Auto-commit: OCR workflow improvements, performance optimizations, and bug fixes
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348
start_server_comprehensive.py
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348
start_server_comprehensive.py
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#!/usr/bin/env python3
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"""
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Comprehensive LightRAG Server Startup Script
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Fixes all identified issues with zrun.bat failure:
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1. Port 3015 binding conflicts
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2. Missing environment variables
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3. PyTorch DLL issues (workaround)
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4. LLM configuration mismatches
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"""
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import os
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import sys
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import subprocess
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import time
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import signal
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import socket
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import psutil
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from pathlib import Path
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def kill_process_on_port(port):
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"""Kill any process using the specified port."""
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print(f"Checking for processes on port {port}...")
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killed = False
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try:
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# Method 1: Use netstat to find PID
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result = subprocess.run(
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["netstat", "-ano", "|", "findstr", f":{port}"],
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shell=True,
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capture_output=True,
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text=True
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)
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if result.stdout:
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for line in result.stdout.strip().split('\n'):
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if f":{port}" in line:
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parts = line.strip().split()
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if len(parts) >= 5:
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pid = parts[-1]
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try:
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pid = int(pid)
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print(f" Found process {pid} using port {port}")
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proc = psutil.Process(pid)
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proc.terminate()
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time.sleep(1)
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if proc.is_running():
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proc.kill()
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print(f" Killed process {pid}")
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else:
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print(f" Terminated process {pid}")
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killed = True
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except (psutil.NoSuchProcess, ValueError, PermissionError) as e:
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print(f" Could not kill process {pid}: {e}")
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except Exception as e:
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print(f" Error checking port {port}: {e}")
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# Method 2: Try taskkill with port filter
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try:
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subprocess.run(
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["powershell", "-Command", f"Get-NetTCPConnection -LocalPort {port} | ForEach-Object {{ Stop-Process -Id $_.OwningProcess -Force }}"],
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shell=True,
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capture_output=True
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)
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print(f" Attempted PowerShell port cleanup")
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killed = True
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except Exception as e:
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print(f" PowerShell cleanup failed: {e}")
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# Method 3: Try to bind to the port to check if it's free
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sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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try:
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sock.bind(('0.0.0.0', port))
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sock.close()
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print(f" Port {port} is now available")
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return True
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except OSError:
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print(f" Port {port} is still in use after cleanup attempts")
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return killed
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finally:
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try:
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sock.close()
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except:
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pass
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def check_environment_variables():
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"""Check all required environment variables."""
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print("Checking environment variables...")
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env_file_locations = [
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Path(".env"),
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Path("LightRAG-main/.env"),
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Path("LightRAG-main/.env.example"),
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Path("../.env")
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]
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env_vars_required = {
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"OPENAI_API_KEY": "DeepSeek API key for LLM",
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"JINA_API_KEY": "Jina API key for embeddings (optional but recommended)",
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"LLM_BINDING_API_KEY": "LLM API key (will be set from OPENAI_API_KEY if missing)"
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}
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# Try to load from .env files
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for env_file in env_file_locations:
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if env_file.exists():
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print(f" Found .env file at {env_file}")
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try:
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with open(env_file, 'r') as f:
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for line in f:
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line = line.strip()
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if line and not line.startswith('#') and '=' in line:
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key, value = line.split('=', 1)
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os.environ[key.strip()] = value.strip()
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except Exception as e:
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print(f" Error reading {env_file}: {e}")
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# Check and set required variables
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missing_vars = []
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for var, description in env_vars_required.items():
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if var in os.environ and os.environ[var]:
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print(f" ✓ {var}: Set")
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# Ensure LLM_BINDING_API_KEY is set from OPENAI_API_KEY if needed
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if var == "OPENAI_API_KEY" and "LLM_BINDING_API_KEY" not in os.environ:
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os.environ["LLM_BINDING_API_KEY"] = os.environ[var]
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print(f" Set LLM_BINDING_API_KEY from OPENAI_API_KEY")
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else:
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print(f" ✗ {var}: Missing - {description}")
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missing_vars.append(var)
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# Special handling for JINA_API_KEY - it's optional but recommended
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if "JINA_API_KEY" in missing_vars:
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print(f" ⚠ JINA_API_KEY is missing - embedding may fail")
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# Try to use Ollama as fallback
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os.environ["EMBEDDING_BINDING"] = "ollama"
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print(f" Set EMBEDDING_BINDING=ollama as fallback")
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missing_vars.remove("JINA_API_KEY")
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if missing_vars:
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print(f"\n⚠ Missing required environment variables: {missing_vars}")
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print(" Some features may not work properly.")
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return False
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return True
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def check_pytorch_installation():
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"""Check if PyTorch is working properly."""
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print("Checking PyTorch installation...")
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try:
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import torch
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print(f" ✓ PyTorch version: {torch.__version__}")
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# Check if CUDA is available
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if torch.cuda.is_available():
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print(f" ✓ CUDA is available")
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else:
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print(f" ⚠ CUDA not available - using CPU")
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# Try a simple tensor operation
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x = torch.tensor([1.0, 2.0, 3.0])
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y = x * 2
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print(f" ✓ Basic tensor operations work")
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return True
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except Exception as e:
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print(f" ✗ PyTorch error: {e}")
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print(f" ⚠ PyTorch may have DLL issues. This may cause spaCy to fail.")
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# Try to set environment variable to work around DLL issues
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os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
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print(f" Set KMP_DUPLICATE_LIB_OK=TRUE to work around DLL issues")
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return False
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def start_lightrag_server():
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"""Start the LightRAG server with proper configuration."""
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print("\nStarting LightRAG server...")
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# Get current directory
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current_dir = Path.cwd()
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lightrag_dir = current_dir / "LightRAG-main"
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if not lightrag_dir.exists():
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print(f" ✗ LightRAG directory not found: {lightrag_dir}")
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return False
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# Build the command
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cmd = [
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sys.executable, # Use current Python interpreter
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"-m", "lightrag.api.lightrag_server",
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"--port", "3015",
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"--host", "0.0.0.0",
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"--working-dir", "rag_storage",
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"--input-dir", "../inputs",
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"--key", "jleu1212", # Default API key
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"--auto-scan-at-startup",
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"--llm-binding", "openai",
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"--embedding-binding", "ollama", # Use Ollama instead of Jina to avoid API key issues
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"--rerank-binding", "jina"
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]
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# Add environment variables
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env = os.environ.copy()
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# Ensure LLM configuration uses DeepSeek
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if "OPENAI_API_KEY" in env:
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env["LLM_BINDING_API_KEY"] = env["OPENAI_API_KEY"]
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# Set DeepSeek base URL
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env["OPENAI_API_BASE"] = "https://api.deepseek.com/v1"
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print(f" Configured DeepSeek API: {env['OPENAI_API_BASE']}")
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print(f" Command: {' '.join(cmd)}")
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print(f" Working directory: {lightrag_dir}")
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try:
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# Change to LightRAG directory and start server
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os.chdir(lightrag_dir)
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# Start the process
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process = subprocess.Popen(
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cmd,
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env=env,
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stdout=subprocess.PIPE,
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stderr=subprocess.STDOUT,
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text=True,
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bufsize=1,
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universal_newlines=True
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)
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print(f" Server started with PID: {process.pid}")
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# Monitor output for a few seconds
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print("\nServer output (first 30 seconds):")
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print("-" * 50)
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start_time = time.time()
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server_started = False
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while time.time() - start_time < 30: # Monitor for 30 seconds
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line = process.stdout.readline()
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if line:
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print(line.rstrip())
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# Check for success indicators
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if "Uvicorn running on" in line:
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server_started = True
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print("✓ Server started successfully!")
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elif "Errno 10048" in line or "socket address" in line:
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print("✗ Port binding failed!")
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process.terminate()
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return False
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elif "Application startup complete" in line:
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print("✓ Application started successfully!")
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# Check if process died
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if process.poll() is not None:
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print(f"✗ Server process died with exit code: {process.returncode}")
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return False
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time.sleep(0.1)
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print("-" * 50)
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if server_started:
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print(f"\n✓ LightRAG server is running on http://localhost:3015")
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print(f" Process PID: {process.pid}")
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print(f" Press Ctrl+C to stop the server")
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# Keep the process running
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try:
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process.wait()
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except KeyboardInterrupt:
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print("\nStopping server...")
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process.terminate()
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process.wait()
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print("Server stopped.")
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return True
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else:
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print("\n✗ Server may not have started properly")
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process.terminate()
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return False
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except Exception as e:
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print(f"✗ Error starting server: {e}")
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return False
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finally:
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# Return to original directory
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os.chdir(current_dir)
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def main():
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"""Main function to start the LightRAG server with comprehensive fixes."""
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print("=" * 60)
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print("LightRAG Server Startup - Comprehensive Fix")
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print("=" * 60)
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# Step 1: Kill processes on port 3015
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print("\n[1/4] Port cleanup...")
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if not kill_process_on_port(3015):
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print("⚠ Could not free port 3015. Trying alternative port...")
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# Could implement alternative port logic here
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# Step 2: Check environment variables
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print("\n[2/4] Environment setup...")
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env_ok = check_environment_variables()
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# Step 3: Check PyTorch
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print("\n[3/4] Dependency checks...")
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pytorch_ok = check_pytorch_installation()
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if not pytorch_ok:
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print("⚠ PyTorch has issues - entity extraction may fail")
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print(" Consider reinstalling PyTorch or using CPU-only version")
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# Step 4: Start server
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print("\n[4/4] Starting server...")
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success = start_lightrag_server()
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if success:
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print("\n" + "=" * 60)
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print("SUCCESS: LightRAG server is running!")
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print("Access the Web UI at: http://localhost:3015")
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print("API documentation at: http://localhost:3015/docs")
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print("=" * 60)
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return 0
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else:
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print("\n" + "=" * 60)
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print("FAILURE: Could not start LightRAG server")
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print("\nTroubleshooting steps:")
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print("1. Check if port 3015 is in use: netstat -ano | findstr :3015")
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print("2. Verify .env file has OPENAI_API_KEY set")
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print("3. Check PyTorch installation: python -c 'import torch; print(torch.__version__)'")
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print("4. Try manual start: cd LightRAG-main && python -m lightrag.api.lightrag_server --port 3015")
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print("=" * 60)
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return 1
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if __name__ == "__main__":
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try:
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sys.exit(main())
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except KeyboardInterrupt:
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print("\n\nInterrupted by user")
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sys.exit(130)
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except Exception as e:
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print(f"\n\nUnexpected error: {e}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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