InsightAI Backend

Overview

Welcome to the backend of InsightAI, an application designed to revolutionize your banking experience. This backend is built using FastAPI, providing a robust and efficient structure for our application.

Technologies Used

• FastAPI: A modern, fast (high-performance), web framework for building APIs with Python 3.6+.
• Unstructured: For document parsing
• Serper: For Web-search
• Qdrant: For Vector Database
• OpenAI: As Ai model
• Structured-output: For structuring openai response
• beautifulsoup4: For scraping web content
• Roboflow: For generating embedding for image
• Supabase: Used for database hosting and authentication.

Getting Started

Making the Environment

To make a virtual environment, use the following command:

python3 -m venv .venv

Activate the virtual Environment:

source .venv/bin/activate

Install the Requirements:

Install The requirements with the following command:

pip install -r requirements.txt

It may lag. So better add a timeout

pip install -r requirements.txt --timeout=1000

Running the Backend

To run the backend server, use the following command:

uvicorn app.main:app --reload

The app will start:

http://127.0.0.1:8000/

Once the application is running, you can access the API documentation provided by Swagger at:

http://127.0.0.1:8000/docs

Here, you can explore and interact with the various API endpoints.

Changes will migrate automatically

Endpoints

Endpoints are defined in api/api_v1/endpoints/

Helper functions

Helper functions are defined in /helpers. Most LLM Tasks will be performed here

Environment File

It will be provided Privately

Deployment

The application is hosted in Render

• Deployment.
• Deployment Docs.