morphik-core/start_server.py

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import argparse
import atexit
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import logging
import os
import signal
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import socket
import subprocess
import sys
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import time
import requests
import tomli
import uvicorn
from dotenv import load_dotenv
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from core.config import get_settings
from core.logging_config import setup_logging
# Global variable to store the worker process
worker_process = None
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def wait_for_redis(host="localhost", port=6379, timeout=20):
"""
Wait for Redis to become available.
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Args:
host: Redis host address
port: Redis port number
timeout: Maximum time to wait in seconds
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Returns:
True if Redis becomes available within the timeout, False otherwise
"""
logging.info(f"Waiting for Redis to be available at {host}:{port}...")
t0 = time.monotonic()
while time.monotonic() - t0 < timeout:
try:
with socket.create_connection((host, port), timeout=1):
logging.info("Redis is accepting connections.")
return True
except (OSError, socket.error):
logging.debug(f"Redis not available yet, retrying... ({int(time.monotonic() - t0)}s elapsed)")
time.sleep(0.3)
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logging.error(f"Redis not reachable after {timeout}s")
return False
def check_and_start_redis():
"""Check if the Redis container is running, start if necessary."""
try:
# Check if container exists and is running
check_running_cmd = ["docker", "ps", "-q", "-f", "name=morphik-redis"]
running_container = subprocess.check_output(check_running_cmd).strip()
if running_container:
logging.info("Redis container (morphik-redis) is already running.")
return
# Check if container exists but is stopped
check_exists_cmd = ["docker", "ps", "-a", "-q", "-f", "name=morphik-redis"]
existing_container = subprocess.check_output(check_exists_cmd).strip()
if existing_container:
logging.info("Starting existing Redis container (morphik-redis)...")
subprocess.run(["docker", "start", "morphik-redis"], check=True, capture_output=True)
logging.info("Redis container started.")
else:
logging.info("Creating and starting Redis container (morphik-redis)...")
subprocess.run(
["docker", "run", "-d", "--name", "morphik-redis", "-p", "6379:6379", "redis"],
check=True,
capture_output=True,
)
logging.info("Redis container created and started.")
except subprocess.CalledProcessError as e:
logging.error(f"Failed to manage Redis container: {e}")
logging.error(f"Stderr: {e.stderr.decode() if e.stderr else 'N/A'}")
sys.exit(1)
except FileNotFoundError:
logging.error("Docker command not found. Please ensure Docker is installed and in PATH.")
sys.exit(1)
def start_arq_worker():
"""Start the ARQ worker as a subprocess."""
global worker_process
try:
logging.info("Starting ARQ worker...")
# Ensure logs directory exists
log_dir = os.path.join(os.getcwd(), "logs")
os.makedirs(log_dir, exist_ok=True)
# Worker log file paths
worker_log_path = os.path.join(log_dir, "worker.log")
# Open log files
worker_log = open(worker_log_path, "a")
# Add timestamp to log
timestamp = subprocess.check_output(["date"]).decode().strip()
worker_log.write(f"\n\n--- Worker started at {timestamp} ---\n\n")
worker_log.flush()
# Use sys.executable to ensure the same Python environment is used
worker_cmd = [sys.executable, "-m", "arq", "core.workers.ingestion_worker.WorkerSettings"]
# Start the worker with output redirected to log files
worker_process = subprocess.Popen(
worker_cmd,
stdout=worker_log,
stderr=worker_log,
env=dict(os.environ, PYTHONUNBUFFERED="1"), # Ensure unbuffered output
)
logging.info(f"ARQ worker started with PID: {worker_process.pid}")
logging.info(f"Worker logs available at: {worker_log_path}")
except Exception as e:
logging.error(f"Failed to start ARQ worker: {e}")
sys.exit(1)
def cleanup_processes():
"""Stop the ARQ worker process on exit."""
global worker_process
if worker_process and worker_process.poll() is None: # Check if process is still running
logging.info(f"Stopping ARQ worker (PID: {worker_process.pid})...")
# Log the worker termination
try:
log_dir = os.path.join(os.getcwd(), "logs")
worker_log_path = os.path.join(log_dir, "worker.log")
with open(worker_log_path, "a") as worker_log:
timestamp = subprocess.check_output(["date"]).decode().strip()
worker_log.write(f"\n\n--- Worker stopping at {timestamp} ---\n\n")
except Exception as e:
logging.warning(f"Could not write worker stop message to log: {e}")
# Send SIGTERM first for graceful shutdown
worker_process.terminate()
try:
# Wait a bit for graceful shutdown
worker_process.wait(timeout=5)
logging.info("ARQ worker stopped gracefully.")
except subprocess.TimeoutExpired:
logging.warning("ARQ worker did not terminate gracefully, sending SIGKILL.")
worker_process.kill() # Force kill if it doesn't stop
logging.info("ARQ worker killed.")
# Close any open file descriptors for the process
if hasattr(worker_process, "stdout") and worker_process.stdout:
worker_process.stdout.close()
if hasattr(worker_process, "stderr") and worker_process.stderr:
worker_process.stderr.close()
# Optional: Add Redis container stop logic here if desired
# try:
# logging.info("Stopping Redis container...")
# subprocess.run(["docker", "stop", "morphik-redis"], check=False, capture_output=True)
# except Exception as e:
# logging.warning(f"Could not stop Redis container: {e}")
# Register the cleanup function to be called on script exit
atexit.register(cleanup_processes)
# Also register for SIGINT (Ctrl+C) and SIGTERM
signal.signal(signal.SIGINT, lambda sig, frame: sys.exit(0))
signal.signal(signal.SIGTERM, lambda sig, frame: sys.exit(0))
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def check_ollama_running(base_url):
"""Check if Ollama is running and accessible at the given URL."""
try:
api_url = f"{base_url}/api/tags"
response = requests.get(api_url, timeout=2)
return response.status_code == 200
except requests.RequestException:
return False
def get_ollama_usage_info():
"""Check if Ollama is required based on the configuration file and get base URLs."""
try:
with open("morphik.toml", "rb") as f:
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config = tomli.load(f)
ollama_configs = []
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# Get registered Ollama models first
ollama_models = {}
if "registered_models" in config:
for model_key, model_config in config["registered_models"].items():
model_name = model_config.get("model_name", "")
if "ollama" in model_name:
api_base = model_config.get("api_base")
if api_base:
ollama_models[model_key] = api_base
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# Check which components are using Ollama models
components_to_check = ["embedding", "completion", "rules", "graph", "parser.vision"]
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for component in components_to_check:
if component == "parser.vision":
# Special handling for parser.vision
if "parser" in config and "vision" in config["parser"]:
model_key = config["parser"]["vision"].get("model")
if model_key in ollama_models:
ollama_configs.append({"component": component, "base_url": ollama_models[model_key]})
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else:
# Standard component check
if component in config:
model_key = config[component].get("model")
if model_key in ollama_models:
ollama_configs.append({"component": component, "base_url": ollama_models[model_key]})
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# Add contextual chunking model check
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if (
"parser" in config
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and config["parser"].get("use_contextual_chunking")
and "contextual_chunking_model" in config["parser"]
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):
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model_key = config["parser"]["contextual_chunking_model"]
if model_key in ollama_models:
ollama_configs.append(
{
"component": "parser.contextual_chunking",
"base_url": ollama_models[model_key],
}
)
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return ollama_configs
except Exception as e:
logging.error(f"Error checking Ollama configuration: {e}")
return []
def main():
# Parse command line arguments
parser = argparse.ArgumentParser(description="Start the Morphik server")
parser.add_argument(
"--log",
choices=["debug", "info", "warning", "error"],
default="info",
help="Set the logging level",
)
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parser.add_argument(
"--skip-ollama-check",
action="store_true",
help="Skip Ollama availability check",
)
args = parser.parse_args()
# Set up logging first with specified level
setup_logging(log_level=args.log.upper())
# Check and start Redis container
check_and_start_redis()
# Load environment variables from .env file
load_dotenv()
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# Check if Ollama is required and running
if not args.skip_ollama_check:
ollama_configs = get_ollama_usage_info()
if ollama_configs:
# Group configs by base_url to avoid redundant checks
base_urls = {}
for config in ollama_configs:
if config["base_url"] not in base_urls:
base_urls[config["base_url"]] = []
base_urls[config["base_url"]].append(config["component"])
all_running = True
for base_url, components in base_urls.items():
if not check_ollama_running(base_url):
print(f"ERROR: Ollama is not accessible at {base_url}")
print(f"This URL is used by these components: {', '.join(components)}")
all_running = False
if not all_running:
print("\nPlease ensure Ollama is running at the configured URLs before starting the server")
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print("Run with --skip-ollama-check to bypass this check")
sys.exit(1)
else:
component_list = [config["component"] for config in ollama_configs]
print(f"Ollama is running and will be used for: {', '.join(component_list)}")
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# Load settings (this will validate all required env vars)
settings = get_settings()
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# Wait for Redis to be available (using environment variables or defaults)
redis_host = os.environ.get("REDIS_HOST", "127.0.0.1")
redis_port = int(os.environ.get("REDIS_PORT", "6379"))
if not wait_for_redis(host=redis_host, port=redis_port):
logging.error("Cannot start server without Redis. Please ensure Redis is running.")
sys.exit(1)
# Start ARQ worker in the background
start_arq_worker()
# Start server (this is blocking)
logging.info("Starting Uvicorn server...")
uvicorn.run(
"core.api:app",
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host=settings.HOST,
port=settings.PORT,
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loop="asyncio",
log_level=args.log,
# reload=settings.RELOAD # Reload might interfere with subprocess management
)
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if __name__ == "__main__":
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main()