from langchain_chroma import Chroma
from langchain_openai import OpenAIEmbeddings

vectorstore = Chroma.from_documents(
    documents=docs,
    embedding=OpenAIEmbeddings(),
    persist_directory="./chroma_db"
)

# Query
results = vectorstore.similarity_search("query", k=3)

# As retriever
retriever = vectorstore.as_retriever()

from llama_index.vector_stores.chroma import ChromaVectorStore
import chromadb

db = chromadb.PersistentClient(path="./chroma_db")
collection = db.get_or_create_collection("docs")

vector_store = ChromaVectorStore(chroma_collection=collection)