Bug: AnthropicClassifier requires AWS settings?

Expected Behaviour

AnthropicClassifier only requires Anthropic API key, does not require any AWS settings like credentials or regions.

Current Behaviour

AnthropicClassifier requires AWS region settings even if I don't want to use Bedrock.

Code snippet

!pip install multi-agent-orchestrator

import getpass
import os

os.environ["ANTHROPIC_API_KEY"] = getpass.getpass('ANTHROPIC_API_KEY')

from multi_agent_orchestrator.classifiers import AnthropicClassifier, AnthropicClassifierOptions
from multi_agent_orchestrator.orchestrator import MultiAgentOrchestrator

anthropic_classifier = AnthropicClassifier(AnthropicClassifierOptions(
    api_key=os.environ["ANTHROPIC_API_KEY"]
))

resulted in NoRegionError.

---------------------------------------------------------------------------
NoRegionError                             Traceback (most recent call last)
Cell In[5], line 4
      1 from multi_agent_orchestrator.classifiers import AnthropicClassifier, AnthropicClassifierOptions
      2 from multi_agent_orchestrator.orchestrator import MultiAgentOrchestrator
----> 4 anthropic_classifier = AnthropicClassifier(AnthropicClassifierOptions(
      5     api_key=os.environ["ANTHROPIC_API_KEY"]
      6 ))

File /opt/conda/lib/python3.12/site-packages/multi_agent_orchestrator/classifiers/anthropic_classifier.py:23, in AnthropicClassifier.__init__(self, options)
     22 def __init__(self, options: AnthropicClassifierOptions):
---> 23     super().__init__()
     25     if not options.api_key:
     26         raise ValueError("Anthropic API key is required")

File /opt/conda/lib/python3.12/site-packages/multi_agent_orchestrator/classifiers/classifier.py:16, in Classifier.__init__(self)
     15 def __init__(self):
---> 16     self.default_agent = BedrockLLMAgent(
     17         options=BedrockLLMAgentOptions(
     18         name=AgentTypes.DEFAULT.value,
     19         streaming=True,
     20         description="A knowledgeable generalist capable of addressing a wide range of topics.\
     21         This agent should be selected if no other specialized agent is a better fit."
     22     ))
     24     self.agent_descriptions = ""
     25     self.history = ""

File /opt/conda/lib/python3.12/site-packages/multi_agent_orchestrator/agents/bedrock_llm_agent.py:39, in BedrockLLMAgent.__init__(self, options)
     34         self.client = boto3.client(
     35             'bedrock-runtime',
     36             region_name=options.region or os.environ.get('AWS_REGION')
     37         )
     38     else:
---> 39         self.client = boto3.client('bedrock-runtime')
     41 self.model_id: str = options.model_id or BEDROCK_MODEL_ID_CLAUDE_3_HAIKU
     42 self.streaming: bool = options.streaming

File /opt/conda/lib/python3.12/site-packages/boto3/__init__.py:92, in client(*args, **kwargs)
     86 def client(*args, **kwargs):
     87     """
     88     Create a low-level service client by name using the default session.
     89 
     90     See :py:meth:`boto3.session.Session.client`.
     91     """
---> 92     return _get_default_session().client(*args, **kwargs)

File /opt/conda/lib/python3.12/site-packages/boto3/session.py:297, in Session.client(self, service_name, region_name, api_version, use_ssl, verify, endpoint_url, aws_access_key_id, aws_secret_access_key, aws_session_token, config)
    215 def client(
    216     self,
    217     service_name,
   (...)
    226     config=None,
    227 ):
    228     """
    229     Create a low-level service client by name.
    230 
   (...)
    295 
    296     """
--> 297     return self._session.create_client(
    298         service_name,
    299         region_name=region_name,
    300         api_version=api_version,
    301         use_ssl=use_ssl,
    302         verify=verify,
    303         endpoint_url=endpoint_url,
    304         aws_access_key_id=aws_access_key_id,
    305         aws_secret_access_key=aws_secret_access_key,
    306         aws_session_token=aws_session_token,
    307         config=config,
    308     )

File /opt/conda/lib/python3.12/site-packages/botocore/session.py:997, in Session.create_client(self, service_name, region_name, api_version, use_ssl, verify, endpoint_url, aws_access_key_id, aws_secret_access_key, aws_session_token, config)
    980 self._add_configured_endpoint_provider(
    981     client_name=service_name,
    982     config_store=config_store,
    983 )
    985 client_creator = botocore.client.ClientCreator(
    986     loader,
    987     endpoint_resolver,
   (...)
    995     user_agent_creator=user_agent_creator,
    996 )
--> 997 client = client_creator.create_client(
    998     service_name=service_name,
    999     region_name=region_name,
   1000     is_secure=use_ssl,
   1001     endpoint_url=endpoint_url,
   1002     verify=verify,
   1003     credentials=credentials,
   1004     scoped_config=self.get_scoped_config(),
   1005     client_config=config,
   1006     api_version=api_version,
   1007     auth_token=auth_token,
   1008 )
   1009 monitor = self._get_internal_component('monitor')
   1010 if monitor is not None:

File /opt/conda/lib/python3.12/site-packages/botocore/client.py:161, in ClientCreator.create_client(self, service_name, region_name, is_secure, endpoint_url, verify, credentials, scoped_config, api_version, client_config, auth_token)
    148 region_name, client_config = self._normalize_fips_region(
    149     region_name, client_config
    150 )
    151 endpoint_bridge = ClientEndpointBridge(
    152     self._endpoint_resolver,
    153     scoped_config,
   (...)
    159     ),
    160 )
--> 161 client_args = self._get_client_args(
    162     service_model,
    163     region_name,
    164     is_secure,
    165     endpoint_url,
    166     verify,
    167     credentials,
    168     scoped_config,
    169     client_config,
    170     endpoint_bridge,
    171     auth_token,
    172     endpoints_ruleset_data,
    173     partition_data,
    174 )
    175 service_client = cls(**client_args)
    176 self._register_retries(service_client)

File /opt/conda/lib/python3.12/site-packages/botocore/client.py:520, in ClientCreator._get_client_args(self, service_model, region_name, is_secure, endpoint_url, verify, credentials, scoped_config, client_config, endpoint_bridge, auth_token, endpoints_ruleset_data, partition_data)
    496 def _get_client_args(
    497     self,
    498     service_model,
   (...)
    509     partition_data,
    510 ):
    511     args_creator = ClientArgsCreator(
    512         self._event_emitter,
    513         self._user_agent,
   (...)
    518         user_agent_creator=self._user_agent_creator,
    519     )
--> 520     return args_creator.get_client_args(
    521         service_model,
    522         region_name,
    523         is_secure,
    524         endpoint_url,
    525         verify,
    526         credentials,
    527         scoped_config,
    528         client_config,
    529         endpoint_bridge,
    530         auth_token,
    531         endpoints_ruleset_data,
    532         partition_data,
    533     )

File /opt/conda/lib/python3.12/site-packages/botocore/args.py:101, in ClientArgsCreator.get_client_args(self, service_model, region_name, is_secure, endpoint_url, verify, credentials, scoped_config, client_config, endpoint_bridge, auth_token, endpoints_ruleset_data, partition_data)
     86 def get_client_args(
     87     self,
     88     service_model,
   (...)
     99     partition_data=None,
    100 ):
--> 101     final_args = self.compute_client_args(
    102         service_model,
    103         client_config,
    104         endpoint_bridge,
    105         region_name,
    106         endpoint_url,
    107         is_secure,
    108         scoped_config,
    109     )
    111     service_name = final_args['service_name']  # noqa
    112     parameter_validation = final_args['parameter_validation']

File /opt/conda/lib/python3.12/site-packages/botocore/args.py:220, in ClientArgsCreator.compute_client_args(self, service_model, client_config, endpoint_bridge, region_name, endpoint_url, is_secure, scoped_config)
    213 s3_config = self.compute_s3_config(client_config)
    215 configured_endpoint_url = self._compute_configured_endpoint_url(
    216     client_config=client_config,
    217     endpoint_url=endpoint_url,
    218 )
--> 220 endpoint_config = self._compute_endpoint_config(
    221     service_name=service_name,
    222     region_name=region_name,
    223     endpoint_url=configured_endpoint_url,
    224     is_secure=is_secure,
    225     endpoint_bridge=endpoint_bridge,
    226     s3_config=s3_config,
    227 )
    228 endpoint_variant_tags = endpoint_config['metadata'].get('tags', [])
    230 # Some third-party libraries expect the final user-agent string in
    231 # ``client.meta.config.user_agent``. To maintain backwards
    232 # compatibility, the preliminary user-agent string (before any Config
    233 # object modifications and without request-specific user-agent
    234 # components) is stored in the new Config object's ``user_agent``
    235 # property but not used by Botocore itself.

File /opt/conda/lib/python3.12/site-packages/botocore/args.py:370, in ClientArgsCreator._compute_endpoint_config(self, service_name, region_name, endpoint_url, is_secure, endpoint_bridge, s3_config)
    368 if service_name == 'sts':
    369     return self._compute_sts_endpoint_config(**resolve_endpoint_kwargs)
--> 370 return self._resolve_endpoint(**resolve_endpoint_kwargs)

File /opt/conda/lib/python3.12/site-packages/botocore/args.py:475, in ClientArgsCreator._resolve_endpoint(self, service_name, region_name, endpoint_url, is_secure, endpoint_bridge)
    467 def _resolve_endpoint(
    468     self,
    469     service_name,
   (...)
    473     endpoint_bridge,
    474 ):
--> 475     return endpoint_bridge.resolve(
    476         service_name, region_name, endpoint_url, is_secure
    477     )

File /opt/conda/lib/python3.12/site-packages/botocore/client.py:625, in ClientEndpointBridge.resolve(self, service_name, region_name, endpoint_url, is_secure)
    619 use_dualstack_endpoint = self._resolve_use_dualstack_endpoint(
    620     service_name
    621 )
    622 use_fips_endpoint = self._resolve_endpoint_variant_config_var(
    623     'use_fips_endpoint'
    624 )
--> 625 resolved = self.endpoint_resolver.construct_endpoint(
    626     service_name,
    627     region_name,
    628     use_dualstack_endpoint=use_dualstack_endpoint,
    629     use_fips_endpoint=use_fips_endpoint,
    630 )
    632 # If we can't resolve the region, we'll attempt to get a global
    633 # endpoint for non-regionalized services (iam, route53, etc)
    634 if not resolved:
    635     # TODO: fallback partition_name should be configurable in the
    636     # future for users to define as needed.

File /opt/conda/lib/python3.12/site-packages/botocore/regions.py:230, in EndpointResolver.construct_endpoint(self, service_name, region_name, partition_name, use_dualstack_endpoint, use_fips_endpoint)
    225 if use_dualstack_endpoint and (
    226     partition['partition']
    227     in self._UNSUPPORTED_DUALSTACK_PARTITIONS
    228 ):
    229     continue
--> 230 result = self._endpoint_for_partition(
    231     partition,
    232     service_name,
    233     region_name,
    234     use_dualstack_endpoint,
    235     use_fips_endpoint,
    236 )
    237 if result:
    238     return result

File /opt/conda/lib/python3.12/site-packages/botocore/regions.py:278, in EndpointResolver._endpoint_for_partition(self, partition, service_name, region_name, use_dualstack_endpoint, use_fips_endpoint, force_partition)
    276         region_name = service_data['partitionEndpoint']
    277     else:
--> 278         raise NoRegionError()
    280 resolve_kwargs = {
    281     'partition': partition,
    282     'service_name': service_name,
   (...)
    286     'use_fips_endpoint': use_fips_endpoint,
    287 }
    289 # Attempt to resolve the exact region for this partition.

NoRegionError: You must specify a region.

Possible Solution

As my understanding, AnthropicClassifier does not use not Bedrock's API, but native Anthropic API. This error should not happen.

Steps to Reproduce

https://awslabs.github.io/multi-agent-orchestrator/classifiers/built-in/anthropic-classifier/

awslabs / multi-agent-orchestrator

Bug: AnthropicClassifier requires AWS settings? #106

Expected Behaviour

Current Behaviour

Code snippet

Possible Solution

Steps to Reproduce