mirror of
https://github.com/BerriAI/litellm.git
synced 2026-09-08 22:21:35 +00:00
chore: format
This commit is contained in:
Yuta Saito
parent
caf5f7f8ae
commit
72cbc295e5
5 changed files with 110 additions and 82 deletions
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@ -807,9 +807,9 @@ if MCP_AVAILABLE:
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"user_api_key"
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] = user_api_key
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user_identifier = getattr(user_api_key_auth, "end_user_id", None) or getattr(
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user_api_key_auth, "user_id", None
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)
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user_identifier = getattr(
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user_api_key_auth, "end_user_id", None
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) or getattr(user_api_key_auth, "user_id", None)
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if user_identifier:
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list_tools_request_data["user"] = user_identifier
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@ -838,7 +838,9 @@ if MCP_AVAILABLE:
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# Decide whether to add prefix based on number of allowed servers
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add_prefix = not (len(allowed_mcp_servers) == 1)
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async def _fetch_and_filter_server_tools(server: MCPServer) -> List[MCPTool]:
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async def _fetch_and_filter_server_tools(
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server: MCPServer,
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) -> List[MCPTool]:
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"""Fetch and filter tools from a single server with error handling."""
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if server is None:
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return []
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@ -1517,11 +1519,9 @@ if MCP_AVAILABLE:
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**kwargs,
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)
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except Exception as e:
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traceback_str = traceback.format_exc(
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limit=MAXIMUM_TRACEBACK_LINES_TO_LOG
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)
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traceback_str = traceback.format_exc(limit=MAXIMUM_TRACEBACK_LINES_TO_LOG)
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from litellm.proxy.proxy_server import proxy_logging_obj
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if proxy_logging_obj and user_api_key_auth:
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await proxy_logging_obj.post_call_failure_hook(
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request_data=kwargs,
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@ -169,7 +169,9 @@ async def aresponses_api_with_mcp(
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# Process MCP tools through the complete pipeline (fetch + filter + deduplicate + transform)
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# Extract user_api_key_auth from litellm_metadata (where it's added by add_user_api_key_auth_to_request_metadata)
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user_api_key_auth = kwargs.get("user_api_key_auth") or kwargs.get("litellm_metadata", {}).get("user_api_key_auth")
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user_api_key_auth = kwargs.get("user_api_key_auth") or kwargs.get(
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"litellm_metadata", {}
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).get("user_api_key_auth")
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# Get original MCP tools (for events) and OpenAI tools (for LLM) by reusing existing methods
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(
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@ -280,7 +282,7 @@ async def aresponses_api_with_mcp(
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user_api_key_auth = kwargs.get("litellm_metadata", {}).get(
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"user_api_key_auth"
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)
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# Extract MCP auth headers from the request to pass to MCP server
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secret_fields: Optional[Dict[str, Any]] = kwargs.get("secret_fields")
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(
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@ -292,7 +294,7 @@ async def aresponses_api_with_mcp(
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secret_fields=secret_fields,
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tools=tools,
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)
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tool_results = await LiteLLM_Proxy_MCP_Handler._execute_tool_calls(
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tool_server_map=tool_server_map,
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tool_calls=tool_calls,
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@ -590,9 +592,12 @@ def responses(
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#########################################################
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# Update input with provider-specific file IDs if managed files are used
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#########################################################
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input = cast(Union[str, ResponseInputParam], update_responses_input_with_model_file_ids(input=input))
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input = cast(
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Union[str, ResponseInputParam],
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update_responses_input_with_model_file_ids(input=input),
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)
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local_vars["input"] = input
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#########################################################
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# Native MCP Responses API
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#########################################################
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@ -627,11 +632,11 @@ def responses(
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)
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# get provider config
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responses_api_provider_config: Optional[BaseResponsesAPIConfig] = (
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ProviderConfigManager.get_provider_responses_api_config(
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model=model,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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responses_api_provider_config: Optional[
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BaseResponsesAPIConfig
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] = ProviderConfigManager.get_provider_responses_api_config(
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model=model,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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local_vars.update(kwargs)
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@ -826,11 +831,11 @@ def delete_responses(
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raise ValueError("custom_llm_provider is required but passed as None")
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# get provider config
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responses_api_provider_config: Optional[BaseResponsesAPIConfig] = (
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ProviderConfigManager.get_provider_responses_api_config(
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model=None,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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responses_api_provider_config: Optional[
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BaseResponsesAPIConfig
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] = ProviderConfigManager.get_provider_responses_api_config(
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model=None,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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if responses_api_provider_config is None:
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@ -1006,11 +1011,11 @@ def get_responses(
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raise ValueError("custom_llm_provider is required but passed as None")
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# get provider config
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responses_api_provider_config: Optional[BaseResponsesAPIConfig] = (
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ProviderConfigManager.get_provider_responses_api_config(
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model=None,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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responses_api_provider_config: Optional[
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BaseResponsesAPIConfig
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] = ProviderConfigManager.get_provider_responses_api_config(
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model=None,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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if responses_api_provider_config is None:
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@ -1163,11 +1168,11 @@ def list_input_items(
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if custom_llm_provider is None:
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raise ValueError("custom_llm_provider is required but passed as None")
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responses_api_provider_config: Optional[BaseResponsesAPIConfig] = (
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ProviderConfigManager.get_provider_responses_api_config(
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model=None,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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responses_api_provider_config: Optional[
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BaseResponsesAPIConfig
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] = ProviderConfigManager.get_provider_responses_api_config(
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model=None,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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if responses_api_provider_config is None:
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@ -1321,11 +1326,11 @@ def cancel_responses(
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raise ValueError("custom_llm_provider is required but passed as None")
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# get provider config
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responses_api_provider_config: Optional[BaseResponsesAPIConfig] = (
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ProviderConfigManager.get_provider_responses_api_config(
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model=None,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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responses_api_provider_config: Optional[
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BaseResponsesAPIConfig
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] = ProviderConfigManager.get_provider_responses_api_config(
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model=None,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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if responses_api_provider_config is None:
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@ -1503,11 +1508,11 @@ def compact_responses(
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raise ValueError("custom_llm_provider is required but passed as None")
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# get provider config
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responses_api_provider_config: Optional[BaseResponsesAPIConfig] = (
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ProviderConfigManager.get_provider_responses_api_config(
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model=model,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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responses_api_provider_config: Optional[
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BaseResponsesAPIConfig
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] = ProviderConfigManager.get_provider_responses_api_config(
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model=model,
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provider=litellm.LlmProviders(custom_llm_provider),
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)
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if responses_api_provider_config is None:
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@ -19,7 +19,12 @@ from litellm.proxy._experimental.mcp_server.utils import split_server_prefix_fro
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from litellm.responses.main import aresponses
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from litellm.responses.streaming_iterator import BaseResponsesAPIStreamingIterator
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from litellm.types.llms.openai import ResponsesAPIResponse
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from litellm.types.utils import CallTypes, Choices, ModelResponse, StandardLoggingMCPToolCall
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from litellm.types.utils import (
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CallTypes,
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Choices,
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ModelResponse,
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StandardLoggingMCPToolCall,
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)
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from litellm.utils import Rules, function_setup
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if TYPE_CHECKING:
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@ -564,9 +569,9 @@ class LiteLLM_Proxy_MCP_Handler:
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if user_api_key:
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logging_request_data["metadata"]["user_api_key"] = user_api_key
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user_identifier = getattr(user_api_key_auth, "end_user_id", None) or getattr(
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user_api_key_auth, "user_id", None
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)
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user_identifier = getattr(
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user_api_key_auth, "end_user_id", None
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) or getattr(user_api_key_auth, "user_id", None)
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if user_identifier:
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logging_request_data["user"] = user_identifier
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@ -620,7 +625,9 @@ class LiteLLM_Proxy_MCP_Handler:
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standard_logging_mcp_tool_call["mcp_server_logo_url"] = logo_url
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cost_info = mcp_info.get("mcp_server_cost_info")
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if cost_info:
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standard_logging_mcp_tool_call["mcp_server_cost_info"] = cost_info
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standard_logging_mcp_tool_call[
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"mcp_server_cost_info"
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] = cost_info
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if litellm_logging_obj:
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litellm_logging_obj.model_call_details[
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@ -895,9 +902,7 @@ class LiteLLM_Proxy_MCP_Handler:
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return
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try:
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traceback_str = traceback.format_exc(
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limit=MAXIMUM_TRACEBACK_LINES_TO_LOG
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)
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traceback_str = traceback.format_exc(limit=MAXIMUM_TRACEBACK_LINES_TO_LOG)
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await proxy_logging_obj.post_call_failure_hook(
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request_data=request_data,
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original_exception=error,
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@ -948,7 +953,8 @@ class LiteLLM_Proxy_MCP_Handler:
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mcp_events=mcp_discovery_events, # Pre-generated MCP discovery events
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tool_server_map=tool_server_map,
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mcp_tools_with_litellm_proxy=mcp_tools_with_litellm_proxy,
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user_api_key_auth=kwargs.get("user_api_key_auth") or kwargs.get("litellm_metadata", {}).get("user_api_key_auth"),
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user_api_key_auth=kwargs.get("user_api_key_auth")
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or kwargs.get("litellm_metadata", {}).get("user_api_key_auth"),
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original_request_params=request_params,
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)
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@ -273,9 +273,9 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
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self.finished = False
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# Event queues and generation flags
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self.mcp_discovery_events: List[ResponsesAPIStreamingResponse] = (
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mcp_events # Pre-generated MCP discovery events
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)
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self.mcp_discovery_events: List[
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ResponsesAPIStreamingResponse
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] = mcp_events # Pre-generated MCP discovery events
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self.tool_execution_events: List[ResponsesAPIStreamingResponse] = []
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self.mcp_discovery_generated = True # Events are already generated
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self.mcp_events = (
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@ -284,9 +284,9 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
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self.tool_server_map = tool_server_map
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# Iterator references
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self.base_iterator: Optional[Union[Any, ResponsesAPIResponse]] = (
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base_iterator # Will be created when needed
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)
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self.base_iterator: Optional[
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Union[Any, ResponsesAPIResponse]
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] = base_iterator # Will be created when needed
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self.follow_up_iterator: Optional[Any] = None
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# Response collection for tool execution
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@ -305,7 +305,7 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
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# Mark as async iterator
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self.is_async = True
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def _extract_mcp_headers_from_params(self) -> None:
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"""Extract MCP headers from original request params to pass to tool calls"""
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from typing import Dict, Optional
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@ -313,25 +313,31 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
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from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import (
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MCPRequestHandler,
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)
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# Extract headers from secret_fields in original_request_params
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raw_headers_from_request: Optional[Dict[str, str]] = None
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secret_fields = self.original_request_params.get("secret_fields")
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if secret_fields and isinstance(secret_fields, dict):
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raw_headers_from_request = secret_fields.get("raw_headers")
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# Extract MCP-specific headers
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self.mcp_auth_header: Optional[str] = None
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self.mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None
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self.oauth2_headers: Optional[Dict[str, str]] = None
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self.raw_headers: Optional[Dict[str, str]] = raw_headers_from_request
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if raw_headers_from_request:
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headers_obj = Headers(raw_headers_from_request)
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self.mcp_auth_header = MCPRequestHandler._get_mcp_auth_header_from_headers(headers_obj)
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self.mcp_server_auth_headers = MCPRequestHandler._get_mcp_server_auth_headers_from_headers(headers_obj)
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self.oauth2_headers = MCPRequestHandler._get_oauth2_headers_from_headers(headers_obj)
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self.mcp_auth_header = MCPRequestHandler._get_mcp_auth_header_from_headers(
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headers_obj
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)
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self.mcp_server_auth_headers = (
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MCPRequestHandler._get_mcp_server_auth_headers_from_headers(headers_obj)
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)
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self.oauth2_headers = MCPRequestHandler._get_oauth2_headers_from_headers(
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headers_obj
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)
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# Also check if headers are provided in tools array (from request body)
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tools = self.original_request_params.get("tools")
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if tools:
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@ -341,17 +347,26 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
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if tool_headers and isinstance(tool_headers, dict):
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# Merge tool headers into mcp_server_auth_headers
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headers_obj_from_tool = Headers(tool_headers)
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tool_mcp_server_auth_headers = MCPRequestHandler._get_mcp_server_auth_headers_from_headers(headers_obj_from_tool)
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tool_mcp_server_auth_headers = (
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MCPRequestHandler._get_mcp_server_auth_headers_from_headers(
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headers_obj_from_tool
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)
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)
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if tool_mcp_server_auth_headers:
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if self.mcp_server_auth_headers is None:
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self.mcp_server_auth_headers = {}
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# Merge the headers from tool into existing headers
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for server_alias, headers_dict in tool_mcp_server_auth_headers.items():
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for (
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server_alias,
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headers_dict,
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) in tool_mcp_server_auth_headers.items():
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if server_alias not in self.mcp_server_auth_headers:
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self.mcp_server_auth_headers[server_alias] = {}
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self.mcp_server_auth_headers[server_alias].update(headers_dict)
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self.mcp_server_auth_headers[server_alias].update(
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headers_dict
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)
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# Also merge raw headers
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if self.raw_headers is None:
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self.raw_headers = {}
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@ -489,9 +504,9 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
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# Use the pre-fetched all_tools from original_request_params (no re-processing needed)
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params_for_llm = {}
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for key, value in params.items():
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params_for_llm[key] = (
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value # Copy all params as-is since tools are already processed
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)
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params_for_llm[
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key
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] = value # Copy all params as-is since tools are already processed
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tools_count = (
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len(params_for_llm.get("tools", []))
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@ -545,9 +560,11 @@ class MCPEnhancedStreamingIterator(BaseResponsesAPIStreamingIterator):
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return
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for tool_call in tool_calls:
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tool_name, tool_arguments, tool_call_id = (
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LiteLLM_Proxy_MCP_Handler._extract_tool_call_details(tool_call)
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)
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(
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tool_name,
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tool_arguments,
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tool_call_id,
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) = LiteLLM_Proxy_MCP_Handler._extract_tool_call_details(tool_call)
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if tool_name and tool_call_id:
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# Create MCP call events for this tool execution
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call_events = create_mcp_call_events(
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|
|
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@ -63,11 +63,11 @@ def _generate_id(): # private helper function
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return "chatcmpl-" + str(uuid.uuid4())
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class SafeAttributeModel:
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"""
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A base model that provides safe attribute access.
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"""
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def __delattr__(self, name):
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try:
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super().__delattr__(name)
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@ -125,13 +125,14 @@ class SearchContextCostPerQuery(TypedDict, total=False):
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class AgenticLoopParams(TypedDict, total=False):
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"""
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Parameters passed to agentic loop hooks (e.g., WebSearch interception).
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Stored in logging_obj.model_call_details["agentic_loop_params"] to provide
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agentic hooks with the original request context needed for follow-up calls.
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"""
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model: str
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"""The model string with provider prefix (e.g., 'bedrock/invoke/...')"""
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custom_llm_provider: str
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"""The LLM provider name (e.g., 'bedrock', 'anthropic')"""
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|
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@ -1345,8 +1346,7 @@ class CacheCreationTokenDetails(BaseModel):
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class PromptTokensDetailsWrapper(
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SafeAttributeModel,
|
||||
PromptTokensDetails
|
||||
SafeAttributeModel, PromptTokensDetails
|
||||
): # extends with image generation fields (text_tokens, image_tokens)
|
||||
text_tokens: Optional[int] = None
|
||||
"""Text tokens sent to the model."""
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue