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I am following the Movie recomendation service article. What is the correct way of extending the embeddings entity table that is created so that we can link an embedding to the original Movie entity it comes from? I.e so that each Embedding has a foreign key movie_id. Currently the tables that are generated in Postgres look like this. I don't want it to be nested in the metadata but a real id column.
quarkus=# \d embeddings
Table "public.embeddings"
Column | Type | Collation | Nullable | Default
--------------+--------------+-----------+----------+---------
embedding_id | uuid | | not null |
embedding | vector(1536) | | |
text | text | | |
metadata | json | | |
Indexes:
"embeddings_pkey" PRIMARY KEY, btree (embedding_id)
quarkus=# \d movie
Table "public.movie"
Column | Type | Collation | Nullable | Default
----------+------------------------+-----------+----------+---------
id | bigint | | not null |
link | character varying(255) | | |
overview | character varying(255) | | |
title | character varying(255) | | |
Indexes:
"movie_pkey" PRIMARY KEY, btree (
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I am following the Movie recomendation service article. What is the correct way of extending the embeddings entity table that is created so that we can link an embedding to the original Movie entity it comes from? I.e so that each Embedding has a foreign key movie_id. Currently the tables that are generated in Postgres look like this. I don't want it to be nested in the metadata but a real id column.
From this article: https://quarkus.io/blog/movie-similarity-search-using-vector-databases/
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