Update vectorstore.py

This commit is contained in:
2026-06-02 07:13:00 +00:00
parent 8754881bf2
commit 144be41b2a
+22 -22
View File
@@ -1,53 +1,53 @@
"""Module for creating and loading a Chroma vector store with Ollama embeddings."""
"""
Vector store utilities for ChromaDB.
"""
from pathlib import Path
from typing import List
from langchain_ollama import OllamaEmbeddings
from langchain_chroma import Chroma
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain.docstore.document import Document
def create_vectorstore(persist_directory: str = "./chroma_db") -> Chroma:
"""Create a Chroma vector store with Ollama embeddings.
def create_vectorstore(persist_directory: str = "./chroma_db"):
"""Create or load a Chroma vector store.
Parameters
----------
persist_directory: str
Directory where the vector store will be persisted.
Directory where the Chroma database is persisted.
Returns
-------
Chroma
The created Chroma vector store.
The Chroma vector store instance.
"""
embeddings = OllamaEmbeddings(model="nomic-embed-text")
return Chroma(persist_directory=persist_directory, embedding_function=embeddings)
def load_documents(directory: str, vectorstore: Chroma, chunk_size: int = 1000, chunk_overlap: int = 200) -> None:
"""Load .txt and .md files from a directory, split them into chunks, and add to the vector store.
def load_documents(directory: str, vectorstore: Chroma, chunk_size: int = 1000, chunk_overlap: int = 200):
"""Read all .txt and .md files from a directory, split them into chunks and add to the vectorstore.
Parameters
----------
directory: str
Path to the directory containing documents.
Path to the folder containing documents.
vectorstore: Chroma
The vector store to add documents to.
The vector store to which documents will be added.
chunk_size: int
Maximum size of each chunk.
Maximum number of characters per chunk.
chunk_overlap: int
Number of characters to overlap between chunks.
Number of overlapping characters between consecutive chunks.
"""
splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
documents: List[Document] = []
for file_path in Path(directory).glob("**/*"):
if file_path.suffix.lower() in {".txt", ".md"}:
text = file_path.read_text(encoding="utf-8")
chunks = splitter.split_text(text)
for chunk in chunks:
documents.append(Document(page_content=chunk, metadata={"source": str(file_path)}))
if documents:
vectorstore.add_documents(documents)
docs = []
for file_path in Path(directory).rglob("*.txt"):
docs.append(file_path.read_text(encoding="utf-8"))
for file_path in Path(directory).rglob("*.md"):
docs.append(file_path.read_text(encoding="utf-8"))
if not docs:
return
texts = splitter.split_text("\n\n".join(docs))
vectorstore.add_texts(texts)
vectorstore.persist()