Backend Service - FastAPI Server with LAN Discovery""" -import sys import argparse +import logging import random -import time +import sys import threading -import requests -import logging +import time from datetime import datetime from typing import Dict, List, Optional +import requests import uvicorn from fastapi import FastAPI, HTTPException +from fastapi.middleware.cors import CORSMiddleware from fastapi.responses import JSONResponse from pydantic import BaseModel -from fastapi.middleware.cors import CORSMiddleware try: from prototype.service_discovery import ( - MohawkServiceDiscovery, LanServiceRegistry, MohawkService, get_local_ip + LanServiceRegistry, + MohawkService, + MohawkServiceDiscovery, + get_local_ip, ) + HAS_DISCOVERY = True except ImportError: HAS_DISCOVERY = False @@ -65,31 +69,33 @@ "error_count": 0, } - class HealthRequest(BaseModel): """Health check request.""" - status: str = "ok" + status: str = "ok" class InferenceRequest(BaseModel): """Inference request.""" + message: str temperature: float = 0.7 top_p: float = 0.9 max_tokens: int = 2048 system_prompt: str = "You are a helpful AI assistant." - class ModelRequest(BaseModel): """Model load request.""" - model: str + model: str @app.get("/health") async def health_check(): """Health check endpoint.""" - return {"status": "healthy", "service": "mohawk-gui", "timestamp": datetime.now().isoformat()} - + return { + "status": "healthy", + "service": "mohawk-gui", + "timestamp": datetime.now().isoformat(), + } @app.get("/") async def root(): @@ -99,10 +105,9 @@ async def root(): "version": "2.1.0", "status": "running", "local_ip": get_local_ip(), - "discovery_enabled": service_discovery is not None + "discovery_enabled": service_discovery is not None, } - @app.get("/api/health") async def api_health(): """API health check.""" @@ -110,33 +115,34 @@ async def api_health(): "status": "ok", "workers_connected": len(workers_connected), "current_model": current_model, - "active_sessions": len(active_sessions) + "active_sessions": len(active_sessions), } - @app.post("/api/inference/chat") async def inference_chat(req: InferenceRequest): """Process inference request - routes to worker.""" global current_model - + try: with metrics_lock: metrics["total_requests"] += 1 - + # Try to call worker service try: - worker_url = "http://mohawk-worker:8003" + import os + + worker_url = os.getenv("MOHAWK_WORKER_URL", "http://mohawk-worker:8003") worker_response = requests.post( f"{worker_url}/api/inference/chat", json={ "prompt": req.message, "temperature": req.temperature, "top_p": req.top_p, - "max_tokens": req.max_tokens + "max_tokens": req.max_tokens, }, - timeout=5 + timeout=5, ) - + if worker_response.status_code == 200: result = worker_response.json() with metrics_lock: @@ -145,42 +151,49 @@ async def inference_chat(req: InferenceRequest): metrics["latency_p50"] = random.randint(10, 20) metrics["latency_p95"] = random.randint(30, 60) metrics["latency_p99"] = random.randint(70, 100) - + return result except requests.RequestException: pass - + # Fallback to simulated response response = f"Response to: {req.message[:100]}..." tokens = random.randint(100, 500) - + with metrics_lock: metrics["success_count"] += 1 metrics["throughput"] = random.randint(800, 1500) metrics["latency_p50"] = random.randint(10, 20) metrics["latency_p95"] = random.randint(30, 60) metrics["latency_p99"] = random.randint(70, 100) - + return { "response": response, "tokens_used": tokens, "latency_ms": random.randint(5, 50), - "model": current_model or "Llama-3-8B-Instruct-Q4_K_M" + "model": current_model or "Llama-3-8B-Instruct-Q4_K_M", } - + except Exception as e: with metrics_lock: metrics["error_count"] += 1 raise HTTPException(status_code=500, detail=str(e)) - @app.get("/api/metrics") async def get_metrics(): """Get current metrics.""" + try: + import psutil + + with metrics_lock: + metrics["cpu"] = psutil.cpu_percent() + metrics["memory"] = psutil.virtual_memory().percent + # Keep GPU simulated or fallback if nvidia-smi doesn't exist + except Exception: + pass with metrics_lock: return dict(metrics) - @app.post("/api/metrics/update") async def update_metrics(data: dict): """Update metrics.""" @@ -188,7 +201,6 @@ async def update_metrics(data: dict): metrics.update(data) return {"status": "updated"} - @app.get("/api/models") async def list_models(): """List available models.""" @@ -199,89 +211,92 @@ async def list_models(): "size_gb": 7.2, "type": "LLM", "quantization": "Q4_K_M", - "status": "Ready" + "status": "Ready", }, { "name": "Mistral-7B-v0.3-Q5_K_M", "size_gb": 6.1, "type": "LLM", "quantization": "Q5_K_M", - "status": "Ready" + "status": "Ready", }, { "name": "CodeLlama-13B-Instruct-Q3_K_M", "size_gb": 9.8, "type": "LLM", "quantization": "Q3_K_M", - "status": "Ready" - } + "status": "Ready", + }, ] } - @app.post("/api/models/load") async def load_model(req: ModelRequest): """Load a model.""" global current_model current_model = req.model - + with metrics_lock: active_models[req.model] = { "loaded_at": datetime.now().isoformat(), - "status": "loaded" + "status": "loaded", } - + return { "status": "loaded", "model": req.model, "size_mb": random.randint(5000, 10000), - "load_time_ms": random.randint(500, 2000) + "load_time_ms": random.randint(500, 2000), } - @app.get("/api/workers") async def list_workers(): """List connected workers.""" workers = [] for wid, info in workers_connected.items(): - workers.append({ - "id": wid, - "host": "localhost", - "port": info.get("port", 8003), - "status": info.get("status", "connected"), - "model": current_model or "None", - "threads": 8, - "load": random.randint(10, 80) - }) - - return {"workers": workers, "total": len(workers)} + workers.append( + { + "id": wid, + "host": "localhost", + "port": info.get("port", 8003), + "status": info.get("status", "connected"), + "model": current_model or "None", + "threads": 8, + "load": random.randint(10, 80), + } + ) + return {"workers": workers, "total": len(workers)} @app.get("/api/sessions") async def list_sessions(): """List active sessions.""" sessions = [] for sid, session in active_sessions.items(): - sessions.append({ - "id": sid, - "model": session.get("model", "Llama-3-8B"), - "status": session.get("status", "Running"), - "throughput": random.randint(800, 1500), - "latency": random.randint(10, 50), - "tokens": random.randint(100, 500) - }) - - return {"sessions": sessions} + sessions.append( + { + "id": sid, + "model": session.get("model", "Llama-3-8B"), + "status": session.get("status", "Running"), + "throughput": random.randint(800, 1500), + "latency": random.randint(10, 50), + "tokens": random.randint(100, 500), + } + ) + return {"sessions": sessions} @app.post("/api/sessions/create") async def create_session(model: str = "Llama-3-8B"): """Create a new session.""" sid = f"sess_{int(time.time() * 1000) % 10000:04d}" - active_sessions[sid] = {"model": model, "status": "Running", "created": datetime.now()} + active_sessions[sid] = { + "model": model, + "status": "Running", + "created": datetime.now(), + } return {"session_id": sid, "model": model, "status": "created"} - @app.post("/api/sessions/{session_id}/cancel") async def cancel_session(session_id: str): """Cancel a session.""" @@ -290,54 +305,49 @@ async def cancel_session(session_id: str): return {"status": "cancelled"} raise HTTPException(status_code=404, detail="Session not found") - @app.post("/api/queue") async def queue_job(priority: str = "normal"): """Queue a job.""" return { "status": "queued", "job_id": f"job_{int(time.time() * 1000) % 10000:04d}", - "priority": priority + "priority": priority, } - @app.post("/api/workers/connect") async def connect_workers(): """Connect to worker services.""" try: - worker_response = requests.get( - "http://mohawk-worker:8003/health", - timeout=5 - ) + import os + + worker_url = os.getenv("MOHAWK_WORKER_URL", "http://mohawk-worker:8003") + worker_response = requests.get(f"{worker_url}/health", timeout=5) if worker_response.status_code == 200: workers_connected["worker_0"]["status"] = "connected" return { "status": "connected", "workers": list(workers_connected.keys()), - "count": len(workers_connected) + "count": len(workers_connected), } except requests.RequestException: pass - + return { "status": "connected", "workers": list(workers_connected.keys()), - "count": len(workers_connected) + "count": len(workers_connected), } - @app.post("/api/security/jwt/refresh") async def refresh_jwt_token(): """Refresh JWT token.""" return {"status": "refreshed", "token": "jwt_token_...", "expires_in": 86400} - @app.post("/api/security/pqc/enable") async def enable_pqc(): """Enable Post-Quantum Cryptography.""" return {"status": "enabled", "type": "hybrid_kem"} - # ============================================================================ # SERVICE DISCOVERY ENDPOINTS # ============================================================================ @@ -347,51 +357,39 @@ async def get_discovered_services(service_type: Optional[str] = None): """Get all discovered Mohawk services on LAN.""" if not service_discovery: return {"services": [], "count": 0, "error": "Discovery not available"} - - services = service_discovery.get_services(service_type) - return { - "services": [s.to_dict() for s in services], - "count": len(services) - } + services = service_discovery.get_services(service_type) + return {"services": [s.to_dict() for s in services], "count": len(services)} @app.get("/api/discovery/gui") async def get_gui_services(): """Get all discovered GUI services.""" if not service_discovery: return {"guis": [], "count": 0, "error": "Discovery not available"} - - services = service_discovery.find_gui_services() - return { - "guis": [s.to_dict() for s in services], - "count": len(services) - } + services = service_discovery.find_gui_services() + return {"guis": [s.to_dict() for s in services], "count": len(services)} @app.get("/api/discovery/workers") async def get_worker_services(): """Get all discovered worker services.""" if not service_discovery: return {"workers": [], "count": 0, "error": "Discovery not available"} - - services = service_discovery.find_worker_services() - return { - "workers": [s.to_dict() for s in services], - "count": len(services) - } + services = service_discovery.find_worker_services() + return {"workers": [s.to_dict() for s in services], "count": len(services)} @app.post("/api/discovery/connect/{service_name}") async def connect_to_discovered_service(service_name: str): """Connect to a discovered service.""" if not service_discovery: raise HTTPException(status_code=503, detail="Discovery not available") - + service = service_discovery.get_service_by_name(service_name) - + if not service: raise HTTPException(status_code=404, detail=f"Service {service_name} not found") - + # Try to connect try: response = requests.get(f"{service.url}/health", timeout=3) @@ -401,33 +399,28 @@ async def connect_to_discovered_service(service_name: str): workers_connected[service_name] = { "url": service.url, "status": "connected", - "discovered_at": service.discovered_at + "discovered_at": service.discovered_at, } - + return { "status": "connected", "service": service.to_dict(), - "url": service.url + "url": service.url, } except Exception as e: logger.error(f"Failed to connect to {service_name}: {e}") raise HTTPException(status_code=503, detail=f"Service unreachable: {str(e)}") - @app.post("/api/discovery/refresh") async def refresh_service_discovery(): """Refresh service discovery (rescan LAN).""" if not service_discovery: return {"status": "error", "message": "Discovery not available"} - + if not service_discovery._running: service_discovery.start() - - return { - "status": "refreshing", - "message": "Rescanning LAN for Mohawk services..." - } + return {"status": "refreshing", "message": "Rescanning LAN for Mohawk services..."} @app.get("/api/discovery/status") async def discovery_status(): @@ -437,27 +430,30 @@ async def discovery_status(): "discovery_enabled": False, "local_ip": get_local_ip(), "services_found": 0, - "workers_connected": len(workers_connected) + "workers_connected": len(workers_connected), } - + return { "discovery_enabled": True, "discovery_running": service_discovery._running, "local_ip": get_local_ip(), "services_found": len(service_discovery.discovered_services), - "workers_connected": len(workers_connected) + "workers_connected": len(workers_connected), } - def main(): """Main entry point.""" parser = argparse.ArgumentParser(description="Mohawk GUI Backend Service") parser.add_argument("--host", default="0.0.0.0", help="Host to bind to") parser.add_argument("--port", type=int, default=8003, help="Port to listen on") - parser.add_argument("--discovery", action="store_true", help="Enable LAN service discovery") - parser.add_argument("--register", action="store_true", help="Register this service for discovery") + parser.add_argument( + "--discovery", action="store_true", help="Enable LAN service discovery" + ) + parser.add_argument( + "--register", action="store_true", help="Register this service for discovery" + ) args = parser.parse_args() - + print("=" * 60) print("[MOHAWK GUI BACKEND] Starting Inference Engine GUI Service") print("=" * 60) @@ -466,23 +462,22 @@ def main(): if args.discovery: print("LAN Discovery: ENABLED") print("=" * 60) - + # Start service discovery if enabled if args.discovery and service_discovery: service_discovery.start() - + # Register this service if requested if args.register and service_discovery: registry = LanServiceRegistry( hostname="mohawk-gui", service_type="gui", port=args.port, - properties={"version": "2.1.0"} + properties={"version": "2.1.0"}, ) registry.register() - - uvicorn.run(app, host=args.host, port=args.port, log_level="info") + uvicorn.run(app, host=args.host, port=args.port, log_level="info") if __name__ == "__main__": main() diff --git a/prototype/hf_model_loader.py b/prototype/hf_model_loader.py index afe8e98..e73051b 100644 --- a/prototype/hf_model_loader.py +++ b/prototype/hf_model_loader.py @@ -1,92 +1,91 @@ # prototype/hf_model_loader.py (NEW) -from transformers import AutoModelForCausalLM, AutoTokenizer -import torch from typing import Dict, Optional, Tuple + import numpy as np +import torch +from transformers import AutoModelForCausalLM, AutoTokenizer class HuggingFaceModelLoader: """Production-grade HF model loading with optimization.""" - + def __init__( self, model_id: str, device_map: Optional[Dict[int, str]] = None, load_in_8bit: bool = False, load_in_4bit: bool = False, - quantization_config: Optional[dict] = None + quantization_config: Optional[dict] = None, ): self.model_id = model_id self.device_map = device_map self.load_in_8bit = load_in_8bit self.load_in_4bit = load_in_4bit - + def load_model(self) -> Tuple[torch.nn.Module, AutoTokenizer]: """Load HF model with optimal settings.""" # Determine loading strategy if self.load_in_4bit: - from bitsandbytes import AutoFloat8Quantizer from accelerate import dispatch_model - + from bitsandbytes import AutoFloat8Quantizer + model = AutoModelForCausalLM.from_pretrained( self.model_id, load_in_4bit=True, - quantization_config=quantization_config or { + quantization_config=quantization_config + or { "llm_int8_has_fp16_weight": False, "llm_int8_threshold": 6.0, - } + }, ) elif self.load_in_8bit: model = AutoModelForCausalLM.from_pretrained( - self.model_id, - load_in_8bit=True + self.model_id, load_in_8bit=True ) else: # Full precision with device mapping for multi-GPU model = AutoModelForCausalLM.from_pretrained( self.model_id, torch_dtype=torch.float16 if self.device_map else torch.float32, - device_map=self.device_map or "auto" + device_map=self.device_map or "auto", ) - + tokenizer = AutoTokenizer.from_pretrained(self.model_id) return model.eval(), tokenizer - + def slice_model_for_distribution( - self, - num_slices: int = 2, - split_strategy: str = "layer_boundary" + self, num_slices: int = 2, split_strategy: str = "layer_boundary" ) -> List[Dict[str, Any]]: """Partition HF model for distributed inference.""" # For transformer models, split at attention/MLP block boundaries from transformers import AutoConfig - + config = AutoConfig.from_pretrained(self.model_id) - num_layers = getattr(config, 'num_hidden_layers', 8) - + num_layers = getattr(config, "num_hidden_layers", 8) + slices = [] layers_per_slice = num_layers // num_slices - + for i in range(num_slices): start_layer = i * layers_per_slice end_layer = (i + 1) * layers_per_slice if i < num_slices - 1 else num_layers - + # Extract slice metadata slice_metadata = { "slice_id": f"hf_slice_{start_layer}_{end_layer}", "start_layer": start_layer, "end_layer": end_layer, "param_count": self._count_parameters(start_layer, end_layer), - "compute_flops": self._estimate_compute(start_layer, end_layer) + "compute_flops": self._estimate_compute(start_layer, end_layer), } slices.append(slice_metadata) - + return slices - + def _count_parameters(self, start: int, end: int) -> int: """Count parameters in layer range.""" # Implementation to count transformer weights pass - + def _estimate_compute(self, start: int, end: int) -> float: """Estimate FLOPs per token for slice.""" # Implementation based on attention heads + MLP size diff --git a/prototype/integration_helpers.py b/prototype/integration_helpers.py index 8a521dd..072e960 100644 --- a/prototype/integration_helpers.py +++ b/prototype/integration_helpers.py @@ -6,7 +6,6 @@ from prototype import worker_secure - def reset_worker_state() -> None: worker_secure.slices.clear() worker_secure.keys.clear() @@ -14,13 +13,11 @@ def reset_worker_state() -> None: for key in worker_secure.metrics: worker_secure.metrics[key] = 0 - def make_worker_client() -> httpx.Client: reset_worker_state() transport = httpx.ASGITransport(app=worker_secure.app) return httpx.Client(transport=transport, base_url="http://worker-inproc") - class _InProcessResponse: def __init__(self, response, url: str): self._response = response @@ -38,7 +35,6 @@ def raise_for_status(self): response=self._response, ) - class InProcessWorkerTransport: def __init__(self, client: httpx.Client): self.client = client diff --git a/prototype/load_harness.py b/prototype/load_harness.py index 90d1467..7639cf1 100644 --- a/prototype/load_harness.py +++ b/prototype/load_harness.py @@ -1,44 +1,48 @@ import time +from concurrent.futures import ThreadPoolExecutor, as_completed + import numpy as np + from prototype.model_tools import ToyModel from prototype.session_manager import SessionManager -from concurrent.futures import ThreadPoolExecutor, as_completed - def run_session_sync(sm: SessionManager, model, session_idx, encrypt=False): sid = sm.start_session(model, num_slices=2, encrypt=encrypt) - x = np.random.default_rng(session_idx).standard_normal((8,1)).astype('float32') + x = np.random.default_rng(session_idx).standard_normal((8, 1)).astype("float32") out = sm.infer(sid, x) sm.end_session(sid) return out - def run_load(workers, concurrency=20, total=100, encrypt=False): sm = SessionManager(workers) - model = ToyModel([8,16,16,8], seed=42) + model = ToyModel([8, 16, 16, 8], seed=42) results = [] start = time.time() with ThreadPoolExecutor(max_workers=concurrency) as ex: - futures = [ex.submit(run_session_sync, sm, model, i, encrypt) for i in range(total)] + futures = [ + ex.submit(run_session_sync, sm, model, i, encrypt) for i in range(total) + ] for f in as_completed(futures): results.append(f.result()) end = time.time() print(f"Completed {total} sessions in {end-start:.2f}s") return results - -if __name__ == '__main__': +if __name__ == "__main__": workers = ["http://127.0.0.1:8003", "http://127.0.0.1:8003"] - import requests, json + import json + + import requests + runs = [ - {'concurrency': 50, 'total': 200}, - {'concurrency': 100, 'total': 500}, - {'concurrency': 200, 'total': 1000}, + {"concurrency": 50, "total": 200}, + {"concurrency": 100, "total": 500}, + {"concurrency": 200, "total": 1000}, ] all_agg = {} for rconf in runs: - c = rconf['concurrency'] - t = rconf['total'] + c = rconf["concurrency"] + t = rconf["total"] print(f"Starting run total={t} concurrency={c}") run_load(workers, concurrency=c, total=t, encrypt=True) # fetch metrics from workers @@ -57,7 +61,7 @@ def run_load(workers, concurrency=20, total=100, encrypt=False): all_agg[f"run_{t}"] = agg # persist a copy try: - with open(f"/tmp/metrics_run_{t}.json", 'w') as fh: + with open(f"/tmp/metrics_run_{t}.json", "w") as fh: json.dump(agg, fh) except Exception as e: print(f"failed to write metrics file: {e}") diff --git a/prototype/model_quantize.py b/prototype/model_quantize.py index 06f477e..12c50a6 100644 --- a/prototype/model_quantize.py +++ b/prototype/model_quantize.py @@ -1,54 +1,49 @@ # prototype/model_quantize.py (NEW) from typing import Optional, Union -import torch + import numpy as np +import torch class ModelQuantizer: """Production model quantization for memory efficiency.""" - + def __init__(self): pass - + def quantize_to_int8(self, model: torch.nn.Module) -> torch.nn.Module: """Quantize model to INT8 for CPU inference.""" from optimum.quanto import QuantizationConfig - - config = QuantizationConfig( - "int8", - default_target_device="cpu" - ) - + + config = QuantizationConfig("int8", default_target_device="cpu") + # Quantize weights in-place or create new model quantized_model = optimum.exporters.tasks.from_transformers( - model, - task="text-generation", - quantization_config=config + model, task="text-generation", quantization_config=config ) - + return quantized_model - - def kv_cache_quantize(self, - model: torch.nn.Module, - bits: int = 8) -> torch.nn.Module: + + def kv_cache_quantize( + self, model: torch.nn.Module, bits: int = 8 + ) -> torch.nn.Module: """Quantize only KV cache (memory intensive).""" # Only quantize attention KV caches for name, module in model.named_modules(): - if 'attention' in name.lower() and isinstance(module, torch.nn.Linear): - if 'q_proj' in name or 'k_proj' in name: + if "attention" in name.lower() and isinstance(module, torch.nn.Linear): + if "q_proj" in name or "k_proj" in name: # Quantize to INT8 pass - + return model - - def mixed_precision_split(self, - model: torch.nn.Module) -> Tuple[torch.nn.Module]: + + def mixed_precision_split(self, model: torch.nn.Module) -> Tuple[torch.nn.Module]: """Split model into FP16 (compute-heavy) and FP32 (precision-critical).""" # Move attention layers to FP16 # Keep RMSNorm/Embedding in FP32 - + fp16_layers = [] fp32_layers = [] - + for name, module in model.named_modules(): if isinstance(module, torch.nn.Linear): # Compute-heavy: use FP16 @@ -56,5 +51,5 @@ def mixed_precision_split(self, elif isinstance(module, (torch.nn.LayerNorm, torch.nn.Embedding)): # Precision-critical: keep FP32 fp32_layers.append((name, module)) - + return fp16_layers, fp32_layers diff --git a/prototype/model_tools.py b/prototype/model_tools.py index 919133f..380355a 100644 --- a/prototype/model_tools.py +++ b/prototype/model_tools.py @@ -3,14 +3,13 @@ Uses numpy.tobytes() for weights and protobuf-like manifest format. """ -import time -import struct import io +import struct +import time from typing import Dict, Optional, Tuple import numpy as np - class WeightSlice: """Encapsulates a model slice with metadata.""" @@ -142,7 +141,6 @@ def __repr__(self): f"WeightSlice({self.start_layer}:{self.end_layer}, version={self.version})" ) - class ToyModel: """ Neural network model with safe binary serialization. @@ -310,7 +308,6 @@ def from_bytes(cls, data: bytes, version: str = "v1.0") -> "ToyModel": def __repr__(self): return f"ToyModel(layers={self.layer_sizes}, version={self.version})" - def create_model_from_slice(slice_obj: WeightSlice) -> ToyModel: """Create a ToyModel from a WeightSlice for testing.""" # This is mainly for debugging - in production use the slice directly diff --git a/prototype/model_tools_backup.py b/prototype/model_tools_backup.py index 7aee7e6..c24dcec 100644 --- a/prototype/model_tools_backup.py +++ b/prototype/model_tools_backup.py @@ -8,7 +8,6 @@ import numpy as np - class WeightSlice: """Encapsulates a model slice with metadata.""" @@ -95,7 +94,6 @@ def __repr__(self): f"WeightSlice({self.start_layer}:{self.end_layer}, version={self.version})" ) - class ToyModel: """ Neural network model with safe binary serialization. @@ -258,7 +256,6 @@ def from_bytes(cls, data: bytes, version: str = "v1.0") -> "ToyModel": def __repr__(self): return f"ToyModel(layers={self.layer_sizes}, version={self.version})" - def create_model_from_slice(slice_obj: WeightSlice) -> ToyModel: """Create a ToyModel from a WeightSlice for testing.""" # This is mainly for debugging - in production use the slice directly diff --git a/prototype/model_tools_v2.py b/prototype/model_tools_v2.py index 3c82538..c24dcec 100644 --- a/prototype/model_tools_v2.py +++ b/prototype/model_tools_v2.py @@ -3,22 +3,26 @@ Uses numpy.tobytes() for weights and protobuf-like manifest format. """ -import numpy as np import time -from typing import Dict, Tuple, Optional +from typing import Dict, Optional, Tuple +import numpy as np class WeightSlice: """Encapsulates a model slice with metadata.""" - - def __init__(self, start_layer: int, end_layer: int, - weights: Tuple[Tuple[np.ndarray, np.ndarray], ...], - version: str = "v1.0"): + + def __init__( + self, + start_layer: int, + end_layer: int, + weights: Tuple[Tuple[np.ndarray, np.ndarray], ...], + version: str = "v1.0", + ): self.start_layer = start_layer self.end_layer = end_layer self.weights = weights # List of (weight, bias) tuples self.version = version - + def to_bytes(self) -> bytes: """Serialize weights to binary format (no pickle).""" # Pack all weight and bias arrays into a single binary blob @@ -26,110 +30,122 @@ def to_bytes(self) -> bytes: for w, b in self.weights: packed.append(w.tobytes()) packed.append(b.tobytes()) - return b'\x00'.join(packed) - + return b"\x00".join(packed) + @classmethod - def from_bytes(cls, data: bytes, start: int, end: int, version: str = "v1.0") -> 'WeightSlice': + def from_bytes( + cls, data: bytes, start: int, end: int, version: str = "v1.0" + ) -> "WeightSlice": """Deserialize weights from binary format.""" # Split by null bytes and reconstruct arrays weight_data = [] idx = 0 while idx < len(data): - if data[idx:idx+1] == b'\x00': + if data[idx : idx + 1] == b"\x00": idx += 1 else: # Find end of this array (next null byte) - end_idx = data.find(b'\x00', idx) + end_idx = data.find(b"\x00", idx) if end_idx == -1: end_idx = len(data) weight_data.append(data[idx:end_idx]) idx = end_idx + 1 - + # Reconstruct arrays from bytes weights = [] i = 0 while i < len(weight_data): w_bytes = weight_data[i] - b_bytes = weight_data[i+1] if i+1 < len(weight_data) else b'' - + b_bytes = weight_data[i + 1] if i + 1 < len(weight_data) else b"" + # Try to infer shape from data size (simplified - assumes known shapes) try: w = np.frombuffer(w_bytes, dtype=np.float32) - b = np.frombuffer(b_bytes, dtype=np.float32) if b_bytes else np.array([]) + b = ( + np.frombuffer(b_bytes, dtype=np.float32) + if b_bytes + else np.array([]) + ) weights.append((w, b)) except Exception: # Fallback: reshape based on common layer sizes w = np.frombuffer(w_bytes, dtype=np.float32).reshape(-1, 8) - b = np.frombuffer(b_bytes, dtype=np.float32).reshape(-1, 1) if len(b_bytes) > 0 else np.array([]) + b = ( + np.frombuffer(b_bytes, dtype=np.float32).reshape(-1, 1) + if len(b_bytes) > 0 + else np.array([]) + ) weights.append((w, b)) - + i += 2 - + return cls(start, end, tuple(weights), version) - + def get_shapes(self) -> Dict[str, Tuple[int, ...]]: """Get shapes of all weight/bias arrays.""" shapes = {} for i, (w, b) in enumerate(self.weights): - shapes[f'layer_{self.start_layer}_{i}_weight'] = w.shape - shapes[f'layer_{self.start_layer}_{i}_bias'] = b.shape if len(b) > 0 else () + shapes[f"layer_{self.start_layer}_{i}_weight"] = w.shape + shapes[f"layer_{self.start_layer}_{i}_bias"] = b.shape if len(b) > 0 else () return shapes - - def __repr__(self): - return f"WeightSlice({self.start_layer}:{self.end_layer}, version={self.version})" + def __repr__(self): + return ( + f"WeightSlice({self.start_layer}:{self.end_layer}, version={self.version})" + ) class ToyModel: """ Neural network model with safe binary serialization. - + Replaces pickle-based serialization with numpy.tobytes() for security. Maintains numerical correctness while preventing deserialization attacks. """ - + def __init__(self, layer_sizes: list, seed: int = 0, version: str = "v1.0"): rng = np.random.default_rng(seed) self.weights = [] self.shapes = [] - + for i in range(len(layer_sizes) - 1): - w = rng.standard_normal((layer_sizes[i+1], layer_sizes[i])).astype(np.float32) - b = rng.standard_normal((layer_sizes[i+1],)).astype(np.float32) + w = rng.standard_normal((layer_sizes[i + 1], layer_sizes[i])).astype( + np.float32 + ) + b = rng.standard_normal((layer_sizes[i + 1],)).astype(np.float32) self.weights.append((w, b)) - self.shapes.append((layer_sizes[i+1], layer_sizes[i])) - + self.shapes.append((layer_sizes[i + 1], layer_sizes[i])) + self.layer_sizes = layer_sizes self.version = version - + def forward(self, x: np.ndarray) -> np.ndarray: """Forward pass through all layers.""" out = x - for (w, b) in self.weights: + for w, b in self.weights: out = w @ out + b[:, None] out = np.tanh(out) return out - + def apply(self, x: np.ndarray) -> np.ndarray: """Alias for forward().""" return self.forward(x) - + def slice(self, start_layer: int, end_layer: int) -> WeightSlice: """Create a WeightSlice with subset of layers.""" weights = self.weights[start_layer:end_layer] shapes = self.get_slice_shapes(start_layer, end_layer) return WeightSlice( - start=start_layer, - end=end_layer, - weights=weights, - version=self.version + start=start_layer, end=end_layer, weights=weights, version=self.version ) - + @staticmethod def get_slice_shapes(start: int, end: list) -> Dict[str, Tuple[int, ...]]: """Get shapes for a slice (used during partitioning).""" - return {f'layer_{start}_{i}_weight': ToyModel._infer_shape(i) - for i in range(len(end))} - + return { + f"layer_{start}_{i}_weight": ToyModel._infer_shape(i) + for i in range(len(end)) + } + @staticmethod def _infer_shape(layer_idx: int) -> Tuple[int, ...]: """Infer shape based on layer index (for deserialization).""" @@ -138,7 +154,7 @@ def _infer_shape(layer_idx: int) -> Tuple[int, ...]: return (16, 8) else: return (8,) - + def to_bytes(self) -> bytes: """Serialize entire model to binary format.""" packed = [] @@ -151,93 +167,96 @@ def to_bytes(self) -> bytes: header += f"layer_{i}:\n".encode() header += f" weight_shape: {w.shape}\n".encode() header += f" bias_shape: {b.shape}\n".encode() - return header + b'\x00'.join(packed) - + return header + b"\x00".join(packed) + @classmethod - def from_bytes(cls, data: bytes, version: str = "v1.0") -> 'ToyModel': + def from_bytes(cls, data: bytes, version: str = "v1.0") -> "ToyModel": """Deserialize model from binary format.""" # Parse header - lines = data.split(b'\n') + lines = data.split(b"\n") header_end = 0 for i, line in enumerate(lines): - if line.startswith(b'layer_'): + if line.startswith(b"layer_"): header_end = i break - + # Extract version version_line = lines[0].decode() if lines else f"version:{version}" - if 'version:' in version_line: - version = version_line.split(':', 1)[1].strip() - + if "version:" in version_line: + version = version_line.split(":", 1)[1].strip() + # Parse shapes from header shape_info = {} for line in lines[header_end:]: - if line.startswith(b'layer_'): + if line.startswith(b"layer_"): layer_str = line.decode().strip() - if 'weight_shape:' in layer_str: - parts = layer_str.split('weight_shape: ')[1].split(')') + if "weight_shape:" in layer_str: + parts = layer_str.split("weight_shape: ")[1].split(")") shape_str = parts[0] - dims = [int(x.strip()) for x in shape_str.replace(',', ' ').split()] - shape_info['weight'] = tuple(dims) - if 'bias_shape:' in layer_str: - parts = layer_str.split('bias_shape: ')[1].split(')') + dims = [int(x.strip()) for x in shape_str.replace(",", " ").split()] + shape_info["weight"] = tuple(dims) + if "bias_shape:" in layer_str: + parts = layer_str.split("bias_shape: ")[1].split(")") shape_str = parts[0] - dims = [int(x.strip()) for x in shape_str.replace(',', ' ').split()] - shape_info['bias'] = tuple(dims) if dims else (8,) - + dims = [int(x.strip()) for x in shape_str.replace(",", " ").split()] + shape_info["bias"] = tuple(dims) if dims else (8,) + # Reconstruct model from binary data weight_data = [] idx = header_end + 1 while idx < len(data): - if data[idx:idx+1] == b'\x00': + if data[idx : idx + 1] == b"\x00": idx += 1 else: - end_idx = data.find(b'\x00', idx) + end_idx = data.find(b"\x00", idx) if end_idx == -1: end_idx = len(data) weight_data.append(data[idx:end_idx]) idx = end_idx + 1 - + # Reconstruct weights weights = [] i = 0 while i < len(weight_data): w_bytes = weight_data[i] - b_bytes = weight_data[i+1] if i+1 < len(weight_data) else b'' - + b_bytes = weight_data[i + 1] if i + 1 < len(weight_data) else b"" + try: w = np.frombuffer(w_bytes, dtype=np.float32) - b = np.frombuffer(b_bytes, dtype=np.float32) if b_bytes else np.array([]) + b = ( + np.frombuffer(b_bytes, dtype=np.float32) + if b_bytes + else np.array([]) + ) # Infer shapes from header info or defaults - ws = shape_info.get('weight', (16, 8)) - bs = shape_info.get('bias', (8,)) if len(b_bytes) > 0 else () - + ws = shape_info.get("weight", (16, 8)) + bs = shape_info.get("bias", (8,)) if len(b_bytes) > 0 else () + # Reshape based on known shapes if len(ws) == 2: w = w.reshape(ws) if len(bs) == 1 and len(b) > 0: b = b.reshape((bs[0],)) - + weights.append((w, b)) except Exception as e: # Fallback shapes w = np.frombuffer(w_bytes, dtype=np.float32).reshape(-1, 8) - b = np.frombuffer(b_bytes, dtype=np.float32).reshape(-1, 1) if len(b_bytes) > 0 else np.array([]) + b = ( + np.frombuffer(b_bytes, dtype=np.float32).reshape(-1, 1) + if len(b_bytes) > 0 + else np.array([]) + ) weights.append((w, b)) - + i += 2 - + return cls(layer_sizes=[8, 16, 16, 8], seed=42, version=version) - + def __repr__(self): return f"ToyModel(layers={self.layer_sizes}, version={self.version})" - def create_model_from_slice(slice_obj: WeightSlice) -> ToyModel: """Create a ToyModel from a WeightSlice for testing.""" # This is mainly for debugging - in production use the slice directly - return ToyModel( - layer_sizes=[8, 16, 16, 8], - seed=42, - version=slice_obj.version - ) + return ToyModel(layer_sizes=[8, 16, 16, 8], seed=42, version=slice_obj.version) diff --git a/prototype/mohawk_operator.py b/prototype/mohawk_operator.py index 3bce631..1f066ce 100644 --- a/prototype/mohawk_operator.py +++ b/prototype/mohawk_operator.py @@ -1,120 +1,116 @@ # prototype/mohawk_operator.py (NEW) - K8s operator for deployment +import time + import kubernetes as k8s from kubernetes.client import AppsV1Api, CoreV1Api -import time class MohawkOperator: """Kubernetes operator for Mohawk Inference Engine deployment.""" - + def __init__(self, namespace: str = "mohawk"): self.apps_v1 = AppsV1Api() self.core_v1 = CoreV1Api() self.namespace = namespace - + def deploy_worker_statefulset( self, replicas: int, model_id: str, - worker_image: str = "rwilliamspbg-ops/mohawk-worker:latest" + worker_image: str = "rwilliamspbg-ops/mohawk-worker:latest", ): """Deploy worker StatefulSet with GPU scheduling.""" - + stateful_set = { "apiVersion": "apps/v1", "kind": "StatefulSet", "metadata": { "name": "mohawk-worker", "namespace": self.namespace, - "labels": {"app": "mohawk-worker"} + "labels": {"app": "mohawk-worker"}, }, "spec": { "serviceName": "mohawk-workers", "replicas": replicas, - "selector": { - "matchLabels": {"app": "mohawk-worker"} - }, + "selector": {"matchLabels": {"app": "mohawk-worker"}}, "template": { - "metadata": { - "labels": {"app": "mohawk-worker"} - }, + "metadata": {"labels": {"app": "mohawk-worker"}}, "spec": { - "containers": [{ - "name": "worker", - "image": worker_image, - "ports": [{"containerPort": 8003}], - "resources": { - "requests": {"cpu": "4", "memory": "16Gi"}, - "limits": {"cpu": "8", "memory": "24Gi"} - }, - "env": [ - {"name": "WORKER_PORT", "value": "8003"}, - {"name": "ENABLE_PQC", "value": "true"}, - {"name": "MODEL_ID", "value": model_id} - ], - "volumeMounts": [{ + "containers": [ + { + "name": "worker", + "image": worker_image, + "ports": [{"containerPort": 8003}], + "resources": { + "requests": {"cpu": "4", "memory": "16Gi"}, + "limits": {"cpu": "8", "memory": "24Gi"}, + }, + "env": [ + {"name": "WORKER_PORT", "value": "8003"}, + {"name": "ENABLE_PQC", "value": "true"}, + {"name": "MODEL_ID", "value": model_id}, + ], + "volumeMounts": [ + { + "name": "model-weights", + "mountPath": "/app/weights", + "readOnly": True, + } + ], + } + ], + "volumes": [ + { "name": "model-weights", - "mountPath": "/app/weights", - "readOnly": True - }] - }], - "volumes": [{ - "name": "model-weights", - "persistentVolumeClaim": { - "claimName": "mohawk-model-weights-pvc" + "persistentVolumeClaim": { + "claimName": "mohawk-model-weights-pvc" + }, } - }] - } - } - } + ], + }, + }, + }, } - + k8s_api = k8s.client.ApiClient() stateful_set_obj = k8s.client.V1StatefulSet.from_dict(stateful_set) self.apps_v1.create_namespaced_stateful_set( - namespace=self.namespace, - body=stateful_set_obj + namespace=self.namespace, body=stateful_set_obj ) - + def deploy_controller_deployment(self, replicas: int): """Deploy controller Deployment.""" - + deployment = { "apiVersion": "apps/v1", "kind": "Deployment", - "metadata": { - "name": "mohawk-controller", - "namespace": self.namespace - }, + "metadata": {"name": "mohawk-controller", "namespace": self.namespace}, "spec": { "replicas": replicas, - "selector": { - "matchLabels": {"app": "mohawk-controller"} - }, + "selector": {"matchLabels": {"app": "mohawk-controller"}}, "template": { - "metadata": { - "labels": {"app": "mohawk-controller"} - }, + "metadata": {"labels": {"app": "mohawk-controller"}}, "spec": { - "containers": [{ - "name": "controller", - "image": "rwilliamspbg-ops/mohawk-controller:latest", - "ports": [{"containerPort": 9000}], - "resources": { - "requests": {"cpu": "2", "memory": "8Gi"}, - "limits": {"cpu": "4", "memory": "16Gi"} + "containers": [ + { + "name": "controller", + "image": "rwilliamspbg-ops/mohawk-controller:latest", + "ports": [{"containerPort": 9000}], + "resources": { + "requests": {"cpu": "2", "memory": "8Gi"}, + "limits": {"cpu": "4", "memory": "16Gi"}, + }, } - }] - } - } - } + ] + }, + }, + }, } - + deployment_obj = k8s.client.V1Deployment.from_dict(deployment) self.apps_v1.create_namespaced_deployment( - namespace=self.namespace, - body=deployment_obj + namespace=self.namespace, body=deployment_obj ) - + def deploy_prometheus_monitoring(self): """Deploy Prometheus for monitoring.""" # Create ServiceMonitor for Mohawk workers @@ -124,58 +120,49 @@ def deploy_prometheus_monitoring(self): "kind": "ServiceMonitor", "metadata": { "name": "mohawk-worker-monitor", - "namespace": self.namespace + "namespace": self.namespace, }, "spec": { - "selector": { - "matchLabels": {"app": "mohawk-worker"} - }, - "endpoints": [{ - "port": "http-metrics", - "path": "/metrics", - "interval": "15s" - }] - } + "selector": {"matchLabels": {"app": "mohawk-worker"}}, + "endpoints": [ + {"port": "http-metrics", "path": "/metrics", "interval": "15s"} + ], + }, } ] - + for crd in prometheus_crds: core_api = k8s.client.ApiClient() # Create CRD objects pass - + def scale_workers(self, target_replicas: int): """Scale workers using HorizontalPodAutoscaler.""" hpa = { "apiVersion": "autoscaling/v2", "kind": "HorizontalPodAutoscaler", - "metadata": { - "name": "mohawk-worker-hpa", - "namespace": self.namespace - }, + "metadata": {"name": "mohawk-worker-hpa", "namespace": self.namespace}, "spec": { "scaleTargetRef": { "apiVersion": "apps/v1", "kind": "StatefulSet", - "name": "mohawk-worker" + "name": "mohawk-worker", }, "minReplicas": 3, "maxReplicas": 12, - "metrics": [{ - "type": "Resource", - "resource": { - "name": "cpu", - "target": { - "type": "Utilization", - "averageUtilization": 70 - } + "metrics": [ + { + "type": "Resource", + "resource": { + "name": "cpu", + "target": {"type": "Utilization", "averageUtilization": 70}, + }, } - }] - } + ], + }, } - + hpa_obj = k8s.client.V1HorizontalPodAutoscaler.from_dict(hpa) self.apps_v1.create_namespaced_horizontal_pod_autoscaler( - namespace=self.namespace, - body=hpa_obj + namespace=self.namespace, body=hpa_obj ) diff --git a/prototype/production_scheduler.py b/prototype/production_scheduler.py index 3a3237d..e966076 100644 --- a/prototype/production_scheduler.py +++ b/prototype/production_scheduler.py @@ -1,13 +1,15 @@ # prototype/production_scheduler.py (ENHANCED) -from typing import Dict, List, Optional +import threading import time -import requests from dataclasses import dataclass, field -import threading +from typing import Dict, List, Optional + +import requests @dataclass class WorkerHealthMetrics: """Real-time worker health metrics.""" + gpu_utilization: float = 0.0 memory_free_gb: float = 0.0 cpu_utilization: float = 0.0 @@ -16,7 +18,7 @@ class WorkerHealthMetrics: p99_latency_ms: float = 0.0 is_healthy: bool = True last_error: Optional[str] = None - + def __post_init__(self): # Validate ranges if not (0 <= self.gpu_utilization <= 1): @@ -24,34 +26,35 @@ def __post_init__(self): class ProductionScheduler: """Production-grade cost-aware scheduler with real-time metrics.""" - + def __init__( self, workers: List[str], health_endpoint: str = "/metrics", health_interval: float = 5.0, circuit_breaker_threshold: int = 5, - circuit_breaker_timeout: int = 30 + circuit_breaker_timeout: int = 30, ): self.workers = [w for w in workers if w.startswith("http")] self.health_endpoint = health_endpoint self.health_interval = health_interval - + # Worker profiles with real-time metrics self.worker_metrics: Dict[str, WorkerHealthMetrics] = {} self._metrics_lock = threading.Lock() - + # Circuit breaker state self.circuit_breakers: Dict[str, CircuitBreaker] = { w: CircuitBreaker( failure_threshold=circuit_breaker_threshold, - timeout=circuit_breaker_timeout - ) for w in workers + timeout=circuit_breaker_timeout, + ) + for w in workers } - + # Last health check time self._last_health_check: Dict[str, float] = {w: time.time() for w in workers} - + def update_worker_metrics(self): """Poll all workers for real-time metrics.""" for worker in self.workers: @@ -60,96 +63,110 @@ def update_worker_metrics(self): if resp.status_code == 200: metrics_data = resp.json() worker_url = worker.replace("/metrics", "") - + # Parse Prometheus metrics gpu_util = self._parse_metric(metrics_data, "gpu_utilization", 0.0) - mem_free_gb = self._parse_metric(metrics_data, "memory_free_gb", 0.0) - + mem_free_gb = self._parse_metric( + metrics_data, "memory_free_gb", 0.0 + ) + self.worker_metrics[worker_url] = WorkerHealthMetrics( gpu_utilization=gpu_util, memory_free_gb=mem_free_gb, - cpu_utilization=self._parse_metric(metrics_data, "cpu_utilization", 0.0), - inference_queue_depth=self._parse_metric(metrics_data, "inference_queue", 0), - p50_latency_ms=self._parse_metric(metrics_data, "p50_latency_ms", 0.0), - p99_latency_ms=self._parse_metric(metrics_data, "p99_latency_ms", 0.0), + cpu_utilization=self._parse_metric( + metrics_data, "cpu_utilization", 0.0 + ), + inference_queue_depth=self._parse_metric( + metrics_data, "inference_queue", 0 + ), + p50_latency_ms=self._parse_metric( + metrics_data, "p50_latency_ms", 0.0 + ), + p99_latency_ms=self._parse_metric( + metrics_data, "p99_latency_ms", 0.0 + ), ) - + self._last_health_check[worker] = time.time() except Exception as e: # Mark worker unhealthy if worker_url not in self.worker_metrics: - self.worker_metrics[worker_url] = WorkerHealthMetrics(is_healthy=False, last_error=str(e)) - + self.worker_metrics[worker_url] = WorkerHealthMetrics( + is_healthy=False, last_error=str(e) + ) + def _parse_metric(self, metrics_dict: dict, metric_name: str, default) -> float: """Parse Prometheus-style metric from JSON.""" key = f"{metric_name}_sum" if "_sum" not in metric_name else metric_name - count_key = f"{metric_name}_count" if "_count" not in metric_name else metric_name - + count_key = ( + f"{metric_name}_count" if "_count" not in metric_name else metric_name + ) + if count_key in metrics_dict and metrics_dict[count_key] > 0: return metrics_dict[key] / metrics_dict[count_key] return default - + def select_best_worker( - self, - slice_metadata: SliceMetadata, - target_latency_ms: Optional[float] = None + self, slice_metadata: SliceMetadata, target_latency_ms: Optional[float] = None ) -> Optional[str]: """Select best worker using cost model with real-time metrics.""" - + # Update all worker metrics if stale now = time.time() for worker in self.workers: if now - self._last_health_check[worker] > self.health_interval * 2: self.update_worker_metrics() - + # Filter healthy workers with available memory candidates = [ - w for w, m in self.worker_metrics.items() - if m.is_healthy and m.memory_free_gb >= slice_metadata.activation_size_bytes / (1024**3) + w + for w, m in self.worker_metrics.items() + if m.is_healthy + and m.memory_free_gb >= slice_metadata.activation_size_bytes / (1024**3) ] - + if not candidates: return None - + # Sort by composite cost score scored_workers = [] for worker_url, metrics in self.worker_metrics.items(): if not metrics.is_healthy: continue - + # Check circuit breaker if self.circuit_breakers[worker_url].is_open(): continue - + # Compute cost score (lower is better) gpu_penalty = metrics.gpu_utilization * 10 # Penalize high GPU util latency_penalty = metrics.p99_latency_ms / 100 if target_latency_ms else 0 - + cost_score = ( - metrics.gpu_utilization + # Normalized GPU util - latency_penalty + # Latency penalty - metrics.cpu_utilization * 2 # CPU pressure + metrics.gpu_utilization # Normalized GPU util + + latency_penalty # Latency penalty + + metrics.cpu_utilization * 2 # CPU pressure ) - + scored_workers.append((worker_url, cost_score)) - + if not scored_workers: return None - + # Select worker with lowest cost score scored_workers.sort(key=lambda x: x[1]) best_worker = scored_workers[0][0] - + # Record placement decision for telemetry self.record_placement_decision(slice_metadata.slice_id, best_worker) - + return best_worker - + def record_placement_decision(self, slice_id: str, worker_url: str): """Record placement for telemetry/observability.""" # Emit to Prometheus/OpenTelemetry pass - + def record_failure(self, worker_url: str): """Record request failure to circuit breaker.""" self.circuit_breakers[worker_url].record_failure() diff --git a/prototype/run_demo.py b/prototype/run_demo.py index 045639f..9e1d9cc 100644 --- a/prototype/run_demo.py +++ b/prototype/run_demo.py @@ -3,12 +3,10 @@ from prototype.controller import Controller from prototype.model_tools import ToyModel, WeightSlice - def single_node_run(model, x): """Baseline: run model on single node (all layers).""" return model.forward(x) - def distributed_run(model, x): """ Run model distributed across workers. @@ -25,7 +23,6 @@ def distributed_run(model, x): return out - if __name__ == "__main__": # Build model model = ToyModel([8, 16, 16, 8], seed=42) diff --git a/prototype/scheduler.py b/prototype/scheduler.py index d0ac170..ed3a88a 100644 --- a/prototype/scheduler.py +++ b/prototype/scheduler.py @@ -9,167 +9,178 @@ 5. Slice characteristics (size, compute requirements) """ +import threading import time -from typing import Dict, List, Optional, Any, Tuple from dataclasses import dataclass, field -import threading - +from typing import Any, Dict, List, Optional, Tuple @dataclass class WorkerProfile: """Worker device profile.""" + url: str device_type: str # 'gpu', 'cpu', 'npu' gpu_model: Optional[str] = None - + # Memory (bytes) memory_total: int = 0 memory_free: int = 0 memory_reserved: int = 0 - + # Compute capability cpu_cores: int = 0 gpu_flops_tflops: float = 0.0 # TFLOPS - + # Network network_interface: str = "eth0" network_bandwidth_gbps: float = 1.0 - + # Health is_healthy: bool = True last_error: Optional[str] = None - + # Current load current_gpu_utilization: float = 0.0 # 0-1 current_cpu_utilization: float = 0.0 # 0-1 current_memory_utilization: float = 0.0 # 0-1 - @dataclass class SliceMetadata: """Slice metadata for placement decisions.""" + slice_id: str start_layer: int end_layer: int - + # Size characteristics parameter_count: int = 0 activation_size_bytes: int = 0 estimated_flops_per_token: float = 0.0 - + # Device hints preferred_device_type: Optional[str] = None min_memory_bytes: int = 0 - + # Policy tags is_private: bool = False latency_sensitive: bool = False - class CostModel: """ Computes cost estimates for slice placement decisions. - + Cost factors: - Compute cost: FLOPS / device capability - Memory cost: size / available memory - Network cost: bandwidth requirements / network capacity - Latency cost: estimated execution time """ - + def __init__(self): self._lock = threading.Lock() - + def compute_compute_cost( - self, - slice_metadata: SliceMetadata, - worker_profile: WorkerProfile + self, slice_metadata: SliceMetadata, worker_profile: WorkerProfile ) -> float: """ Compute normalized compute cost for placing slice on worker. - + Returns lower value = better fit """ - if worker_profile.device_type == 'gpu': + if worker_profile.device_type == "gpu": device_flops = worker_profile.gpu_flops_tflops * 1e12 # Convert to FLOPS else: # CPU estimate (rough) device_flops = worker_profile.cpu_cores * 30e9 # ~30 GFLOPS per core - + compute_cost = slice_metadata.estimated_flops_per_token / device_flops - + return compute_cost - + def compute_memory_cost( - self, - slice_metadata: SliceMetadata, - worker_profile: WorkerProfile + self, slice_metadata: SliceMetadata, worker_profile: WorkerProfile ) -> float: """ Compute normalized memory cost for placing slice on worker. - + Returns lower value = better fit """ if worker_profile.memory_free <= 0: - return float('inf') - + return float("inf") + memory_cost = slice_metadata.activation_size_bytes / worker_profile.memory_free - + return memory_cost - + def compute_network_cost( self, slice_metadata: SliceMetadata, source_worker: WorkerProfile, - target_worker: WorkerProfile + target_worker: WorkerProfile, ) -> float: """ Compute normalized network cost for transferring slice. - + Returns lower value = better fit (faster transfer) """ - if source_worker.network_bandwidth_gbps <= 0 or target_worker.network_bandwidth_gbps <= 0: - return float('inf') - - bandwidth_bytes_per_sec = (source_worker.network_bandwidth_gbps + - target_worker.network_bandwidth_gbps) / 2 * 1e9 - - network_cost = slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec # bytes per sec - + if ( + source_worker.network_bandwidth_gbps <= 0 + or target_worker.network_bandwidth_gbps <= 0 + ): + return float("inf") + + bandwidth_bytes_per_sec = ( + ( + source_worker.network_bandwidth_gbps + + target_worker.network_bandwidth_gbps + ) + / 2 + * 1e9 + ) + + network_cost = ( + slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec + ) # bytes per sec + return network_cost - + def estimate_latency( self, slice_metadata: SliceMetadata, worker_profile: WorkerProfile, - network_latency_ms: float = 0.1 + network_latency_ms: float = 0.1, ) -> float: """ Estimate total latency for executing slice on worker. - + Includes: network transfer + compute time """ # Network latency (if not colocated) network_cost_ms = 0.0 if network_latency_ms > 0: bandwidth_bytes_per_sec = worker_profile.network_bandwidth_gbps * 1e9 - network_cost_ms = slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec * 1000 - + network_cost_ms = ( + slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec * 1000 + ) + # Compute latency estimate - if worker_profile.device_type == 'gpu': - compute_latency_ms = (slice_metadata.estimated_flops_per_token / - (worker_profile.gpu_flops_tflops * 1e12)) * 1000 + if worker_profile.device_type == "gpu": + compute_latency_ms = ( + slice_metadata.estimated_flops_per_token + / (worker_profile.gpu_flops_tflops * 1e12) + ) * 1000 else: - compute_latency_ms = (slice_metadata.estimated_flops_per_token / - (worker_profile.cpu_cores * 30e9)) * 1000 - - return network_cost_ms + compute_latency_ms + compute_latency_ms = ( + slice_metadata.estimated_flops_per_token + / (worker_profile.cpu_cores * 30e9) + ) * 1000 + return network_cost_ms + compute_latency_ms class Scheduler: """ Cost-aware scheduler for slice placement decisions. - + Features: - Greedy best-fit placement - Load balancing across workers @@ -177,291 +188,317 @@ class Scheduler: - Memory-aware placement - Network topology awareness """ - + def __init__(self, worker_profiles: List[WorkerProfile]): self.workers = worker_profiles self.cost_model = CostModel() - + # Track current slice placements self._slice_placements: Dict[str, str] = {} # slice_id -> worker_url - + # Lock for thread safety self._lock = threading.Lock() - + def build_worker_inventory(self) -> Dict[str, WorkerProfile]: """Build worker inventory from profiles.""" return {w.url: w for w in self.workers} - + def select_best_worker( - self, - slice_metadata: SliceMetadata + self, slice_metadata: SliceMetadata ) -> Optional[WorkerProfile]: """ Select best worker for given slice using cost model. - + Returns worker profile with lowest total cost, or None if no suitable worker. """ inventory = self.build_worker_inventory() - + # Filter healthy workers candidates = [w for w in self.workers if w.is_healthy] - + if not candidates: return None - + best_worker = None - min_cost = float('inf') - + min_cost = float("inf") + for worker in candidates: # Skip if memory insufficient if slice_metadata.activation_size_bytes > worker.memory_free: continue - + # Skip if GPU requested but unavailable - if (slice_metadata.preferred_device_type == 'gpu' and - worker.device_type != 'gpu'): + if ( + slice_metadata.preferred_device_type == "gpu" + and worker.device_type != "gpu" + ): continue - + # Compute total cost - compute_cost = self.cost_model.compute_compute_cost( - slice_metadata, worker - ) - memory_cost = self.cost_model.compute_memory_cost( - slice_metadata, worker - ) + compute_cost = self.cost_model.compute_compute_cost(slice_metadata, worker) + memory_cost = self.cost_model.compute_memory_cost(slice_metadata, worker) network_cost = 0.0 # Assuming colocated for simplicity - + total_cost = compute_cost + memory_cost + network_cost - + if total_cost < min_cost: min_cost = total_cost best_worker = worker - + return best_worker - + def assign_slice(self, slice_metadata: SliceMetadata) -> Optional[str]: """ Assign slice to best available worker. - + Returns worker URL or None if assignment fails. """ with self._lock: best_worker = self.select_best_worker(slice_metadata) - + if best_worker is None: return None - + # Record placement self._slice_placements[slice_metadata.slice_id] = best_worker.url - + return best_worker.url - + def get_placement_plan( - self, - slices: List[Tuple[int, int, SliceMetadata]] + self, slices: List[Tuple[int, int, SliceMetadata]] ) -> Dict[str, str]: """ Get placement plan for all slices. - + Returns mapping of slice_id -> worker_url """ placements = {} - + # Sort slices by size (largest first) for better packing sorted_slices = sorted( - slices, - key=lambda s: s[2].activation_size_bytes, - reverse=True + slices, key=lambda s: s[2].activation_size_bytes, reverse=True ) - + for start, end, metadata in sorted_slices: worker_url = self.assign_slice(metadata) - + if worker_url is not None: placements[f"slice_{start}_{end}"] = worker_url - + return placements - + def rebalance_load(self) -> Optional[WorkerProfile]: """ Identify most loaded worker and suggest moving slices to less loaded workers. - + Returns overloaded worker profile or None if balanced. """ inventory = self.build_worker_inventory() - + # Calculate load score for each worker worker_scores = [] for worker in self.workers: if not worker.is_healthy: continue - + # Load score based on utilization and memory pressure utilization_score = ( - 0.4 * worker.current_gpu_utilization + - 0.3 * worker.current_cpu_utilization + - 0.3 * worker.current_memory_utilization + 0.4 * worker.current_gpu_utilization + + 0.3 * worker.current_cpu_utilization + + 0.3 * worker.current_memory_utilization ) - + worker_scores.append((worker, utilization_score)) - + # Sort by score descending worker_scores.sort(key=lambda x: x[1], reverse=True) - + # Identify overloaded worker (>70% load) if worker_scores and worker_scores[0][1] > 0.7: return worker_scores[0][0] - + return None - + def get_placement_statistics(self) -> Dict[str, Any]: """Get placement statistics.""" inventory = self.build_worker_inventory() - + # Count slices per worker placements_per_worker = {} for slice_id, worker_url in self._slice_placements.items(): - placements_per_worker[worker_url] = placements_per_worker.get(worker_url, 0) + 1 - + placements_per_worker[worker_url] = ( + placements_per_worker.get(worker_url, 0) + 1 + ) + total_slices = len(self._slice_placements) - + return { - 'total_slices': total_slices, - 'placements_per_worker': placements_per_worker, - 'workers_with_slices': sum(1 for p in placements_per_worker.values() if p > 0), - 'utilization_by_worker': { + "total_slices": total_slices, + "placements_per_worker": placements_per_worker, + "workers_with_slices": sum( + 1 for p in placements_per_worker.values() if p > 0 + ), + "utilization_by_worker": { w.url: { - 'gpu_utilization': w.current_gpu_utilization, - 'cpu_utilization': w.current_cpu_utilization, - 'memory_utilization': w.current_memory_utilization, + "gpu_utilization": w.current_gpu_utilization, + "cpu_utilization": w.current_cpu_utilization, + "memory_utilization": w.current_memory_utilization, } - for w in self.workers if w.is_healthy - } + for w in self.workers + if w.is_healthy + }, } - class TopologyAwareScheduler(Scheduler): """ Scheduler with network topology awareness. - + Considers: - Physical distance between devices - Network path quality - Shared memory pools (NUMA) """ - + def __init__( self, worker_profiles: List[WorkerProfile], - topology: Optional[Dict[str, Any]] = None + topology: Optional[Dict[str, Any]] = None, ): super().__init__(worker_profiles) self.topology = topology or {} - + # Build adjacency matrix for network latency self._network_latencies: Dict[Tuple[str, str], float] = {} - + def update_network_latency(self, w1_url: str, w2_url: str, latency_ms: float): """Update measured network latency between workers.""" self._network_latencies[(w1_url, w2_url)] = latency_ms self._network_latencies[(w2_url, w1_url)] = latency_ms - + def compute_network_cost_with_topology( self, slice_metadata: SliceMetadata, source_worker: WorkerProfile, - target_worker: WorkerProfile + target_worker: WorkerProfile, ) -> float: """ Compute network cost considering topology. - + Uses measured latencies when available, estimates otherwise. """ # Check for direct connection if (source_worker.url, target_worker.url) in self._network_latencies: latency_ms = self._network_latencies[(source_worker.url, target_worker.url)] - bandwidth_bytes_per_sec = (source_worker.network_bandwidth_gbps + - target_worker.network_bandwidth_gbps) / 2 * 1e9 - - network_cost = slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec * 1000 - + bandwidth_bytes_per_sec = ( + ( + source_worker.network_bandwidth_gbps + + target_worker.network_bandwidth_gbps + ) + / 2 + * 1e9 + ) + + network_cost = ( + slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec * 1000 + ) + elif source_worker.url == target_worker.url: # Same worker, no network cost return 0.0 - + else: # Estimate based on physical distance if available - w1_location = self.topology.get(source_worker.url, {}).get('location', '') - w2_location = self.topology.get(target_worker.url, {}).get('location', '') - + w1_location = self.topology.get(source_worker.url, {}).get("location", "") + w2_location = self.topology.get(target_worker.url, {}).get("location", "") + # Rough estimate: 10ms per km for fiber (very conservative) - location1 = getattr(source_worker, '_location', '') - location2 = getattr(target_worker, '_location', '') - + location1 = getattr(source_worker, "_location", "") + location2 = getattr(target_worker, "_location", "") + if location1 and location2: # Extract numeric part from location string like "rack-3" or "pod-2" import re - num1 = int(re.search(r'\d+', location1).group()) if re.search(r'\d+', location1) else 0 - num2 = int(re.search(r'\d+', location2).group()) if re.search(r'\d+', location2) else 0 - - distance_km = abs(num1 - num2) * 10 # Rough estimate: 10km per rack difference + + num1 = ( + int(re.search(r"\d+", location1).group()) + if re.search(r"\d+", location1) + else 0 + ) + num2 = ( + int(re.search(r"\d+", location2).group()) + if re.search(r"\d+", location2) + else 0 + ) + + distance_km = ( + abs(num1 - num2) * 10 + ) # Rough estimate: 10km per rack difference latency_ms = distance_km * 0.1 # 10ms per km - - bandwidth_bytes_per_sec = (source_worker.network_bandwidth_gbps + - target_worker.network_bandwidth_gbps) / 2 * 1e9 - - network_cost = slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec * 1000 - + + bandwidth_bytes_per_sec = ( + ( + source_worker.network_bandwidth_gbps + + target_worker.network_bandwidth_gbps + ) + / 2 + * 1e9 + ) + + network_cost = ( + slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec * 1000 + ) + else: # Default estimate latency_ms = 1.0 # Assume 1ms local network bandwidth_bytes_per_sec = source_worker.network_bandwidth_gbps * 1e9 - - network_cost = slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec * 1000 - - return network_cost + network_cost = ( + slice_metadata.parameter_count * 4 / bandwidth_bytes_per_sec * 1000 + ) -if __name__ == '__main__': + return network_cost + +if __name__ == "__main__": # Demo scheduler - + # Create worker profiles workers = [ WorkerProfile( - url='http://worker-gpu-1:8003', - device_type='gpu', - gpu_model='NVIDIA_A100_80GB', - memory_total=80*1024**3, - memory_free=60*1024**3, + url="http://worker-gpu-1:8003", + device_type="gpu", + gpu_model="NVIDIA_A100_80GB", + memory_total=80 * 1024**3, + memory_free=60 * 1024**3, cpu_cores=96, gpu_flops_tflops=2000, # A100 FP16 TFLOPS - network_interface='eth0', - network_bandwidth_gbps=25.0 + network_interface="eth0", + network_bandwidth_gbps=25.0, ), WorkerProfile( - url='http://worker-cpu-1:8003', - device_type='cpu', - memory_total=128*1024**3, - memory_free=100*1024**3, + url="http://worker-cpu-1:8003", + device_type="cpu", + memory_total=128 * 1024**3, + memory_free=100 * 1024**3, cpu_cores=64, - network_interface='eth0', - network_bandwidth_gbps=10.0 + network_interface="eth0", + network_bandwidth_gbps=10.0, ), ] - + # Create slices slices = [ SliceMetadata( - slice_id='slice_0_2', + slice_id="slice_0_2", start_layer=0, end_layer=2, parameter_count=100000, activation_size_bytes=50000, estimated_flops_per_token=1e9, - preferred_device_type='gpu', + preferred_device_type="gpu", ), SliceMetadata( - slice_id='slice_2_3', + slice_id="slice_2_3", start_layer=2, end_layer=3, parameter_count=50000, @@ -469,13 +506,13 @@ def compute_network_cost_with_topology( estimated_flops_per_token=5e8, ), ] - + # Create scheduler scheduler = Scheduler(workers) - + # Get placement plan placements = scheduler.get_placement_plan(slices) - + print("Placement Plan:") for slice_id, worker_url in placements.items(): print(f" {slice_id} -> {worker_url}") diff --git a/prototype/service_discovery.py b/prototype/service_discovery.py index 7c1c707..26974e4 100644 --- a/prototype/service_discovery.py +++ b/prototype/service_discovery.py @@ -5,14 +5,14 @@ Allows clients to find and connect to GUI and worker nodes without manual IP entry. """ -import socket -import ipaddress import asyncio -import threading +import ipaddress import logging -from typing import Dict, List, Optional, Callable -from dataclasses import dataclass, asdict +import socket +import threading +from dataclasses import asdict, dataclass from datetime import datetime +from typing import Callable, Dict, List, Optional try: from zeroconf import ServiceBrowser, ServiceStateChange, Zeroconf @@ -22,20 +22,19 @@ logger = logging.getLogger(__name__) - @dataclass class MohawkService: """Represents a discovered Mohawk service on the LAN.""" - - name: str # Service name (e.g., "Mohawk-GUI-001") - service_type: str # "gui" or "worker" - host: str # Hostname or IP address - port: int # Port number - addresses: List[str] # List of IP addresses + + name: str # Service name (e.g., "Mohawk-GUI-001") + service_type: str # "gui" or "worker" + host: str # Hostname or IP address + port: int # Port number + addresses: List[str] # List of IP addresses properties: Dict[str, str] # Additional metadata - discovered_at: str # ISO timestamp - ttl: int = 4500 # Time to live (seconds) - + discovered_at: str # ISO timestamp + ttl: int = 4500 # Time to live (seconds) + @property def url(self) -> str: """Return the service URL.""" @@ -43,12 +42,12 @@ def url(self) -> str: ip = self.addresses[0] return f"http://{ip}:{self.port}" return f"http://{self.host}:{self.port}" - + @property def is_ipv4(self) -> bool: """Check if service has IPv4 address.""" return any(self._is_ipv4(addr) for addr in self.addresses) - + @staticmethod def _is_ipv4(addr: str) -> bool: try: @@ -56,98 +55,116 @@ def _is_ipv4(addr: str) -> bool: return True except (ipaddress.AddressValueError, ValueError): return False - + def to_dict(self) -> dict: """Convert to dictionary.""" return asdict(self) - class MohawkServiceDiscovery: """Handles mDNS service discovery for Mohawk nodes on LAN.""" - + # mDNS service types MOHAWK_GUI_TYPE = "_mohawk-gui._tcp.local." MOHAWK_WORKER_TYPE = "_mohawk-worker._tcp.local." - - def __init__(self, on_service_added: Optional[Callable] = None, - on_service_removed: Optional[Callable] = None): + + def __init__( + self, + on_service_added: Optional[Callable] = None, + on_service_removed: Optional[Callable] = None, + ): """ Initialize service discovery. - + Args: on_service_added: Callback when service is discovered on_service_removed: Callback when service is lost """ self.on_service_added = on_service_added self.on_service_removed = on_service_removed - + self.zeroconf: Optional[Zeroconf] = None self.browsers: Dict[str, ServiceBrowser] = {} self.discovered_services: Dict[str, MohawkService] = {} self._lock = threading.Lock() self._running = False - + def start(self) -> bool: """Start service discovery. Returns True if mDNS is available.""" if not Zeroconf: logger.warning("Zeroconf not available; LAN discovery disabled") return False - + try: - self.zeroconf = Zeroconf(interfaces=['127.0.0.1']) + self.zeroconf = Zeroconf(interfaces=["127.0.0.1"]) self._running = True - + # Browse for GUI services self.browsers[self.MOHAWK_GUI_TYPE] = ServiceBrowser( - self.zeroconf, self.MOHAWK_GUI_TYPE, handlers=[self._on_service_state_change] + self.zeroconf, + self.MOHAWK_GUI_TYPE, + handlers=[self._on_service_state_change], ) - + # Browse for Worker services self.browsers[self.MOHAWK_WORKER_TYPE] = ServiceBrowser( - self.zeroconf, self.MOHAWK_WORKER_TYPE, handlers=[self._on_service_state_change] + self.zeroconf, + self.MOHAWK_WORKER_TYPE, + handlers=[self._on_service_state_change], + ) + + logger.info( + "Service discovery started - listening for Mohawk services on LAN" ) - - logger.info("Service discovery started - listening for Mohawk services on LAN") return True - + except Exception as e: logger.error(f"Failed to start service discovery: {e}") self._running = False return False - + def stop(self): """Stop service discovery.""" if self.zeroconf: self.zeroconf.close() self._running = False logger.info("Service discovery stopped") - - def _on_service_state_change(self, zeroconf: Zeroconf, service_type: str, - name: str, state_change: ServiceStateChange): + + def _on_service_state_change( + self, + zeroconf: Zeroconf, + service_type: str, + name: str, + state_change: ServiceStateChange, + ): """Handle service state changes (discovery/removal).""" if state_change == ServiceStateChange.Added: self._add_service(zeroconf, service_type, name) elif state_change == ServiceStateChange.Removed: self._remove_service(name) - + def _add_service(self, zeroconf: Zeroconf, service_type: str, name: str): """Add discovered service.""" try: info = zeroconf.get_service_info(service_type, name) if not info: return - + # Parse service info svc_type = "gui" if "gui" in service_type.lower() else "worker" - addresses = [addr.decode() if isinstance(addr, bytes) else addr - for addr in (info.parsed_addresses() or [])] - + addresses = [ + addr.decode() if isinstance(addr, bytes) else addr + for addr in (info.parsed_addresses() or []) + ] + properties = {} if info.properties: - properties = {k.decode() if isinstance(k, bytes) else k: - v.decode() if isinstance(v, bytes) else v - for k, v in info.properties.items()} - + properties = { + k.decode() if isinstance(k, bytes) else k: ( + v.decode() if isinstance(v, bytes) else v + ) + for k, v in info.properties.items() + } + service = MohawkService( name=name, service_type=svc_type, @@ -155,62 +172,66 @@ def _add_service(self, zeroconf: Zeroconf, service_type: str, name: str): port=info.port, addresses=addresses or ["127.0.0.1"], properties=properties, - discovered_at=datetime.now().isoformat() + discovered_at=datetime.now().isoformat(), ) - + with self._lock: self.discovered_services[name] = service - + logger.info(f"Service discovered: {service.url} ({svc_type})") - + if self.on_service_added: self.on_service_added(service) - + except Exception as e: logger.error(f"Error adding service {name}: {e}") - + def _remove_service(self, name: str): """Remove service when it goes offline.""" with self._lock: if name in self.discovered_services: service = self.discovered_services.pop(name) logger.info(f"Service removed: {service.name}") - + if self.on_service_removed: self.on_service_removed(service) - + def get_services(self, service_type: Optional[str] = None) -> List[MohawkService]: """Get all discovered services, optionally filtered by type.""" with self._lock: services = list(self.discovered_services.values()) - + if service_type: services = [s for s in services if s.service_type == service_type] - + return services - + def find_gui_services(self) -> List[MohawkService]: """Find all discovered GUI services.""" return self.get_services("gui") - + def find_worker_services(self) -> List[MohawkService]: """Find all discovered worker services.""" return self.get_services("worker") - + def get_service_by_name(self, name: str) -> Optional[MohawkService]: """Get service by name.""" with self._lock: return self.discovered_services.get(name) - class LanServiceRegistry: """Register and manage Mohawk services for LAN discovery.""" - - def __init__(self, hostname: str, service_type: str, port: int, - properties: Optional[Dict[str, str]] = None): + + def __init__( + self, + hostname: str, + service_type: str, + port: int, + properties: Optional[Dict[str, str]] = None, + ): """ Register a Mohawk service for discovery. - + Args: hostname: Service hostname (e.g., "mohawk-gui-001") service_type: "gui" or "worker" @@ -222,49 +243,48 @@ def __init__(self, hostname: str, service_type: str, port: int, self.port = port self.properties = properties or {} self.zeroconf: Optional[Zeroconf] = None - + def register(self) -> bool: """Register service on mDNS. Returns True if successful.""" if not Zeroconf: logger.warning("Zeroconf not available; service registration disabled") return False - + try: from zeroconf import ServiceInfo - + service_name = f"{self.hostname}._mohawk-{self.service_type}._tcp.local." service_type = f"_mohawk-{self.service_type}._tcp.local." - + # Get local IP hostname_parts = socket.gethostname() local_ip = socket.gethostbyname(socket.gethostname()) - + info = ServiceInfo( service_type, service_name, addresses=[socket.inet_aton(local_ip)], port=self.port, properties=self.properties, - server=f"{hostname_parts}.local." + server=f"{hostname_parts}.local.", ) - + self.zeroconf = Zeroconf() self.zeroconf.register_service(info) - + logger.info(f"Service registered: {service_name} at {local_ip}:{self.port}") return True - + except Exception as e: logger.error(f"Failed to register service: {e}") return False - + def unregister(self): """Unregister service.""" if self.zeroconf: self.zeroconf.close() logger.info("Service unregistered") - def get_local_ip() -> str: """Get local IP address.""" try: @@ -276,14 +296,13 @@ def get_local_ip() -> str: except Exception: return "127.0.0.1" - async def discover_services_async(timeout: float = 5.0) -> List[MohawkService]: """Discover services asynchronously with timeout.""" discovery = MohawkServiceDiscovery() - + if not discovery.start(): return [] - + try: await asyncio.sleep(timeout) services = discovery.get_services() @@ -291,29 +310,29 @@ async def discover_services_async(timeout: float = 5.0) -> List[MohawkService]: finally: discovery.stop() - if __name__ == "__main__": # Demo: start discovery and list services import time - + logging.basicConfig(level=logging.INFO) - + def on_added(service): print(f"โœ“ Found: {service.name} at {service.url}") - + def on_removed(service): print(f"โœ— Lost: {service.name}") - - discovery = MohawkServiceDiscovery(on_service_added=on_added, - on_service_removed=on_removed) - + + discovery = MohawkServiceDiscovery( + on_service_added=on_added, on_service_removed=on_removed + ) + print("Starting LAN service discovery (10 seconds)...") discovery.start() - + time.sleep(10) - + print("\nDiscovered services:") for svc in discovery.get_services(): print(f" - {svc.name:30} ({svc.service_type:6}) -> {svc.url}") - + discovery.stop() diff --git a/prototype/session_manager.py b/prototype/session_manager.py index f32f42e..9c3cfcd 100644 --- a/prototype/session_manager.py +++ b/prototype/session_manager.py @@ -1,7 +1,7 @@ -import uuid import pickle -from prototype.controller_secure import SecureController +import uuid +from prototype.controller_secure import SecureController class SessionManager: def __init__(self, workers): @@ -31,7 +31,7 @@ def infer(self, session_id, x): s = self.sessions[session_id] x_blob = pickle.dumps(x) out_blob = self.controller.run_distributed( - s['assigned'], x_blob, encrypt=s['encrypt'] + s["assigned"], x_blob, encrypt=s["encrypt"] ) out = pickle.loads(out_blob) return out diff --git a/prototype/telemetry.py b/prototype/telemetry.py index 11c10b3..66c1e70 100644 --- a/prototype/telemetry.py +++ b/prototype/telemetry.py @@ -1,8 +1,7 @@ -import time import inspect +import time from functools import wraps - class Telemetry: def __init__(self, metrics_dict, lock): self.metrics = metrics_dict @@ -18,7 +17,7 @@ def record(self, name_sum, name_count, duration): # also update histogram buckets for this metric prefix try: base = name_sum - if base.endswith('_sum'): + if base.endswith("_sum"): base = base[:-4] hist_prefix = f"{base}_hist" # find the appropriate bucket @@ -37,6 +36,7 @@ def record(self, name_sum, name_count, duration): def timed(self, name_sum, name_count): def decorator(func): if inspect.iscoroutinefunction(func): + async def async_wrapper(*args, **kwargs): t0 = time.time() try: @@ -48,6 +48,7 @@ async def async_wrapper(*args, **kwargs): wraps(func)(async_wrapper) return async_wrapper else: + def sync_wrapper(*args, **kwargs): t0 = time.time() try: diff --git a/prototype/test_concurrency_smoke.py b/prototype/test_concurrency_smoke.py index a5a1a1c..81a1e62 100644 --- a/prototype/test_concurrency_smoke.py +++ b/prototype/test_concurrency_smoke.py @@ -9,7 +9,6 @@ ) from prototype.load_harness import run_load - @pytest.fixture() def inprocess_worker(monkeypatch): client = make_worker_client() @@ -18,7 +17,6 @@ def inprocess_worker(monkeypatch): yield client reset_worker_state() - @pytest.mark.integration def test_concurrency_smoke(inprocess_worker): """ diff --git a/prototype/test_correctness_suite.py b/prototype/test_correctness_suite.py index 1da4c1e..a087c39 100644 --- a/prototype/test_correctness_suite.py +++ b/prototype/test_correctness_suite.py @@ -13,26 +13,26 @@ import sys import time + import numpy as np import pytest -from prototype.model_tools import ToyModel +from prototype.model_tools import ToyModel def single_node_forward(model: ToyModel, x: np.ndarray) -> np.ndarray: """Baseline single-node forward pass.""" out = x - for (w, b) in model.weights: + for w, b in model.weights: out = w @ out + b[:, None] out = np.tanh(out) return out - def distributed_forward(model: ToyModel, x: np.ndarray, num_slices=2) -> np.ndarray: """Simulate distributed forward pass (without actual workers).""" # Partition model L = len(model.weights) per = max(1, L // num_slices) - + # Split into slices slices = [] for i in range(0, L, per): @@ -41,18 +41,17 @@ def distributed_forward(model: ToyModel, x: np.ndarray, num_slices=2) -> np.ndar sub = ToyModel.__new__(ToyModel) sub.weights = model.weights[start:end] slices.append((start, end, sub)) - + # Sequential execution on "workers" (simulated) current = x for start, end, slice_model in slices: out = current - for (w, b) in slice_model.weights: + for w, b in slice_model.weights: out = w @ out + b[:, None] out = np.tanh(out) current = out - - return current + return current class TestNumericalCorrectness: """Test numerical correctness of distributed inference.""" @@ -61,192 +60,204 @@ def test_toymodel_small_layers(self): """Test with small layer configuration [4,8,8,4].""" model = ToyModel([4, 8, 8, 4], seed=42) x = np.random.randn(4, 1).astype(np.float32) - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - + # FP32 operations should be deterministic - assert np.allclose(baseline, distributed, rtol=1e-5, atol=1e-7), \ - f"Small layers: baseline={baseline.flatten()}, distributed={distributed.flatten()}" + assert np.allclose( + baseline, distributed, rtol=1e-5, atol=1e-7 + ), f"Small layers: baseline={baseline.flatten()}, distributed={distributed.flatten()}" def test_toymodel_medium_layers(self): """Test with medium layer configuration [8,16,16,8].""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - - assert np.allclose(baseline, distributed, rtol=1e-5, atol=1e-7), \ - f"Medium layers failed: max diff = {np.max(np.abs(baseline - distributed))}" + + assert np.allclose( + baseline, distributed, rtol=1e-5, atol=1e-7 + ), f"Medium layers failed: max diff = {np.max(np.abs(baseline - distributed))}" def test_toymodel_large_layers(self): """Test with large layer configuration [32,64,64,32].""" model = ToyModel([32, 64, 64, 32], seed=42) x = np.random.randn(32, 1).astype(np.float32) - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - - assert np.allclose(baseline, distributed, rtol=1e-5, atol=1e-7), \ - f"Large layers failed: max diff = {np.max(np.abs(baseline - distributed))}" + + assert np.allclose( + baseline, distributed, rtol=1e-5, atol=1e-7 + ), f"Large layers failed: max diff = {np.max(np.abs(baseline - distributed))}" def test_toymodel_very_large_layers(self): """Test with very large layer configuration [64,128,128,64].""" model = ToyModel([64, 128, 128, 64], seed=42) x = np.random.randn(64, 1).astype(np.float32) - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - - assert np.allclose(baseline, distributed, rtol=1e-5, atol=1e-7), \ - f"Very large layers failed: max diff = {np.max(np.abs(baseline - distributed))}" + + assert np.allclose( + baseline, distributed, rtol=1e-5, atol=1e-7 + ), f"Very large layers failed: max diff = {np.max(np.abs(baseline - distributed))}" def test_toymodel_many_slices(self): """Test with many fine-grained slices [4,4,4,4].""" model = ToyModel([4, 4, 4, 4], seed=42) x = np.random.randn(4, 1).astype(np.float32) - + # Use more slices (finer partitioning) distributed = distributed_forward(model, x, num_slices=3) - + baseline = single_node_forward(model, x) - - assert np.allclose(baseline, distributed, rtol=1e-5, atol=1e-7), \ - f"Fine-grained partitioning failed: max diff = {np.max(np.abs(baseline - distributed))}" + + assert np.allclose( + baseline, distributed, rtol=1e-5, atol=1e-7 + ), f"Fine-grained partitioning failed: max diff = {np.max(np.abs(baseline - distributed))}" def test_three_way_split(self): """Test three-way split across devices.""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) - + # Simulate three-way split slices = [] L = len(model.weights) per = max(1, L // 3) - + for i in range(0, L, per): start = i end = min(L, i + per) sub = ToyModel.__new__(ToyModel) sub.weights = model.weights[start:end] slices.append((start, end, sub)) - + current = x for start, end, slice_model in slices: out = current - for (w, b) in slice_model.weights: + for w, b in slice_model.weights: out = w @ out + b[:, None] out = np.tanh(out) current = out - + baseline = single_node_forward(model, x) - - assert np.allclose(baseline, current, rtol=1e-5, atol=1e-7), \ - f"Three-way split failed: max diff = {np.max(np.abs(baseline - current))}" + + assert np.allclose( + baseline, current, rtol=1e-5, atol=1e-7 + ), f"Three-way split failed: max diff = {np.max(np.abs(baseline - current))}" def test_edge_case_zero_input(self): """Test with zero input vector.""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.zeros((8, 1), dtype=np.float32) - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - - assert np.allclose(baseline, distributed, rtol=1e-5, atol=1e-7), \ - f"Zero input failed: baseline={baseline.flatten()}, distributed={distributed.flatten()}" + + assert np.allclose( + baseline, distributed, rtol=1e-5, atol=1e-7 + ), f"Zero input failed: baseline={baseline.flatten()}, distributed={distributed.flatten()}" def test_edge_case_large_input(self): """Test with large-magnitude input (stress numerical stability).""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) * 10.0 - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - + # Tanh bounds output to [-1, 1], so differences should be small - assert np.allclose(baseline, distributed, rtol=1e-4, atol=1e-6), \ - f"Large input failed: max diff = {np.max(np.abs(baseline - distributed))}" + assert np.allclose( + baseline, distributed, rtol=1e-4, atol=1e-6 + ), f"Large input failed: max diff = {np.max(np.abs(baseline - distributed))}" def test_edge_case_small_input(self): """Test with small-magnitude input.""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) * 0.001 - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - - assert np.allclose(baseline, distributed, rtol=1e-5, atol=1e-7), \ - f"Small input failed: max diff = {np.max(np.abs(baseline - distributed))}" + + assert np.allclose( + baseline, distributed, rtol=1e-5, atol=1e-7 + ), f"Small input failed: max diff = {np.max(np.abs(baseline - distributed))}" def test_different_seeds(self): """Test correctness across different random seeds.""" seeds = [0, 42, 123, 999, 7777] - + for seed in seeds: model = ToyModel([8, 16, 16, 8], seed=seed) x = np.random.default_rng(seed).standard_normal((8, 1)).astype(np.float32) - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - - assert np.allclose(baseline, distributed, rtol=1e-5, atol=1e-7), \ - f"Seed {seed} failed: max diff = {np.max(np.abs(baseline - distributed))}" + + assert np.allclose( + baseline, distributed, rtol=1e-5, atol=1e-7 + ), f"Seed {seed} failed: max diff = {np.max(np.abs(baseline - distributed))}" def test_layer_boundary_activations(self): """Verify activations at layer boundaries are consistent.""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) - + # Compute single-node with intermediate outputs out = x layer_outputs = [] - for (w, b) in model.weights: + for w, b in model.weights: out = w @ out + b[:, None] layer_outputs.append(out.copy()) out = np.tanh(out) - + # Compare with distributed (which also computes same intermediates) distributed = distributed_forward(model, x, num_slices=2) - + # All intermediate outputs should match for i, (single_out, dist_out) in enumerate(zip(layer_outputs, [None])): if i == 0: # First layer is shared continue - - assert np.allclose(distributed, out, rtol=1e-5, atol=1e-7), \ - f"Boundary activations mismatch after {len(model.weights)} layers" + + assert np.allclose( + distributed, out, rtol=1e-5, atol=1e-7 + ), f"Boundary activations mismatch after {len(model.weights)} layers" def test_numerical_precision_fp32(self): """Verify FP32 precision is maintained throughout.""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) - + baseline = single_node_forward(model, x) distributed = distributed_forward(model, x, num_slices=2) - + # Check that results are within FP32 epsilon tolerance max_diff = np.max(np.abs(baseline - distributed)) fp32_epsilon = np.finfo(np.float32).eps - - assert max_diff < 100 * fp32_epsilon, \ - f"FP32 precision violated: max diff={max_diff}, eps={fp32_epsilon}" + + assert ( + max_diff < 100 * fp32_epsilon + ), f"FP32 precision violated: max diff={max_diff}, eps={fp32_epsilon}" def test_consistency_across_multiple_runs(self): """Verify deterministic behavior across multiple runs.""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) - + results = [] for _ in range(5): result = distributed_forward(model, x, num_slices=2) results.append(result.copy()) - + # All results should be identical for i in range(1, len(results)): - assert np.allclose(results[0], results[i], rtol=0, atol=0), \ - f"Run {i} produced non-deterministic result vs run 0" - + assert np.allclose( + results[0], results[i], rtol=0, atol=0 + ), f"Run {i} produced non-deterministic result vs run 0" class TestPartitionConsistency: """Test partition consistency across different slicing strategies.""" @@ -255,7 +266,7 @@ def test_static_partition_vs_dynamic(self): """Compare static vs dynamic partitioning results.""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) - + # Static partition: equal-sized slices L = len(model.weights) per_static = max(1, L // 2) @@ -266,7 +277,7 @@ def test_static_partition_vs_dynamic(self): sub = ToyModel.__new__(ToyModel) sub.weights = model.weights[start:end] static_slices.append((start, end, sub)) - + # Dynamic partition: weighted by layer size (for larger layers) dynamic_slices = [] for i in range(0, L, per_static): # Same partition for this test @@ -275,37 +286,41 @@ def test_static_partition_vs_dynamic(self): sub = ToyModel.__new__(ToyModel) sub.weights = model.weights[start:end] dynamic_slices.append((start, end, sub)) - + static_result = single_node_forward(model, x) # Both are effectively same here - + # Verify both approaches produce same result - assert np.allclose(static_result, distributed_forward(model, x, num_slices=2), - rtol=1e-5, atol=1e-7) + assert np.allclose( + static_result, + distributed_forward(model, x, num_slices=2), + rtol=1e-5, + atol=1e-7, + ) def test_slice_order_independence(self): """Verify that slice execution order doesn't affect results.""" model = ToyModel([8, 16, 16, 8], seed=42) x = np.random.randn(8, 1).astype(np.float32) - + # Normal order: layers 0-1, then 2-3 result_normal = distributed_forward(model, x, num_slices=2) - + # Reverse order (should fail for sequential models like transformers) try: # Simulate reverse order by manually reversing slice weights L = len(model.weights) reversed_model = ToyModel.__new__(ToyModel) reversed_model.weights = list(reversed(model.weights)) - + # This should produce different results (transformer is order-dependent) result_reversed = distributed_forward(reversed_model, x, num_slices=2) - - assert not np.allclose(result_normal, result_reversed), \ - "Reverse order should produce different results for sequential models" + + assert not np.allclose( + result_normal, result_reversed + ), "Reverse order should produce different results for sequential models" except: pass # Expected if reversed model fails - class TestPerformanceMetrics: """Test performance characteristics alongside correctness.""" @@ -313,17 +328,17 @@ class TestPerformanceMetrics: def test_throughput_consistency(self): """Verify consistent throughput across multiple batches.""" model = ToyModel([8, 16, 16, 8], seed=42) - + batch_sizes = [1, 4, 8, 16] latencies = [] - + for bs in batch_sizes: x = np.random.randn(bs, 8).astype(np.float32) - + # Warm up to avoid first-run JIT/cache effects for _ in range(3): _ = single_node_forward(model, x[0]) - + # Take best-of-N to reduce OS scheduling noise samples = [] for _ in range(10): @@ -331,21 +346,23 @@ def test_throughput_consistency(self): _ = single_node_forward(model, x[0]) # First element only end = time.perf_counter_ns() samples.append(end - start) - + best_latency = float(min(samples)) # nanoseconds latencies.append(best_latency) - + # Latencies should be reasonably close; allow larger variance in shared CI/runtime environments. min_latency = min(latencies) max_latency = max(latencies) - + if min_latency < 100: pytest.skip("Timer resolution too low to measure latency reliably") - - assert (max_latency - min_latency) / min_latency < 1.0, \ - f"Latency variance too high: {min_latency} vs {max_latency}" + assert ( + max_latency - min_latency + ) / min_latency < 1.0, ( + f"Latency variance too high: {min_latency} vs {max_latency}" + ) -if __name__ == '__main__': +if __name__ == "__main__": # Run tests directly - pytest.main([__file__, '-v', '--tb=short']) + pytest.main([__file__, "-v", "--tb=short"]) diff --git a/prototype/test_oqs_hybrid.py b/prototype/test_oqs_hybrid.py index 11564fe..75abc6a 100644 --- a/prototype/test_oqs_hybrid.py +++ b/prototype/test_oqs_hybrid.py @@ -1,17 +1,18 @@ import sys + import pytest -from prototype.crypto import PQCAdapter, derive_hybrid_key, AEAD, OQS_AVAILABLE +from prototype.crypto import AEAD, OQS_AVAILABLE, PQCAdapter, derive_hybrid_key def test_oqs_hybrid_encap_decap(): if not OQS_AVAILABLE: - pytest.skip('oqs module not available') + pytest.skip("oqs module not available") # create two adapters (controller and worker) c = PQCAdapter() w = PQCAdapter() # ensure both report oqs_supported; skip if pyOQS API not present - if not getattr(c, 'oqs_supported', False) or not getattr(w, 'oqs_supported', False): - pytest.skip('pyOQS KEM API not available in this environment') + if not getattr(c, "oqs_supported", False) or not getattr(w, "oqs_supported", False): + pytest.skip("pyOQS KEM API not available in this environment") # exchange oqs public keys c_pub = c.get_oqs_public() w_pub = w.get_oqs_public() @@ -29,7 +30,7 @@ def test_oqs_hybrid_encap_decap(): hybrid_w = derive_hybrid_key(x_w, ss_w) assert hybrid_c == hybrid_w aead = AEAD(hybrid_c) - plaintext = b'test message' + plaintext = b"test message" nonce, ct = aead.encrypt(plaintext) out = aead.decrypt(nonce, ct) assert out == plaintext diff --git a/prototype/test_secure_hybrid_integration.py b/prototype/test_secure_hybrid_integration.py index 7e8f0e5..2202e6b 100644 --- a/prototype/test_secure_hybrid_integration.py +++ b/prototype/test_secure_hybrid_integration.py @@ -1,34 +1,35 @@ import numpy as np import pytest +import prototype.controller_secure as controller_secure from prototype.crypto import OQS_AVAILABLE, PQCAdapter -from prototype.integration_helpers import InProcessWorkerTransport, make_worker_client, reset_worker_state +from prototype.integration_helpers import ( + InProcessWorkerTransport, + make_worker_client, + reset_worker_state, +) from prototype.model_tools import ToyModel from prototype.session_manager import SessionManager -import prototype.controller_secure as controller_secure - def _hybrid_supported() -> bool: return OQS_AVAILABLE and PQCAdapter().oqs_supported - @pytest.fixture() def inprocess_worker(monkeypatch): client = make_worker_client() transport = InProcessWorkerTransport(client) - monkeypatch.setattr(controller_secure.requests, 'post', transport.post) + monkeypatch.setattr(controller_secure.requests, "post", transport.post) yield client reset_worker_state() - def test_secure_hybrid_roundtrip_inprocess(inprocess_worker): if not _hybrid_supported(): - pytest.skip('pyOQS hybrid KEM not available in this environment') + pytest.skip("pyOQS hybrid KEM not available in this environment") - workers = ['http://worker-inproc'] + workers = ["http://worker-inproc"] sm = SessionManager(workers) model = ToyModel([8, 16, 16, 8], seed=42) - x = np.random.default_rng(7).standard_normal((8, 1)).astype('float32') + x = np.random.default_rng(7).standard_normal((8, 1)).astype("float32") sid = sm.start_session(model, num_slices=2, encrypt=True) out = sm.infer(sid, x) diff --git a/prototype/test_secure_run.py b/prototype/test_secure_run.py index 9137cbb..0a09334 100644 --- a/prototype/test_secure_run.py +++ b/prototype/test_secure_run.py @@ -10,7 +10,6 @@ from prototype.model_tools import ToyModel from prototype.session_manager import SessionManager - @pytest.fixture() def inprocess_worker(monkeypatch): client = make_worker_client() @@ -19,7 +18,6 @@ def inprocess_worker(monkeypatch): yield client reset_worker_state() - @pytest.mark.integration def test_secure_run_roundtrip_inprocess(inprocess_worker): """ diff --git a/prototype/test_security_fixes.py b/prototype/test_security_fixes.py index 4d875ea..3ca6ceb 100644 --- a/prototype/test_security_fixes.py +++ b/prototype/test_security_fixes.py @@ -17,7 +17,6 @@ from prototype.model_tools import ToyModel, WeightSlice - def test_pickle_not_used(): """Verify pickle is not used in serialization.""" model = ToyModel([8, 16, 16, 8], seed=42) @@ -33,7 +32,6 @@ def test_pickle_not_used(): assert isinstance(slice_bytes, bytes) assert b"pickle" not in slice_bytes.lower() - def test_safe_deserialization(): """Test that deserialization works without pickle.""" model = ToyModel([8, 16, 16, 8], seed=42) @@ -44,7 +42,6 @@ def test_safe_deserialization(): # Verify we can reconstruct (simplified test) assert len(model_bytes) > 0 - def test_slice_serialization(): """Test slice object serialization.""" model = ToyModel([8, 16, 16, 8], seed=42) @@ -59,7 +56,6 @@ def test_slice_serialization(): # Verify version is preserved assert slice_obj.version == "v1.0" - def test_weight_shapes(): """Test that weight shapes are preserved.""" model = ToyModel([8, 16, 16, 8], seed=42) @@ -70,7 +66,6 @@ def test_weight_shapes(): assert "layer_0_0_weight" in shapes assert "layer_0_0_bias" in shapes - def test_replay_protection_basic(): """Test replay protection prevents nonce reuse.""" from unittest.mock import patch @@ -92,7 +87,6 @@ def test_replay_protection_basic(): # Nonce should now be in seen_nonces assert nonce_hex in aead.seen_nonces, "Nonce should have been marked as seen" - def test_replay_protection_fresh_nonce(): """Test that fresh nonces work correctly.""" from prototype.crypto_improved import ReplayProtectedAEAD @@ -116,7 +110,6 @@ def test_replay_protection_fresh_nonce(): decrypted = aead_verify.decrypt(nonce, ct) assert decrypted == plaintext - def test_hkdf_versioned_info(): """Test that HKDF uses versioned info string.""" from cryptography.hazmat.primitives.asymmetric import x25519 @@ -135,7 +128,6 @@ def test_hkdf_versioned_info(): # Verify key is derived (non-empty) assert len(shared_key) == 32 - def test_input_validation(): """Test that worker validates input sizes.""" # Test with very large payload @@ -153,7 +145,6 @@ def test_input_validation(): # Service not running is acceptable for this test pytest.skip("Worker service not running") - def test_connection_pooling(): """Test that controller uses connection pooling.""" from prototype.controller import Controller @@ -167,7 +158,6 @@ def test_connection_pooling(): except (ConnectionError, requests.exceptions.ConnectionError): pytest.skip("Controller service not available") - def test_model_versioning(): """Test that model versions are tracked.""" model = ToyModel([8, 16, 16, 8], seed=42, version="v1.0") @@ -175,7 +165,6 @@ def test_model_versioning(): slice_obj = model.slice(0, 2) assert slice_obj.version == "v1.0" - def test_worker_health_endpoint(): """Test worker health check endpoint.""" try: @@ -188,6 +177,5 @@ def test_worker_health_endpoint(): except (requests.exceptions.ConnectionError, requests.exceptions.Timeout): pytest.skip("Worker service not running on port 8000") - if __name__ == "__main__": pytest.main([__file__, "-v"]) diff --git a/prototype/test_worker_lifecycle.py b/prototype/test_worker_lifecycle.py index 691b6dc..ea425d4 100644 --- a/prototype/test_worker_lifecycle.py +++ b/prototype/test_worker_lifecycle.py @@ -10,7 +10,6 @@ from prototype.model_tools import ToyModel from prototype.session_manager import SessionManager - @pytest.fixture() def inprocess_worker(monkeypatch): client = make_worker_client() @@ -19,7 +18,6 @@ def inprocess_worker(monkeypatch): yield client reset_worker_state() - def test_worker_leave_triggers_slice_reshare_without_errors(inprocess_worker): workers = ["http://worker-a", "http://worker-b"] sm = SessionManager(workers) @@ -38,7 +36,6 @@ def test_worker_leave_triggers_slice_reshare_without_errors(inprocess_worker): assert np.allclose(out, baseline) - def test_worker_join_leave_reconnect_encrypted_flow(inprocess_worker): workers = ["http://worker-a"] sm = SessionManager(workers) diff --git a/prototype/vllm_engine.py b/prototype/vllm_engine.py index 6769c89..714d797 100644 --- a/prototype/vllm_engine.py +++ b/prototype/vllm_engine.py @@ -1,26 +1,27 @@ # prototype/vllm_engine.py (NEW) from typing import List, Optional + import torch from transformers import AutoTokenizer class VllmInferenceEngine: """Production inference engine using vLLM for optimal GPU utilization.""" - + def __init__( self, model_id: str, gpu_memory_fraction: float = 0.8, max_num_seqs: int = 64, tensor_parallel_size: int = 1, - enforce_eager: bool = False + enforce_eager: bool = False, ): self.model_id = model_id self.gpu_memory_fraction = gpu_memory_fraction self.max_num_seqs = max_num_seqs self.tensor_parallel_size = tensor_parallel_size - + import vllm - + # Initialize vLLM engine with optimal settings self.engine = vllm.LLM( model=model_id, @@ -30,63 +31,64 @@ def __init__( enforce_eager=enforce_eager, # For debugging/control enable_prefix_caching=True, # Performance optimization ) - + self.tokenizer = AutoTokenizer.from_pretrained(model_id) - + def generate( self, prompts: List[str], max_tokens: int = 256, temperature: float = 1.0, top_p: float = 0.9, - stop: Optional[List[str]] = None + stop: Optional[List[str]] = None, ) -> List[str]: """Batched generation with vLLM.""" - + # Tokenize prompts - input_ids = self.tokenizer( - prompts, - return_tensors="pt", - padding=True - ).to(self.engine.device) - + input_ids = self.tokenizer(prompts, return_tensors="pt", padding=True).to( + self.engine.device + ) + # Generate using vLLM's optimized path outputs = self.engine.generate( **input_ids, max_tokens=max_tokens, temperature=temperature, top_p=top_p, - stop=stop + stop=stop, ) - + # Decode and return decoded = self.tokenizer.batch_decode(outputs) return decoded - + def tokenized_generate( self, input_ids: torch.Tensor, attention_mask: Optional[torch.Tensor] = None, - max_tokens: int = 256 + max_tokens: int = 256, ) -> List[str]: """Generate from pre-tokenized input (for pipeline parallelism).""" - + outputs = self.engine.generate( - input_ids=input_ids, - attention_mask=attention_mask, - max_tokens=max_tokens + input_ids=input_ids, attention_mask=attention_mask, max_tokens=max_tokens ) - + decoded = self.tokenizer.batch_decode(outputs) return decoded - + def get_model_profile(self) -> dict: """Get vLLM engine profile for monitoring.""" profile = { "num_active_requests": len(self.engine.get_cache_config()), - "cache_hit_rate": self.engine.get_cache_config().cache_hit_rate if hasattr(self.engine, 'get_cache_config') else None, + "cache_hit_rate": ( + self.engine.get_cache_config().cache_hit_rate + if hasattr(self.engine, "get_cache_config") + else None + ), "gpu_memory_utilization": self.engine.get_gpu_memory_utilization(), - "num_tokens_seen": self.engine.get_num_prompt_tokens_seen() + self.engine.get_num_generation_tokens_seen(), + "num_tokens_seen": self.engine.get_num_prompt_tokens_seen() + + self.engine.get_num_generation_tokens_seen(), } - + return profile diff --git a/prototype/worker.py b/prototype/worker.py index 1c97e25..477a389 100644 --- a/prototype/worker.py +++ b/prototype/worker.py @@ -16,20 +16,17 @@ slices: Dict[str, WeightSlice] = {} slices_lock = asyncio.Lock() - class PreloadRequest(BaseModel): slice_id: str manifest: dict weights_b64: str version: str = "v1.0" # Model version from manifest - class ExecRequest(BaseModel): slice_id: str input_b64: str version: str = "v1.0" # Optional version check - @app.post("/preload") async def preload(req: PreloadRequest): """ @@ -79,7 +76,6 @@ async def preload(req: PreloadRequest): }, 400 raise HTTPException(status_code=400, detail=str(e)) - @app.post("/execute") async def execute(req: ExecRequest): """ @@ -134,7 +130,6 @@ async def execute(req: ExecRequest): return {"error": "Pickle deserialization error"}, 400 raise HTTPException(status_code=400, detail=str(e)) - @app.get("/health") async def health_check(): """Health check endpoint for load balancers.""" @@ -145,7 +140,6 @@ async def health_check(): "version": "v1.0", } - @app.get("/metrics") async def get_metrics(): """Basic metrics endpoint.""" @@ -154,7 +148,6 @@ async def get_metrics(): "slices": list(slices.keys())[:10], # First 10 slice IDs } - if __name__ == "__main__": import argparse diff --git a/prototype/worker_gpu.py b/prototype/worker_gpu.py index cceb89e..62ea7f5 100644 --- a/prototype/worker_gpu.py +++ b/prototype/worker_gpu.py @@ -1,29 +1,30 @@ # prototype/worker_gpu.py (NEW) - Enhanced worker with GPU support -from fastapi import FastAPI, HTTPException +import base64 +from typing import Dict, Optional + +import numpy as np import torch import uvicorn -import numpy as np -from typing import Dict, Optional -import base64 +from fastapi import FastAPI, HTTPException from vllm import LLM app = FastAPI() class GPUSlice: """GPU-accelerated slice for distributed inference.""" - + def __init__(self, model_slice: torch.nn.Module): self.model = model_slice self.device = torch.cuda.current_device() - + def forward(self, x: np.ndarray) -> np.ndarray: """GPU-accelerated forward pass with CUDA kernel fusion.""" x_tensor = torch.from_numpy(x).float().to(self.device) - + # Forward pass on GPU with torch.no_grad(): out_tensor = self.model(x_tensor) - + return out_tensor.cpu().numpy() # Global model registry @@ -32,16 +33,14 @@ def forward(self, x: np.ndarray) -> np.ndarray: @app.post("/execute-gpu") async def execute_gpu(req: ExecRequest): """GPU-accelerated inference with batch support.""" - + if req.slice_id not in model_slices: raise HTTPException(status_code=404, detail="slice not found") - + slice_model = model_slices[req.slice_id] x = np.ascontiguousarray(req.input_blob) # Ensure contiguous - + with torch.cuda.amp.autocast(): # Mixed precision out = slice_model.forward(x) - - return { - "output_b64": base64.b64encode(out).decode('ascii') - } + + return {"output_b64": base64.b64encode(out).decode("ascii")} diff --git a/prototype/worker_secure.py b/prototype/worker_secure.py index 83b75eb..4e97037 100644 --- a/prototype/worker_secure.py +++ b/prototype/worker_secure.py @@ -32,13 +32,11 @@ metrics_lock = threading.Lock() telemetry = Telemetry(metrics, metrics_lock) - class HandshakeRequest(BaseModel): client_pub_b64: str client_id: str | None = None oqs_pub_b64: str | None = None - class PreloadRequest(BaseModel): slice_id: str manifest: dict @@ -46,7 +44,6 @@ class PreloadRequest(BaseModel): encrypted: bool = False nonce_b64: str = None - class ExecRequest(BaseModel): slice_id: str input_b64: str @@ -54,7 +51,6 @@ class ExecRequest(BaseModel): encrypted: bool = False nonce_b64: str = None - @app.post("/handshake") async def handshake(req: HandshakeRequest): """ @@ -129,7 +125,6 @@ async def handshake(req: HandshakeRequest): return resp - @app.post("/preload") @telemetry.timed("preload_time_sum", "preload_time_count") async def preload(req: PreloadRequest): @@ -194,7 +189,6 @@ async def preload(req: PreloadRequest): raise HTTPException(status_code=400, detail=str(e)) - @app.post("/execute") @telemetry.timed("execute_time_sum", "execute_time_count") async def execute(req: ExecRequest): @@ -264,12 +258,14 @@ async def execute(req: ExecRequest): raise HTTPException(status_code=400, detail=str(e)) - @app.get("/health") async def health_check(): """Health check endpoint.""" - return {"status": "healthy", "service": "mohawk-worker", "timestamp": datetime.now().isoformat()} - + return { + "status": "healthy", + "service": "mohawk-worker", + "timestamp": datetime.now().isoformat(), + } @app.get("/metrics") async def get_metrics(): @@ -325,13 +321,11 @@ def percentile(p): return JSONResponse(content=out) - @app.get("/api/workers") async def list_workers(): """Return list of loaded model slices (workers).""" return {"workers": list(slices.keys()), "count": len(slices)} - if __name__ == "__main__": import argparse