Class ToolCallData

src/mcp_cli/chat/models.py:72–120

Tool call data structure (OpenAI format).

class ToolCallData(BaseModel):
    """Tool call data structure (OpenAI format)."""

    id: str = Field(description="Tool call ID")
    type: str = Field(default="function", description="Type of tool call")
    function: FunctionCallData = Field(description="Function call data")
    index: int = Field(default=0, description="Tool call index in batch")

    model_config = {"frozen": False}

    def to_dict(self) -> dict[str, Any]:
        """Convert to dict for API."""
        return {
            ToolCallField.ID: self.id,
            ToolCallField.TYPE: self.type,
            ToolCallField.FUNCTION: {
                ToolCallField.NAME: self.function.name,
                ToolCallField.ARGUMENTS: self.function.arguments,
            },
        }

    @classmethod
    def from_dict(cls, data: dict[str, Any]) -> "ToolCallData":
        """Create from dict."""
        return cls(
            id=data.get(ToolCallField.ID, ""),
            type=data.get(ToolCallField.TYPE, "function"),
            index=data.get(ToolCallField.INDEX, 0),
            function=FunctionCallData(
                name=data.get(ToolCallField.FUNCTION, {}).get(ToolCallField.NAME, ""),
                arguments=data.get(ToolCallField.FUNCTION, {}).get(
                    ToolCallField.ARGUMENTS, ""
                ),
            ),
        )

    def merge_chunk(self, chunk: "ToolCallData") -> None:
        """Merge data from a streaming chunk into this tool call.

        Args:
            chunk: New chunk data to merge
        """
        # Update function name if provided
        if chunk.function.name:
            self.function.name = chunk.function.name

        # Accumulate arguments (concatenate JSON strings)
        if chunk.function.arguments:
            self.function.arguments += chunk.function.arguments


class HistoryMessage(BaseModel):