michaelliao/llm-embedding-sample

LLM Embedding Sample App using Flask and PostgreSQL with pgvector extension.

llm-embedding-sample

LLM Embedding Sample App using Flask and PostgreSQL with pgvector extension.

Install Python 3.11 and dependencies

pip install openai numpy flask jinja2 psycopg2 pgvector

Run PostgreSQL with pgvector

docker run -d \
       --rm \
       --name pgvector \
       -p 5432:5432 \
       -e POSTGRES_PASSWORD=password \
       -e POSTGRES_USER=postgres \
       -e POSTGRES_DB=postgres \
       -e PGDATA=/var/lib/postgresql/data/pgdata \
       -v /path/to/llm-embedding-sample/pg-data:/var/lib/postgresql/data \
       -v /path/to/llm-embedding-sample/pg-init-script:/docker-entrypoint-initdb.d \
       ankane/pgvector:latest

NOTE: replace /path/to/... with real path.

The initial script is in pg-init-script and it is only executed once when container started.

The db files are stores at pg-data.

Run Flask app

$ python3 app.py

When app starts:

• load all .md files from docs;
• create embedding and save into db if record is not exist.

Ask

Open http://localhost:5000: