Special thanks to
DevKit - The Essential Developer Toolkit
DSoC 2023
pip install citrusdb
import citrusdb
# Initialize client
citrus = citrusdb.Client()
# Create index
citrus.create_index(
max_elements=1000, # increases dynamically as you insert more vectors
persist_directory="/db" # save data and load index from disk
)ids = [1, 2, 3]
docuemnts = [
"Your time is limited, so don't waste it living someone else's life",
"I'd rather be optimistic and wrong than pessimistic and right.",
"Running a start-up is like chewing glass and staring into the abyss."
]
citrus.add(ids, documents=documents)You can directly pass vector embeddings as well. If you're passing a list of strings like we have done here, ensure you have your OPENAI_API_KEY in the environment. By default we use OpenAI to to generate the embeddings. Please reach out if you're looking for support from a different provider!
result, distances = citrus.query("What is it like to launch a startup", k=1)Go launch a repl on Replit and see what result you get after running the query! result will contain the ids of the top k search hits.