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"""
API utility functions for pipelines.
"""
import logging
from typing import Dict, Any, Optional
from .common import get_evaluation_type
logger = logging.getLogger(__name__)
def update_status(run_id: str) -> Dict[str, Any]:
"""
Update status for the current evaluation type
Args:
run_id: The run ID to check status for
Returns:
Dict with status information
"""
if not run_id:
return {
"status": "error",
"message": "No run ID provided"
}
logger.info(f"Checking status for run ID: {run_id}")
# In the new design, we're using a unified Airflow approach
# This function is kept for compatibility with existing code
return {
"status": "pending",
"message": "Status checking is not implemented in the unified benchmark approach"
}
def fetch_logs(run_id: str) -> Dict[str, Any]:
"""
Fetch logs for the current evaluation type
Args:
run_id: The run ID to fetch logs for
Returns:
Dict with logs information
"""
if not run_id:
return {
"status": "error",
"message": "No run ID provided"
}
logger.info(f"Fetching logs for run ID: {run_id}")
# In the new design, we're using a unified Airflow approach
# This function is kept for compatibility with existing code
return {
"status": "pending",
"logs": f"Logs for run ID {run_id} are not available in the unified benchmark approach"
}
def fetch_results(run_id: str) -> Dict[str, Any]:
"""
Fetch results for the current evaluation type
Args:
run_id: The run ID to fetch results for
Returns:
Dict with results information
"""
if not run_id:
return {
"status": "error",
"message": "No run ID provided"
}
logger.info(f"Fetching results for run ID: {run_id}")
# In the new design, we're using a unified Airflow approach
# This function is kept for compatibility with existing code
return {
"status": "pending",
"results": f"Results for run ID {run_id} are not available in the unified benchmark approach"
} |