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task-6a1864f78a94f887e50d46da/vectorstore.py
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2026-06-02 07:20:49 +00:00

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2.9 KiB
Python

"""
Vector store utilities for ChromaDB.
"""
import os
from pathlib import Path
from langchain_chroma import Chroma
from langchain_ollama import OllamaEmbeddings
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_community.document_loaders import TextLoader, UnstructuredMarkdownLoader
# ---------------------------------------------------------------------------
# Create a persistent Chroma vector store
# ---------------------------------------------------------------------------
def create_vectorstore(persist_directory: str = "./chroma_db") -> Chroma:
"""Create or load a Chroma vector store.
Parameters
----------
persist_directory: str
Directory where the Chroma DB will be persisted.
Returns
-------
Chroma
A Chroma vector store instance.
"""
os.makedirs(persist_directory, exist_ok=True)
embeddings = OllamaEmbeddings(model="nomic-embed-text")
return Chroma(persist_directory=persist_directory, embedding_function=embeddings)
# ---------------------------------------------------------------------------
# Load documents from a directory and add them to the vector store
# ---------------------------------------------------------------------------
def load_documents(directory: str, vectorstore: Chroma, chunk_size: int = 500, chunk_overlap: int = 50) -> None:
"""Load `.txt` and `.md` files from *directory*, split them into chunks, and add to *vectorstore*.
Parameters
----------
directory: str
Directory containing the source documents.
vectorstore: Chroma
The vector store to which documents will be added.
chunk_size: int, optional
Maximum chunk size in characters.
chunk_overlap: int, optional
Number of overlapping characters between consecutive chunks.
"""
loader_classes = {
".txt": TextLoader,
".md": UnstructuredMarkdownLoader,
}
splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
docs = []
for root, _, files in os.walk(directory):
for file in files:
ext = Path(file).suffix.lower()
if ext not in loader_classes:
continue
loader = loader_classes[ext](os.path.join(root, file))
loaded_docs = loader.load()
docs.extend(loaded_docs)
if not docs:
return
# Split documents into smaller chunks
split_docs = splitter.split_documents(docs)
vectorstore.add_documents(split_docs)
# ---------------------------------------------------------------------------
# Example usage
# ---------------------------------------------------------------------------
if __name__ == "__main__":
# This block is only executed when running the module directly.
store = create_vectorstore()
load_documents("documents", store)
print("Vector store populated.")