Show HN: Open-Source API for AI Presentation Generation

3 months ago 4

Presenton is an open-source application for generating presentations with AI — all running locally on your device. Stay in control of your data and privacy while using models like OpenAI and Gemini, or use your own hosted models through Ollama.

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For detailed setup guides, API documentation, and advanced configuration options, visit our Official Documentation

✨ More Freedom with AI Presentations

✅ Bring Your Own Key — Only pay for what you use. OpenAI, Gemini (More coming soon...)
✅ API Presentation Generation — Host as API to generate presentations over requests
✅ Ollama Support — Run open-source models locally with Ollama integration
✅ OpenAI API Compatibility — Use any OpenAI-compatible API endpoint with your own models
✅ Runs Locally — All code runs on your device
✅ Privacy-First — No tracking, no data stored by us
✅ Flexible — Generate presentations from prompts or outlines
✅ Export Ready — Save as PowerPoint (PPTX) and PDF
✅ Fully Open-Source — Apache 2.0 licensed

Deploy on Cloud (one click deployment)

Linux/MacOS (Bash/Zsh Shell):

docker run -it --name presenton -p 5000:80 -v "./user_data:/app/user_data" ghcr.io/presenton/presenton:latest

docker run -it --name presenton -p 5000:80 -v "${PWD}\user_data:/app/user_data" ghcr.io/presenton/presenton:latest

Open http://localhost:5000 on browser of your choice to use Presenton.

Note: You can replace 5000 with any other port number of your choice to run Presenton on a different port number.

Deployment Configurations

You may want to directly provide your API KEYS as environment variables and keep them hidden. You can set these environment variables to achieve it.

CAN_CHANGE_KEYS=[true/false]: Set this to false if you want to keep API Keys hidden and make them unmodifiable.
LLM=[openai/google/ollama/custom]: Select LLM of your choice.
OPENAI_API_KEY=[Your OpenAI API Key]: Provide this if LLM is set to openai
GOOGLE_API_KEY=[Your Google API Key]: Provide this if LLM is set to google
OLLAMA_URL=[Custom Ollama URL]: Provide this if you want to custom Ollama URL and LLM is set to ollama
OLLAMA_MODEL=[Ollama Model ID]: Provide this if LLM is set to ollama
CUSTOM_LLM_URL=[Custom OpenAI Compatible URL]: Provide this if LLM is set to custom
CUSTOM_LLM_API_KEY=[Custom OpenAI Compatible API KEY]: Provide this if LLM is set to custom
CUSTOM_MODEL=[Custom Model ID]: Provide this if LLM is set to custom
PEXELS_API_KEY=[Your Pexels API Key]: Provide this to generate images if LLM is set to ollama or custom

docker run -it --name presenton -p 5000:80 -e LLM="openai" -e OPENAI_API_KEY="******" -e CAN_CHANGE_KEYS="false" -v "./user_data:/app/user_data" ghcr.io/presenton/presenton:latest

docker run -it --name presenton -p 5000:80 -e LLM="ollama" -e OLLAMA_MODEL="llama3.2:3b" -e PEXELS_API_KEY="*******" -e CAN_CHANGE_KEYS="false" -v "./user_data:/app/user_data" ghcr.io/presenton/presenton:latest

Using OpenAI Compatible API

docker run -it -p 5000:80 -e CAN_CHANGE_KEYS="false" -e LLM="custom" -e CUSTOM_LLM_URL="http://*****" -e CUSTOM_LLM_API_KEY="*****" -e CUSTOM_MODEL="llama3.2:3b" -v "./user_data:/app/user_data" ghcr.io/presenton/presenton:latest

Running Presenton with GPU Support

To use GPU acceleration with Ollama models, you need to install and configure the NVIDIA Container Toolkit. This allows Docker containers to access your NVIDIA GPU.

Once the NVIDIA Container Toolkit is installed and configured, you can run Presenton with GPU support by adding the --gpus=all flag:

docker run -it --name presenton --gpus=all -p 5000:80 -e LLM="ollama" -e OLLAMA_MODEL="llama3.2:3b" -e PEXELS_API_KEY="*******" -e CAN_CHANGE_KEYS="false" -v "./user_data:/app/user_data" ghcr.io/presenton/presenton:latest

Note: GPU acceleration significantly improves the performance of Ollama models, especially for larger models. Make sure you have sufficient GPU memory for your chosen model.

Generate Presentation over API

Endpoint: /api/v1/ppt/generate/presentation

Method: POST

Content-Type: multipart/form-data

Note: Make sure to set Content-Type as multipart/form-data and not application/json.

Parameter Type Required Description

prompt	string	Yes	The main topic or prompt for generating the presentation
n_slides	integer	No	Number of slides to generate (default: 8, min: 5, max: 15)
language	string	No	Language for the presentation (default: "English")
theme	string	No	Presentation theme (default: "light"). Available options: "light", "dark", "cream", "royal_blue", "faint_yellow", "light_red", "dark_pink"
documents	File[]	No	Optional list of document files to include in the presentation. Supported file types: PDF, TXT, PPTX, DOCX
export_as	string	No	Export format ("pptx" or "pdf", default: "pptx")

{ "presentation_id": "string", "path": "string", "edit_path": "string" }

curl -X POST http://localhost:5000/api/v1/ppt/generate/presentation \ -F "prompt=Introduction to Machine Learning" \ -F "n_slides=5" \ -F "language=English" \ -F "theme=light" \ -F "export_as=pptx"

{ "presentation_id": "d3000f96-096c-4768-b67b-e99aed029b57", "path": "/static/user_data/d3000f96-096c-4768-b67b-e99aed029b57/Introduction_to_Machine_Learning.pptx", "edit_path": "/presentation?id=d3000f96-096c-4768-b67b-e99aed029b57" }

Note: Make sure to prepend your server's root URL to the path and edit_path fields in the response to construct valid links.

For detailed info checkout API documentation.