dephinate/kai-ai-backend

This is the Kai Teaching Assistant ai repo.

Kai AI Platform

Table of Contents

• Architecture
• Folder Structure
• Setup
• Local Development
• Contributing

Folder Structure

backend/
├── app/                     # Contains the main application code
│   ├── Api/                 # Contains the API router for handling requests
│   │   └── router.py        # Endpoints for FastAPI to test features and handle incoming requests
│   ├── chats/               # Handles chat functionalities
│   ├── Features/            # Contains feature-specific modules
│   │   ├── Feature1/
│   │   │   ├── core.py
│   │   │   ├── tools.py
│   │   │   ├── Prompt/
│   │   │   └── metadata.json
│   │   ├── Feature2/
│   │   │   ├── core.py
│   │   │   ├── tools.py
│   │   │   ├── Prompt/
│   │   │   └── metadata.json
│   ├── services/            # Contains service modules
│   ├── utils/               # Contains utility modules
│   ├── app.yaml             # Application configuration file
│   ├── Dependencies.py      # Dependency management
│   ├── Main.py              # Main entry point for the application
│   └── requirements.txt     # Python dependencies
├── Dockerfile               # Dockerfile for containerizing the application
└── README.md                # Documentation file

Install all the necessary libraries:

Navigate to the app directory

cd backend/app

Create and activate Virtual Environment

python -m venv env
source env/bin/activate

pip install -r requirements.txt

To Run Locally and Test

Prerequisites

• A Google Cloud account.
• Access to the Google Cloud Platform console.

Steps for Authentication Setup

Step 1: Create a Service Account

1. Navigate to the Google Cloud Console.
2. Go to IAM & Admin > Service Accounts.
3. Click Create Service Account.
4. Enter a name and description for the service account.
5. Click Create.
6. Assign the necessary roles to the service account (e.g., Editor, Viewer).
7. Click Continue and then Done to finish creating the service account.

Step 2: Download the Service Account Key

1. In the Service Accounts page, click on the newly created service account.
2. Go to the Keys tab.
3. Click Add Key, then select Create new key.
4. Choose JSON as the key type and click Create.
5. The key will be downloaded automatically. Save this file securely.

Step 3: Rename and Store the Key

1. Rename the downloaded JSON key to local-auth.json.
2. Move or copy this file to your application's directory, specifically inside the /app directory.

Step 4: Set Environment Variables

1. Open your command line interface.
2. Set the path to the JSON key file by running:

   set GOOGLE_APPLICATION_CREDENTIALS=/app/local-auth.json```

Set the environment type and project ID:

  set ENV_TYPE="dev"
  set PROJECT_ID="Enter your project ID here"

  uvicorn main:app --reload

Docker Setup Guide

Overview

This guide is designed to help contributors set up and run the backend service using Docker. Follow these steps to ensure that your development environment is configured correctly.

NOTE: if you choose to authenticate Google Cloud through the SDK and not with a local serice account key, you must comment out GOOGLE_APPLICATION_CREDENTIALS in the Dockerfile.

Prerequisites

Before you start, ensure you have the following installed:

• Docker
• Python

Installation Instructions

1. Setting Up Local Credentials

Obtain a local-auth.json file which contains the Google service account credentials and place it in the root of the app/ directory within your project.

2. Build the Docker Image

Navigate to the project's root directory and build the Docker image:

docker build -t kai-backend:latest .

3 Run the Docker Container

Run the Docker container using the following command:

docker run -p 8000:8000 kai-backend:latest

This command starts a detached container that maps port 8000 of the container to port 8000 on the host.

Environment Variables

The Docker container uses several key environment variables:

• GOOGLE_APPLICATION_CREDENTIALS points to /app/local-auth.json.
• ENV_TYPE set to "sandbox" for development.
• PROJECT_ID specifies your Google Cloud project ID.
• LangChain API integration is configured via: LANGCHAIN_TRACING_V2 LANGCHAIN_ENDPOINT LANGCHAIN_API_KEY LANGCHAIN_PROJECT
• Ensure these variables are correctly configured in your Dockerfile or passed as additional parameters to your Docker run command if needed.

Accessing the Application

You can access the backend by visiting:

http://localhost:8000

After your container starts, you should see the FastAPI landing page, indicating that the application is running successfully.