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fix(bedrock): resolve the region prefix the same way on every Bedrock surface

Browse source 
One region precedence for every call: aws_region_name, then the ARN region
(model_id or model), then the region prefix in the model id, then env, with an
empty aws_region_name treated as unset. The converse handler stops injecting the
prefix region itself, the invoke config inherits the BaseAWSLLM provider resolver
and transforms with the bare model, and count_tokens, batch jobs, realtime
sessions, and the OpenAI-compatible invoke route send the bare id to AWS.

get_bedrock_base_model strips the routing prefix, the region prefix, the ARN, the
throughput suffix, and the cross-region prefix in one pass, and the cost lookup
keeps the us./eu. profile row for a region-prefixed profile id. mx-central-1
leaves the region list because Bedrock does not run there.
This commit is contained in:
mateo-berri 2026-09-05 02:23:14 -07:00
parent 4de94a0460
commit dfac6289e4
21 changed files with 210 additions and 118 deletions
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4
basedpyright-code-budget.json
View file

@ -1,6 +1,6 @@
{
"reportAny": {
"limit": 13429
"limit": 13427
},
"reportArgumentType": {
"limit": 2198
@ -84,7 +84,7 @@
"limit": 56
},
"reportPrivateUsage": {
"limit": 1808
"limit": 1807
},
"reportRedeclaration": {
"limit": 8

11
litellm/llms/bedrock/base_aws_llm.py
View file

@ -582,12 +582,8 @@ class BaseAWSLLM:
Returns:
str: The AWS region name
"""
aws_region_name = optional_params.get("aws_region_name", None)
aws_region_name = optional_params.get("aws_region_name") or None
self._validate_aws_region_name(aws_region_name)
if aws_region_name is None and model:
from litellm.llms.bedrock.common_utils import split_bedrock_region_prefix, strip_bedrock_routing_prefix
aws_region_name = split_bedrock_region_prefix(strip_bedrock_routing_prefix(model))[0]
### SET REGION NAME ###
if aws_region_name is None:
# check model arn #
@ -595,6 +591,11 @@ class BaseAWSLLM:
aws_region_name = self._get_aws_region_from_model_arn(model_id)
else:
aws_region_name = self._get_aws_region_from_model_arn(model)
if aws_region_name is None and model:
from litellm.llms.bedrock.common_utils import split_bedrock_region_prefix, strip_bedrock_routing_prefix
aws_region_name = split_bedrock_region_prefix(strip_bedrock_routing_prefix(model))[0]
if aws_region_name is None:
# check env #
litellm_aws_region_name: Final = get_secret("AWS_REGION_NAME", None)

3
litellm/llms/bedrock/batches/transformation.py
View file

@ -33,6 +33,7 @@ from ..common_utils import (
CommonBatchFilesUtils,
merge_bedrock_aws_request_params,
resolve_s3_encryption_key_id,
split_bedrock_region_prefix,
)
if TYPE_CHECKING:
@ -221,7 +222,7 @@ class BedrockBatchesConfig(BaseAWSLLM, BaseBatchesConfig):
# Create Bedrock batch request with proper typing
bedrock_request: Final[BedrockCreateBatchRequest] = {
"modelId": model,
"modelId": split_bedrock_region_prefix(model)[1],
"jobName": job_name,
"inputDataConfig": input_data_config,
"outputDataConfig": output_data_config,

3
litellm/llms/bedrock/chat/converse_handler.py
View file

@ -308,9 +308,6 @@ class BedrockConverseLLM(BaseAWSLLM):
_model_for_id = _model_for_id.replace(_nova_prefix, "", 1)
break
modelId = self.encode_model_id(model_id=_model_for_id)
# Inject region extracted from model path so _get_aws_region_name picks it up
if _region_from_model is not None and not optional_params.get("aws_region_name"):
optional_params["aws_region_name"] = _region_from_model
fake_stream = litellm.AmazonConverseConfig().should_fake_stream(
fake_stream=fake_stream,

10
litellm/llms/bedrock/chat/invoke_transformations/amazon_openai_transformation.py
View file

@ -12,7 +12,7 @@ from typing import TYPE_CHECKING, Any, Final
import httpx
from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
from litellm.llms.bedrock.common_utils import BedrockError
from litellm.llms.bedrock.common_utils import BedrockError, split_bedrock_region_prefix
from litellm.llms.bedrock.request_metadata import (
bedrock_request_metadata_headers,
merge_bedrock_invoke_headers,
@ -59,13 +59,7 @@ class AmazonBedrockOpenAIConfig(OpenAIGPTConfig, BaseAWSLLM):
Input format: bedrock/openai/<model-id>
Returns: <model-id>
"""
# Remove bedrock/ prefix if present
model = model.removeprefix("bedrock/")
# Remove openai/ prefix
model = model.removeprefix("openai/")
return model
return split_bedrock_region_prefix(model.removeprefix("bedrock/").removeprefix("openai/"))[1]
def get_complete_url(
self,

73
litellm/llms/bedrock/chat/invoke_transformations/base_invoke_transformation.py
View file

@ -1,7 +1,7 @@
import copy
import json
import time
from typing import TYPE_CHECKING, Any, Final, cast, get_args
from typing import TYPE_CHECKING, Any, Final
import httpx
from pydantic import TypeAdapter, ValidationError
@ -18,7 +18,7 @@ from litellm.litellm_core_utils.prompt_templates.factory import (
)
from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
from litellm.llms.bedrock.chat.invoke_handler import make_call, make_sync_call
from litellm.llms.bedrock.common_utils import BedrockError
from litellm.llms.bedrock.common_utils import BedrockError, split_bedrock_region_prefix
from litellm.llms.bedrock.request_metadata import (
bedrock_request_metadata_headers,
merge_bedrock_invoke_headers,
@ -184,11 +184,12 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM):
optional_params.pop("stream_chunk_size", None)
custom_prompt_dict: Final[dict] = litellm_params.pop("custom_prompt_dict", None) or {}
hf_model_name: Final = litellm_params.get("hf_model_name", None)
bare_model: Final = split_bedrock_region_prefix(model.removeprefix("invoke/"))[1]
provider: Final = self.get_bedrock_invoke_provider(model)
prompt, chat_history = self.convert_messages_to_prompt(
model=hf_model_name or model,
model=hf_model_name or bare_model,
messages=messages,
provider=provider,
custom_prompt_dict=custom_prompt_dict,
@ -197,7 +198,7 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM):
inference_params = {k: v for k, v in inference_params.items() if k not in self.aws_authentication_params}
request_data: dict = {}
if provider == "cohere":
if model.startswith("cohere.command-r"):
if bare_model.startswith("cohere.command-r"):
## LOAD CONFIG
config = litellm.AmazonCohereChatConfig().get_config()
self._apply_config_to_params(config, inference_params)
@ -214,7 +215,7 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM):
request_data = {"prompt": prompt, **inference_params}
elif provider == "anthropic":
transformed_request: Final = litellm.AmazonAnthropicClaudeConfig().transform_request(
model=model,
model=bare_model,
messages=messages,
optional_params=optional_params,
litellm_params=litellm_params,
@ -224,7 +225,7 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM):
return transformed_request
elif provider == "nova":
return litellm.AmazonInvokeNovaConfig().transform_request(
model=model,
model=bare_model,
messages=messages,
optional_params=optional_params,
litellm_params=litellm_params,
@ -255,7 +256,7 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM):
request_data = {"prompt": prompt, **inference_params}
elif provider == "twelvelabs":
return litellm.AmazonTwelveLabsPegasusConfig().transform_request(
model=model,
model=bare_model,
messages=messages,
optional_params=optional_params,
litellm_params=litellm_params,
@ -264,7 +265,7 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM):
elif provider == "openai":
# OpenAI imported models use OpenAI Chat Completions format
return litellm.AmazonBedrockOpenAIConfig().transform_request(
model=model,
model=bare_model,
messages=messages,
optional_params=optional_params,
litellm_params=litellm_params,
@ -518,62 +519,6 @@ class AmazonInvokeConfig(BaseConfig, BaseAWSLLM):
"""
return False
@staticmethod
def get_bedrock_invoke_provider(
model: str,
) -> litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL | None:
"""
Helper function to get the bedrock provider from the model
handles 4 scenarios:
1. model=invoke/anthropic.claude-3-5-sonnet-20240620-v1:0 -> Returns `anthropic`
2. model=anthropic.claude-3-5-sonnet-20240620-v1:0 -> Returns `anthropic`
3. model=llama/arn:aws:bedrock:us-east-1:086734376398:imported-model/r4c4kewx2s0n -> Returns `llama`
4. model=us.amazon.nova-pro-v1:0 -> Returns `nova`
"""
if model.startswith("invoke/"):
model = model.replace("invoke/", "", 1)
# Special case: Check for "nova" in model name first (before "amazon")
# This handles amazon.nova-* models which would otherwise match "amazon" (Titan)
if "nova" in model.lower():
if "nova" in get_args(litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL):
return cast(litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL, "nova")
_split_model: Final = model.split(".")[0]
if _split_model in get_args(litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL):
return cast(litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL, _split_model)
# If not a known provider, check for pattern with two slashes
provider = AmazonInvokeConfig._get_provider_from_model_path(model)
if provider is not None:
return provider
for provider in get_args(litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL):
if provider in model:
return provider
return None
@staticmethod
def _get_provider_from_model_path(
model_path: str,
) -> litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL | None:
"""
Helper function to get the provider from a model path with format: provider/model-name
Args:
model_path (str): The model path (e.g., 'llama/arn:aws:bedrock:us-east-1:086734376398:imported-model/r4c4kewx2s0n' or 'anthropic/model-name')
Returns:
Optional[str]: The provider name, or None if no valid provider found
"""
parts: Final = model_path.split("/")
if len(parts) >= 1:
provider: Final = parts[0]
if provider in get_args(litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL):
return cast(litellm.BEDROCK_INVOKE_PROVIDERS_LITERAL, provider)
return None
def convert_messages_to_prompt(self, model, messages, provider, custom_prompt_dict) -> tuple[str, list | None]:
# handle anthropic prompts and amazon titan prompts
prompt = ""

19
litellm/llms/bedrock/common_utils.py
View file

@ -402,7 +402,6 @@ class AmazonBedrockGlobalConfig:
*self.get_sa_regions(),
*self.get_me_regions(),
*self.get_af_regions(),
*self.get_mx_regions(),
)
def get_ap_regions(self) -> list[str]:
@ -434,9 +433,6 @@ class AmazonBedrockGlobalConfig:
def get_af_regions(self) -> tuple[str, ...]:
return ("af-south-1",)
def get_mx_regions(self) -> tuple[str, ...]:
return ("mx-central-1",)
def get_eu_regions(self) -> list[str]:
"""
Source: https://www.aws-services.info/bedrock.html
@ -831,19 +827,14 @@ def get_bedrock_base_model(model: str) -> str:
elif stripped.startswith("nova/"):
return "amazon.nova-custom"
model = strip_bedrock_routing_prefix(model)
model = extract_model_name_from_bedrock_arn(model)
model = strip_bedrock_throughput_suffix(model)
potential_region: Final = model.split(".", 1)[0]
alt_potential_region: Final = model.split("/", 1)[0]
region_free: Final = split_bedrock_region_prefix(strip_bedrock_routing_prefix(model))[1]
bare: Final = strip_bedrock_throughput_suffix(extract_model_name_from_bedrock_arn(region_free))
potential_region: Final = bare.split(".", 1)[0]
if potential_region in get_bedrock_cross_region_inference_regions():
return model.split(".", 1)[1]
elif alt_potential_region in _get_all_bedrock_regions() and len(model.split("/", 1)) > 1:
return model.split("/", 1)[1]
return bare.split(".", 1)[1]
return model
return bare
def bedrock_converse_supports_parallel_tool_use_config(model: str) -> bool:

7
litellm/llms/bedrock/count_tokens/bedrock_token_counter.py
View file

@ -6,7 +6,7 @@ from typing import Any, Final
from litellm._logging import verbose_logger
from litellm.llms.base_llm.base_utils import BaseTokenCounter
from litellm.llms.bedrock.common_utils import BedrockError, get_bedrock_base_model
from litellm.llms.bedrock.common_utils import BedrockError
from litellm.llms.bedrock.count_tokens.handler import BedrockCountTokensHandler
from litellm.types.utils import LlmProviders, TokenCountResponse
@ -67,15 +67,12 @@ class BedrockTokenCounter(BaseTokenCounter):
if system:
request_data["system"] = system
# Get the resolved model (strip prefixes like bedrock/, converse/, etc.)
resolved_model: Final = get_bedrock_base_model(model_to_use)
try:
handler: Final = BedrockCountTokensHandler()
result: Final = await handler.handle_count_tokens_request(
request_data=request_data,
litellm_params=litellm_params,
resolved_model=resolved_model,
resolved_model=model_to_use,
)
# Transform response to TokenCountResponse

4
litellm/llms/bedrock/realtime/handler.py
View file

@ -22,7 +22,7 @@ from litellm.types.llms.openai import OpenAIRealtimeEvents
from litellm.types.realtime import RealtimeResponseTransformInput
from ..base_aws_llm import BaseAWSLLM
from ..common_utils import BedrockError
from ..common_utils import BedrockError, split_bedrock_region_prefix
from .transformation import BedrockRealtimeConfig
_CLIENT_MODALITIES_ADAPTER: Final[TypeAdapter["list[str] | None"]] = TypeAdapter(list[str] | None)
@ -184,7 +184,7 @@ class BedrockRealtime(BaseAWSLLM):
async def open_bidirectional_stream() -> BedrockBidirectionalStream:
return await bedrock_client.invoke_model_with_bidirectional_stream(
InvokeModelWithBidirectionalStreamOperationInput(model_id=model)
InvokeModelWithBidirectionalStreamOperationInput(model_id=split_bedrock_region_prefix(model)[1])
)
transformation_config: Final = BedrockRealtimeConfig()

4
litellm/utils.py
View file

@ -5482,9 +5482,9 @@ def _get_potential_model_names(model: str, custom_llm_provider: str | None) -> P
provider_prefixed_model_name = combined_model_name
if custom_llm_provider in ("bedrock", "bedrock_converse"):
from litellm.llms.bedrock.common_utils import strip_bedrock_routing_prefix
from litellm.llms.bedrock.common_utils import split_bedrock_region_prefix, strip_bedrock_routing_prefix
split_model = strip_bedrock_routing_prefix(split_model)
split_model = split_bedrock_region_prefix(strip_bedrock_routing_prefix(split_model))[1]
return PotentialModelNamesAndCustomLLMProvider(
split_model=split_model,

6
ruff-strict-budget.json
View file

@ -168,7 +168,7 @@
"limit": 3
},
"RET504": {
"limit": 173
"limit": 172
},
"RUF012": {
"limit": 239
@ -198,7 +198,7 @@
"limit": 56
},
"SIM102": {
"limit": 310
"limit": 309
},
"SIM103": {
"limit": 119
@ -231,7 +231,7 @@
"limit": 5
},
"TID251": {
"limit": 1035
"limit": 1034
},
"TRY002": {
"limit": 524

24
tests/test_litellm/llms/bedrock/batches/test_transformation.py
View file

@ -16,6 +16,8 @@ we mock; everything else runs for real.
from unittest.mock import MagicMock, patch
import json
import httpx
import pytest
@ -819,3 +821,25 @@ def test_retrieve_request_accepts_partition_arns(config: BedrockBatchesConfig, a
batch_id=arn, optional_params={}, litellm_params={}
)
assert result["url"].startswith(expected_prefix)
def test_create_request_targets_the_prefix_region_with_the_bare_model_id(config, monkeypatch: pytest.MonkeyPatch):
monkeypatch.setenv("AWS_REGION_NAME", "us-west-2")
result = config.transform_create_batch_request(
model="eu-central-1/anthropic.claude-3-5-sonnet",
create_batch_data={
"input_file_id": "s3://in-bucket/path/to/input.jsonl",
"endpoint": "/v1/chat/completions",
"completion_window": "24h",
},
optional_params={},
litellm_params={
"s3_output_bucket_name": "out-bucket",
"aws_batch_role_arn": "arn:aws:iam::123:role/my-batch-role",
"aws_access_key_id": "fake-access-key",
"aws_secret_access_key": "fake-secret-key",
},
)
assert result["url"] == "https://bedrock.eu-central-1.amazonaws.com/model-invocation-job"
assert json.loads(result["data"])["modelId"] == "anthropic.claude-3-5-sonnet"

39
tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_amazon_openai_transformation.py Normal file
View file

@ -0,0 +1,39 @@
from typing import Final
import pytest
from litellm.llms.bedrock.chat.invoke_transformations.amazon_openai_transformation import (
AmazonBedrockOpenAIConfig,
)
IMPORTED_MODEL_ARN: Final = "arn:aws:bedrock:us-east-1:123456789012:imported-model/abc123"
@pytest.mark.parametrize(
"model",
[
f"bedrock/openai/us-east-1/{IMPORTED_MODEL_ARN}",
f"openai/us-east-1/{IMPORTED_MODEL_ARN}",
f"bedrock/openai/{IMPORTED_MODEL_ARN}",
],
)
def test_region_prefixed_imported_model_invokes_the_bare_arn_in_the_prefix_region(monkeypatch, model):
monkeypatch.setenv("AWS_REGION_NAME", "us-west-2")
config: Final = AmazonBedrockOpenAIConfig()
url: Final = config.get_complete_url(
api_base=None, api_key=None, model=model, optional_params={}, litellm_params={}, stream=False
)
body: Final = config.transform_request(
model=model,
messages=[{"role": "user", "content": "Hello"}],
optional_params={},
litellm_params={},
headers={},
)
assert url == (
"https://bedrock-runtime.us-east-1.amazonaws.com/model/"
"arn:aws:bedrock:us-east-1:123456789012:imported-model%2Fabc123/invoke"
)
assert body["model"] == IMPORTED_MODEL_ARN

12
tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_base_invoke_transformation.py
View file

@ -233,3 +233,15 @@ def test_region_prefixed_invoke_model_calls_that_region_with_the_bare_model_id(
monkeypatch.setenv("AWS_REGION_NAME", "us-west-2")
monkeypatch.delenv("AWS_BEDROCK_RUNTIME_ENDPOINT", raising=False)
assert _invoke_with_mocked_post(model, aws_region_name) == expected_url
def test_transform_request_builds_the_command_r_chat_body_for_a_region_prefixed_model():
request = AmazonInvokeConfig().transform_request(
model="us-east-1/cohere.command-r-plus-v1:0",
messages=[{"role": "user", "content": "Hello"}],
optional_params={"max_tokens": 16},
litellm_params={},
headers={},
)
assert request == {"message": "Hello", "max_tokens": 16, "chat_history": []}

35
tests/test_litellm/llms/bedrock/count_tokens/test_bedrock_token_counter.py Normal file
View file

@ -0,0 +1,35 @@
from typing import Final
import httpx
import pytest
import respx
import litellm
from litellm.llms.bedrock.count_tokens.bedrock_token_counter import BedrockTokenCounter
COUNT_TOKENS_URL_IN_THE_PREFIX_REGION: Final = (
"https://bedrock-runtime.us-east-1.amazonaws.com/model/anthropic.claude-haiku-4-5-20251001-v1%3A0/count-tokens"
)
@pytest.mark.asyncio
async def test_count_tokens_calls_the_region_named_in_the_model_prefix_with_the_bare_model_id(
monkeypatch: pytest.MonkeyPatch,
):
monkeypatch.setenv("AWS_REGION_NAME", "us-west-2")
monkeypatch.delenv("AWS_BEDROCK_RUNTIME_ENDPOINT", raising=False)
monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
with respx.mock:
respx.post(COUNT_TOKENS_URL_IN_THE_PREFIX_REGION).mock(
return_value=httpx.Response(200, json={"inputTokens": 7})
)
result = await BedrockTokenCounter().count_tokens(
model_to_use="us-east-1/us.anthropic.claude-haiku-4-5-20251001-v1:0",
messages=[{"role": "user", "content": "hi"}],
contents=None,
deployment={"litellm_params": {"aws_access_key_id": "fake", "aws_secret_access_key": "fake"}},
)
assert result is not None
assert result.total_tokens == 7

19
tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py
View file

@ -492,6 +492,25 @@ class TestBedrockRealtimeAwsAuth:
assert stub_aws_sdk_client["operation_input"].model_id == "amazon.nova-sonic-v1:0"
assert websocket.closed
@pytest.mark.asyncio
async def test_region_prefixed_model_opens_the_stream_in_that_region_with_the_bare_model_id(
self, stub_aws_sdk_client, monkeypatch: pytest.MonkeyPatch
):
monkeypatch.setenv("AWS_REGION_NAME", "us-west-2")
handler = BedrockRealtime()
websocket = RealtimeClientWS()
await handler.async_realtime(
model="eu-north-1/amazon.nova-sonic-v1:0",
websocket=websocket,
logging_obj=FakeLogging(),
aws_access_key_id="litellm-params-access-key",
aws_secret_access_key="litellm-params-secret-key",
)
assert stub_aws_sdk_client["config_kwargs"]["region"] == "eu-north-1"
assert stub_aws_sdk_client["operation_input"].model_id == "amazon.nova-sonic-v1:0"
@pytest.mark.asyncio
async def test_role_assumption_params_forwarded_to_get_credentials(self, stub_aws_sdk_client):
handler = StubCredentialsBedrockRealtime(

2
tests/test_litellm/llms/bedrock/rerank/test_bedrock_rerank_handler.py
View file

@ -8,7 +8,7 @@ import litellm
from litellm.llms.custom_httpx.http_handler import HTTPHandler
def _rerank_with_mocked_post(model: str) -> tuple[str, dict]:
def _rerank_with_mocked_post(model: str) -> tuple[str, dict[str, object]]:
body = {"results": [{"index": 0, "relevanceScore": 0.9}], "usage": {"search_units": 1}}
mock_response = MagicMock()
mock_response.status_code = 200

17
tests/test_litellm/llms/bedrock/test_base_aws_llm.py
View file

@ -505,7 +505,6 @@ def test_get_aws_region_name_boto3_fallback():
"us-east-1\\path",
"US-EAST-1", # uppercase not allowed
"us east 1", # spaces not allowed
"", # empty string not allowed
"us-east-1\n", # trailing newline must not slip past $
],
)
@ -546,13 +545,14 @@ def test_get_aws_region_name_accepts_valid_regions(valid_region):
"model,explicit_region,expected_region",
[
("bedrock/invoke/eu-west-1/mistral.mistral-7b-instruct-v0:2", None, "eu-west-1"),
("eu-west-1/mistral.mistral-7b-instruct-v0:2", "", "eu-west-1"),
("eu-west-1/mistral.mistral-7b-instruct-v0:2", "ap-south-1", "ap-south-1"),
("eu-west-1/arn:aws:bedrock:us-east-1::foundation-model/cohere.rerank-v3-5:0", None, "eu-west-1"),
("eu-west-1/arn:aws:bedrock:us-east-1::foundation-model/cohere.rerank-v3-5:0", None, "us-east-1"),
("arn:aws:bedrock:us-east-1::foundation-model/cohere.rerank-v3-5:0", None, "us-east-1"),
("mistral.mistral-7b-instruct-v0:2", None, "us-west-2"),
],
)
def test_get_aws_region_name_prefers_explicit_region_then_model_prefix_then_arn_then_env(
def test_get_aws_region_name_prefers_explicit_region_then_arn_then_model_prefix_then_env(
monkeypatch: pytest.MonkeyPatch, model: str, explicit_region: str | None, expected_region: str
):
monkeypatch.setenv("AWS_REGION_NAME", "us-west-2")
@ -561,6 +561,17 @@ def test_get_aws_region_name_prefers_explicit_region_then_model_prefix_then_arn_
assert BaseAWSLLM()._get_aws_region_name(optional_params, model=model) == expected_region
def test_get_aws_region_name_prefers_the_model_id_arn_region_over_the_model_prefix(monkeypatch: pytest.MonkeyPatch):
monkeypatch.setenv("AWS_REGION_NAME", "us-west-2")
profile_arn = "arn:aws:bedrock:eu-central-1:123456789012:application-inference-profile/abc123"
region = BaseAWSLLM()._get_aws_region_name(
{}, model="us-east-1/anthropic.claude-haiku-4-5-20251001-v1:0", model_id=profile_arn
)
assert region == "eu-central-1"
@pytest.mark.parametrize(
"model,expected_model_id",
[

17
tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
View file

@ -647,3 +647,20 @@ def test_every_region_prefix_the_cost_map_prices_is_a_known_bedrock_region():
assert prefixed_keys
unrecognized = sorted({key.split("/")[0] for key in prefixed_keys if split_bedrock_region_prefix(key)[0] is None})
assert unrecognized == []
@pytest.mark.parametrize(
"model,expected",
[
("bedrock/us-east-1/us.anthropic.claude-haiku-4-5-20251001-v1:0", "anthropic.claude-haiku-4-5-20251001-v1:0"),
("eu-west-1/amazon.titan-embed-text-v2:0", "amazon.titan-embed-text-v2:0"),
(
"bedrock/invoke/ap-south-1/arn:aws:bedrock:ap-south-1::foundation-model/meta.llama3-70b-instruct-v1:0",
"meta.llama3-70b-instruct-v1:0",
),
],
)
def test_get_bedrock_base_model_strips_the_region_prefix_before_the_cross_region_prefix(model, expected):
from litellm.llms.bedrock.common_utils import get_bedrock_base_model
assert get_bedrock_base_model(model) == expected

9
tests/test_litellm/test_utils.py
View file

@ -6067,3 +6067,12 @@ class TestFinalOptionalParamsLineRedaction:
assert "'max_tokens': 17" in printed
assert "'temperature': 0.25" in printed
def test_get_model_info_prices_a_region_prefixed_cross_region_profile_as_that_profile(local_model_cost_map):
prefixed = litellm.get_model_info(model="bedrock/us-east-1/us.anthropic.claude-haiku-4-5-20251001-v1:0")
plain = litellm.get_model_info(model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0")
assert prefixed["key"] == plain["key"] == "us.anthropic.claude-haiku-4-5-20251001-v1:0"
assert prefixed["input_cost_per_token"] == plain["input_cost_per_token"]
assert prefixed["output_cost_per_token"] == plain["output_cost_per_token"]

10
type-discipline-budget.json
View file

@ -1,9 +1,9 @@
{
"LIT001": {
"limit": 22178
"limit": 22175
},
"LIT002": {
"limit": 26744
"limit": 26743
},
"LIT003": {
"limit": 261
@ -15,7 +15,7 @@
"limit": 0
},
"LIT006": {
"limit": 1035
"limit": 1032
},
"LIT007": {
"limit": 0
@ -27,10 +27,10 @@
"limit": 0
},
"LIT010": {
"limit": 16454
"limit": 16449
},
"LIT011": {
"limit": 5506
"limit": 5499
},
"LIT012": {
"limit": 4486