"""Chunk agenda-packet PDFs, store them in ChromaDB, and summarize with an LLM.

Typical use::

    from chroma import AgendaStore, ingest_and_summarize_pdfs

    store = AgendaStore(".chroma")
    results = ingest_and_summarize_pdfs(["packet.pdf"], store=store)
    for r in results:
        print(r["metadata"]["file_name"], "->", r["summary"])

    # later, query across everything stored
    hits = store.query("zoning variance", n_results=5)
"""

from __future__ import annotations

from .answer import answer_question
from .chunking import chunk_text
from .llm import chat_complete, get_client, load_llm_config
from .loader import (
    documents_from_pdfs,
    load_pdf_text,
)
from .pipeline import (
    ingest_and_summarize_pdfs,
    ingest_documents,
    summarize_documents,
)
from .report import generate_report
from .store import AgendaStore
from .summarize import summarize_document, summarize_text

__all__ = [
    "AgendaStore",
    "answer_question",
    "chat_complete",
    "chunk_text",
    "documents_from_pdfs",
    "generate_report",
    "get_client",
    "ingest_and_summarize_pdfs",
    "ingest_documents",
    "load_llm_config",
    "load_pdf_text",
    "summarize_document",
    "summarize_documents",
    "summarize_text",
]