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.
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.
- 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.
- 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.
To run this project locally, you'll need to set up a Python environment and install the necessary dependencies.
- Python 3.7 or higher
- Streamlit
- Hugging Face Transformers
- LangChain
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Clone this repository:
git clone https://github.com/2003HARSH/Blog-Generation-using-Llama2.git
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Change to the project directory:
cd Blog-Generation-using-Llama2 -
Install the required dependencies:
pip install -r requirements.txt
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Run the Streamlit application:
streamlit run app.py
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Open the generated Streamlit URL in your browser and start generating blogs!
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.
This project is licensed under the MIT License. Feel free to use and adapt the code for your own projects.
If you have any questions or need assistance, please reach out to the project maintainer at [harshnkgupta@example.com]. We'd love to hear from you!