lang_tools.llm.tutor ¶

TutorResponseChain: produce a correction + conversation continuation.

Classes:

ConversationBlock –

Tutor's conversation continuation.
CorrectionBlock –

Tutor's correction block.
ErrorDetail –

Structured grammar / vocabulary error.
TutorInput –

Inputs to TutorResponseChain.
TutorOutput –

Outputs from TutorResponseChain.

Functions:

build_tutor_chain –

Build a tutor response chain wired to chat_config.

ConversationBlock ¶

Bases: BaseModel

Tutor's conversation continuation.

Attributes:

content (str) –

Continuation text in the target language.
translation (str) –

Translation of the continuation.

CorrectionBlock ¶

Bases: BaseModel

Tutor's correction block.

Attributes:

content (str) –

Correction text in the target language.
translation (str) –

Translation of the correction text.
errors (list[ErrorDetail]) –

Structured list of individual errors.

ErrorDetail ¶

Bases: BaseModel

Structured grammar / vocabulary error.

Attributes:

original (str) –

The user's wording.
corrected (str) –

The corrected wording.
explanation (str) –

Brief grammar / vocab note.

TutorInput ¶

Bases: BaseModelKwargs

Inputs to TutorResponseChain.

Attributes:

topic (str) –

Conversation topic.
language (str) –

ISO 639-1 target language code.
user_message (str) –

Latest user message.
history (list[TutorMessage]) –

Prior TutorMessages.
difficulty_level (str) –

"beginner" / "intermediate" / "advanced".

TutorOutput ¶

Bases: BaseModel

Outputs from TutorResponseChain.

Attributes:

correction (CorrectionBlock) –

Correction block (may be empty when no errors).
conversation (ConversationBlock) –

Conversation continuation block.

build_tutor_chain ¶

build_tutor_chain(
    chat_config: ChatConfig,
    *,
    base_prompt_fol: Path | None = None,
    version: str = "auto",
) -> StructuredLLMChain[TutorInput, TutorOutput]

Build a tutor response chain wired to chat_config.

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

def build_tutor_chain(
    chat_config: ChatConfig,
    *,
    base_prompt_fol: Path | None = None,
    version: str = "auto",
) -> StructuredLLMChain[TutorInput, TutorOutput]:
    """Build a tutor response chain wired to `chat_config`."""
    return StructuredLLMChain(
        chat_config=chat_config,
        prompt_str=load_prompt(
            "tutor_response",
            base_prompt_fol=base_prompt_fol,
            version=version,
        ),
        input_model=TutorInput,
        output_model=TutorOutput,
    )