Presenton: Open-Source AI Presentation Generator Puts Privacy and Control in Developers' Hands

In an era where AI-powered tools often demand cloud dependencies and data concessions, Presenton delivers a compelling counter-narrative. This newly open-sourced application generates presentations entirely on-device, allowing developers to harness AI from OpenAI, Google Gemini, or self-hosted models via Ollama—all while retaining complete ownership of their data. Licensed under Apache 2.0, Presenton challenges proprietary alternatives like Gamma by prioritizing privacy, flexibility, and infrastructure control.

Why Local AI Generation Matters

"The shift toward local AI execution isn't just about performance—it's a fundamental reclamation of data sovereignty," notes a cybersecurity architect familiar with the project. Presenton eliminates third-party data exposure risks by processing everything locally. Users bring their own API keys (BYOK), paying only for consumed resources without surrendering sensitive content to external servers. This is particularly crucial for industries handling confidential data, where cloud-based AI tools pose compliance nightmares.

Key technical advantages include:

• Model Agnosticism: Seamlessly switch between OpenAI, Gemini, Ollama (for local LLMs), or custom OpenAI-compatible endpoints
• Docker-First Deployment: One-command setup with GPU acceleration support for resource-intensive models
• API-Driven Automation: Programmatically generate slides via REST API for CI/CD pipelines or custom workflows
• Zero Tracking: No telemetry or data retention—user files stay on their infrastructure

Technical Deep Dive: Deployment and API Workflow

Deploying Presenton is streamlined for developer workflows. For Ollama with GPU acceleration (using NVIDIA Container Toolkit):

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

The API enables batch presentation generation—ideal for automated reporting. A multipart/form-data request to /api/v1/ppt/generate/presentation accepts prompts, slide counts, themes, and supporting documents (PDF/TXT/PPTX):

curl -X POST http://localhost:5000/api/v1/ppt/generate/presentation \
  -F "prompt=Quantum Computing Basics" \
  -F "n_slides=8" \
  -F "theme=dark" \
  -F "export_as=pdf"

Response structure provides direct access paths:

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

The Broader Impact: A New Standard for Developer-Centric AI

Presenton reflects a rising demand for ethical AI infrastructure. By running locally, it sidesteps latency and cost issues of cloud APIs while enabling offline use—critical for remote or secure environments. The Ollama integration democratizes access to open-source models, letting teams fine-tune presentations without proprietary constraints. Upcoming features like custom HTML templates and SQL database support hint at its potential as a framework, not just a tool.

For developers drowning in manual slide creation or wary of data leaks, Presenton offers more than convenience—it represents architectural sovereignty. As AI permeates workflows, solutions prioritizing user control could redefine how enterprises approach generative tools.

Source: Presenton GitHub Repository