End-to-End Text Summarizer Project 📃

This project aims to develop an end-to-end solution for text summarization, enabling the generation of concise summaries from textual data. The project leverages AWS services and follows a structured workflow to ensure efficient summarization of information.

Workflows 🔄

The following workflows are involved in the text summarizer project

1. 📝 Update config.yaml: Modify the configuration file (config.yaml) to customize settings based on specific project requirements.
2. 📝 Update params.yaml: Adjust the parameters file (params.yaml) to configure specific summarization parameters according to your needs.
3. 📝 Update entity: Modify the entity file to include relevant entities for the summarization process.
4. 📝 Update the configuration manager in src/config: Make necessary updates to the configuration manager in the source code (src/config) to ensure proper integration of project components.
5. 📝 Update the components: Update individual components of the text summarizer, such as data preprocessing, feature extraction, and summarization algorithms, as required.
6. 📝 Update the pipeline: Enhance the pipeline that orchestrates the flow of data through the summarization process.
7. 📝 Update main.py: Modify the main script file (main.py) to incorporate any changes or improvements to the overall functionality of the text summarizer.
8. 📝 Update app.py: Make necessary updates to the app script file (app.py), which is responsible for running the text summarizer as a web application.

How to Run ▶️

Follow the steps below to run the project:

##Step 1: Clone the Repository 📥

Clone the project repository using the following command:

git clone https://github.com/somanathkshirsagar/End_to_end_Text-Summarizer-Project-With-AWS-Services.git
cd End_to_end_Text-Summarizer-Project-With-AWS-Services

##Step 2: Create Conda Environment 🐍

After opening the repository, create a Conda environment using the provided command:
conda create -n summary python=3.8 -y
conda activate summary

##Step 3: Install Requirements 📦

Install the required dependencies by running the following command:
pip install -r requirements.txt

##Step 4: Run the Project 🚀

Finally, execute the following command to start the text summarizer:
python app.py

##Step 5: Access the Application 🌐

Open your web browser and enter the localhost and port to access the running application.

Author 🧑‍💻

Somnath Kshirasagar
Data Scientist
Email: somanathtk198@gmail.com

AWS CI/CD Deployment with GitHub Actions ☁️🔧

This project includes AWS CI/CD deployment using GitHub Actions. The deployment process involves the following steps:

🔑 Login to AWS Console.
🧑‍💼 Create IAM User for Deployment:
✅ EC2 access: It is a virtual machine.
✅ ECR: Elastic Container Registry to save your Docker image in AWS.
Deployment Description 🚀

The deployment process can be summarized as follows:

🐳 Build a Docker image of the source code.
📤 Push your Docker image to ECR.
🚀 Launch your EC2 instance.
📥 Pull your image from ECR on EC2.
🏃‍♀️ Run your Docker image on EC2.
Policy 📜
Ensure that the following AWS policies are assigned:

AmazonEC2ContainerRegistryFullAccess
AmazonEC2FullAccess
Additional Steps for Deployment 🔄

Follow these additional steps to complete the deployment setup:

1. Create an ECR repository to store/save the Docker image.
Save the URI: 566373416292.dkr.ecr.us-east-1.amazonaws.com/text-s
1. Create an EC2 machine (Ubuntu).
3. Install Docker on the EC2 machine:
Optional:
sudo apt-get update -y
sudo apt-get upgrade

Required:

curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker ubuntu
newgrp docker

4. Configure EC2 as a self-hosted runner:
Go to Settings > Actions > Runner > New self-hosted runner.
Choose the appropriate operating system.
Run the provided commands one by one.

5. Setup GitHub secrets:
Set the following secrets in your GitHub repository's settings:

AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
AWS_REGION = us-east-1
AWS_ECR_LOGIN_URI = 566373416292.dkr.ecr.ap-south-

1.amazonaws.com
ECR_REPOSITORY_NAME = simple-app

Please note that some formatting elements may not be displayed correctly in the plain text format, but they will be rendered correctly in the Markdown format when viewed on platforms like GitHub.