Harnessing the power of Generative AI (Artificial Intelligence) and LLM (Large Language Models), creating dynamic and engaging PowerPoint presentations has never been easier. By leveraging cutting-edge technology, users can now generate compelling slideshows on a myriad of topics with unprecedented ease and efficiency.
Generative AI refers to a class of algorithms that can autonomously produce content, mimicking human creativity and decision-making processes. These algorithms are trained on vast datasets, enabling them to understand and generate contextually relevant content. LLM, in particular, stands out as a powerful tool in this domain, capable of understanding and generating human-like text with remarkable accuracy.
The following technologies and libraries were used in the development of this chatbot:
Python: Programming language used for the implementation.
Langchain: LangChain is a framework designed to simplify the creation of applications using large language models.
Ctransformers: The C Transformers library provides Python bindings for GGML/GGUF models.
Model Used: Llama 2 is a family of pre-trained and fine-tuned large language models (LLMs) released by Meta AI in 2023. Released free of charge for research and commercial use, Llama 2 AI models are capable of a variety of natural language processing (NLP) tasks, from text generation to programming code.
To get started with the Open-source AI equipped PowerPoint Generator, follow these steps:
- Clone the repository
git clone https://github.com/Ginga1402/Generate_PPT_using_llama2
- Install the required dependencies:
pip install -r requirements.txt
- Run the Streamlit application
streamlit run app.py
The application uses a simple command-line interface. Enter your topic, and the application will generate a Power point presentation for you.
Contributions to this project are welcome! If you have ideas for improvements, bug fixes, or new features, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.