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feat: reuse previous mcp tool listings where possible (#3710)
# What does this PR do? This PR checks whether, if a previous response is linked, there are mcp_list_tools objects that can be reused instead of listing the tools explicitly every time. Closes #3106 ## Test Plan Tested manually. Added unit tests to cover new behaviour. --------- Signed-off-by: Gordon Sim <gsim@redhat.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
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12 changed files with 1835 additions and 983 deletions
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@ -346,6 +346,138 @@ class OpenAIResponseText(BaseModel):
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format: OpenAIResponseTextFormat | None = None
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# Must match type Literals of OpenAIResponseInputToolWebSearch below
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WebSearchToolTypes = ["web_search", "web_search_preview", "web_search_preview_2025_03_11"]
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@json_schema_type
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class OpenAIResponseInputToolWebSearch(BaseModel):
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"""Web search tool configuration for OpenAI response inputs.
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:param type: Web search tool type variant to use
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:param search_context_size: (Optional) Size of search context, must be "low", "medium", or "high"
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"""
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# Must match values of WebSearchToolTypes above
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type: Literal["web_search"] | Literal["web_search_preview"] | Literal["web_search_preview_2025_03_11"] = (
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"web_search"
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)
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# TODO: actually use search_context_size somewhere...
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search_context_size: str | None = Field(default="medium", pattern="^low|medium|high$")
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# TODO: add user_location
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@json_schema_type
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class OpenAIResponseInputToolFunction(BaseModel):
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"""Function tool configuration for OpenAI response inputs.
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:param type: Tool type identifier, always "function"
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:param name: Name of the function that can be called
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:param description: (Optional) Description of what the function does
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:param parameters: (Optional) JSON schema defining the function's parameters
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:param strict: (Optional) Whether to enforce strict parameter validation
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"""
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type: Literal["function"] = "function"
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name: str
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description: str | None = None
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parameters: dict[str, Any] | None
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strict: bool | None = None
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@json_schema_type
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class OpenAIResponseInputToolFileSearch(BaseModel):
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"""File search tool configuration for OpenAI response inputs.
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:param type: Tool type identifier, always "file_search"
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:param vector_store_ids: List of vector store identifiers to search within
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:param filters: (Optional) Additional filters to apply to the search
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:param max_num_results: (Optional) Maximum number of search results to return (1-50)
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:param ranking_options: (Optional) Options for ranking and scoring search results
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"""
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type: Literal["file_search"] = "file_search"
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vector_store_ids: list[str]
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filters: dict[str, Any] | None = None
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max_num_results: int | None = Field(default=10, ge=1, le=50)
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ranking_options: FileSearchRankingOptions | None = None
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class ApprovalFilter(BaseModel):
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"""Filter configuration for MCP tool approval requirements.
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:param always: (Optional) List of tool names that always require approval
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:param never: (Optional) List of tool names that never require approval
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"""
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always: list[str] | None = None
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never: list[str] | None = None
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class AllowedToolsFilter(BaseModel):
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"""Filter configuration for restricting which MCP tools can be used.
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:param tool_names: (Optional) List of specific tool names that are allowed
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"""
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tool_names: list[str] | None = None
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@json_schema_type
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class OpenAIResponseInputToolMCP(BaseModel):
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"""Model Context Protocol (MCP) tool configuration for OpenAI response inputs.
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:param type: Tool type identifier, always "mcp"
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:param server_label: Label to identify this MCP server
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:param server_url: URL endpoint of the MCP server
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:param headers: (Optional) HTTP headers to include when connecting to the server
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:param require_approval: Approval requirement for tool calls ("always", "never", or filter)
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:param allowed_tools: (Optional) Restriction on which tools can be used from this server
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"""
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type: Literal["mcp"] = "mcp"
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server_label: str
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server_url: str
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headers: dict[str, Any] | None = None
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require_approval: Literal["always"] | Literal["never"] | ApprovalFilter = "never"
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allowed_tools: list[str] | AllowedToolsFilter | None = None
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OpenAIResponseInputTool = Annotated[
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OpenAIResponseInputToolWebSearch
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| OpenAIResponseInputToolFileSearch
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| OpenAIResponseInputToolFunction
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| OpenAIResponseInputToolMCP,
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Field(discriminator="type"),
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]
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register_schema(OpenAIResponseInputTool, name="OpenAIResponseInputTool")
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@json_schema_type
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class OpenAIResponseToolMCP(BaseModel):
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"""Model Context Protocol (MCP) tool configuration for OpenAI response object.
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:param type: Tool type identifier, always "mcp"
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:param server_label: Label to identify this MCP server
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:param allowed_tools: (Optional) Restriction on which tools can be used from this server
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"""
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type: Literal["mcp"] = "mcp"
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server_label: str
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allowed_tools: list[str] | AllowedToolsFilter | None = None
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OpenAIResponseTool = Annotated[
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OpenAIResponseInputToolWebSearch
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| OpenAIResponseInputToolFileSearch
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| OpenAIResponseInputToolFunction
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| OpenAIResponseToolMCP, # The only type that differes from that in the inputs is the MCP tool
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Field(discriminator="type"),
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]
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register_schema(OpenAIResponseTool, name="OpenAIResponseTool")
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class OpenAIResponseUsageOutputTokensDetails(BaseModel):
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"""Token details for output tokens in OpenAI response usage.
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@ -398,6 +530,7 @@ class OpenAIResponseObject(BaseModel):
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:param temperature: (Optional) Sampling temperature used for generation
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:param text: Text formatting configuration for the response
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:param top_p: (Optional) Nucleus sampling parameter used for generation
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:param tools: (Optional) An array of tools the model may call while generating a response.
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:param truncation: (Optional) Truncation strategy applied to the response
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:param usage: (Optional) Token usage information for the response
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"""
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@ -416,6 +549,7 @@ class OpenAIResponseObject(BaseModel):
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# before the field was added. New responses will have this set always.
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text: OpenAIResponseText = OpenAIResponseText(format=OpenAIResponseTextFormat(type="text"))
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top_p: float | None = None
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tools: list[OpenAIResponseTool] | None = None
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truncation: str | None = None
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usage: OpenAIResponseUsage | None = None
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@ -878,114 +1012,6 @@ OpenAIResponseInput = Annotated[
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register_schema(OpenAIResponseInput, name="OpenAIResponseInput")
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# Must match type Literals of OpenAIResponseInputToolWebSearch below
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WebSearchToolTypes = ["web_search", "web_search_preview", "web_search_preview_2025_03_11"]
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@json_schema_type
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class OpenAIResponseInputToolWebSearch(BaseModel):
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"""Web search tool configuration for OpenAI response inputs.
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:param type: Web search tool type variant to use
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:param search_context_size: (Optional) Size of search context, must be "low", "medium", or "high"
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"""
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# Must match values of WebSearchToolTypes above
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type: Literal["web_search"] | Literal["web_search_preview"] | Literal["web_search_preview_2025_03_11"] = (
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"web_search"
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)
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# TODO: actually use search_context_size somewhere...
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search_context_size: str | None = Field(default="medium", pattern="^low|medium|high$")
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# TODO: add user_location
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@json_schema_type
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class OpenAIResponseInputToolFunction(BaseModel):
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"""Function tool configuration for OpenAI response inputs.
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:param type: Tool type identifier, always "function"
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:param name: Name of the function that can be called
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:param description: (Optional) Description of what the function does
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:param parameters: (Optional) JSON schema defining the function's parameters
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:param strict: (Optional) Whether to enforce strict parameter validation
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"""
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type: Literal["function"] = "function"
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name: str
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description: str | None = None
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parameters: dict[str, Any] | None
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strict: bool | None = None
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@json_schema_type
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class OpenAIResponseInputToolFileSearch(BaseModel):
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"""File search tool configuration for OpenAI response inputs.
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:param type: Tool type identifier, always "file_search"
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:param vector_store_ids: List of vector store identifiers to search within
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:param filters: (Optional) Additional filters to apply to the search
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:param max_num_results: (Optional) Maximum number of search results to return (1-50)
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:param ranking_options: (Optional) Options for ranking and scoring search results
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"""
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type: Literal["file_search"] = "file_search"
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vector_store_ids: list[str]
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filters: dict[str, Any] | None = None
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max_num_results: int | None = Field(default=10, ge=1, le=50)
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ranking_options: FileSearchRankingOptions | None = None
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class ApprovalFilter(BaseModel):
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"""Filter configuration for MCP tool approval requirements.
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:param always: (Optional) List of tool names that always require approval
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:param never: (Optional) List of tool names that never require approval
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"""
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always: list[str] | None = None
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never: list[str] | None = None
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class AllowedToolsFilter(BaseModel):
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"""Filter configuration for restricting which MCP tools can be used.
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:param tool_names: (Optional) List of specific tool names that are allowed
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"""
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tool_names: list[str] | None = None
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@json_schema_type
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class OpenAIResponseInputToolMCP(BaseModel):
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"""Model Context Protocol (MCP) tool configuration for OpenAI response inputs.
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:param type: Tool type identifier, always "mcp"
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:param server_label: Label to identify this MCP server
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:param server_url: URL endpoint of the MCP server
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:param headers: (Optional) HTTP headers to include when connecting to the server
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:param require_approval: Approval requirement for tool calls ("always", "never", or filter)
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:param allowed_tools: (Optional) Restriction on which tools can be used from this server
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"""
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type: Literal["mcp"] = "mcp"
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server_label: str
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server_url: str
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headers: dict[str, Any] | None = None
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require_approval: Literal["always"] | Literal["never"] | ApprovalFilter = "never"
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allowed_tools: list[str] | AllowedToolsFilter | None = None
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OpenAIResponseInputTool = Annotated[
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OpenAIResponseInputToolWebSearch
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| OpenAIResponseInputToolFileSearch
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| OpenAIResponseInputToolFunction
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| OpenAIResponseInputToolMCP,
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Field(discriminator="type"),
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]
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register_schema(OpenAIResponseInputTool, name="OpenAIResponseInputTool")
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class ListOpenAIResponseInputItem(BaseModel):
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"""List container for OpenAI response input items.
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