Part of a ProjectText Suite
. VecMetaQ (Vector Metadata Query) is a FastAPI web app encapsulating a FAISS vector index for easy management of embeddings and metadata.
POST /add_data/
.DELETE /delete_data/
.POST /search_similar/
.Make sure to have docker installed on your system and then simply copy and initialize the .env file and do a docker compose up:
mv .env-example .env
docker compose up
Or to use the GHCR you can (make sure to have the .env file ready):
docker pull ghcr.io/flagro/vecmetaq
docker run -it --env-file .env ghcr.io/flagro/vecmetaq
Accessible by default at 127.0.0.1:8000
.
π οΈ API Endpoints
text
, tag
, metadata
, and credentials.tag
and credentials.query
, optional k
(int), distance_threshold
(float), and credentials.Open for collaboration; check the issues page for discussions.