Greenplum Q&A is a project that demonstrates how to use word embeddings and Postgres to build a chatbot. The chatbot is implemented using pgvector and relies on OpenAI's GPT-3.5 API to generate responses.

To get started with this project, you'll need to have:

• an API key for the OpenAI GPT-3.5 API, which you can obtain from https://openai.com/.

Once you have the prerequisites installed, follow these steps to get the project up and running:

Clone the repository:

git clone https://github.com/yihong0618/ask-greenplum.git
cd ask-greenplum

docker run --name some-greenplum1 -e POSTGRES_PASSWORD=postgres -p 5432:5432  -d ankane/pgvector

cd data
python -m venv env
source env/bin/activate
pip install -r requirements.txt

Import the schema to your database:

psql <database-url> -f database.sql

Let’s now add DATABASE_URL and OPENAI_API_KEY to our environment variables:

export DATABASE_URL=<YOUR_PG_CONEECTION_STRING> 
OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>

Run main.py to import the emebbeding to your pg database:

python main.py

Relax and grab a cup of coffee as this section might take 60mins to process!

Expcted result:

Saving to CSV...
Loading tokenizer...
Embedding text...
Connecting to database...
Done!

Set the following environment variables:

OPENAI_API_KEY= Your OpenAI API key.
DATABASE_URL= The connection URL for your docker postgres database.

pip install git+https://github.com/yihong0618/GPTerminator.git

gpterm # go ask

We welcome contributions to this project! If you find a bug, have a suggestion, or want to contribute code, please open an issue or pull request on the GitHub repository.

This project is licensed under the MIT License. See the LICENSE file for more information.