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    A lightweight question runner that answers metadata-focused questions (signatures, sign status, completion, dates) using a single structured-output LLM call against compact per-type summary tables.

    No agent loop, no vector retrieval, no full document fetching. Designed as a cheap shortcut: when the LLM answers confidently (pass/fail) we use the result; otherwise it throws NotEnoughInformationError and the composite runner falls through to the full agent pipeline.

    Hierarchy (View Summary)

    Index

    Constructors

    Properties

    enableNoDocsBailout: boolean
    logger: BaseLogger
    model: ChatOpenAI
    sessionId?: SessionId
    sessionNoteContext?: string
    supabase: SupabaseClient<Database>
    treatmentEpisodeId?: string
    useFullEmrDocuments: boolean

    Methods