ractogateway._models.chat

Strongly-typed input models for chat completion calls.

class ractogateway._models.chat.MessageRole(*values)[source]

Bases: str, Enum

Role of a single message in a conversation.

SYSTEM = 'system'

USER = 'user'

ASSISTANT = 'assistant'

class ractogateway._models.chat.Message(**data)[source]

Bases: BaseModel

A single conversation turn.

Used inside ChatConfig.history to provide prior conversation context to the model for multi-turn conversations.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

role: MessageRole

content: str

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class ractogateway._models.chat.ChatConfig(**data)[source]

Bases: BaseModel

Validated input for every chat / achat / stream / astream call.

Pass a single ChatConfig to any developer-kit method. Every field has a safe default so you only need to supply what you actually need.

Minimal example:

config = ChatConfig(user_message="Explain Python generators.")
response = kit.chat(config)

Vision / multimodal example:

from ractogateway.prompts.engine import RactoFile

config = ChatConfig(
    user_message="Describe this chart.",
    attachments=[RactoFile.from_path("sales_q4.png")],
)

Structured JSON output example:

class Sentiment(BaseModel):
    label: str
    score: float

config = ChatConfig(
    user_message="I love this library!",
    response_model=Sentiment,
)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

user_message: str

prompt: RactoPrompt | None

temperature: float

max_tokens: int

tools: ToolRegistry | None

auto_execute_tools: bool

max_tool_turns: int

response_model: type[BaseModel] | None

max_validation_retries: int

history: list[Message]

attachments: list[RactoFile] | None

chain_of_thought: bool

native_thinking: bool

thinking_budget: int

extra: dict[str, Any]

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].