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feat(advisor): call strip_advisor_blocks in chat/completions transform_request

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Ishaan Jaffer 2026-04-10 13:15:45 -07:00
parent 3a89465d18
commit ab8d92c14c
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1 changed files with 34 additions and 21 deletions
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55
litellm/llms/anthropic/chat/transformation.py
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@ -75,7 +75,12 @@ from litellm.utils import (
token_counter,
)
from ..common_utils import AnthropicError, AnthropicModelInfo, process_anthropic_headers
from ..common_utils import (
AnthropicError,
AnthropicModelInfo,
process_anthropic_headers,
strip_advisor_blocks_from_messages,
)
if TYPE_CHECKING:
from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
@ -981,11 +986,11 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
if mcp_servers:
optional_params["mcp_servers"] = mcp_servers
elif param == "tool_choice" or param == "parallel_tool_calls":
_tool_choice: Optional[
AnthropicMessagesToolChoice
] = self._map_tool_choice(
tool_choice=non_default_params.get("tool_choice"),
parallel_tool_use=non_default_params.get("parallel_tool_calls"),
_tool_choice: Optional[AnthropicMessagesToolChoice] = (
self._map_tool_choice(
tool_choice=non_default_params.get("tool_choice"),
parallel_tool_use=non_default_params.get("parallel_tool_calls"),
)
)
if _tool_choice is not None:
@ -1083,9 +1088,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
self.map_openai_context_management_to_anthropic(value)
)
if anthropic_context_management is not None:
optional_params[
"context_management"
] = anthropic_context_management
optional_params["context_management"] = (
anthropic_context_management
)
elif param == "speed" and isinstance(value, str):
# Pass through Anthropic-specific speed parameter for fast mode
optional_params["speed"] = value
@ -1159,9 +1164,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
text=system_message_block["content"],
)
if "cache_control" in system_message_block:
anthropic_system_message_content[
"cache_control"
] = system_message_block["cache_control"]
anthropic_system_message_content["cache_control"] = (
system_message_block["cache_control"]
)
anthropic_system_message_list.append(
anthropic_system_message_content
)
@ -1185,9 +1190,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
)
)
if "cache_control" in _content:
anthropic_system_message_content[
"cache_control"
] = _content["cache_control"]
anthropic_system_message_content["cache_control"] = (
_content["cache_control"]
)
anthropic_system_message_list.append(
anthropic_system_message_content
@ -1413,6 +1418,16 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
message="{}\nReceived Messages={}".format(str(e), messages),
) # don't use verbose_logger.exception, if exception is raised
## Auto-strip advisor blocks from history if advisor tool is absent.
## Prevents Anthropic 400: advisor_tool_result in history requires advisor tool.
_all_tools = optional_params.get("tools") or []
_has_advisor = any(
isinstance(t, dict) and t.get("type") == "advisor_20260301"
for t in _all_tools
)
if not _has_advisor:
anthropic_messages = strip_advisor_blocks_from_messages(anthropic_messages)
## Add code_execution tool if container_upload is in messages
_tools = (
cast(
@ -1500,9 +1515,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
)
return _message
def extract_response_content(
self, completion_response: dict
) -> Tuple[
def extract_response_content(self, completion_response: dict) -> Tuple[
str,
Optional[List[Any]],
Optional[
@ -1796,9 +1809,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
code_interpreter_results = self._build_code_interpreter_results(
tool_results, code_by_id, container_id
)
provider_specific_fields[
"code_interpreter_results"
] = code_interpreter_results
provider_specific_fields["code_interpreter_results"] = (
code_interpreter_results
)
container = completion_response.get("container")
if container is not None: