Chroma
chroma-core/chroma: the AI-native open-source embedding database
code: core_api.py
import chromadb
# setup Chroma in-memory, for easy prototyping. Can add persistence easily!
client = chromadb.Client()
# Create collection. get_collection, get_or_create_collection, delete_collection also available!
collection = client.create_collection("all-my-documents")
# Add docs to the collection. Can also update and delete. Row-based API coming soon!
collection.add(
documents="This is document1", "This is document2", # we handle tokenization, embedding, and indexing automatically. You can skip that and add your own embeddings as well
metadatas={"source": "notion"}, {"source": "google-docs"}, # filter on these!
ids="doc1", "doc2", # unique for each doc
)
# Query/search 2 most similar results. You can also .get by id
results = collection.query(
query_texts="This is a query document",
n_results=2,
# where={"metadata_field": "is_equal_to_this"}, # optional filter
# where_document={"$contains":"search_string"} # optional filter
)