Add src/rag_tools.py

src/rag_tools.py

@@ -0,0 +1,24 @@
+"""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)