Files
ai-training-monitor/backend/app/services/config_manager.py
2025-01-23 13:46:30 +01:00

152 lines
6.0 KiB
Python

# app/services/config_manager.py
import logging
import os
import aiofiles
import paramiko
import yaml
from fastapi import HTTPException
from app.core.config import settings
from app.models.config import TrainingConfig, ProcessConfig, SaveConfig, DatasetConfig
logger = logging.getLogger(__name__)
class ConfigManager:
"""
Manages access to training configuration files, supporting both local and remote (SFTP) paths.
Handles YAML parsing and conversion to strongly-typed configuration objects.
"""
def __init__(self):
# Initialize paths from settings, defaulting to None if not configured
self.remote_path = getattr(settings, 'TRAINING_CONFIG_REMOTE_PATH', None)
self.local_path = getattr(settings, 'TRAINING_CONFIG_LOCAL_PATH', None)
self.sftp_client = None
self.cached_config = None
# Validate that at least one path is configured
if not self.remote_path and not self.local_path:
raise ValueError("Either TRAINING_CONFIG_REMOTE_PATH or TRAINING_CONFIG_LOCAL_PATH must be configured")
logger.info(f"ConfigManager initialized with remote_path={self.remote_path}, local_path={self.local_path}")
async def _connect_sftp(self):
"""Establishes SFTP connection using SSH key authentication"""
try:
key_path = os.path.expanduser(settings.SFTP_KEY_PATH)
logger.info(f"Connecting to SFTP {settings.SFTP_HOST} with key {key_path}")
ssh = paramiko.SSHClient()
ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
ssh.connect(
hostname=settings.SFTP_HOST,
username=settings.SFTP_USER,
port=settings.SFTP_PORT,
key_filename=key_path,
)
self.sftp_client = ssh.open_sftp()
logger.info("SFTP connection established successfully")
except Exception as e:
logger.error(f"Failed to establish SFTP connection: {str(e)}")
raise HTTPException(status_code=500, detail=f"SFTP connection failed: {str(e)}")
def _disconnect_sftp(self):
"""Safely closes SFTP connection if it exists"""
if self.sftp_client:
try:
self.sftp_client.close()
self.sftp_client = None
logger.info("SFTP connection closed")
except Exception as e:
logger.error(f"Error closing SFTP connection: {str(e)}")
async def _read_remote_config(self) -> dict:
"""Reads and parses YAML configuration from remote SFTP location"""
if not self.sftp_client:
await self._connect_sftp()
try:
with self.sftp_client.open(self.remote_path, 'r') as f:
content = f.read()
return yaml.safe_load(content)
except Exception as e:
logger.error(f"Failed to read remote config: {str(e)}")
raise HTTPException(status_code=500, detail=f"Failed to read remote config: {str(e)}")
finally:
self._disconnect_sftp()
async def _read_local_config(self) -> dict:
"""Reads and parses YAML configuration from local filesystem"""
try:
async with aiofiles.open(self.local_path, 'r') as f:
content = await f.read()
return yaml.safe_load(content)
except Exception as e:
logger.error(f"Failed to read local config: {str(e)}")
raise HTTPException(status_code=500, detail=f"Failed to read local config: {str(e)}")
def _parse_config(self, raw_config: dict) -> TrainingConfig:
"""
Converts raw YAML dictionary into strongly-typed configuration objects.
Handles optional fields and nested configurations.
"""
try:
# Extract the first process configuration (assuming single process for now)
process_data = raw_config['config']['process'][0]
# Build the process config with all its nested components
process = ProcessConfig(
type=process_data['type'],
training_folder=process_data['training_folder'],
performance_log_every=process_data.get('performance_log_every'),
device=process_data.get('device'),
trigger_word=process_data.get('trigger_word'),
save=SaveConfig(**process_data['save']) if 'save' in process_data else None,
datasets=[DatasetConfig(**ds) for ds in process_data.get('datasets', [])],
train=process_data['train'],
model=process_data['model'],
sample=process_data['sample']
)
# Reconstruct the config dictionary with our parsed process
config_dict = dict(raw_config['config'])
config_dict['process'] = [process]
# Create the full training config
return TrainingConfig(
job=raw_config.get('job', ''),
config=config_dict,
meta=raw_config.get('meta', {})
)
except Exception as e:
logger.error(f"Failed to parse config: {str(e)}")
raise HTTPException(status_code=500, detail=f"Config parsing failed: {str(e)}")
async def get_config(self) -> TrainingConfig:
"""
Main method to retrieve and parse configuration.
Automatically handles local or remote access based on configuration.
"""
if self.cached_config is not None:
return self.cached_config
try:
# Read raw config from appropriate source
raw_config = await self._read_remote_config() if self.remote_path else await self._read_local_config()
# Parse and return strongly-typed config
parsed_config = self._parse_config(raw_config)
self.cached_config = parsed_config
return parsed_config
except Exception as e:
logger.error(f"Failed to get config: {str(e)}")
raise HTTPException(status_code=500, detail=str(e))