kiarina-agi-text

[!NOTE] What is this? Provides interchangeable chat models, chat logging, and text embeddings for AI agents.

Dependencies

Required Dependencies

Optional Dependencies

The all Extra installs every optional dependency listed above.

Installation

pip install "kiarina-agi-text[all]"

Features

• Chat Models Select a model by name or alias and receive one response or a stream. Tool calls and image, audio, video, and PDF inputs and outputs are also supported.
• Text Embeddings Select a registered model and vectorize text through one API.

API Reference

kiarina.agi.chat_model

from kiarina.agi.chat_model import (
    ChatModel,
    ChatModelAlias,
    ChatModelConfig,
    ChatModelName,
    ChatModelSettings,
    ChatModelSpecifier,
    ChatOptions,
    chat_model_registry,
    invoke_chat,
    run_chat,
    settings_manager,
    stream_chat,
)

async def invoke_chat(
    messages: list[Message],
    *,
    tool_infos: list[ToolInfo] | None = None,
    chat_options: ChatOptions | None = None,
    cost_recorder: CostRecorder | None = None,
    run_context: RunContext,
) -> AIMessage: ...

async def run_chat(
    messages: list[Message],
    *,
    tool_infos: list[ToolInfo] | None = None,
    chat_options: ChatOptions | None = None,
    cost_recorder: CostRecorder | None = None,
    run_context: RunContext,
) -> AsyncIterator[AIMessageChunk | AIMessage]: ...

async def stream_chat(
    messages: list[Message],
    *,
    tool_infos: list[ToolInfo] | None = None,
    chat_options: ChatOptions | None = None,
    cost_recorder: CostRecorder | None = None,
    run_context: RunContext,
) -> AsyncIterator[AIMessageChunk | AIMessage]: ...

class ChatModel:
    def __init__(self, name: ChatModelName, config: ChatModelConfig) -> None: ...
    @property
    def provider_name(self) -> ChatProviderName: ...
    @property
    def provider_config(self) -> dict[str, Any]: ...
    @property
    def token_scale_factor(self) -> float: ...
    @property
    def provider(self) -> ChatProvider: ...
    def get_capabilities(self) -> ChatCapabilities: ...
    async def run(
        self,
        messages: list[Message],
        *,
        tool_infos: list[ToolInfo] | None = None,
        tool_choice: ToolChoice | None = None,
        parallel_tool_calls: bool | None = None,
        streaming: bool | None = None,
        cost_recorder: CostRecorder | None = None,
        run_context: RunContext,
    ) -> AsyncIterator[AIMessageChunk | AIMessage]: ...

class ChatModelConfig(BaseModel):
    provider_name: ChatProviderName
    provider_config: dict[str, Any] = {}
    token_scale_factor: float = 1.0
    visible: bool = True

class ChatOptions(TypedDict, total=False):
    chat_model: ChatModel | ChatModelSpecifier | None
    tool_choice: ToolChoice | None
    parallel_tool_calls: bool | None
    streaming: bool | None

ChatModelName: TypeAlias = str
ChatModelAlias: TypeAlias = str
ChatModelSpecifier: TypeAlias = ChatModelName | ChatModelAlias | str

chat_model_registry: ObjectRegistry[ChatModel, ChatModelConfig]
settings_manager: SettingsManager[ChatModelSettings]

ChatModelSettings is a Pydantic settings class with default, aliases, presets, and customs fields.

kiarina.agi.text_embedding_model

from kiarina.agi.text_embedding_model import (
    TextEmbeddingModel,
    TextEmbeddingModelAlias,
    TextEmbeddingModelConfig,
    TextEmbeddingModelName,
    TextEmbeddingModelSettings,
    TextEmbeddingModelSpecifier,
    TextEmbeddingOptions,
    embed_text,
    settings_manager,
    text_embedding_model_registry,
)

async def embed_text(
    text: str,
    *,
    text_embedding_options: TextEmbeddingOptions | None = None,
    cost_recorder: CostRecorder | None = None,
    run_context: RunContext,
) -> Embedding: ...

class TextEmbeddingModel:
    def __init__(
        self, name: TextEmbeddingModelName, config: TextEmbeddingModelConfig
    ) -> None: ...
    @property
    def provider_name(self) -> TextEmbeddingProviderName: ...
    @property
    def provider_config(self) -> dict[str, Any]: ...
    @property
    def provider(self) -> TextEmbeddingProvider: ...
    def get_space(self) -> EmbeddingSpace: ...
    async def embed(
        self,
        text: str,
        *,
        cost_recorder: CostRecorder | None = None,
        run_context: RunContext,
    ) -> Embedding: ...

class TextEmbeddingModelConfig(BaseModel):
    provider_name: TextEmbeddingProviderName
    provider_config: dict[str, Any] = {}
    visible: bool = True

class TextEmbeddingOptions(TypedDict, total=False):
    text_embedding_model: TextEmbeddingModel | TextEmbeddingModelSpecifier | None

TextEmbeddingModelName: TypeAlias = str
TextEmbeddingModelAlias: TypeAlias = str
TextEmbeddingModelSpecifier: TypeAlias = (
    TextEmbeddingModelName | TextEmbeddingModelAlias | str
)
text_embedding_model_registry: ObjectRegistry[
    TextEmbeddingModel, TextEmbeddingModelConfig
]
settings_manager: SettingsManager[TextEmbeddingModelSettings]

TextEmbeddingModelSettings has default, aliases, presets, and customs fields.