berriai-litellm-21658-22884

/repo
./.circleci/config.yml
./.circleci/requirements.txt
./.claude/settings.json
./.devcontainer/devcontainer.json
./.devcontainer/post-create.sh
./.dockerignore
./.env.example
./.flake8
./.git/COMMIT_EDITMSG
./.git/config
./.git/description

./.git/HEAD
./.git/hooks/applypatch-msg.sample
./.git/hooks/commit-msg.sample
./.git/hooks/fsmonitor-watchman.sample
./.git/hooks/post-update.sample
./.git/hooks/pre-applypatch.sample
./.git/hooks/pre-commit.sample
./.git/hooks/pre-merge-commit.sample
./.git/hooks/pre-push.sample
./.git/hooks/pre-rebase.sample
./.git/hooks/pre-receive.sample
./.git/hooks/prepare-commit-msg.sample
./.git/hooks/push-to-checkout.sample
./.git/hooks/sendemail-validate.sample
./.git/hooks/update.sample
./.git/index
./.git/info/exclude
./.git/info/refs
./.git/logs/HEAD
./.git-blame-ignore-revs
./.gitattributes
./.gitguardian.yaml
./.github/dependabot.yaml
./.github/dep
…[1333 chars omitted]…
itellm-matrix.yml
./.github/workflows/test-litellm-ui-build.yml
./.github/workflows/test-litellm.yml
./.github/workflows/test-mcp.yml
./.github/workflows/test-model-map.yaml
./.github/workflows/test_server_root_path.yml
./.github/workflows/update_release.py
./.gitignore
./.pre-commit-config.yaml
./.semgrep/rules/README.md
./.trivyignore
./AGENTS.md
./ARCHITECTURE.md
bash: line 6: rg: command not found

litellm/llms/anthropic/chat/transformation.py:1363:        ## Handle output_config (Anthropic-specific parameter)
litellm/llms/anthropic/chat/transformation.py:1364:        if "output_config" in optional_params:
litellm/llms/anthropic/chat/transformation.py:1365:            output_config = optional_params.get("output_config")
litellm/llms/anthropic/chat/transformation.py:1366:            if output_config and isinstance(output_config, dict):
litellm/llms/anthropic/chat/transformation.py:1367:                effort = output_config.get("effort")
litellm/llms/anthropic/chat/transformation.py:1376:                data["output_config"] = output_config
litellm/llms/anthropic/common_utils.py:244:        # Check if output_config is directly provided
litellm/llms/anthropic/common_utils.py:245:        output_config = optional_params.get("output_config")
litellm/llms/anthropic/common_utils.py:246
…[8629 chars omitted]…
agesConfig()
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:201:        config, "get_complete_vertex_url", return_value="https://mock-url"

tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py:447:        VertexAIPartnerModelsAnthropicMessagesConfig,

"""
Base Vertex, Google AI Studio LLM Class

Handles Authentication and generating request urls for Vertex AI and Google AI Studio
"""

import json
import os
from typing import TYPE_CHECKING, Any, Dict, Literal, Optional, Tuple

import litellm
from litellm._logging import verbose_logger

from litellm.litellm_core_utils.asyncify import asyncify
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
from litellm.secret_managers.main import get_secret_str
from litellm.types.llms.vertex_ai import VERTEX_CREDENTIALS_TYPES, VertexPartnerProvider

from .common_utils import (
    _get_gemini_url,
    _get_vertex_url,
    all_gemini_url_modes,
    get_vertex_base_model_name,
    get_vertex_base_url,
    is_global_only_vertex_model,
)

GOOGLE_IMPORT_ERROR_MESSAGE = (
    "Google Cloud SDK not found. Install it with: pip install 'litellm[google]' "
    "or pip install google-cloud-ai
…[8629 chars omitted]…
custom_proxy(
        self,
        api_base: Optional[str],
        custom_llm_provider: str,
        gemini_api_key: Optional[str],
        endpoint: str,
        stream: Optional[bool],
        auth_header: Optional[str],
        url: str,
        model: Optional[str] = None,
        vertex_project: Optional[str] = None,
        vertex_location: Optional[str] = None,
1246:    def transform_request(

litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py
            beta_values.add(get_tool_search_beta_header("vertex_ai"))
        
        if beta_values:
            headers["anthropic-beta"] = ",".join(beta_values)
        
        return headers, api_base

    def get_complete_url(
        self,
        api_base: Optional[str],

        api_key: Optional[str],
        model: str,
        optional_params: dict,
        litellm_params: dict,
        stream: Optional[bool] = None,
    ) -> str:
        if api_base is None:
            raise ValueError(
                "api_base is required. Unable to determine the correct api_base for the request."
            )
        return api_base  # no transformation is needed - handled in validate_environment

    def tra
…[4727 chars omitted]…
    break
        
        # Check for tool search tools - Vertex AI uses different beta header
        anthropic_model_info = AnthropicModelInfo()
        if anthropic_model_info.is_tool_search_used(tools):
            beta_values.add(get_tool_search_beta_header("vertex_ai"))
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py:28:class VertexAIAnthropicConfig(AnthropicConfig):

# What is this?
## Handler file for calling claude-3 on vertex ai
from typing import Any, List, Optional

import httpx

import litellm
from litellm.llms.base_llm.chat.transformation import LiteLLMLoggingObj
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import ModelResponse

from ....anthropic.chat.transformation import AnthropicConfig

class VertexAIError(Exception):
    def __init__(self, status_code, message):
        self.status_code = status_code
        self.message = message
        self.request = httpx.Request(
            method="POST", url=" https://cloud.google.com/vertex-ai/"
        )
        self.response = httpx.Response(status_code=status_code, request=self.request)
        super().__init__(
            self.message
        )  # Call the base class constructor with the parameters it needs


class VertexAIAnthropicConfig(AnthropicConfig
…[4038 chars omitted]…
     context_management = optional_params.get("context_management")
        if context_management:
45:            "output_format",
48:            "output_config",
240:        - output_format: adds 'structured-outputs-2025-11-13'
245:            optional_params: Optional parameters including tools, context_management, output_format, speed
281:        if optional_params.get("output_format") is not None:

20:50:51 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
{'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 10, 'output_config': {'format': {}}, 'anthropic_version': 'vertex-2023-10-16'}
......                                                                   [100%]
6 passed in 1.27s

20:51:27 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
({'Authorization': 'Bearer cached', 'content-type': 'application/json'}, 'https://vertex')
url called True token called False
{'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 10, 'anthropic_version': 'vertex-2023-10-16'}

............................                                             [100%]
28 passed in 1.86s
 .../experimental_pass_through/transformation.py      | 20 +++++++++++++-------
 .../anthropic/transformation.py                      |  5 ++++-
 2 files changed, 17 insertions(+), 8 deletions(-)
diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..110e1fb 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -31,19 +31,23 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
 
         Validate the environment 

…[2633 chars omitted]…
's Anthropic endpoint rejects Anthropic-only structured-output
+        # fields as extra inputs.  Structured output is represented differently
+        # (when supported) and these fields must not be sent through.
         data.pop("output_format", None)
+        data.pop("output_config", None)
 
         tools = optional_params.get("tools")
         tool_search_used = self.is_tool_search_used(tools)

679:    def get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
696:    def get_vertex_ai_location(litellm_params: dict) -> Optional[str]:
        Args:
            credentials: The original credentials
            project_id: The project ID
            credential_cache_key: The cache key to clear
            error: The original error that triggered reauthentication

        Returns:
            Tuple of (access_token, project_id)

        Raises:

            The original error if reauthentication fails
        """
        verbose_logger.debug(
            f"Handling reauthentication for project_id: {project_id}. "
            f"Clearing cache and retrying once."
        )

        # Clear the cached credentials
        if credential_cache_key in self._credentials_project_mapping:
            del self._credentials_project_mapping[credential_cache_key]

        # Retry once w
…[1085 chars omitted]…
  5. Return access token and project id

        Args:
            credentials: The credentials to use for authentication
            project_id: The Google Cloud project ID
            _retry_reauth: Internal flag to prevent infinite recursion during reauthentication

        Returns:
            Tuple of (access_token, project_id)
        """

        # Convert dict credentials to string for caching

}
        if auth_header is not None:
            headers["Authorization"] = f"Bearer {auth_header}"
        if extra_headers is not None:
            headers.update(extra_headers)

        return headers

    @staticmethod
    def get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
        return (
            litellm_params.pop("vertex_project", None)

            or litellm_params.pop("vertex_ai_project", None)
            or litellm.vertex_project
            or get_secret_str("VERTEXAI_PROJECT")
        )

    @staticmethod
    def get_vertex_ai_credentials(litellm_params: dict) -> Optional[str]:
        return (
            litellm_params.pop("vertex_credentials", None)
            or litellm_params.pop("vertex_ai_credentials", None)
            or get_secret_str("VERTEXAI_CREDENTIALS")
        )

    @staticmethod
    def get_vertex_ai_location(litellm_params: 
…[332 chars omitted]…
ef safe_get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
        """
        Safely get Vertex AI project without mutating the litellm_params dict.

        Unlike get_vertex_ai_project(), this does NOT pop values from the dict,
        making it safe to call multiple times with the same litellm_params.

        Args:
            litellm_params: Dictionary containing Vertex AI parameters

.............                                                            [100%]
13 passed in 1.27s
 M litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
 M litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py

submitted.

/repo
AGENTS.md
ARCHITECTURE.md
CLAUDE.md
CONTRIBUTING.md
Dockerfile
GEMINI.md
LICENSE
Makefile
README.md
ci_cd
codecov.yaml

cookbook
db_scripts
deploy
dist
docker
docker-compose.hardened.yml
docker-compose.yml
docs
enterprise
index.yaml
litellm
litellm-js
litellm-proxy-extras
mcp_servers.json
model_prices_and_context_window.json
package-lock.json
package.json
poetry.lock
policy_templates.json
prometheus.yml
provider_endpoints_support.json
proxy_server_config.yaml
pyproject.toml
pyrightconfig.json
render.yaml
requirements.txt
ruff.toml
schema.prisma
scripts
security.md
taplo.toml
tests
ui
uv.lock
bash: line 6: rg: command not found

litellm/anthropic_beta_headers_config.json
litellm/anthropic_beta_headers_manager.py
litellm/anthropic_interface
litellm/integrations/anthropic_cache_control_hook.py
litellm/litellm_core_utils/tokenizers/anthropic_tokenizer.json
litellm/llms/anthropic
litellm/llms/azure_ai/anthropic
litellm/llms/base_llm/anthropic_messages
litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude2_transformation.py
litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
litellm/llms/vertex_ai

litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py
litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py
litellm/llms/vertex_ai/image_edit/vertex_imagen_transformation.py
litellm/llms/vertex_ai
…[972 chars omitted]…
k.py
litellm/types/llms/anthropic.py
litellm/types/llms/anthropic_messages
litellm/types/llms/anthropic_messages/anthropic_request.py
litellm/types/llms/anthropic_messages/anthropic_response.py
litellm/types/llms/anthropic_skills.py
litellm/types/llms/anthropic_tool_search.py
litellm/types/llms/vertex_ai.py
litellm/types/llms/vertex_ai_text_to_speech.py
litellm/types/passthrough_endpoints/vertex_ai.py

litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:103:    def validate_anthropic_messages_environment(
litellm/llms/azure_ai/anthropic/messages_transformation.py:23:    def validate_anthropic_messages_environment(
litellm/llms/base_llm/anthropic_messages/transformation.py:22:    def validate_anthropic_messages_environment(  # use different name because return type is different from base config's validate_environment
litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py:63:    def validate_anthropic_messages_environment(
litellm/llms/custom_httpx/llm_http_handler.py:1866:        ) = anthropic_messages_provider_config.validate_anthropic_messages_environment(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:19:    def validate_anthropic_messages_environment(
tests/pass_throug
…[4019 chars omitted]…
tex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:164:        updated_headers, api_base = config.validate_anthropic_messages_environment(
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:203:        updated_headers, api_base = config.validate_anthropic_messages_environment(

# What is this?
## Handler file for calling claude-3 on vertex ai
from typing import Any, List, Optional

import httpx

import litellm
from litellm.llms.base_llm.chat.transformation import LiteLLMLoggingObj
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import ModelResponse

from ....anthropic.chat.transformation import AnthropicConfig

class VertexAIError(Exception):
    def __init__(self, status_code, message):
        self.status_code = status_code
        self.message = message
        self.request = httpx.Request(
            method="POST", url=" https://cloud.google.com/vertex-ai/"
        )
        self.response = httpx.Response(status_code=status_code, request=self.request)
        super().__init__(
            self.message
        )  # Call the base class constructor with the parameters it needs


class VertexAIAnthropicConfig(AnthropicConfig
…[8022 chars omitted]…
        model=model,
            optional_params=dict(anthropic_messages_optional_request_params),
            litellm_params={
                "metadata": kwargs.get("metadata", {}),
                "preset_cache_key": None,
                "stream_response": {},
                **anthropic_messages_optional_request_params,
            },
            custom_llm_provider=custom_llm_provider,
        )

return f"{api_base}/v1/projects/{vertex_project}/locations/{vertex_location}/endpoints/openapi/chat/completions"
        elif partner == VertexPartnerProvider.mistralai:
            if stream:
                return f"{api_base}/v1/projects/{vertex_project}/locations/{vertex_location}/publishers/mistralai/models/{model}:streamRawPredict"
            else:
                return f"{api_base}/v1/projects/{vertex_project}/locations/{vertex_location}/publishers/mistralai/models/{model}:rawPredict"
        elif partner == VertexPartnerProvider.ai21:
            if stream:
                return f"{api_base}/v1beta1/projects/{vertex_project}/locations/{vertex_location}/publishers/ai21/models/{model}:streamRawPredict"
            else:
                return f"{api_base}/v1beta1/projects/{vertex_project}/locations/{vertex_location}/publishers/ai21/models/{model}:rawPredict"
     

…[8380 chars omitted]…
      request_body=request_body,
225-            litellm_logging_obj=litellm_logging_obj,
226-        )
227-
228-    @staticmethod
229-    def _update_headers_with_anthropic_beta(
230-        headers: dict,
231-        optional_params: dict,
232-        custom_llm_provider: str = "anthropic",
233-    ) -> dict:
234-        """
235-        Auto-inject anthropic-beta headers based on features used.
236-

diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..c7ae83b 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -31,24 +31,30 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
 
         Validate the environment for the request
         """
+        # Resolve the Vertex endpoint independently of authentication. Headers can be
+        # reused between requests, but that must not prevent us from constructing the
+        # URL when the caller did not provide one.
+        project_id = None

         if "
…[2535 chars omitted]…
one)  # vertex anthropic doesn't accept 'model' parameter
 
-        # VertexAI doesn't support output_format parameter, remove it if present
+        # VertexAI doesn't support these Anthropic API-only parameters.
         data.pop("output_format", None)
+        data.pop("output_config", None)
 
         tools = optional_params.get("tools")
         tool_search_used = self.is_tool_search_used(tools)

...................                                                      [100%]
21:00:42 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
{'Authorization': 'cached', 'content-type': 'application/json'} url call(custom_api_base=None, vertex_location='l', vertex_project='p', project_id='p', partner=<VertexPartnerProvider.claude: 'claude'>, stream=False, model='claude') False

21:01:00 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
{'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 42, 'anthropic_version': 'vertex-2023-10-16'}
 M litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
 M litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py

submitted.

AGENTS.md
ARCHITECTURE.md
CLAUDE.md
CONTRIBUTING.md
Dockerfile
GEMINI.md
LICENSE
Makefile
README.md
ci_cd
codecov.yaml
cookbook

db_scripts
deploy
dist
docker
docker-compose.hardened.yml
docker-compose.yml
docs
enterprise
index.yaml
litellm
litellm-js
litellm-proxy-extras
mcp_servers.json
model_prices_and_context_window.json
package-lock.json
package.json
poetry.lock
policy_templates.json
prometheus.yml
provider_endpoints_support.json
proxy_server_config.yaml
pyproject.toml
pyrightconfig.json
render.yaml
requirements.txt
ruff.toml
schema.prisma
scripts
security.md
taplo.toml
tests
ui
uv.lock
bash: line 6: rg: command not found

litellm/llms/anthropic/chat/transformation.py:1363:        ## Handle output_config (Anthropic-specific parameter)
litellm/llms/anthropic/chat/transformation.py:1364:        if "output_config" in optional_params:
litellm/llms/anthropic/chat/transformation.py:1365:            output_config = optional_params.get("output_config")
litellm/llms/anthropic/chat/transformation.py:1366:            if output_config and isinstance(output_config, dict):
litellm/llms/anthropic/chat/transformation.py:1367:                effort = output_config.get("effort")
litellm/llms/anthropic/chat/transformation.py:1376:                data["output_config"] = output_config
litellm/llms/anthropic/common_utils.py:244:        # Check if output_config is directly provided
litellm/llms/anthropic/common_utils.py:245:        output_config = optional_params.get("output_config")
litellm/llms/anthropic/common_utils.py:246
…[2815 chars omitted]…
_vertex_url(
litellm/llms/vertex_ai/vertex_llm_base.py:237:    def get_complete_vertex_url(

litellm/types/llms/anthropic.py:365:    output_config: Optional[AnthropicOutputConfig]  # Configuration for Claude's output behavior
litellm/utils.py:8177:                    VertexAIPartnerModelsAnthropicMessagesConfig,
litellm/utils.py:8180:                return VertexAIPartnerModelsAnthropicMessagesConfig()

tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:5:from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.experimental_pass_through.transformation import (
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:6:    VertexAIPartnerModelsAnthropicMessagesConfig,
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:11:    config = VertexAIPartnerModelsAnthropicMessagesConfig()
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:38:    config = VertexAIPartnerModelsAnthropicMessagesConfig()
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_
…[1266 chars omitted]…
tex_ai.vertex_ai_partner_models.anthropic.experimental_pass_through.transformation import (
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py:447:        VertexAIPartnerModelsAnthropicMessagesConfig,
tests/test_litellm/test_utils.py:367:    from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.transformation import (

from unittest.mock import patch

import pytest

from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.experimental_pass_through.transformation import (
    VertexAIPartnerModelsAnthropicMessagesConfig,
)


def test_validate_environment_uses_vertex_ai_location():
    config = VertexAIPartnerModelsAnthropicMessagesConfig()
    headers = {}

    litellm_params = {
        "vertex_ai_project": "test-project",
        "vertex_ai_location": "europe-west1",
        "vertex_credentials": "{}",
    }
    optional_params = {}

    with patch.object(
        config, "_ensure_access_token", return_value=("token", "test-project")
    ), patch.object(
        config, "get_complete_vertex_url", return_value="https://mock-url"
    ) as mock_get_url:
        config.validate_anthropic_messages_environment(
            headers=headers,
            model="claude-3-sonnet",
            messages=[]
…[8629 chars omitted]…
 transformed_context_management is not None:
                anthropic_messages_optional_request_params["context_management"] = transformed_context_management

        ####### get required params for all anthropic messages requests ######
        verbose_logger.debug(f"TRANSFORMATION DEBUG - Messages: {messages}")
        anthropic_messages_request: AnthropicMessagesRequest = AnthropicMessagesRequest(

anthropic_messages_request: AnthropicMessagesRequest = AnthropicMessagesRequest(
            messages=messages,
            max_tokens=max_tokens,
            model=model,
            **anthropic_messages_optional_request_params,
        )
        return dict(anthropic_messages_request)

    def transform_anthropic_messages_response(
        self,
        model: str,
        raw_response: httpx.Response,

        logging_obj: LiteLLMLoggingObj,
    ) -> AnthropicMessagesResponse:
        """
        No transformation is needed for Anthropic messages, since we want the response in the Anthropic /v1/messages API spec
        """
        try:
            raw_response_json = raw_response.json()
        except Exception:
            raise AnthropicError(
                message=raw_response.text, status_code=raw_response.status_code
            )
        return AnthropicMessagesResp
…[8629 chars omitted]…
ld be present"
        assert "compact-2026-01-12" in updated_headers["anthropic-beta"], \
            f"anthropic-beta should contain 'compact-2026-01-12', got: {updated_headers['anthropic-beta']}"
        assert "context-management-2025-06-27" in updated_headers["anthropic-beta"], \
            f"anthropic-beta should contain 'context-management-2025-06-27', got: {updated_headers['anthropic-beta']}"

from typing import Any, Dict, List, Optional, Tuple

from litellm.llms.anthropic.common_utils import AnthropicModelInfo
from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
    AnthropicMessagesConfig,
)
from litellm.types.llms.anthropic import (
    ANTHROPIC_BETA_HEADER_VALUES,
    ANTHROPIC_HOSTED_TOOLS,
)
from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header
from litellm.types.llms.vertex_ai import VertexPartnerProvider

from litellm.types.router import GenericLiteLLMParams

from ....vertex_llm_base import VertexBase


class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase):
    def validate_anthropic_messages_environment(
        self,
        headers: dict,
        model: str,
        messages: List[Any],
        optional_params: dict,
        litellm_params: dict,
        api_key: Option
…[5326 chars omitted]…
rmation.py:240:        - output_format: adds 'structured-outputs-2025-11-13'
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:245:            optional_params: Optional parameters including tools, context_management, output_format, speed
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:281:        if optional_params.get("output_format") is not None:

VertexLLM,
            )
        except Exception as e:
            raise VertexAIError(
                status_code=400,
                message=f"""vertexai import failed please run `pip install -U "google-cloud-aiplatform>=1.38"`. Got error: {e}""",
            )

        if not (
            hasattr(vertexai, "preview") or hasattr(vertexai.preview, "language_models")
        ):
            raise VertexAIError(

                status_code=400,
                message="""Upgrade vertex ai. Run `pip install "google-cloud-aiplatform>=1.38"`""",
            )
        try:
            vertex_httpx_logic = VertexLLM()

            access_token, project_id = vertex_httpx_logic._ensure_access_token(
                credentials=vertex_credentials,
                project_id=vertex_project,
                custom_llm_provider="vertex_ai",
            )

            openai_lik
…[4440 chars omitted]…
set.add(
                "tool-search-tool-2025-10-19"
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:47:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_ai_partner_models/main.py:164:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_llm_base.py:237:    def get_complete_vertex_url(

679:    def get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
696:    def get_vertex_ai_location(litellm_params: dict) -> Optional[str]:
)

if TYPE_CHECKING:
    from google.auth.credentials import Credentials as GoogleCredentialsObject
else:
    GoogleCredentialsObject = Any


class VertexBase:
    def __init__(self) -> None:

        super().__init__()
        self.access_token: Optional[str] = None
        self.refresh_token: Optional[str] = None
        self._credentials: Optional[GoogleCredentialsObject] = None
        self._credentials_project_mapping: Dict[
            Tuple[Optional[VERTEX_CREDENTIALS_TYPES], Optional[str]],
            Tuple[GoogleCredentialsObject, str],
        ] = {}
        self.project_id: Optional[str] = None
        self.async_handler: Optional[AsyncHTTPHandler] = None

    def get_vertex_region(self, vertex_region: Optional[str], model: str
…[3242 chars omitted]…
anthropic_version"] = "vertex-2023-10-16"

        anthropic_messages_request.pop(
            "model", None
        )  # do not pass model in request body to vertex ai

        anthropic_messages_request.pop(
            "output_format", None
        )  # do not pass output_format in request body to vertex ai - vertex ai does not support output_format as yet

        return anthropic_messages_request

21:36:12 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
({'Authorization': 'Bearer cached', 'content-type': 'application/json'}, None) calls 0

project_id=project_id,
                )
            except Exception as e:
                raise e

    def set_headers(
        self, auth_header: Optional[str], extra_headers: Optional[dict]
    ) -> dict:
        headers = {
            "Content-Type": "application/json",
        }
        if auth_header is not None:

            headers["Authorization"] = f"Bearer {auth_header}"
        if extra_headers is not None:
            headers.update(extra_headers)

        return headers

    @staticmethod
    def get_vertex_ai_project(litellm_params: dict) -> Optional[str]:
        return (
            litellm_params.pop("vertex_project", None)
            or litellm_params.pop("vertex_ai_project", None)
            or litellm.vertex_project
            or get_secret_str("VERTEXAI_PROJECT")
        )

    @staticmethod
    def get_vertex_ai_credentials(litellm_params
…[783 chars omitted]…
 dict.

        Unlike get_vertex_ai_project(), this does NOT pop values from the dict,
        making it safe to call multiple times with the same litellm_params.

        Args:
            litellm_params: Dictionary containing Vertex AI parameters

litellm/llms/bedrock/chat/converse_transformation.py:1195:        output_config: Optional[OutputConfigBlock] = inference_params.pop("outputConfig", None)

21:36:47 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
({'Authorization': 'Bearer cached', 'content-type': 'application/json'}, 'https://vertex') {'custom_api_base': None, 'vertex_location': 'loc', 'vertex_project': 'p', 'project_id': 'p', 'partner': <VertexPartnerProvider.claude: 'claude'>, 'stream': False, 'model': 'claude'} 0
{'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 10, 'anthropic_version': 'vertex-2023-10-16'}

.............                                                            [100%]
13 passed in 1.42s

diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..54f8671 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -31,19 +31,25 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
 
         Validate the environment for the request
         """
+        # Resolve the project and location independently of authentication. Request
+        # headers may be reused (and therefore already contain Authorization), but
+        # the endpoint still needs to be constructed for Vertex partner models.
+        vertex_

…[1478 chars omitted]…
does not support output_format as yet
+        # These are Anthropic API-only fields. Vertex validates the raw request
+        # body and rejects them as extra inputs (structured output is not
+        # supported by this endpoint).
+        anthropic_messages_request.pop("output_format", None)
+        anthropic_messages_request.pop("output_config", None)
 
         return anthropic_messages_request

submitted.

AGENTS.md
ARCHITECTURE.md
CLAUDE.md
CONTRIBUTING.md
Dockerfile
GEMINI.md
LICENSE
Makefile
README.md
ci_cd
codecov.yaml
cookbook

db_scripts
deploy
dist
docker
docker-compose.hardened.yml
docker-compose.yml
docs
enterprise
index.yaml
litellm
litellm-js
litellm-proxy-extras
mcp_servers.json
model_prices_and_context_window.json
package-lock.json
package.json
poetry.lock
policy_templates.json
prometheus.yml
provider_endpoints_support.json
proxy_server_config.yaml
pyproject.toml
pyrightconfig.json
render.yaml
requirements.txt
ruff.toml
schema.prisma
scripts
security.md
taplo.toml
tests
ui
uv.lock
bash: line 6: rg: command not found

litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:18:class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase):
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:47:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_ai_partner_models/main.py:164:            api_base = self.get_complete_vertex_url(
litellm/llms/vertex_ai/vertex_llm_base.py:237:    def get_complete_vertex_url(
litellm/utils.py:8177:                    VertexAIPartnerModelsAnthropicMessagesConfig,
litellm/utils.py:8180:                return VertexAIPartnerModelsAnthropicMessagesConfig()
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py:6:    VertexAIPartnerModelsAnthropicMessagesC
…[8630 chars omitted]…
sformation.py:3371:    output_config = AmazonConverseConfig._create_output_config_for_response_format(
tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py:3374:    parsed = json.loads(output_config["textFormat"]["structure"]["jsonSchema"]["schema"])
tests/test_litellm/llms/stability/image_generation/test_stability_image_generation.py:194:        assert result["output_format"] == "png"

from unittest.mock import patch

import pytest

from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.experimental_pass_through.transformation import (
    VertexAIPartnerModelsAnthropicMessagesConfig,
)


def test_validate_environment_uses_vertex_ai_location():
    config = VertexAIPartnerModelsAnthropicMessagesConfig()
    headers = {}

    litellm_params = {
        "vertex_ai_project": "test-project",
        "vertex_ai_location": "europe-west1",
        "vertex_credentials": "{}",
    }
    optional_params = {}

    with patch.object(
        config, "_ensure_access_token", return_value=("token", "test-project")
    ), patch.object(
        config, "get_complete_vertex_url", return_value="https://mock-url"
    ) as mock_get_url:
        config.validate_anthropic_messages_environment(
            headers=headers,
            model="claude-3-sonnet",
            messages=[]
…[8629 chars omitted]…
  result = config.transform_request(
        model="claude-opus-4-6",
        messages=messages,
        optional_params=optional_params,
        litellm_params={},
        headers={},
    )

    # Verify both beta headers are present
    assert "anthropic_beta" in result
    assert "compact-2026-01-12" in result["anthropic_beta"]
    assert "context-management-2025-06-27" in result["anthropic_beta"]

from typing import Any, Dict, List, Optional, Tuple

from litellm.llms.anthropic.common_utils import AnthropicModelInfo
from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
    AnthropicMessagesConfig,
)
from litellm.types.llms.anthropic import (
    ANTHROPIC_BETA_HEADER_VALUES,
    ANTHROPIC_HOSTED_TOOLS,
)
from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header
from litellm.types.llms.vertex_ai import VertexPartnerProvider

from litellm.types.router import GenericLiteLLMParams

from ....vertex_llm_base import VertexBase


class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase):
    def validate_anthropic_messages_environment(
        self,
        headers: dict,
        model: str,
        messages: List[Any],
        optional_params: dict,
        litellm_params: dict,
        api_key: Option
…[8629 chars omitted]…
ex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py:446:    from litellm.llms.vertex_ai.vertex_ai_partner_models.anthropic.experimental_pass_through.transformation import (
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py:447:        VertexAIPartnerModelsAnthropicMessagesConfig,

# Check for web search tool
        for tool in tools:
            if isinstance(tool, dict) and tool.get("type", "").startswith(ANTHROPIC_HOSTED_TOOLS.WEB_SEARCH.value):
                beta_values.add(ANTHROPIC_BETA_HEADER_VALUES.WEB_SEARCH_2025_03_05.value)
                break
        
        # Check for tool search tools - Vertex AI uses different beta header
        anthropic_model_info = AnthropicModelInfo()
        if anthropic_model_info.is_tool_search_used(tools):
            beta_values.add(get_tool_search_beta_header("vertex_ai"))
        
        if beta_values:

            headers["anthropic-beta"] = ",".join(beta_values)
        
        return headers, api_base

    def get_complete_url(
        self,
        api_base: Optional[str],
        api_key: Optional[str],
        model: str,
        optional_params: dict,
        litellm_params: dict,
        strea
…[7704 chars omitted]…
beta_header or ""
    ), "Other non-excluded beta headers should remain"
    # If prompt-caching was the only value, header should be removed completely
    headers2 = {"anthropic-beta": PROMPT_CACHING_BETA_HEADER}
    headers2 = update_headers_with_filtered_beta(headers2, "vertex_ai")
    assert (
        "anthropic-beta" not in headers2
    ), "Header should be removed if no supported values remain"

litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:48:            "output_config",
litellm/llms/anthropic/chat/transformation.py:1363:        ## Handle output_config (Anthropic-specific parameter)
litellm/llms/anthropic/chat/transformation.py:1364:        if "output_config" in optional_params:
litellm/llms/anthropic/chat/transformation.py:1365:            output_config = optional_params.get("output_config")
litellm/llms/anthropic/chat/transformation.py:1366:            if output_config and isinstance(output_config, dict):
litellm/llms/anthropic/chat/transformation.py:1367:                effort = output_config.get("effort")
litellm/llms/anthropic/chat/transformation.py:1376:                data["output_config"] = output_config
litellm/llms/anthropic/common_utils.py:244:        # Check if output_config is directly provided
litellm/llms/anthropic/common_utils.py
…[7671 chars omitted]…
      request_body=request_body,
225-            litellm_logging_obj=litellm_logging_obj,

226-        )
227-
228-    @staticmethod
229-    def _update_headers_with_anthropic_beta(
230-        headers: dict,
231-        optional_params: dict,
232-        custom_llm_provider: str = "anthropic",
233-    ) -> dict:
234-        """
235-        Auto-inject anthropic-beta headers based on features used.
236-

21:45:20 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
({'Authorization': 'Bearer cached', 'content-type': 'application/json'}, None)
url calls 0

self,
        headers: dict,
        model: str,
        messages: List[Any],
        optional_params: dict,
        litellm_params: dict,
        api_key: Optional[str] = None,
        api_base: Optional[str] = None,
    ) -> Tuple[dict, Optional[str]]:
        """
        OPTIONAL

        Validate the environment for the request
        """
        # An Authorization header can be supplied by a reused/cached request. It
        # must not prevent us from resolving the Vertex URL: get_complete_url()
        # still needs an endpoint when no api_base was supplied.
        vertex_ai_project = VertexBase.get_vertex_ai_project(litellm_params)
        vertex_ai_location = VertexBase.get_vertex_ai_location(litellm_params)
        project_id = vertex_ai_project

        if "Authorization" not in headers:
            vertex_credentials = VertexBase.get_vertex_ai_credentials(litellm_
…[2386 chars omitted]…
       )  # do not pass model in request body to vertex ai

        # These are Anthropic Messages API fields, but Vertex's Anthropic
        # endpoint rejects them as unknown inputs (structured output is not
        # supported there).
        anthropic_messages_request.pop("output_format", None)
        anthropic_messages_request.pop("output_config", None)

        return anthropic_messages_request

21:45:53 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
({'Authorization': 'Bearer cached', 'content-type': 'application/json'}, 'derived')
{'custom_api_base': None, 'vertex_location': 'l', 'vertex_project': 'p', 'project_id': 'p', 'partner': <VertexPartnerProvider.claude: 'claude'>, 'stream': False, 'model': 'claude'}
{'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 100, 'anthropic_version': 'vertex-2023-10-16'}
...................                                                      [100%]
19 passed in 1.55s

diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
index 54c3f9e..57ee3f7 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py
@@ -31,19 +31,26 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert
 
         Validate the environment for the request
         """
-        if "Authorization" not in headers:
-            vertex_ai_project = VertexBase.get_vertex_ai_project(litellm_params)
+        # An Authorization header can be supplied by a reused/cached request. It
+        # must not prevent us from resolving the Vertex U

…[1528 chars omitted]…
ai - vertex ai does not support output_format as yet
+        # These are Anthropic Messages API fields, but Vertex's Anthropic
+        # endpoint rejects them as unknown inputs (structured output is not
+        # supported there).
+        anthropic_messages_request.pop("output_format", None)
+        anthropic_messages_request.pop("output_config", None)
 
         return anthropic_messages_request

submitted.

AGENTS.md
ARCHITECTURE.md
CLAUDE.md
CONTRIBUTING.md
Dockerfile
GEMINI.md
LICENSE
Makefile
README.md
ci_cd
codecov.yaml
cookbook

db_scripts
deploy
dist
docker
docker-compose.hardened.yml
docker-compose.yml
docs
enterprise
index.yaml
litellm
litellm-js
litellm-proxy-extras
mcp_servers.json
model_prices_and_context_window.json
package-lock.json
package.json
poetry.lock
policy_templates.json
prometheus.yml
provider_endpoints_support.json
proxy_server_config.yaml
pyproject.toml
pyrightconfig.json
render.yaml
requirements.txt
ruff.toml
schema.prisma
scripts
security.md
taplo.toml
tests
ui
uv.lock
litellm/llms/anthropic/experimental_pass_through/messages/transformation.py:103:    def validate_anthropic_messages_environment(
litellm/llms/azure_ai/anthropic/messages_transformation.py:23:    def validate_anthropic_messages_environment(
litellm/llms/base_llm/anthropic_messages/transformation.py:
…[806 chars omitted]…
through.py:611:#     mock_provider_config.validate_anthropic_messages_environment.return_value = (
tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py:654:#         # Verify that validate_anthropic_messages_environment was called
tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py:655:#         assert mock_provider_config.validate_anthropic_messages_environment.called

from typing import Any, Dict, List, Optional, Tuple

from litellm.llms.anthropic.common_utils import AnthropicModelInfo
from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
    AnthropicMessagesConfig,
)
from litellm.types.llms.anthropic import (
    ANTHROPIC_BETA_HEADER_VALUES,
    ANTHROPIC_HOSTED_TOOLS,
)
from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header
from litellm.types.llms.vertex_ai import VertexPartnerProvider

from litellm.types.router import GenericLiteLLMParams

from ....vertex_llm_base import VertexBase


class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, VertexBase):
    def validate_anthropic_messages_environment(
        self,
        headers: dict,
        model: str,
        messages: List[Any],
        optional_params: dict,
        litellm_params: dict,
        api_key: Option
…[3337 chars omitted]…
onal[str],
        model: str,
        optional_params: dict,
        litellm_params: dict,
        stream: Optional[bool] = None,
    ) -> str:
        if api_base is None:
            raise ValueError(
                "api_base is required. Unable to determine the correct api_base for the request."
            )
        return api_base  # no transformation is needed - handled in validate_environment

45:            "output_format",
48:            "output_config",
240:        - output_format: adds 'structured-outputs-2025-11-13'
245:            optional_params: Optional parameters including tools, context_management, output_format, speed
281:        if optional_params.get("output_format") is not None:

from typing import Any, AsyncIterator, Dict, List, Optional, Tuple

import httpx

from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
from litellm.litellm_core_utils.litellm_logging import verbose_logger
from litellm.llms.base_llm.anthropic_messages.transformation import (
    BaseAnthropicMessagesConfig,
)
from litellm.types.llms.anthropic import (
    ANTHROPIC_BETA_HEADER_VALUES,
    AnthropicMessagesRequest,

)
from litellm.types.llms.anthropic_messages.anthropic_response import (
    AnthropicMessagesResponse,
)
from litellm.types.llms.anthropic_tool_search import get_tool_search_beta_header
from litellm.types.router import GenericLiteLLMParams

from ...common_utils import (
    AnthropicError,
    AnthropicModelInfo,
    optionally_handle_anthropic_oauth,
)

DEFAULT_ANTHROPIC_API_BASE = "https://api.anthropic.com"
DEFAULT_ANTHROPIC_API_VERSION = "2
…[2804 chars omitted]…
dict,
        api_key: Optional[str] = None,
        api_base: Optional[str] = None,
    ) -> Tuple[dict, Optional[str]]:
        import os

        # Check for Anthropic OAuth token in Authorization header
        headers, api_key = optionally_handle_anthropic_oauth(
            headers=headers, api_key=api_key
        )
        if api_key is None:
            api_key = os.getenv("ANTHROPIC_API_KEY")

api_key = os.getenv("ANTHROPIC_API_KEY")

        if "x-api-key" not in headers and "authorization" not in headers and api_key:
            headers["x-api-key"] = api_key
        if "anthropic-version" not in headers:
            headers["anthropic-version"] = DEFAULT_ANTHROPIC_API_VERSION
        if "content-type" not in headers:
            headers["content-type"] = "application/json"

        headers = self._update_headers_with_anthropic_beta(
            headers=headers,
            optional_params=optional_params,

        )

        return headers, api_base

    def transform_anthropic_messages_request(
        self,
        model: str,
        messages: List[Dict],
        anthropic_messages_optional_request_params: Dict,
        litellm_params: GenericLiteLLMParams,
        headers: dict,
    ) -> Dict:
        """
        No transformation is needed for Anthropic m
…[3785 chars omitted]…
     headers: dict,
        optional_params: dict,
        custom_llm_provider: str = "anthropic",
    ) -> dict:
        """
        Auto-inject anthropic-beta headers based on features used.

        Handles:
        - context_management: adds 'context-management-2025-06-27'
        - tool_search: adds provider-specific tool search header
        - output_format: adds 'structured-outputs-2025-11-13'

experimental_pass_through
transformation.py
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:122:    def transform_anthropic_messages_request(
litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py:130:        anthropic_messages_request = super().transform_anthropic_messages_request(

return api_base  # no transformation is needed - handled in validate_environment

    def transform_anthropic_messages_request(
        self,
        model: str,
        messages: List[Dict],
        anthropic_messages_optional_request_params: Dict,
        litellm_params: GenericLiteLLMParams,
        headers: dict,
    ) -> Dict:
        anthropic_messages_request = super().transform_anthropic_messages_request(
            model=model,

            messages=messages,
            anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )

        anthropic_messages_request["anthropic_version"] = "vertex-2023-10-16"

        anthropic_messages_request.pop(
            "model", None
        )  # do not pass model in request body to vertex ai

        anthropic_messages_request.pop(
            "output_format", None
        )  # do not pass output_format in request body to vertex ai - vertex ai does not support output_format as yet

        return anthropic_messages_request

class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
    def get_supported_anthropic_messages_params(self, model: str) -> list:
        return [
            "messages",
            "model",
            "system",
            "max_tokens",
            "stop_sequences",
            "temperature",
            "top_p",
            "top_k",
            "tools",

            "tool_choice",
            "thinking",
            "context_management",
            "output_format",
            "inference_geo",
            "speed",
            "output_config",
            # TODO: Add Anthropic `metadata` support
            # "metadata",
        ]

    @staticmethod
    def _filter_billing_headers_from_system(system_param):
        """
        Filter out x-anthropic-billing-header metadata from system parameter.

        Args:
            system_param: Can be a string or a list of system messa
…[666 chars omitted]…
config
litellm/llms/anthropic/common_utils.py:244:        # Check if output_config is directly provided
litellm/llms/anthropic/common_utils.py:245:        output_config = optional_params.get("output_config")
litellm/llms/anthropic/common_utils.py:246:        if output_config and isinstance(output_config, dict):
litellm/llms/anthropic/common_utils.py:247:            effort = output_config.get("effort")

def validate_anthropic_messages_environment(
        self,
        headers: dict,
        model: str,
        messages: List[Any],
        optional_params: dict,
        litellm_params: dict,
        api_key: Optional[str] = None,
        api_base: Optional[str] = None,
    ) -> Tuple[dict, Optional[str]]:
        """
        OPTIONAL

        Validate the environment for the request
        """
        if "Authorization" not in headers:
            vertex_ai_project = VertexBase.get_vertex_ai_project(litellm_params)
            vertex_credentials = VertexBase.get_vertex_ai_credentials(litellm_params)
            vertex_ai_location = VertexBase.get_vertex_ai_location(litellm_params)

            access_token, project_id = self._ensure_access_token(
                credentials=vertex_credentials,
                project_id=vertex_ai_project,
                custom_llm_provider="ver
…[434 chars omitted]…
lse),
                model=model,
            )
        elif api_base is None:
            # Authorization header already present (e.g. reused/cached headers) -
            # skip the token exchange but still derive the Vertex AI endpoint.
            vertex_ai_project = VertexBase.get_vertex_ai_project(litellm_params)
            vertex_ai_location = VertexBase.get_vertex_ai_location(litellm_params)

237:    def get_complete_vertex_url(
238-        self,
239-        custom_api_base: Optional[str],
240-        vertex_location: Optional[str],
241-        vertex_project: Optional[str],
242-        project_id: str,
243-        partner: VertexPartnerProvider,
244-        stream: Optional[bool],
245-        model: str,
246-    ) -> str:
247-        # Use get_vertex_region to handle global-only models
248-        resolved_location = self.get_vertex_region(vertex_location, model)

249-        api_base = self.get_api_base(
250-            api_base=custom_api_base, vertex_location=resolved_location
251-        )
252-        default_api_base = VertexBase.create_vertex_url(
253-            vertex_location=resolved_location,
254-            vertex_project=vertex_project or project_id,
255-            partner=partner,
256-            stream=stream,
257-            model=model,

00:31:38 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
{'Authorization': 'Bearer cached', 'content-type': 'application/json'}
Traceback (most recent call last):
  File "<stdin>", line 8, in <module>
AssertionError: {'Authorization': 'Bearer cached', 'content-type': 'application/json'}

00:31:53 - LiteLLM:WARNING: get_model_cost_map.py:174 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: [Errno -3] Temporary failure in name resolution. Falling back to local backup.
https://us-central1-aiplatform.googleapis.com/v1/projects/proj/locations/us-central1/publishers/anthropic/models/claude-3-sonnet@20240229:rawPredict
{'messages': [{'role': 'user', 'content': 'hi'}], 'max_tokens': 10, 'temperature': 1, 'anthropic_version': 'vertex-2023-10-16'}
OK

tests/llm_translation/:
Readme.md
base_audio_transcription_unit_tests.py
base_embedding_unit_tests.py
base_llm_unit_tests.py
base_rerank_unit_tests.py
conftest.py
dog.wav
duck.png
fixtures
gettysburg.wav
guinea.png

log.xt
realtime
test-skill
test_a2a.py
test_anthropic_completion.py
test_aws_base_llm.py
test_azure_agents.py
test_azure_ai.py
test_azure_o_series.py
test_azure_openai.py
test_bedrock_agentcore.py
test_bedrock_agents.py
test_bedrock_anthropic_regression.py
test_bedrock_common_utils.py
test_bedrock_completion.py
test_bedrock_dynamic_auth_params_unit_tests.py
test_bedrock_embedding.py
test_bedrock_govcloud.py
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_messages_config.py
tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py

............................                                             [100%]
28 passed in 1.48s

verbose_logger.debug(print_statement)
Message: 'Logging Details LiteLLM-Async Success Call, cache_hit=None'
Arguments: ()
 .../experimental_pass_through/transformation.py       | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)

),  # dynamic aws_* params are passed under litellm_params
            ),  # dynamic aws_* params are passed under litellm_params
            ),  # dynamic aws_* params are passed under litellm_params
            ),  # dynamic aws_* params are passed under litellm_params
LiteLLM: Params passed to completion() {'model': 'gpt-4o-mini', 'functions': None, 'function_call': None, 'temperature': None, 'top_p': None, 'n': None, 'stream': None, 'stream_options': None, 'stop': None, 'max_tokens': 100, 'max_completion_tokens': None, 'modalities': None, 'prediction': None, 'audio': None, 'presence_penalty': None, 'frequency_penalty': None, 'logit_bias': None, 'user': None, 'custom_llm_provider': 'openai', 'response_format': None, 'seed': None, 'tools': None, 'tool_choice': None, 'max_retries': None, 'logprobs': None, 'top_logprobs': None, 'extra_headers': None, 'api_version': None, '
…[8628 chars omitted]…
wed_openai_params': None, 'reasoning_effort': None, 'verbosity': None, 'additional_drop_params': None, 'messages': [{'role': 'user', 'content': 'Hello, can you tell me a short joke?'}], 'thinking': None, 'web_search_options': None, 'safety_identifier': None, 'service_tier': None}
LiteLLM: Non-Default params passed to completion() {'max_tokens': 100}
20 failed, 4 passed, 34 warnings in 60.52s (0:01:00)

FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicDirectAPI::test_non_streaming_base
FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicDirectAPI::test_streaming_base
FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicDirectAPI::test_response_format_consistency
FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicDirectAPI::test_anthropic_messages_litellm_router_streaming_with_logging
FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicBedrockAPI::test_non_streaming_base
FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicBedrockAPI::test_streaming_base
FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicBedrockAPI::test
…[37 chars omitted]…
ests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicBedrockAPI::test_anthropic_messages_litellm_router_streaming_with_logging
FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicOpenAIAPI::test_non_streaming_base
FAILED tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py::TestAnthropicOpenAIAPI::test_streaming_base
20

Saved working directory and index state WIP on master: 646dbbb base
!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!
1 failed, 21 deselected, 3 warnings in 6.13s
On branch master
Changes not staged for commit:
  (use "git add <file>..." to update what will be committed)
  (use "git restore <file>..." to discard changes in working directory)
	modified:   litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/experimental_pass_through/transformation.py

no changes added to commit (use "git add" and/or "git commit -a")
Dropped refs/stash@{0} (5bd6e033ea2e1aa9865912c69fb5e042979629da)

…[196 chars omitted]…
) from the Vertex AI request body. Reproducer passes; existing vertex anthropic config tests (28) pass; passthrough test failures are pre-existing/network-dependent."}
submitted.