"""Search tool for the Chroma vector store.

The function `search_course_docs` performs a similarity search on the
persisted Chroma collection and returns the top *k* documents.
"""

from typing import List

from langchain_chroma import Chroma
from langchain_core.documents import Document

from .config import CHROMA_DIR, CHROMA_TOP_K

# Load the persistent store once – this is cheap because it just reads
# the SQLite file.
_chroma = Chroma(persist_directory=CHROMA_DIR)

def search_course_docs(query: str, k: int = CHROMA_TOP_K) -> List[Document]:
    """Return the top *k* documents that match *query*.

    The function is intentionally simple; it does not filter by metadata
    because the FAQ files are small.
    """
    return _chroma.similarity_search(query, k=k)