Module src.models.models

Classes

class ConversationRolesEnum (value, names=None, *, module=None, qualname=None, type=None, start=1)

Conversation roles for the LLM API.

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class ConversationRolesEnum(str, Enum):
    """Conversation roles for the LLM API."""

    SYSTEM = "system"
    USER = "user"
    ASSISTANT = "assistant"
    FUNCTION = "function"

Ancestors

• builtins.str
• enum.Enum

Class variables

var ASSISTANT

var FUNCTION

var SYSTEM

var USER

class ConversationRolesInternalEnum (value, names=None, *, module=None, qualname=None, type=None, start=1)

Conversation roles for the internal usage.

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class ConversationRolesInternalEnum(str, Enum):
    """Conversation roles for the internal usage."""

    CODE = "code_generation"
    ANALYSIS = "analysis_suggestion_interpretation"

Ancestors

• builtins.str
• enum.Enum

Class variables

var ANALYSIS

var CODE

class LLMType (value, names=None, *, module=None, qualname=None, type=None, start=1)

The type of LLM to use.

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class LLMType(Enum):
    """The type of LLM to use."""

    GPT4 = "gpt4"
    LLAMA2 = "llama2"

Ancestors

• enum.Enum

Class variables

var GPT4

var LLAMA2

class Message (**data: Any)

Messages are the basic building blocks of a conversation.

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

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class Message(BaseModel):
    """Messages are the basic building blocks of a conversation."""

    role: ConversationRolesEnum | ConversationRolesInternalEnum
    content: str

Ancestors

• pydantic.main.BaseModel

Class variables

var content : str

var model_config

var model_fields

var role : ConversationRolesEnum | ConversationRolesInternalEnum