This project contains a web service with the following endpoints under http://localhost:8080
- POST
/data/load
- GET
/data/count
- POST
/data/delete
- GET
/qa
The /qa
endpoint takes a question
parameter which is the question you want to ask the AI model.
The /qa
endpoint also takes a stuffit
boolean parameter, whose default it true, that will 'stuff the prompt' with
similar documents to the question. When stuffing the prompt, this follows the RAG pattern.
Create an account at OpenAI # and generate the token at API Keys.
The Spring AI project defines a configuration property named spring.ai.openai.api-key
that you should set to the value of the API Key
obtained from openai.com
.
You can set this in the projects /resources/application.yml
file or by exporting an environment variable, for example.
export SPRING_AI_OPENAI_API_KEY=<INSERT KEY HERE>
The /resources/application.yml
references the environment variable ${OPENAI_API_KEY}
as that is what the onboarding instructions for OpenAI suggest.
In short, Spring Boot provides many ways to set this property, pick a method that works for your needs.
If you have the direnv shell extension an easy way to manage your environment variable is to create a .envrc file from the example file.
You can do this with cp .envrc.example .envrc
.
Then enter values for all variables in the .envrc
(This file is in the .gitignore so it will not be checked in)
This will automatically load the environment variables within the project directory.
Run direnv allow
or source .envrc
after modifying the .envrc file.
To run the PgVectorStore locally, using docker-compose. From the top project directory and run:
docker-compose up
Later starts Postgres DB on localhost and port 5432.
Then you can connect to the database (password: postgres
) and inspect or alter the vector_store
table content:
psql -U postgres -h localhost -p 5432
\l
\c vector_store
\dt
select count(*) from vector_store;
delete from vector_store;
You can connect to the pgAdmin on http://localhost:5050 as user: pgadmin4@pgadmin.org
and pass: admin
.
Then navigate to the Databases/vector_store/Schemas/public/Tables/vector_store
.
The UI tool DBeaver is also a useful GUI for postgres.
./mvnw spring-boot:run
The first thing you should do is load the data. The examples show usage with the HTTPie command line utility as it simplifies sending HTTP requests with data as compared to curl.
http POST http://localhost:8080/data/load
Next you can see how many document fragments were loaded into the Vector Store using
http http://localhost:8080/data/count
If you want to start over, for example because you changed in the code which document is being loaded, then execute
http POST http://localhost:8080/data/delete
Send you question to the AI Model using
http --body --unsorted localhost:8080/qa message==<insert question here>
Note that there are two equal signs ==
, that separate the key-value pairs
To ask the same question but without the similar documents stuffing the prompt, that is, not using the RAG pattern,
http --body --unsorted http://localhost:8080/qa message==<insert question here> stuffit==false
$ http --body --unsorted localhost:8080/qa question=="What is the purpose of Carina?"
{
"question": "What is the purpose of Carina?",
"answer": "The purpose of Carina is to provide a safe and easy-to-use online care matching service. It aims to connect care providers with individuals and families who are in need of home care or child care services. Carina prioritizes building community and supporting care workers by bringing good jobs to them. Its goal is to strengthen the care economy and support workers, individuals, and families in the process."
}
and without stuffing the prompt
$ http --body --unsorted localhost:8080/qa question=="What is the purpose of Carina?" stuffit==false
{
"question": "What is the purpose of Carina?",
"answer": "Carina is a constellation located in the southern sky. It does not have a specific purpose, but like other constellations, it serves as a way to organize and identify stars in the night sky. Constellations have been used for navigation, storytelling, and scientific observation throughout history."
}