lang_tools.llm.conversation ¶

ConversationGeneratorChain: generate a multi-turn bilingual dialogue.

Classes:

ConversationInput –

Inputs to ConversationGeneratorChain.
ConversationOutput –

Outputs from ConversationGeneratorChain.
ConversationTurn –

One turn in a generated conversation.

Functions:

build_conversation_chain –

Build a conversation generator chain wired to chat_config.

ConversationInput ¶

Bases: BaseModelKwargs

Inputs to ConversationGeneratorChain.

Attributes:

topic (str) –

Topic prompt for the dialogue.
language (str) –

ISO 639-1 code of the target language.
difficulty_level (str) –

"beginner" / "intermediate" / "advanced".
num_turns (int) –

How many turns the dialogue should contain.
max_sentences_per_turn (int) –

Per-turn sentence cap.
sample_conversation (str | None) –

Optional few-shot example to calibrate level.

ConversationOutput ¶

Bases: BaseModel

Outputs from ConversationGeneratorChain.

Attributes:

turns (list[ConversationTurn]) –

Generated dialogue turns.

ConversationTurn ¶

Bases: BaseModel

One turn in a generated conversation.

Attributes:

role (Literal['user', 'system']) –

"user" or "system".
content (str) –

Target-language text.
translation (str) –

User-language translation.

build_conversation_chain ¶

build_conversation_chain(
    chat_config: ChatConfig,
    *,
    base_prompt_fol: Path | None = None,
    version: str = "auto",
) -> StructuredLLMChain[
    ConversationInput, ConversationOutput
]

Build a conversation generator chain wired to chat_config.

Source code in src/lang_tools/llm/conversation.py

def build_conversation_chain(
    chat_config: ChatConfig,
    *,
    base_prompt_fol: Path | None = None,
    version: str = "auto",
) -> StructuredLLMChain[ConversationInput, ConversationOutput]:
    """Build a conversation generator chain wired to `chat_config`."""
    return StructuredLLMChain(
        chat_config=chat_config,
        prompt_str=load_prompt(
            "conversation_generator",
            base_prompt_fol=base_prompt_fol,
            version=version,
        ),
        input_model=ConversationInput,
        output_model=ConversationOutput,
    )