Introduction

Imagine having to go through a stack of lab reports, each filled with complex medical jargon and lengthy explanations. It’s a daunting task, isn’t it? But what if we could use Artificial Intelligence (AI) to simplify this process?

In this blog post, I’ll guide you on how to create a tool that uses AI to read and summarize lab reports. This tool uses two key components: Langchain and OpenAI.

What are Langchain and OpenAI?

Before we dive into the how-to, let’s understand what Langchain and OpenAI are. Langchain is a library that allows us to combine different AI models to perform complex tasks. Think of Langchain as a master chef who knows how to combine different ingredients (in our case, AI models) to create a delicious dish (a summary in our case 😋)

OpenAI, on the other hand, is an AI research lab that provides powerful AI models. We use one of their models, GPT-3.5-turbo, to process the lab reports and generate a summary.

The Magic Behind the Scenes

Our tool consists of two parts: a backend script that processes the lab reports and a frontend script that provides a user interface. The backend script reads the text from a PDF file, identifies the key points using OpenAI, and then creates a summary using Langchain. The frontend script provides a user-friendly interface where you can upload your lab report, and displays the key points and the summary of the report.

Building the AI Tool: A Step-by-Step Guide

Now that we’ve set the stage, let’s get our hands dirty and start building this tool.

A. Backend Script

Install the necessary libraries: First, we need to install some libraries. If you’ve ever baked a cake, think of this step as gathering your ingredients. You can install the libraries using pip, which is a package manager for Python.

git clone https://github.com/robinkiplangat/LabScanner.git
cd LabScanner
pip install -r requirements.txt

Get your OpenAI API key: To use OpenAI, you need an API key. You can get this key from the OpenAI website after creating an account.

Run the backend script: Once you have your ingredients ready, it’s time to start baking! You can run the backend script using Python.

python3 scripts/reports_frontend.py

B. Frontend Script

Install Streamlit : The frontend script is a Streamlit application. Streamlit is a library that allows you to create web applications using Python. You can install it using pip.

Run the frontend script : Once you have installed Streamlit, you can run the frontend script. This will open a new tab in your web browser with the application.

streamlit run scripts/reports_frontend.py

To use the application, upload a lab report, enter your OpenAI API key, and click Submit. Check out the demo below.