LLMService

from mango.llm import LLMService

Abstract base class for all LLM providers. Implement this to add any LLM with tool/function calling support.

Interface

class LLMService(ABC):

    @abstractmethod
    def chat(
        self,
        messages: list[Message],
        tools: list[ToolDef],
        system_prompt: str = "",
    ) -> LLMResponse:
        ...

    @abstractmethod
    def get_model_name(self) -> str:
        ...

Data types

Message

@dataclass
class Message:
    role: str           # "user" | "assistant" | "tool"
    content: str | list # text or structured content blocks
    tool_call_id: str | None = None  # required when role="tool"

ToolDef

@dataclass
class ToolDef:
    name: str
    description: str
    params: list[ToolParam]

ToolParam

@dataclass
class ToolParam:
    name: str
    type: str           # "string" | "integer" | "number" | "boolean" | "array" | "object"
    description: str
    required: bool = True
    enum: list | None = None
    items: dict | None = None   # for array types

LLMResponse

@dataclass
class LLMResponse:
    text: str | None
    tool_calls: list[ToolCall]
    model: str
    input_tokens: int
    output_tokens: int

    @property
    def has_tool_calls(self) -> bool:
        return len(self.tool_calls) > 0

ToolCall

@dataclass
class ToolCall:
    tool_name: str
    tool_args: dict
    tool_call_id: str
    thought_signature: str | None = None   # Gemini 3 round-trip requirement

Built-in implementations

Custom implementation

from mango.llm import LLMService, LLMResponse, Message, ToolDef, ToolCall

class MyLlmService(LLMService):

    def chat(
        self,
        messages: list[Message],
        tools: list[ToolDef],
        system_prompt: str = "",
    ) -> LLMResponse:
        # Convert to your provider's format
        # Call API
        # Parse response
        return LLMResponse(
            text="...",
            tool_calls=[ToolCall(...)],
            model="my-model",
            input_tokens=100,
            output_tokens=50,
        )

    def get_model_name(self) -> str:
        return "my-model-v1"