Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/2003harsh/blog-generation-using-llama2

The Blog Generation project uses advanced AI technologies like Llama 2, LangChain, and Hugging Face to create custom blog content. With Streamlit, users can input a topic, word count, and audience type to generate blogs quickly and efficiently. The project combines the power of LLms with a simple, interactive interface for easy content creation.
https://github.com/2003harsh/blog-generation-using-llama2

huggingface-transformers langchain llama2 llm nlp

Last synced: about 1 month ago
JSON representation

Host: GitHub
URL: https://github.com/2003harsh/blog-generation-using-llama2
Owner: 2003HARSH
License: mit
Created: 2024-05-01T13:08:05.000Z (8 months ago)
Default Branch: main
Last Pushed: 2024-07-19T13:51:57.000Z (6 months ago)
Last Synced: 2024-10-30T00:52:01.546Z (2 months ago)
Topics: huggingface-transformers, langchain, llama2, llm, nlp
Language: Python
Homepage:
Size: 46.9 KB
Stars: 0
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

# Blog Generation with Llama 2 and LangChain

Welcome to the Blog Generation project! This repository showcases an innovative tool for generating custom blogs based on user-defined topics, word counts, and audience types (beginner, intermediate, or advanced). The project leverages advanced technologies like Llama 2, LangChain, Hugging Face, and Streamlit to create a seamless blog generation experience.

![](https://github.com/2003HARSH/Blog-Generation-using-Llama2/blob/main/docs/static/blog_gen.jpg)

## Project Overview
The Blog Generation project is designed to provide an automated solution for creating engaging blog content. It uses Llama 2, a large language model (LLM), to generate high-quality textual content. The LangChain framework is employed to manage and link various AI components, while Hugging Face provides the pre-trained LLM capabilities. Streamlit is used for the frontend, enabling an interactive and user-friendly interface for users to input their blog parameters.

## Features
- **Customizable Blog Generation**: Define the topic, word count, and audience type to generate tailored blog content.
- **Advanced AI Technologies**: Utilizes Llama 2 for language processing and generation, with Hugging Face providing additional LLM support.
- **Flexible Frontend**: Streamlit is used to create a simple and intuitive user interface for interacting with the tool.
- **Rapid Content Creation**: Quickly generate blogs without the need for extensive manual writing or editing.

## Technologies Used
- **Llama 2**: A state-of-the-art large language model for generating natural language text.
- **LangChain**: A versatile framework that integrates AI components for seamless applications.
- **Hugging Face**: A leading platform for pre-trained language models and NLP frameworks.
- **Streamlit**: A popular tool for building interactive web applications and dashboards.

## Getting Started
To run this project locally, you'll need to set up a Python environment and install the necessary dependencies.

### Prerequisites
- Python 3.7 or higher
- Streamlit
- Hugging Face Transformers
- LangChain

### Installation
1. Clone this repository:
```bash
git clone https://github.com/2003HARSH/Blog-Generation-using-Llama2.git
```

2. Change to the project directory:
```bash
cd Blog-Generation-using-Llama2
```

3. Install the required dependencies:
```bash
pip install -r requirements.txt
```

4. Run the Streamlit application:
```bash
streamlit run app.py
```

5. Open the generated Streamlit URL in your browser and start generating blogs!

## Contributing
Contributions are welcome! If you'd like to contribute to this project, please create a pull request or open an issue to discuss your ideas. We appreciate your feedback and suggestions.

## License
This project is licensed under the [MIT License](LICENSE). Feel free to use and adapt the code for your own projects.

## Contact
If you have any questions or need assistance, please reach out to the project maintainer at [[email protected]]. We'd love to hear from you!