train_dataset.py

from langchain_community.embeddings.sentence_transformer import (
    SentenceTransformerEmbeddings,
)
from langchain_community.vectorstores import Chroma

# create the open-source embedding function
embedding_function = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")

# load Chroma
db = Chroma(embedding_function=embedding_function, persist_directory="./chroma_db")

print("There are", db._collection.count(), " docs in the collection")

docs = db._collection.peek(10)

for doc in docs['documents']:
  print(doc)