mirror of
https://github.com/BerriAI/litellm.git
synced 2026-11-11 08:38:24 +00:00
feat(anthropic): pick beta allowlist row per deployment, add mid-2026 beta rows, surface input_transformations
Foundry-hosted anthropic deployments now filter anthropic-beta by the azure_ai row on /v1/messages and chat completions, the bundled config gains the mid-conversation-system-clear-at-2026-08-21 row plus the tool-changes and output-config betas on azure_ai and vertex_ai from a live probe, and Anthropic's input_transformations array reaches chat completions in provider_specific_fields (non-streaming and the first streaming chunk). Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
mateo
parent
34134d7ae5
commit
7a7abe0d7f
12 changed files with 405 additions and 49 deletions
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@ -31,6 +31,7 @@
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"text_editor_20241022": null,
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"text_editor_20250124": null,
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"thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01",
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"mid-conversation-system-clear-at-2026-08-21": "mid-conversation-system-clear-at-2026-08-21",
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"token-efficient-tools-2025-02-19": "token-efficient-tools-2025-02-19",
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"web-fetch-2025-09-10": "web-fetch-2025-09-10",
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"web-search-2025-03-05": "web-search-2025-03-05",
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@ -68,6 +69,9 @@
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"text_editor_20241022": null,
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"text_editor_20250124": null,
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"thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01",
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"mid-conversation-output-config-2026-07-01": "mid-conversation-output-config-2026-07-01",
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"mid-conversation-tool-changes-2026-07-01": "mid-conversation-tool-changes-2026-07-01",
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"mid-conversation-system-clear-at-2026-08-21": "mid-conversation-system-clear-at-2026-08-21",
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"thinking-display-updates-2026-08-18": "thinking-display-updates-2026-08-18",
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"token-efficient-tools-2025-02-19": null,
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"web-fetch-2025-09-10": "web-fetch-2025-09-10",
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@ -102,6 +106,7 @@
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"text_editor_20241022": null,
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"text_editor_20250124": null,
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"thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01",
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"mid-conversation-system-clear-at-2026-08-21": null,
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"thinking-display-updates-2026-08-18": "thinking-display-updates-2026-08-18",
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"token-efficient-tools-2025-02-19": null,
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"tool-search-tool-2025-10-19": null,
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@ -137,6 +142,7 @@
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"text_editor_20241022": null,
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"text_editor_20250124": null,
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"thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01",
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"mid-conversation-system-clear-at-2026-08-21": null,
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"token-efficient-tools-2025-02-19": null,
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"tool-search-tool-2025-10-19": "tool-search-tool-2025-10-19",
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"web-fetch-2025-09-10": null,
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@ -175,6 +181,7 @@
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"text_editor_20241022": null,
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"text_editor_20250124": null,
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"thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01",
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"mid-conversation-system-clear-at-2026-08-21": null,
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"thinking-display-updates-2026-08-18": "thinking-display-updates-2026-08-18",
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"token-efficient-tools-2025-02-19": "token-efficient-tools-2025-02-19",
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"tool-examples-2025-10-29": "tool-examples-2025-10-29",
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@ -211,6 +218,9 @@
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"text_editor_20241022": null,
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"text_editor_20250124": null,
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"thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01",
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"mid-conversation-output-config-2026-07-01": "mid-conversation-output-config-2026-07-01",
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"mid-conversation-tool-changes-2026-07-01": "mid-conversation-tool-changes-2026-07-01",
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"mid-conversation-system-clear-at-2026-08-21": "mid-conversation-system-clear-at-2026-08-21",
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"thinking-display-updates-2026-08-18": "thinking-display-updates-2026-08-18",
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"token-efficient-tools-2025-02-19": null,
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"tool-search-tool-2025-10-19": "tool-search-tool-2025-10-19",
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@ -248,6 +258,7 @@
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"text_editor_20241022": null,
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"text_editor_20250124": null,
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"thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01",
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"mid-conversation-system-clear-at-2026-08-21": null,
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"token-efficient-tools-2025-02-19": "token-efficient-tools-2025-02-19",
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"web-fetch-2025-09-10": null,
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"web-search-2025-03-05": "web-search-2025-03-05"
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@ -31,6 +31,7 @@ from concurrent.futures import ThreadPoolExecutor
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from functools import cache
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from importlib.resources import files
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from typing import Final, TypeAlias
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from urllib.parse import urlparse
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import httpx
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from pydantic import TypeAdapter
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@ -355,9 +356,33 @@ def get_provider_beta_header(
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return provider_mapping[anthropic_beta_header]
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FOUNDRY_API_BASE_HOST_SUFFIXES: Final[tuple[str, ...]] = ("services.ai.azure.com", "openai.azure.com")
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def is_foundry_api_base(api_base: str | None) -> bool:
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"""Whether ``api_base`` points at an Azure AI Foundry host, where Claude is served by Microsoft."""
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if not api_base:
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return False
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host: Final = urlparse(api_base if "://" in api_base else f"https://{api_base}").hostname or ""
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return any(host == suffix or host.endswith(f".{suffix}") for suffix in FOUNDRY_API_BASE_HOST_SUFFIXES)
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def resolve_beta_provider(provider: str, api_base: str | None = None) -> str:
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"""
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Pick the beta allowlist row for one deployment, not one provider string.
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An ``anthropic`` deployment whose ``api_base`` is a Foundry host is served by Microsoft and
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gets the ``azure_ai`` row, since Foundry accepts a different set of betas than api.anthropic.com.
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"""
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if get_provider_name(provider) == "anthropic" and is_foundry_api_base(api_base):
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return "azure_ai"
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return provider
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def update_headers_with_filtered_beta(
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headers: dict,
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provider: str,
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api_base: str | None = None,
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) -> dict:
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"""
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Update headers dict by filtering and transforming anthropic-beta header values.
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@ -366,6 +391,7 @@ def update_headers_with_filtered_beta(
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Args:
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headers: Request headers dict (will be modified in place)
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provider: Provider name
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api_base: Deployment api_base, used to pick the allowlist row (Foundry hosts use ``azure_ai``)
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Returns:
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Updated headers dict
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@ -380,7 +406,7 @@ def update_headers_with_filtered_beta(
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# Filter and transform based on provider
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filtered_beta_values: Final = filter_and_transform_beta_headers(
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beta_headers=beta_values,
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provider=provider,
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provider=resolve_beta_provider(provider, api_base),
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)
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# Update or remove the header
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@ -397,6 +423,7 @@ def update_request_with_filtered_beta(
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headers: dict,
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request_data: dict,
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provider: str,
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api_base: str | None = None,
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) -> tuple[dict, dict]:
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"""
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Update both headers and request body beta fields based on provider support.
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@ -406,11 +433,13 @@ def update_request_with_filtered_beta(
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headers: Request headers dict (will be modified in place)
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request_data: Request body dict (will be modified in place)
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provider: Provider name
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api_base: Deployment api_base, used to pick the allowlist row (Foundry hosts use ``azure_ai``)
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Returns:
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Tuple of (updated headers, updated request_data)
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"""
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headers = update_headers_with_filtered_beta(headers=headers, provider=provider)
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row_provider: Final = resolve_beta_provider(provider, api_base)
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headers = update_headers_with_filtered_beta(headers=headers, provider=row_provider)
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existing_body_betas: Final = request_data.get("anthropic_beta")
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if not existing_body_betas:
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@ -418,7 +447,7 @@ def update_request_with_filtered_beta(
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filtered_body_betas: Final = filter_and_transform_beta_headers(
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beta_headers=existing_body_betas,
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provider=provider,
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provider=row_provider,
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)
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if filtered_body_betas:
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@ -509,6 +509,7 @@ class AnthropicChatCompletion(BaseLLM):
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headers=headers,
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request_data=request_data,
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provider=custom_llm_provider,
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api_base=api_base,
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)
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logging_obj.pre_call(
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input=messages,
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@ -1165,6 +1166,9 @@ class ModelResponseIterator:
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start_message: Final = message_start_block["message"]
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if "model" in start_message:
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self.served_model = start_message["model"]
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input_transformations: Final = start_message.get("input_transformations")
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if input_transformations is not None:
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provider_specific_fields["input_transformations"] = input_transformations
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if "usage" in message_start_block["message"]:
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usage = self._handle_usage(anthropic_usage_chunk=message_start_block["message"]["usage"])
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elif type_chunk == "error":
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@ -2937,6 +2937,10 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
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if context_management is not None:
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provider_specific_fields["context_management"] = context_management
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input_transformations: Final = completion_response.get("input_transformations")
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if input_transformations is not None:
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provider_specific_fields["input_transformations"] = input_transformations
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if web_search_results is not None:
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provider_specific_fields["web_search_results"] = web_search_results
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provider_specific_fields["web_search_calls"] = self._build_web_search_calls(
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@ -36,7 +36,11 @@ import litellm.litellm_core_utils
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import litellm.types
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import litellm.types.utils
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from litellm._logging import redact_string, verbose_logger
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from litellm.anthropic_beta_headers_manager import aload_beta_headers_config, update_headers_with_filtered_beta
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from litellm.anthropic_beta_headers_manager import (
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aload_beta_headers_config,
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is_foundry_api_base,
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update_headers_with_filtered_beta,
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)
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from litellm.constants import MAX_FILE_LIST_LIMIT, REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES
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from litellm.files.types import FileContentStreamingResult
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from litellm.litellm_core_utils.agentic_followup_kwargs import build_agentic_followup_kwargs
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@ -2494,14 +2498,15 @@ class BaseLLMHTTPHandler:
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litellm_params.get("additional_drop_params") or (),
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anthropic_messages_optional_request_params,
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)
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if (
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request_params.get("safeguards") is not None
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and anthropic_messages_provider_config.should_filter_anthropic_beta_headers()
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):
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await aload_beta_headers_config()
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affinity_api_base: Final = (
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AnthropicModelInfo.get_api_base(api_base) if custom_llm_provider == "anthropic" else api_base
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)
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filters_beta_headers: Final = (
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anthropic_messages_provider_config.should_filter_anthropic_beta_headers()
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or is_foundry_api_base(affinity_api_base)
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)
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if request_params.get("safeguards") is not None and filters_beta_headers:
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await aload_beta_headers_config()
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default_affinity_header: Final = get_provider_affinity_header(affinity_api_base)
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(
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headers,
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@ -2520,8 +2525,10 @@ class BaseLLMHTTPHandler:
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api_base=api_base,
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)
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if anthropic_messages_provider_config.should_filter_anthropic_beta_headers():
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headers = update_headers_with_filtered_beta(headers=headers, provider=custom_llm_provider)
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if filters_beta_headers:
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headers = update_headers_with_filtered_beta(
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headers=headers, provider=custom_llm_provider, api_base=affinity_api_base
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)
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from litellm.llms.vertex_ai.vertex_llm_base import VertexBase
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@ -651,6 +651,7 @@ class MessageChunk(TypedDict, total=False):
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stop_sequence: str | None
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usage: UsageDelta
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safeguard_results: ReadOnly[Sequence[SafeguardResult]]
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input_transformations: ReadOnly[Sequence[Mapping[str, object]]]
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class MessageStartBlock(TypedDict):
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@ -1,4 +1,4 @@
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from collections.abc import Sequence
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from collections.abc import Mapping, Sequence
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from typing import Literal, TypeAlias
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from typing_extensions import NotRequired, ReadOnly, TypedDict
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@ -106,3 +106,4 @@ class AnthropicMessagesResponse(TypedDict, total=False):
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usage: AnthropicUsage | None
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context_management: NotRequired[ContextManagementResponse]
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safeguard_results: NotRequired[ReadOnly[Sequence[SafeguardResult]]]
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input_transformations: NotRequired[ReadOnly[Sequence[Mapping[str, object]]]]
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@ -494,7 +494,11 @@ def test_streamed_thinking_blocks_accumulate_in_the_openai_sdk_and_replay_withou
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{"type": "content_block_delta", "index": 2, "delta": {"type": "thinking_delta", "thinking": "Step 3."}},
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{"type": "content_block_delta", "index": 2, "delta": {"type": "signature_delta", "signature": "sig-b"}},
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{"type": "content_block_stop", "index": 2},
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{"type": "message_delta", "delta": {"stop_reason": "end_turn", "stop_sequence": None}, "usage": {"output_tokens": 9}},
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{
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"type": "message_delta",
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"delta": {"stop_reason": "end_turn", "stop_sequence": None},
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"usage": {"output_tokens": 9},
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},
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{"type": "message_stop"},
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)
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@ -515,7 +519,11 @@ def test_streamed_thinking_blocks_accumulate_in_the_openai_sdk_and_replay_withou
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"thinking_blocks": message["thinking_blocks"],
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}
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replayed: Final = anthropic_messages_pt(
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messages=[{"role": "user", "content": "Capital of France?"}, next_turn, {"role": "user", "content": "And Spain?"}],
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messages=[
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{"role": "user", "content": "Capital of France?"},
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next_turn,
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{"role": "user", "content": "And Spain?"},
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],
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model="claude-haiku-4-5",
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llm_provider="anthropic",
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)
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@ -3607,3 +3615,37 @@ def test_streamed_end_turn_carries_no_stop_details():
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provider_fields: Final = assembled.choices[0].message.provider_specific_fields or {}
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assert "stop_details" not in provider_fields
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assert "stop_reason" not in provider_fields
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def test_message_start_surfaces_input_transformations_on_the_first_chunk():
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input_transformations: Final = [{"type": "thinking_block_binding", "count": 2}]
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chunk: Final = {
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"type": "message_start",
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"message": {
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"id": "msg_1",
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"type": "message",
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"role": "assistant",
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"model": "claude-sonnet-4-6",
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"content": [],
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"stop_reason": None,
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"stop_sequence": None,
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"usage": {"input_tokens": 12, "output_tokens": 1},
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"input_transformations": input_transformations,
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},
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}
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iterator: Final = ModelResponseIterator(streaming_response=MagicMock(), sync_stream=True, json_mode=False)
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first_chunk: Final = iterator.chunk_parser(chunk=chunk)
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assert first_chunk.choices[0].delta.provider_specific_fields == {"input_transformations": input_transformations}
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assert first_chunk.model == "claude-sonnet-4-6"
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def test_message_start_without_input_transformations_has_no_provider_specific_fields():
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chunk: Final = {
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"type": "message_start",
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"message": {"id": "msg_1", "type": "message", "role": "assistant", "model": "claude-sonnet-4-6", "content": []},
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}
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iterator: Final = ModelResponseIterator(streaming_response=MagicMock(), sync_stream=True, json_mode=False)
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assert iterator.chunk_parser(chunk=chunk).choices[0].delta.provider_specific_fields is None
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@ -9804,3 +9804,54 @@ def test_transform_request_tool_config_point_without_tools_drops_the_key():
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assert "cache_control_injection_points" not in data
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assert "tools" not in data
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assert litellm_params["metadata"] == {}
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_INPUT_TRANSFORMATIONS: Final = [{"type": "thinking_block_binding", "count": 2}]
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def _input_transformations_response() -> dict:
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return {
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"id": "msg_input_transformations",
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"type": "message",
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"role": "assistant",
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"model": "claude-sonnet-4-6",
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"content": [{"type": "text", "text": "ok"}],
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"stop_reason": "end_turn",
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"stop_sequence": None,
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"usage": {"input_tokens": 12, "output_tokens": 3},
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"input_transformations": _INPUT_TRANSFORMATIONS,
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}
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def test_chat_response_surfaces_input_transformations_in_provider_specific_fields():
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result = AnthropicConfig().transform_response(
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model="claude-sonnet-4-6",
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raw_response=httpx.Response(200, json=_input_transformations_response()),
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model_response=ModelResponse(),
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logging_obj=MagicMock(),
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request_data={},
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messages=[{"role": "user", "content": "hi"}],
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optional_params={},
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litellm_params={},
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encoding=None,
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)
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assert result.choices[0].message.provider_specific_fields["input_transformations"] == _INPUT_TRANSFORMATIONS
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def test_chat_response_without_input_transformations_adds_no_key():
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completion_response = _input_transformations_response()
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del completion_response["input_transformations"]
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result = AnthropicConfig().transform_response(
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model="claude-sonnet-4-6",
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raw_response=httpx.Response(200, json=completion_response),
|
||||
model_response=ModelResponse(),
|
||||
logging_obj=MagicMock(),
|
||||
request_data={},
|
||||
messages=[{"role": "user", "content": "hi"}],
|
||||
optional_params={},
|
||||
litellm_params={},
|
||||
encoding=None,
|
||||
)
|
||||
|
||||
assert "input_transformations" not in result.choices[0].message.provider_specific_fields
|
||||
|
|
|
|||
|
|
@ -416,3 +416,33 @@ def test_drop_params_forwards_a_non_object_message_item_as_sent_on_the_native_re
|
|||
|
||||
assert request["messages"][1] == 7
|
||||
assert request["messages"][2]["content"][0]["content"] == [{"type": "text", "text": "sunny"}]
|
||||
|
||||
|
||||
def test_native_response_keeps_input_transformations() -> None:
|
||||
input_transformations: Final[list[JsonValue]] = [{"type": "thinking_block_binding", "count": 2}]
|
||||
upstream: Final[dict[str, JsonValue]] = {
|
||||
"id": "msg_test",
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"model": "claude-sonnet-4-6",
|
||||
"content": [{"type": "text", "text": "ok"}],
|
||||
"stop_reason": "end_turn",
|
||||
"stop_sequence": None,
|
||||
"usage": {"input_tokens": 19, "output_tokens": 42},
|
||||
"input_transformations": input_transformations,
|
||||
}
|
||||
logging_obj: Final = Logging(
|
||||
model="claude-sonnet-4-6",
|
||||
messages=[],
|
||||
stream=False,
|
||||
call_type="anthropic_messages",
|
||||
start_time=datetime(2026, 1, 1, tzinfo=timezone.utc),
|
||||
litellm_call_id="test-call",
|
||||
function_id="test-function",
|
||||
)
|
||||
|
||||
response: Final = AnthropicMessagesConfig().transform_anthropic_messages_response(
|
||||
model="claude-sonnet-4-6", raw_response=httpx.Response(200, json=upstream), logging_obj=logging_obj
|
||||
)
|
||||
|
||||
assert response["input_transformations"] == input_transformations
|
||||
|
|
|
|||
|
|
@ -413,9 +413,7 @@ def test_response_api_handler_sends_no_stream_options_when_web_search_forces_a_n
|
|||
):
|
||||
sent: Final = _SentRequestRecorder()
|
||||
recorder: Final = _AgenticLoopKwargsRecorder()
|
||||
monkeypatch.setattr(
|
||||
litellm, "callbacks", [WebSearchInterceptionLogger(enabled_providers=["azure"]), recorder]
|
||||
)
|
||||
monkeypatch.setattr(litellm, "callbacks", [WebSearchInterceptionLogger(enabled_providers=["azure"]), recorder])
|
||||
logging_obj: Final = Mock()
|
||||
logging_obj.dynamic_success_callbacks = []
|
||||
|
||||
|
|
@ -2486,7 +2484,9 @@ async def test_async_anthropic_messages_handler_passes_deployment_api_base_to_ag
|
|||
super().__init__()
|
||||
self.hook_kwargs: dict | None = None
|
||||
|
||||
async def async_should_run_agentic_loop(self, response, model, messages, tools, stream, custom_llm_provider, kwargs):
|
||||
async def async_should_run_agentic_loop(
|
||||
self, response, model, messages, tools, stream, custom_llm_provider, kwargs
|
||||
):
|
||||
self.hook_kwargs = dict(kwargs)
|
||||
return False, {}
|
||||
|
||||
|
|
@ -2846,9 +2846,7 @@ def _transform_subtitle_response(payload):
|
|||
|
||||
|
||||
def test_subtitle_synthesis_fallback_without_timings_drops_words():
|
||||
response = _transform_subtitle_response(
|
||||
{"text": "hello world", "words": [{"word": "hello"}, {"word": "world"}]}
|
||||
)
|
||||
response = _transform_subtitle_response({"text": "hello world", "words": [{"word": "hello"}, {"word": "world"}]})
|
||||
|
||||
assert response.text == "hello world"
|
||||
assert "words" not in response
|
||||
|
|
@ -3840,7 +3838,13 @@ def _capture_video_create_request(captured):
|
|||
captured["body"] = request.content
|
||||
return httpx.Response(
|
||||
200,
|
||||
json={"id": "video_123", "object": "video", "status": "queued", "created_at": 1712697600, "model": "sora-2"},
|
||||
json={
|
||||
"id": "video_123",
|
||||
"object": "video",
|
||||
"status": "queued",
|
||||
"created_at": 1712697600,
|
||||
"model": "sora-2",
|
||||
},
|
||||
)
|
||||
|
||||
return respond
|
||||
|
|
@ -3863,7 +3867,9 @@ def test_video_generation_without_file_sends_multipart_form_data():
|
|||
captured = {}
|
||||
client = HTTPHandler(client=httpx.Client(transport=httpx.MockTransport(_capture_video_create_request(captured))))
|
||||
|
||||
result = BaseLLMHTTPHandler().video_generation_handler(client=client, **_video_create_call_kwargs(OpenAIVideoConfig()))
|
||||
result = BaseLLMHTTPHandler().video_generation_handler(
|
||||
client=client, **_video_create_call_kwargs(OpenAIVideoConfig())
|
||||
)
|
||||
|
||||
assert captured["content_type"].startswith("multipart/form-data")
|
||||
assert _multipart_text_fields(captured["content_type"], captured["body"]) == {
|
||||
|
|
@ -3903,7 +3909,9 @@ def test_azure_video_generation_without_file_sends_multipart_form_data():
|
|||
captured = {}
|
||||
client = HTTPHandler(client=httpx.Client(transport=httpx.MockTransport(_capture_video_create_request(captured))))
|
||||
|
||||
result = BaseLLMHTTPHandler().video_generation_handler(client=client, **_video_create_call_kwargs(AzureVideoConfig()))
|
||||
result = BaseLLMHTTPHandler().video_generation_handler(
|
||||
client=client, **_video_create_call_kwargs(AzureVideoConfig())
|
||||
)
|
||||
|
||||
assert captured["content_type"].startswith("multipart/form-data")
|
||||
assert _multipart_text_fields(captured["content_type"], captured["body"]) == {
|
||||
|
|
@ -3918,7 +3926,9 @@ def test_video_generation_json_provider_keeps_json_body():
|
|||
captured = {}
|
||||
client = HTTPHandler(client=httpx.Client(transport=httpx.MockTransport(_capture_video_create_request(captured))))
|
||||
|
||||
result = BaseLLMHTTPHandler().video_generation_handler(client=client, **_video_create_call_kwargs(_JSONBodyVideoConfig()))
|
||||
result = BaseLLMHTTPHandler().video_generation_handler(
|
||||
client=client, **_video_create_call_kwargs(_JSONBodyVideoConfig())
|
||||
)
|
||||
|
||||
assert captured["content_type"] == "application/json"
|
||||
assert json.loads(captured["body"]) == {"model": "sora-2", "prompt": "a cat surfing", "seconds": "4"}
|
||||
|
|
@ -3948,6 +3958,7 @@ def test_video_generation_with_input_reference_keeps_file_multipart():
|
|||
AZURE_AI_BASE = "https://myfoundry.services.ai.azure.com"
|
||||
AZURE_AI_CHAT_COMPLETIONS_URL = f"{AZURE_AI_BASE}/models/chat/completions"
|
||||
|
||||
|
||||
def _a_tool_with_an_unsupported_field() -> dict:
|
||||
return {
|
||||
"type": "function",
|
||||
|
|
@ -3955,14 +3966,13 @@ def _a_tool_with_an_unsupported_field() -> dict:
|
|||
"strict": True,
|
||||
}
|
||||
|
||||
|
||||
A_COMPLETION = {
|
||||
"id": "chatcmpl-1",
|
||||
"object": "chat.completion",
|
||||
"created": 1,
|
||||
"model": "grok-3",
|
||||
"choices": [
|
||||
{"index": 0, "message": {"role": "assistant", "content": "sent"}, "finish_reason": "stop"}
|
||||
],
|
||||
"choices": [{"index": 0, "message": {"role": "assistant", "content": "sent"}, "finish_reason": "stop"}],
|
||||
"usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
|
||||
}
|
||||
|
||||
|
|
@ -4006,9 +4016,7 @@ def _call_azure_ai(recorder: _RecordedAzureAI, **overrides):
|
|||
|
||||
|
||||
def test_a_tool_field_the_provider_rejects_is_dropped_and_the_call_retried():
|
||||
recorder = _RecordedAzureAI(
|
||||
[_rejection(TOOL_LEVEL_REJECTION), httpx.Response(200, json=A_COMPLETION)]
|
||||
)
|
||||
recorder = _RecordedAzureAI([_rejection(TOOL_LEVEL_REJECTION), httpx.Response(200, json=A_COMPLETION)])
|
||||
|
||||
response = _call_azure_ai(recorder)
|
||||
|
||||
|
|
@ -4019,9 +4027,7 @@ def test_a_tool_field_the_provider_rejects_is_dropped_and_the_call_retried():
|
|||
|
||||
|
||||
def test_the_retry_changes_only_the_field_the_provider_named():
|
||||
recorder = _RecordedAzureAI(
|
||||
[_rejection(TOOL_LEVEL_REJECTION), httpx.Response(200, json=A_COMPLETION)]
|
||||
)
|
||||
recorder = _RecordedAzureAI([_rejection(TOOL_LEVEL_REJECTION), httpx.Response(200, json=A_COMPLETION)])
|
||||
|
||||
_call_azure_ai(recorder)
|
||||
|
||||
|
|
@ -4060,9 +4066,7 @@ def test_an_extra_input_outside_a_tool_is_not_retried_unless_dropping_params_was
|
|||
|
||||
|
||||
def test_an_extra_input_outside_a_tool_is_retried_when_dropping_params_was_asked_for():
|
||||
recorder = _RecordedAzureAI(
|
||||
[_rejection(UNRELATED_REJECTION), httpx.Response(200, json=A_COMPLETION)]
|
||||
)
|
||||
recorder = _RecordedAzureAI([_rejection(UNRELATED_REJECTION), httpx.Response(200, json=A_COMPLETION)])
|
||||
|
||||
response = _call_azure_ai(recorder, drop_params=True)
|
||||
|
||||
|
|
@ -4076,9 +4080,7 @@ async def test_a_tool_field_the_provider_rejects_is_dropped_and_retried_on_the_a
|
|||
):
|
||||
import respx
|
||||
|
||||
recorder = _RecordedAzureAI(
|
||||
[_rejection(TOOL_LEVEL_REJECTION), httpx.Response(200, json=A_COMPLETION)]
|
||||
)
|
||||
recorder = _RecordedAzureAI([_rejection(TOOL_LEVEL_REJECTION), httpx.Response(200, json=A_COMPLETION)])
|
||||
|
||||
with respx.mock(assert_all_called=True) as router:
|
||||
router.post(AZURE_AI_CHAT_COMPLETIONS_URL).mock(side_effect=recorder)
|
||||
|
|
@ -4219,7 +4221,11 @@ async def test_create_batch_says_which_setting_is_missing_when_the_provider_reso
|
|||
|
||||
with pytest.raises(ValueError, match="api_base is required for create_batch"):
|
||||
await BaseLLMHTTPHandler().create_batch(
|
||||
create_batch_data={"input_file_id": "file_1", "endpoint": "/v1/chat/completions", "completion_window": "24h"},
|
||||
create_batch_data={
|
||||
"input_file_id": "file_1",
|
||||
"endpoint": "/v1/chat/completions",
|
||||
"completion_window": "24h",
|
||||
},
|
||||
litellm_params={},
|
||||
provider_config=provider_config,
|
||||
headers={},
|
||||
|
|
@ -4400,7 +4406,9 @@ def _start_async_completion(config, logging_obj=None):
|
|||
custom_llm_provider="openai",
|
||||
model_response=ModelResponse(),
|
||||
encoding=None,
|
||||
logging_obj=logging_obj if logging_obj is not None else Mock(dynamic_success_callbacks=None, model_call_details={}),
|
||||
logging_obj=logging_obj
|
||||
if logging_obj is not None
|
||||
else Mock(dynamic_success_callbacks=None, model_call_details={}),
|
||||
optional_params={},
|
||||
timeout=10.0,
|
||||
litellm_params={},
|
||||
|
|
@ -4788,7 +4796,9 @@ async def test_async_realtime_bridges_a_transcription_session_through_the_provid
|
|||
logging_obj.dispatch_failure_handlers = AsyncMock()
|
||||
handler = BaseLLMHTTPHandler()
|
||||
|
||||
with patch.object(handler, "_open_realtime_backend_ws", AsyncMock(side_effect=AssertionError("dialed a websocket"))) as dial:
|
||||
with patch.object(
|
||||
handler, "_open_realtime_backend_ws", AsyncMock(side_effect=AssertionError("dialed a websocket"))
|
||||
) as dial:
|
||||
await handler.async_realtime(
|
||||
model="chirp_3",
|
||||
websocket=client_ws,
|
||||
|
|
@ -5599,7 +5609,9 @@ async def test_messages_opencode_session_header(
|
|||
model="anthropic/claude-haiku-5-5",
|
||||
messages=[{"role": "user", "content": "hello"}],
|
||||
max_tokens=128000,
|
||||
api_base=None if environment_base and api_base == "https://opencode.ai/inference/go/anthropic" else api_base,
|
||||
api_base=None
|
||||
if environment_base and api_base == "https://opencode.ai/inference/go/anthropic"
|
||||
else api_base,
|
||||
api_key="test-key",
|
||||
stream=stream,
|
||||
litellm_session_id="conversation-123",
|
||||
|
|
@ -5660,17 +5672,27 @@ def test_vector_store_retrieve_handler_sends_id_before_azure_api_version_query()
|
|||
@pytest.mark.parametrize("is_async", (False, True))
|
||||
@pytest.mark.parametrize("provider", ("openai", "azure"))
|
||||
async def test_non_chatgpt_responses_preserves_caller_headers_after_validation(
|
||||
is_async: bool, provider: str, respx_mock: respx.MockRouter,
|
||||
is_async: bool,
|
||||
provider: str,
|
||||
respx_mock: respx.MockRouter,
|
||||
) -> None:
|
||||
route: Final = respx_mock.post(url__regex=r"https://responses\.example\.com/.*").respond(
|
||||
200,
|
||||
json={
|
||||
"id": "resp_headers", "object": "response", "created_at": 1,
|
||||
"model": "gpt-6-luna", "status": "completed", "output": [],
|
||||
"parallel_tool_calls": False, "tool_choice": "auto", "tools": [],
|
||||
"id": "resp_headers",
|
||||
"object": "response",
|
||||
"created_at": 1,
|
||||
"model": "gpt-6-luna",
|
||||
"status": "completed",
|
||||
"output": [],
|
||||
"parallel_tool_calls": False,
|
||||
"tool_choice": "auto",
|
||||
"tools": [],
|
||||
},
|
||||
)
|
||||
client: Final = AsyncHTTPHandler(transport=httpx.AsyncHTTPTransport()) if is_async else HTTPHandler(client=httpx.Client())
|
||||
client: Final = (
|
||||
AsyncHTTPHandler(transport=httpx.AsyncHTTPTransport()) if is_async else HTTPHandler(client=httpx.Client())
|
||||
)
|
||||
kwargs: Final = {
|
||||
"model": f"{provider}/gpt-6-luna",
|
||||
"input": "hello",
|
||||
|
|
@ -5695,3 +5717,49 @@ async def test_non_chatgpt_responses_preserves_caller_headers_after_validation(
|
|||
await client.close()
|
||||
else:
|
||||
client.client.close()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_async_anthropic_messages_handler_filters_betas_by_the_azure_ai_row_on_a_foundry_api_base(monkeypatch):
|
||||
from litellm import anthropic_beta_headers_manager
|
||||
from litellm.llms.anthropic.messages.native.transformation import AnthropicMessagesConfig
|
||||
|
||||
monkeypatch.setenv("LITELLM_LOCAL_ANTHROPIC_BETA_HEADERS", "True")
|
||||
anthropic_beta_headers_manager._BETA_HEADERS_CONFIG = None
|
||||
foundry_api_base = "https://my-resource.services.ai.azure.com/anthropic"
|
||||
upstream_response = httpx.Response(
|
||||
200,
|
||||
json={
|
||||
"id": "msg_123",
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"content": [{"type": "text", "text": "Hello!"}],
|
||||
"model": "claude-sonnet-4-6",
|
||||
"stop_reason": "end_turn",
|
||||
"usage": {"input_tokens": 1, "output_tokens": 1},
|
||||
},
|
||||
request=httpx.Request("POST", f"{foundry_api_base}/v1/messages"),
|
||||
)
|
||||
mock_client = AsyncMock(spec=AsyncHTTPHandler)
|
||||
mock_client.post = AsyncMock(return_value=upstream_response)
|
||||
mock_logging_obj = Mock()
|
||||
mock_logging_obj.model_call_details = {}
|
||||
mock_logging_obj.stream = False
|
||||
mock_logging_obj.dynamic_success_callbacks = None
|
||||
|
||||
await BaseLLMHTTPHandler().async_anthropic_messages_handler(
|
||||
model="claude-sonnet-4-6",
|
||||
messages=[{"role": "user", "content": "Hello"}],
|
||||
anthropic_messages_provider_config=AnthropicMessagesConfig(),
|
||||
anthropic_messages_optional_request_params={"max_tokens": 8},
|
||||
custom_llm_provider="anthropic",
|
||||
litellm_params=GenericLiteLLMParams(api_base=foundry_api_base),
|
||||
logging_obj=mock_logging_obj,
|
||||
api_key="sk-test",
|
||||
api_base=foundry_api_base,
|
||||
client=mock_client,
|
||||
kwargs={"extra_headers": {"anthropic-beta": "advisor-tool-2026-03-01,thinking-binding-controls-2026-08-01"}},
|
||||
)
|
||||
|
||||
sent_headers = mock_client.post.call_args.kwargs["headers"]
|
||||
assert sent_headers["anthropic-beta"] == "thinking-binding-controls-2026-08-01"
|
||||
|
|
|
|||
108
tests/unit/test_anthropic_beta_headers_deployment_rows.py
Normal file
108
tests/unit/test_anthropic_beta_headers_deployment_rows.py
Normal file
|
|
@ -0,0 +1,108 @@
|
|||
"""The beta allowlist row is picked per deployment: an ``anthropic`` deployment on a Foundry host gets ``azure_ai``."""
|
||||
|
||||
import json
|
||||
import os
|
||||
from typing import Final
|
||||
|
||||
import pytest
|
||||
|
||||
import litellm
|
||||
from litellm import anthropic_beta_headers_manager
|
||||
from litellm.anthropic_beta_headers_manager import (
|
||||
is_foundry_api_base,
|
||||
resolve_beta_provider,
|
||||
update_headers_with_filtered_beta,
|
||||
update_request_with_filtered_beta,
|
||||
)
|
||||
|
||||
FOUNDRY_API_BASE: Final = "https://my-resource.services.ai.azure.com/anthropic"
|
||||
DIRECT_API_BASE: Final = "https://api.anthropic.com"
|
||||
DIRECT_ONLY_BETA: Final = "advisor-tool-2026-03-01"
|
||||
PRESERVED_THINKING_BETAS: Final = (
|
||||
"thinking-binding-controls-2026-08-01",
|
||||
"mid-conversation-system-clear-at-2026-08-21",
|
||||
"mid-conversation-tool-changes-2026-07-01",
|
||||
"mid-conversation-output-config-2026-07-01",
|
||||
"thinking-display-updates-2026-08-18",
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _bundled_config(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
monkeypatch.setenv("LITELLM_LOCAL_ANTHROPIC_BETA_HEADERS", "True")
|
||||
anthropic_beta_headers_manager._BETA_HEADERS_CONFIG = None
|
||||
|
||||
|
||||
def _bundled_rows() -> dict:
|
||||
with open(os.path.join(os.path.dirname(litellm.__file__), "anthropic_beta_headers_config.json")) as f:
|
||||
return json.load(f)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("api_base", "expected"),
|
||||
(
|
||||
(FOUNDRY_API_BASE, True),
|
||||
("https://my-resource.openai.azure.com", True),
|
||||
("my-resource.services.ai.azure.com/anthropic", True),
|
||||
(DIRECT_API_BASE, False),
|
||||
("https://services.ai.azure.com.example.com", False),
|
||||
("", False),
|
||||
(None, False),
|
||||
),
|
||||
)
|
||||
def test_is_foundry_api_base_matches_only_foundry_hosts(api_base: str | None, expected: bool) -> None:
|
||||
assert is_foundry_api_base(api_base) is expected
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("provider", "api_base", "expected"),
|
||||
(
|
||||
("anthropic", FOUNDRY_API_BASE, "azure_ai"),
|
||||
("anthropic", DIRECT_API_BASE, "anthropic"),
|
||||
("anthropic", None, "anthropic"),
|
||||
("vertex_ai", FOUNDRY_API_BASE, "vertex_ai"),
|
||||
("bedrock_converse", None, "bedrock_converse"),
|
||||
),
|
||||
)
|
||||
def test_resolve_beta_provider_picks_the_row_per_deployment(provider: str, api_base: str | None, expected: str) -> None:
|
||||
assert resolve_beta_provider(provider, api_base) == expected
|
||||
|
||||
|
||||
def test_foundry_deployment_headers_follow_the_azure_ai_row() -> None:
|
||||
headers: Final = {"anthropic-beta": f"{DIRECT_ONLY_BETA},thinking-binding-controls-2026-08-01"}
|
||||
result: Final = update_headers_with_filtered_beta(headers=headers, provider="anthropic", api_base=FOUNDRY_API_BASE)
|
||||
assert result == {"anthropic-beta": "thinking-binding-controls-2026-08-01"}
|
||||
|
||||
|
||||
def test_direct_deployment_headers_keep_every_anthropic_row_beta() -> None:
|
||||
headers: Final = {"anthropic-beta": f"{DIRECT_ONLY_BETA},thinking-binding-controls-2026-08-01"}
|
||||
result: Final = update_headers_with_filtered_beta(headers=headers, provider="anthropic", api_base=DIRECT_API_BASE)
|
||||
assert result == {"anthropic-beta": f"{DIRECT_ONLY_BETA},thinking-binding-controls-2026-08-01"}
|
||||
|
||||
|
||||
def test_foundry_deployment_request_filters_header_and_body_betas_together() -> None:
|
||||
headers, data = update_request_with_filtered_beta(
|
||||
headers={"anthropic-beta": DIRECT_ONLY_BETA},
|
||||
request_data={"anthropic_beta": [DIRECT_ONLY_BETA, "thinking-binding-controls-2026-08-01"], "max_tokens": 8},
|
||||
provider="anthropic",
|
||||
api_base=FOUNDRY_API_BASE,
|
||||
)
|
||||
assert headers == {}
|
||||
assert data == {"anthropic_beta": ["thinking-binding-controls-2026-08-01"], "max_tokens": 8}
|
||||
|
||||
|
||||
@pytest.mark.parametrize("provider", ("anthropic", "azure_ai", "vertex_ai"))
|
||||
@pytest.mark.parametrize("beta", PRESERVED_THINKING_BETAS)
|
||||
def test_live_verified_platforms_forward_every_preserved_thinking_beta(provider: str, beta: str) -> None:
|
||||
assert _bundled_rows()[provider][beta] == beta
|
||||
|
||||
|
||||
@pytest.mark.parametrize("provider", ("bedrock", "bedrock_converse", "bedrock_mantle", "databricks"))
|
||||
def test_unverified_platforms_hold_back_the_system_clear_beta(provider: str) -> None:
|
||||
assert _bundled_rows()[provider]["mid-conversation-system-clear-at-2026-08-21"] is None
|
||||
assert (
|
||||
update_headers_with_filtered_beta(
|
||||
headers={"anthropic-beta": "mid-conversation-system-clear-at-2026-08-21"}, provider=provider
|
||||
)
|
||||
== {}
|
||||
)
|
||||
Loading…
Add table
Reference in a new issue