stable-diffusion-aws-extension/middleware_api/lambda/inferences/list_inferences.py

80 lines
2.5 KiB
Python

import json
import logging
import os
import boto3
from boto3.dynamodb.conditions import Key
from common.ddb_service.client import DynamoDbUtilsService
from common.response import ok
from common.util import get_query_param
from libs.data_types import InferenceJob
from libs.utils import get_user_roles, check_user_permissions, decode_last_key, encode_last_key, response_error
inference_table_name = os.environ.get('INFERENCE_JOB_TABLE')
user_table = os.environ.get('MULTI_USER_TABLE')
logger = logging.getLogger(__name__)
logger.setLevel(os.environ.get('LOG_LEVEL') or logging.ERROR)
ddb_service = DynamoDbUtilsService(logger=logger)
ddb = boto3.resource('dynamodb')
table = ddb.Table(inference_table_name)
# GET /inferences?last_evaluated_key=xxx&limit=10
def handler(event, ctx):
try:
logger.info(json.dumps(event))
_filter = {}
# todo compatibility with old version
# permissions_check(event, [PERMISSION_INFERENCE_ALL])
username = get_query_param(event, 'username')
last_evaluated_key = get_query_param(event, 'last_evaluated_key')
inference_type = get_query_param(event, 'type', 'txt2img')
limit = int(get_query_param(event, 'limit', 10))
scan_kwargs = {
'Limit': limit,
'IndexName': "taskType-createTime-index",
'KeyConditionExpression': Key('taskType').eq(inference_type),
"ScanIndexForward": False
}
if last_evaluated_key:
scan_kwargs['ExclusiveStartKey'] = decode_last_key(last_evaluated_key)
logger.info(scan_kwargs)
response = table.query(**scan_kwargs)
logger.info(json.dumps(response, default=str))
items = response.get('Items', [])
last_evaluated_key = encode_last_key(response.get('LastEvaluatedKey'))
results = []
user_roles = []
if username:
user_roles = get_user_roles(ddb_service=ddb_service, user_table_name=user_table, username=username)
for row in items:
inference = InferenceJob(**row)
if username:
if check_user_permissions(inference.owner_group_or_role, user_roles, username):
results.append(inference.__dict__)
else:
results.append(inference.__dict__)
data = {
'inferences': results,
'last_evaluated_key': last_evaluated_key
}
return ok(data=data, decimal=True)
except Exception as e:
return response_error(e)