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Automating text summarization using machine learning techniques. Utilizing the Samsum dataset, our model generates concise summaries while retaining key information. Improves content comprehension and efficiency for information retrieval, content curation, and productivity enhancement.

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saibattula93/Text-summarization-project

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End to End Text Summarizer Project 📚

Workflows 🚀

  1. 🛠️ Update config.yaml for project configurations.
  2. ⚙️ Update params.yaml with necessary parameters.
  3. 📖 Update entity details.
  4. 📂 Update the configuration manager in the src config folder.
  5. 🧩 Update the components.
  6. 🔄 Update the pipeline.
  7. 🚀 Update the main.py for project execution.
  8. 📲 Update the app.py for user interface.

How to Run? 🏃‍♀️

STEPS:

👯‍♂️ Clone the repository

https://github.com/saibattula93/Text-summarization-project

📦 Create a conda environment after opening the repository

conda create -n summary python=3.8 -y

conda activate summary

🛠 Install the requirements

pip install -r requirements.txt

🚀 Finally, run the following command

python app.py

🌐 Now, open up your local host and port

AWS-CICD-Deployment-with-Github-Actions 🚢

1. Login to AWS console 🔑

2. Create IAM user for deployment 🤖

# With specific access

1. EC2 access: Virtual machine management.

2. ECR: Elastic Container Registry to save your Docker images in AWS.

# Description: About the deployment 🚀

1. Build Docker image of the source code.

2. Push your Docker image to ECR.

3. Launch Your EC2.

4. Pull Your image from ECR in EC2.

5. Launch your Docker image in EC2.

# Policy:

1. AmazonEC2ContainerRegistryFullAccess

2. AmazonEC2FullAccess

3. Create ECR repo to store/save Docker image

- Save the URI: 566373416292.dkr.ecr.us-east-1.amazonaws.com/text-s

4. Create EC2 machine (Ubuntu) 🖥️

5. Open EC2 and Install Docker in 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

6. Configure EC2 as self-hosted runner:

Setting > Actions > Runner > New Self-hosted Runner > Choose OS > Then run the command one by one

7. Setup GitHub secrets:

AWS_ACCESS_KEY_ID=

AWS_SECRET_ACCESS_KEY=

AWS_REGION = us-east-1

AWS_ECR_LOGIN_URI = demo >> 566373416292.dkr.ecr.ap-south-1.amazonaws.com

ECR_REPOSITORY_NAME = simple-app 📦

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Automating text summarization using machine learning techniques. Utilizing the Samsum dataset, our model generates concise summaries while retaining key information. Improves content comprehension and efficiency for information retrieval, content curation, and productivity enhancement.

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