slide-deck-ai

Co-create a PowerPoint presentation with Generative AI

Stars: 136

Visit

SlideDeck AI is a tool that leverages Generative Artificial Intelligence to co-create slide decks on any topic. Users can describe their topic and let SlideDeck AI generate a PowerPoint slide deck, streamlining the presentation creation process. The tool offers an iterative workflow with a conversational interface for creating and improving presentations. It uses Mistral Nemo Instruct to generate initial slide content, searches and downloads images based on keywords, and allows users to refine content through additional instructions. SlideDeck AI provides pre-defined presentation templates and a history of instructions for users to enhance their presentations.

README:

title: SlideDeck AI emoji: 🏢 colorFrom: yellow colorTo: green sdk: streamlit sdk_version: 1.32.2 app_file: app.py pinned: false license: mit

SlideDeck AI

We spend a lot of time on creating the slides and organizing our thoughts for any presentation. With SlideDeck AI, co-create slide decks on any topic with Generative Artificial Intelligence. Describe your topic and let SlideDeck AI generate a PowerPoint slide deck for you—it's as simple as that!

Star History

Process

SlideDeck AI works in the following way:

Given a topic description, it uses a Large Language Model (LLM) to generate the initial content of the slides. The output is generated as structured JSON data based on a pre-defined schema.
Next, it uses the keywords from the JSON output to search and download a few images with a certain probability.
Subsequently, it uses the python-pptx library to generate the slides, based on the JSON data from the previous step. A user can choose from a set of pre-defined presentation templates.
At this stage onward, a user can provide additional instructions to refine the content. For example, one can ask to add another slide or modify an existing slide. A history of instructions is maintained.
Every time SlideDeck AI generates a PowerPoint presentation, a download button is provided. Clicking on the button will download the file.

Summary of the LLMs

SlideDeck AI allows the use of different LLMs from five online providers—Azure OpenAI, Hugging Face, Google, Cohere, and Together AI. The latter four service providers offer generous free usage of relevant LLMs without requiring any billing information.

Based on several experiments, SlideDeck AI generally recommends the use of Mistral NeMo, Gemini Flash, and GPT-4o to generate the slide decks.

The supported LLMs offer different styles of content generation. Use one of the following LLMs along with relevant API keys/access tokens, as appropriate, to create the content of the slide deck:

LLM	Provider (code)	Requires API key	Characteristics
Mistral 7B Instruct v0.2	Hugging Face (`hf`)	Optional but strongly encouraged; get here	Faster, shorter content
Mistral NeMo Instruct 2407	Hugging Face (`hf`)	Optional but strongly encouraged; get here	Slower, longer content
Gemini 2.0 Flash	Google Gemini API (`gg`)	Mandatory; get here	Faster, longer content
Gemini 2.0 Flash Lite	Google Gemini API (`gg`)	Mandatory; get here	Fastest, longer content
GPT	Azure OpenAI (`az`)	Mandatory; get here NOTE: You need to have your subscription/billing set up	Faster, longer content
Command R+	Cohere (`co`)	Mandatory; get here	Shorter, simpler content
Llama 3.3 70B Instruct Turbo	Together AI (`to`)	Mandatory; get here	Detailed, slower
Llama 3.1 8B Instruct Turbo 128K	Together AI (`to`)	Mandatory; get here	Shorter

The Mistral models (via Hugging Face) do not mandatorily require an access token. In other words, you are always free to use these two LLMs, subject to Hugging Face's usage constrains. However, you are strongly encouraged to get and use your own Hugging Face access token.

IMPORTANT: SlideDeck AI does NOT store your API keys/tokens or transmit them elsewhere. If you provide your API key, it is only used to invoke the relevant LLM to generate contents. That's it! This is an Open-Source project, so feel free to audit the code and convince yourself.

In addition, offline LLMs provided by Ollama can be used. Read below to know more.

Icons

SlideDeck AI uses a subset of icons from bootstrap-icons-1.11.3 (MIT license) in the slides. A few icons from SVG Repo (CC0, MIT, and Apache licenses) are also used.

Local Development

SlideDeck AI uses LLMs via different providers, such as Hugging Face, Google, and Gemini. To run this project by yourself, you need to provide the HUGGINGFACEHUB_API_TOKEN API key, for example, in a .env file. Alternatively, you can provide the access token in the app's user interface itself (UI). For other LLM providers, the API key can only be specified in the UI. For image search, the PEXEL_API_KEY should be made available as an environment variable. Visit the respective websites to obtain the API keys.

Offline LLMs Using Ollama

SlideDeck AI allows the use of offline LLMs to generate the contents of the slide decks. This is typically suitable for individuals or organizations who would like to use self-hosted LLMs for privacy concerns, for example.

Offline LLMs are made available via Ollama. Therefore, a pre-requisite here is to have Ollama installed on the system and the desired LLM pulled locally.

In addition, the RUN_IN_OFFLINE_MODE environment variable needs to be set to True to enable the offline mode. This, for example, can be done using a .env file or from the terminal. The typical steps to use SlideDeck AI in offline mode (in a bash shell) are as follows:

# Install Git Large File Storage (LFS)
sudo apt install git-lfs
git lfs install

ollama list  # View locally available LLMs
export RUN_IN_OFFLINE_MODE=True  # Enable the offline mode to use Ollama
git clone https://github.com/barun-saha/slide-deck-ai.git
cd slide-deck-ai
git lfs pull  # Pull the PPTX template files

python -m venv venv  # Create a virtual environment
source venv/bin/activate  # On a Linux system
pip install -r requirements.txt

streamlit run ./app.py  # Run the application

The .env file should be created inside the slide-deck-ai directory.

The UI is similar to the online mode. However, rather than selecting an LLM from a list, one has to write the name of the Ollama model to be used in a textbox. There is no API key asked here.

The online and offline modes are mutually exclusive. So, setting RUN_IN_OFFLINE_MODE to False will make SlideDeck AI use the online LLMs (i.e., the "original mode."). By default, RUN_IN_OFFLINE_MODE is set to False.

Finally, the focus is on using offline LLMs, not going completely offline. So, Internet connectivity would still be required to fetch the images from Pexels.

Live Demo

SlideDeck AI on Hugging Face Spaces
Demo video of the chat interface on YouTube
Demo video on using Azure OpenAI

Award

SlideDeck AI has won the 3rd Place in the Llama 2 Hackathon with Clarifai in 2023.

For Tasks:

Click tags to check more tools for each tasks

create slides improve presentation refine content download slides generate templates

For Jobs:

presentation designer content creator marketing specialist educational instructor business consultant

Alternative AI tools for slide-deck-ai

Similar Open Source Tools

slide-deck-ai

github

: 136

air-script

AirScript is a domain-specific language for expressing AIR constraints for STARKs, with the goal of enabling writing and auditing constraints without the need to learn a specific programming language. It also aims to perform automated optimizations and output constraint evaluator code in multiple target languages. The project is organized into several crates including Parser, MIR, AIR, Winterfell code generator, ACE code generator, and AirScript CLI for transpiling AIRs to target languages.

github

: 90

codebase-context-spec

The Codebase Context Specification (CCS) project aims to standardize embedding contextual information within codebases to enhance understanding for both AI and human developers. It introduces a convention similar to `.env` and `.editorconfig` files but focused on documenting code for both AI and humans. By providing structured contextual metadata, collaborative documentation guidelines, and standardized context files, developers can improve code comprehension, collaboration, and development efficiency. The project includes a linter for validating context files and provides guidelines for using the specification with AI assistants. Tooling recommendations suggest creating memory systems, IDE plugins, AI model integrations, and agents for context creation and utilization. Future directions include integration with existing documentation systems, dynamic context generation, and support for explicit context overriding.

github

: 75

jaison-core

J.A.I.son is a Python project designed for generating responses using various components and applications. It requires specific plugins like STT, T2T, TTSG, and TTSC to function properly. Users can customize responses, voice, and configurations. The project provides a Discord bot, Twitch events and chat integration, and VTube Studio Animation Hotkeyer. It also offers features for managing conversation history, training AI models, and monitoring conversations.

github

: 216

bao

BaoGPT is an AI project designed to facilitate asking questions about YouTube videos. It features a web UI based on Gradio and Discord integration. The tool utilizes a pipeline that routes input questions to either a greeting-like branch or a query & answer branch. The query analysis is performed by the LLM, which extracts attributes as filters and optimizes and rewrites questions for better vector retrieval in the vector DB. The tool then retrieves top-k candidates for grading and outputs final relative documents after grading. Lastly, the LLM performs summarization based on the reranking output, providing answers and attaching sources to the user.

github

: 123

stagehand

Stagehand is an AI web browsing framework that simplifies and extends web automation using three simple APIs: act, extract, and observe. It aims to provide a lightweight, configurable framework without complex abstractions, allowing users to automate web tasks reliably. The tool generates Playwright code based on atomic instructions provided by the user, enabling natural language-driven web automation. Stagehand is open source, maintained by the Browserbase team, and supports different models and model providers for flexibility in automation tasks.

github

: 5.2k

reai-ida

RevEng.AI IDA Pro Plugin is a tool that integrates with the RevEng.AI platform to provide various features such as uploading binaries for analysis, downloading analysis logs, renaming function names, generating AI summaries, synchronizing functions between local analysis and the platform, and configuring plugin settings. Users can upload files for analysis, synchronize function names, rename functions, generate block summaries, and explain function behavior using this plugin. The tool requires IDA Pro v8.0 or later with Python 3.9 and higher. It relies on the 'reait' package for functionality.

github

: 61

ersilia

The Ersilia Model Hub is a unified platform of pre-trained AI/ML models dedicated to infectious and neglected disease research. It offers an open-source, low-code solution that provides seamless access to AI/ML models for drug discovery. Models housed in the hub come from two sources: published models from literature (with due third-party acknowledgment) and custom models developed by the Ersilia team or contributors.

github

: 249

cloudflare-rag

This repository provides a fullstack example of building a Retrieval Augmented Generation (RAG) app with Cloudflare. It utilizes Cloudflare Workers, Pages, D1, KV, R2, AI Gateway, and Workers AI. The app features streaming interactions to the UI, hybrid RAG with Full-Text Search and Vector Search, switchable providers using AI Gateway, per-IP rate limiting with Cloudflare's KV, OCR within Cloudflare Worker, and Smart Placement for workload optimization. The development setup requires Node, pnpm, and wrangler CLI, along with setting up necessary primitives and API keys. Deployment involves setting up secrets and deploying the app to Cloudflare Pages. The project implements a Hybrid Search RAG approach combining Full Text Search against D1 and Hybrid Search with embeddings against Vectorize to enhance context for the LLM.

github

: 93

ai-exploits

AI Exploits is a repository that showcases practical attacks against AI/Machine Learning infrastructure, aiming to raise awareness about vulnerabilities in the AI/ML ecosystem. It contains exploits and scanning templates for responsibly disclosed vulnerabilities affecting machine learning tools, including Metasploit modules, Nuclei templates, and CSRF templates. Users can use the provided Docker image to easily run the modules and templates. The repository also provides guidelines for using Metasploit modules, Nuclei templates, and CSRF templates to exploit vulnerabilities in machine learning tools.

github

: 1.3k

sunnypilot

Sunnypilot is a fork of comma.ai's openpilot, offering a unique driving experience for over 250+ supported car makes and models with modified behaviors of driving assist engagements. It complies with comma.ai's safety rules and provides features like Modified Assistive Driving Safety, Dynamic Lane Profile, Enhanced Speed Control, Gap Adjust Cruise, and more. Users can install it on supported devices and cars following detailed instructions, ensuring a safe and enhanced driving experience.

github

: 1.6k

zep-python

Zep is an open-source platform for building and deploying large language model (LLM) applications. It provides a suite of tools and services that make it easy to integrate LLMs into your applications, including chat history memory, embedding, vector search, and data enrichment. Zep is designed to be scalable, reliable, and easy to use, making it a great choice for developers who want to build LLM-powered applications quickly and easily.

github

: 60

airflow

Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.

github

: 42.3k

council

Council is an open-source platform designed for the rapid development and deployment of customized generative AI applications using teams of agents. It extends the LLM tool ecosystem by providing advanced control flow and scalable oversight for AI agents. Users can create sophisticated agents with predictable behavior by leveraging Council's powerful approach to control flow using Controllers, Filters, Evaluators, and Budgets. The framework allows for automated routing between agents, comparing, evaluating, and selecting the best results for a task. Council aims to facilitate packaging and deploying agents at scale on multiple platforms while enabling enterprise-grade monitoring and quality control.

github

: 815

dlio_benchmark

DLIO is an I/O benchmark tool designed for Deep Learning applications. It emulates modern deep learning applications using Benchmark Runner, Data Generator, Format Handler, and I/O Profiler modules. Users can configure various I/O patterns, data loaders, data formats, datasets, and parameters. The tool is aimed at emulating the I/O behavior of deep learning applications and provides a modular design for flexibility and customization.

github

: 90

langchainjs-quickstart-demo

Discover the journey of building a generative AI application using LangChain.js and Azure. This demo explores the development process from idea to production, using a RAG-based approach for a Q&A system based on YouTube video transcripts. The application allows to ask text-based questions about a YouTube video and uses the transcript of the video to generate responses. The code comes in two versions: local prototype using FAISS and Ollama with LLaMa3 model for completion and all-minilm-l6-v2 for embeddings, and Azure cloud version using Azure AI Search and GPT-4 Turbo model for completion and text-embedding-3-large for embeddings. Either version can be run as an API using the Azure Functions runtime.

github

: 53

For similar tasks

slide-deck-ai

github

: 136

PPTist

PPTist is a web-based presentation application that replicates most features of Microsoft Office PowerPoint. It supports various elements like text, images, shapes, charts, tables, videos, audio, and formulas. Users can edit and present slides directly in a web browser. It offers easy development with Vue 3.x and TypeScript, user-friendly experience with context menu and keyboard shortcuts, and feature-rich functionalities including AI-generated PPTs and mobile editing. PPTist aims to provide a desktop application-level experience for creating presentations.

github

: 6.4k

AI-on-the-edge-device-docs

This repository contains documentation for the AI on the Edge Device Project. Users can edit Markdown documents in the 'docs' folder, create Pull Requests to merge changes, and Github Actions will regenerate the documentation on the 'gh-pages' branch. The documentation includes parameter documentation, template generation for new parameters, formatting options like boxes using the admonition extension, and local testing instructions using MkDocs.

github

: 79

ComfyUI-Tara-LLM-Integration

Tara is a powerful node for ComfyUI that integrates Large Language Models (LLMs) to enhance and automate workflow processes. With Tara, you can create complex, intelligent workflows that refine and generate content, manage API keys, and seamlessly integrate various LLMs into your projects. It comprises nodes for handling OpenAI-compatible APIs, saving and loading API keys, composing multiple texts, and using predefined templates for OpenAI and Groq. Tara supports OpenAI and Grok models with plans to expand support to together.ai and Replicate. Users can install Tara via Git URL or ComfyUI Manager and utilize it for tasks like input guidance, saving and loading API keys, and generating text suitable for chaining in workflows.

github

: 79

For similar jobs

docq

Docq is a private and secure GenAI tool designed to extract knowledge from business documents, enabling users to find answers independently. It allows data to stay within organizational boundaries, supports self-hosting with various cloud vendors, and offers multi-model and multi-modal capabilities. Docq is extensible, open-source (AGPLv3), and provides commercial licensing options. The tool aims to be a turnkey solution for organizations to adopt AI innovation safely, with plans for future features like more data ingestion options and model fine-tuning.

github

: 51

slide-deck-ai

github

: 136

TinyTroupe

TinyTroupe is an experimental Python library that leverages Large Language Models (LLMs) to simulate artificial agents called TinyPersons with specific personalities, interests, and goals in simulated environments. The focus is on understanding human behavior through convincing interactions and customizable personas for various applications like advertisement evaluation, software testing, data generation, project management, and brainstorming. The tool aims to enhance human imagination and provide insights for better decision-making in business and productivity scenarios.

github

: 5.2k

LLMStack

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

github

: 1.5k

daily-poetry-image

Daily Chinese ancient poetry and AI-generated images powered by Bing DALL-E-3. GitHub Action triggers the process automatically. Poetry is provided by Today's Poem API. The website is built with Astro.

github

: 492

exif-photo-blog

EXIF Photo Blog is a full-stack photo blog application built with Next.js, Vercel, and Postgres. It features built-in authentication, photo upload with EXIF extraction, photo organization by tag, infinite scroll, light/dark mode, automatic OG image generation, a CMD-K menu with photo search, experimental support for AI-generated descriptions, and support for Fujifilm simulations. The application is easy to deploy to Vercel with just a few clicks and can be customized with a variety of environment variables.

github

: 992

SillyTavern

SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters you or the community create. SillyTavern is a fork of TavernAI 1.2.8 which is under more active development and has added many major features. At this point, they can be thought of as completely independent programs.

github

: 18.3k

Twitter-Insight-LLM

This project enables you to fetch liked tweets from Twitter (using Selenium), save it to JSON and Excel files, and perform initial data analysis and image captions. This is part of the initial steps for a larger personal project involving Large Language Models (LLMs).

github

: 401