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ppt_generator's Introduction

PPT Generator

A local LLM assisted ppt generation tool

Why

Writing presentations for course assignments is just boilerplate work most often, especially when even the lecturers dont even care about it. Thats why I automated the boilerplate work, just enter a topic and the tool generates a simple presentation , enough to satisfy the base course requirement.

Running Locally

install ollama and have it up and running with command ollama serve ( applicable to some systems only )

download the required model ( this can be changed in this line )

ollama pull dolphin2.1-mistral

clone the repo and move into the directory

git clone https://github.com/Govind-S-B/ppt_generator.git
cd ppt_generator

install the required python dependencies

pip install -r requirements.txt

run the streamlit app

streamlit run main.py

ppt_generator's People

Contributors

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Stargazers

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Watchers

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Forkers

rkp64 hugomiguel-code a24ibrah iotemylabs

ppt_generator's Issues

Missing requirements.txt

In the installation instructions a requirements.txt is mentioned but there is none available.

Embedded Presentation Preview in Streamlit

Streamlit supports custom widgets , a custom widget that can preview presentations before downloading will be good to have to check out the generated response and regenerate if needed successively

Reducing Number of Prompt Cycles to improve efficiency while not impacting response quality

Right now at certain parts , the input is generated via 2 steps . One is the content generation and the other is a formatter which are two steps to just generate a list of items to be rendered on the presentation.

Trying new models and implementing the Grammar functionality from llama.cpp might help with this situation of reducing the number of prompts needed

Webscraper Integration to generate more accurate information

A webscaper + embedding search to generate more accurate information (optional since this will further slowdown the processing time).

It needs to for each slide web search the topic subtopic and title it generated and write content based on that.

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