SSC Assistant

Second iteration of the SSC chatbot/assistant.

The SSC Assistant leverages the Azure OpenAI API to utilize advanced language models such as GPT-4o. It employs the Retrieval Augmented Generation (RAG) method, integrating external APIs and tools to offer a wide array of options for users.

When the Assistant uses a tool in its API call, it indicates which tools were used in the response and displays the relevant metadata. For example, here is how it presents information retrieved using the GEDS tool:

Developer(s)

This section will help developer understand this project and how to set it up from the ground up and how to run it on their machine.

Codespaces

Simply create your branch and create a codespace for it from github. Load up that codespace you will have everything that you need to start working,

or Dev Containers (recommended)

Here is how you can develop locally with Dev Containers.

Pre-requisites

VSCode with Dev Container extension
Docker engine installed on Linux (Can be via WSL 2.0 on Windows)

NOTE: If you are using Docker Desktop you are required to have an Enterprise lisence.

Steps

Ctrl + Shift + P in VSCode and then Dev Containers: Reopen in Container (or alternatively if you never did open it Dev Containers: Open Folder in Container... and select the repo with ssc-assistant).

NOTE: Sharing SSH Key with the container via ssh-agent

Development steps:

Development steps are the same once you are inside the container (regardless if spun from Codespaces or locally from Dev Containers extension):

Ctrl + Shift + ~ to open 2 new terminals and simply start the services:

NOTE: It is important that you firsts login via az login --use-device-code

API:

cd app/api && flask run --debug --port=5001

Frontend:

cd app/frontend && npm run dev

All the necessary npm install and pip install commands have already been run and you can simply reach the codespace url that points to the 8080 port.

NOTE: You will need to have a 163dev account in order to develop and test on DEV/locally (request an account).

Issues with Dev Container Workspace Cache

If you encounter an issue starting npm in dev containers you can refer to this workaround/bug.

Manual setup (deprecated)

We are developing on python 3.11+.

Please setup your environement like so:

We have 2 python projects in this repo, I create 2 virtual envs and switch between them via command line and/or visual studio.

First we setup the backend API project:

python3 -m venv .venv_api
source .venv_api/bin/activate
pip install -r app/api/requirements.txt --upgrade

You should then see something like this denoting which environement you are in your shell. To leave this .venv simply type deactivate

(.venv_api) ➜  ~/git/ssc-assistant/

Now ensure that VSCode uses the proper .venv folder by pressing Ctrl + Shift + P and then type Python: Select Interpreter

and then the azure function project:

python3 -m venv .venv_func
source .venv_func/bin/activate
pip install -r az-functions/create-index/requirements.txt --upgrade

(for this virtual env the .vscode/settings.json should already be pointing to the proper folder, else re-follow steps above to ensure VSCode uses the proper venv for that section of the project)

npm install
npm run dev

Infrastructure

The current infrastructure of this project is as follow:

Azure Sandbox Subscription
- Azure Function to transform the raw data (SSCPlus, etc.) to a Search Service index
Service dependencie(s)
- SSCPlus Data Fetch services (loads up raw data into blobs)
- Azure OpenAI Services

Spinning up the infrastructure

Prerequisites:

Azure Client, minimum of Contributor role in the subscription, then simply az login
terraform

cd terraform/
terraform init
terraform plan -var-file="secret.tfvars"

163dev Account Permissions

To sign into a Microsoft account during development, a @163dev.onmicrosoft.com account must be used.

The following permisions must be granted to the account through Azure:

dto-btn / ssc-assistant

readme