def initialize_interfaces(app):
app.default_store = DataStore()
app.naitve_interface = NativeInterface()
app.custom_models = CustomModels()
app.dbw = DatabaseWrapper()
config = Config()
app.config_obj = config
if api_name not in config['api']:
print(
f"Trying run '{api_name}' API, but is no config for this api.")
print(f"Please, fill config['api']['{api_name}']")
sys.exit(0)
start_functions = {
'http': start_http,
'mysql': start_mysql,
'mongodb': start_mongo
}
archive_obsolete_predictors(config, '2.11.0')
mdb = MindsdbNative(config)
cst = CustomModels(config)
# @TODO Maybe just use `get_model_data` directly here ? Seems like a useless abstraction
model_data_arr = [{
'name':
x['name'],
'predict':
x['predict'],
'data_analysis':
mdb.get_model_data(x['name'])['data_analysis_v2']
} for x in mdb.get_models()]
model_data_arr.extend(cst.get_models())
dbw = DatabaseWrapper(config)
dbw.register_predictors(model_data_arr)
def __init__(self, config):
self.config = config
self.mindsdb_native = NativeInterface(config)
self.custom_models = CustomModels(config)
def __init__(self, config):
self.config = Config()
self.mindsdb_native = NativeInterface()
self.custom_models = CustomModels()
self.ai_table = AITable_store()
self.default_store = DataStore()
def initialize_interfaces(config, app):
app.default_store = DataStore(config)
app.mindsdb_native = MindsdbNative(config)
app.custom_models = CustomModels(config)
app.config_obj = config
def initialize_interfaces(config, app):
app.default_store = DataStore(config)
app.mindsdb_native = NativeInterface(config)
app.custom_models = CustomModels(config)
app.dbw = DatabaseWrapper(config)
app.config_obj = config
'port': config['api'][api]['port'],
'process': None,
'started': False
} for api in api_arr
}
if not ray_based:
apis['rcp'] = {'process': rpc_proc, 'started': True}
start_functions = {
'http': start_http,
'mysql': start_mysql,
'mongodb': start_mongo
}
mdb = NativeInterface()
cst = CustomModels()
model_data_arr = get_all_models_meta_data(mdb, cst)
dbw = DatabaseWrapper()
for db_alias in config['integrations']:
dbw.setup_integration(db_alias)
dbw.register_predictors(model_data_arr)
for broken_name in [name for name, connected in dbw.check_connections().items() if connected is False]:
log.error(f'Error failed to integrate with database aliased: {broken_name}')
for api_name, api_data in apis.items():
if api_data['started']:
continue
print(f'{api_name} API: starting...')