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obsidian/01 Projects/presenton/Presenton.md
Vadym Samoilenko c352ac8e52 vault backup: 2026-04-29 14:50:31
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name client status tech local_path deploy url tags created server port db
Presenton Open-source (presenton.ai) active
Python 3.11
FastAPI
Next.js 14
SQLModel
python-pptx
OpenAI/Google/Anthropic LLMs
Docker
/Users/ai_leed/Documents/Projects/Oliver/presenton docker compose up production http://localhost:5000
oliver
presentation
ai
open-source
2026-04-14 local 5000 SQLite

Overview

Presenton is an open-source, self-hosted AI presentation generator that transforms prompts, documents, or existing PPTX files into fully designed presentations (PPTX/PDF format). It supports multiple LLM providers (OpenAI, Google, Anthropic, Ollama, custom endpoints) and image providers (DALL-E, Gemini, Pexels, ComfyUI), includes a built-in MCP server for AI agent integration, and exposes a REST API for programmatic access. The project is production-ready, actively maintained, and Apache 2.0 licensed.

Tech Stack

  • Frontend: Next.js 14 (App Router), React, Redux Toolkit, TypeScript
  • Backend: FastAPI (Python 3.11), SQLModel (ORM), uvicorn
  • Database: SQLite (default, can override with PostgreSQL/MySQL via DATABASE_URL)
  • Infrastructure: Docker (single container), nginx reverse proxy, LibreOffice (PDF export), Puppeteer/Chromium
  • AI/ML: OpenAI (GPT-4, DALL-E, GPT-Image-1.5), Google Gemini, Anthropic Claude, Ollama (local models), custom OpenAI-compatible endpoints
  • Key libraries: python-pptx (PPTX generation), docling/pdfplumber (document extraction), fastmcp (MCP server), Pillow (image processing)

Architecture

Presenton runs as a single Docker container with four coordinated processes spawned by start.js:

  • nginx (port 80) — reverse proxy and static file server
  • FastAPI (port 8000) — backend REST API and core logic
  • Next.js (port 3000) — frontend SSR
  • MCP Server (port 8001) — AI agent integration via Claude Desktop
  • Ollama (port 11434) — optional local LLM serving

All processes are internally networked; external access is exclusively through nginx on port 80 (mapped to host port 5000).

Presentation Generation Pipeline

User Input (prompt/files/PPTX)
    ↓
[Outline Generation] — LLM streams slide outlines (SSE)
    ↓
[Structure Assignment] — LLM assigns layout index per slide
    ↓
[Slide Content] — Batch of 10 slides: content generation
    ↓
[Asset Fetching] — Images fetched/generated concurrently per slide
    ↓
[Export] — python-pptx builds PPTX; LibreOffice converts to PDF
    ↓
[Webhook] — presentation.generation.completed event fired

Data Model

  • PresentationModel — metadata (title, template, status, content type)
  • SlideModel[] — per-slide content (outline, title, bullet points, speaker notes, layout index)
  • ImageAsset[] — images per slide (URL, provider, generation prompt, alt text)

All persisted in SQLite at /app_data/fastapi.db.

Dev Commands

FastAPI Backend

cd servers/fastapi

# Install uv package manager
pip install uv

# Install dependencies
uv sync

# Run development server (requires APP_DATA_DIRECTORY env var)
APP_DATA_DIRECTORY=./app_data uv run python server.py --port 8000

# Run tests
uv run pytest

# Lint/format
uv run ruff check .

Next.js Frontend

cd servers/nextjs

# Install dependencies
npm install

# Dev mode with HMR (connects to FastAPI at localhost:8000)
npm run dev

# Production build
npm run build
npm run start

# Lint
npm run lint

# E2E tests (Cypress)
npx cypress open      # interactive
npx cypress run       # headless

Full Stack (Docker)

# Development with hot-reload
docker compose up development

# Production
docker compose up production

# GPU-accelerated (NVIDIA)
docker compose up production-gpu

# View logs
docker compose logs -f production

# Stop and clean up
docker compose down

Deployment

  • Server: Local (self-hosted)
  • Deploy: docker compose up production or docker run -it --name presenton -p 5000:80 [env vars] ghcr.io/presenton/presenton:latest
  • URL: http://localhost:5000
  • Port: 5000 (host) → 80 (container)
  • Service: None (container-based)
  • Local path: /Users/ai_leed/Documents/Projects/Oliver/presenton
  • Image: ghcr.io/presenton/presenton:latest
  • Base: python:3.11-slim-bookworm
  • Persistent volume: ./app_data → /app_data

Quick Start

git clone https://github.com/presenton/presenton.git
cd presenton

docker run -it --name presenton -p 5000:80 \
  -e LLM="openai" \
  -e OPENAI_API_KEY="sk-..." \
  -e IMAGE_PROVIDER="dall-e-3" \
  -v "./app_data:/app_data" \
  ghcr.io/presenton/presenton:latest

# Open http://localhost:5000

Environment Variables

LLM Configuration:

  • LLM — Provider: openai, google, anthropic, ollama, custom
  • OPENAI_API_KEY — OpenAI API key (required for OpenAI LLM or DALL-E/GPT-Image)
  • OPENAI_MODEL — Model ID (default: gpt-4-1)
  • GOOGLE_API_KEY — Google API key (Gemini LLM or image generation)
  • GOOGLE_MODEL — Gemini model ID (default: models/gemini-2.0-flash)
  • ANTHROPIC_API_KEY — Claude API key
  • ANTHROPIC_MODEL — Claude model ID (default: claude-3-5-sonnet-20241022)
  • OLLAMA_URL — Ollama server (default: http://localhost:11434)
  • OLLAMA_MODEL — Model to use (e.g., llama3.2:3b)
  • CUSTOM_LLM_URL — OpenAI-compatible endpoint URL
  • CUSTOM_LLM_API_KEY — API key for custom endpoint
  • CUSTOM_MODEL — Model ID for custom endpoint
  • TOOL_CALLS — Use tool calls for structured output (default: false)
  • DISABLE_THINKING — Disable chain-of-thought (default: false)
  • EXTENDED_REASONING — Enable extended reasoning (default: empty)
  • WEB_GROUNDING — Enable LLM web search (default: false)

Image Provider Configuration:

  • IMAGE_PROVIDER — Provider: dall-e-3, gpt-image-1.5, gemini, pexels, pixabay, comfyui
  • PEXELS_API_KEY — Pexels API key
  • PIXABAY_API_KEY — Pixabay API key
  • COMFYUI_URL — ComfyUI server URL (for local image generation)
  • COMFYUI_WORKFLOW — ComfyUI workflow JSON path

Data & Infrastructure:

  • APP_DATA_DIRECTORY — Root for persistent data (default: /app_data)
  • TEMP_DIRECTORY — Temp file staging (default: /tmp/presenton)
  • DATABASE_URL — Override SQLite; use postgresql:// or mysql:// for other DBs
  • PUPPETEER_EXECUTABLE_PATH — Chromium path (default: /usr/bin/chromium)
  • CAN_CHANGE_KEYS — Allow UI to modify API keys (default: true)

API / Endpoints

REST API Base: http://localhost:5000/api/v1/

Key Endpoints:

  • POST /ppt/presentation/generate — Generate presentation (sync, returns PPTX/PDF path)
  • POST /ppt/presentation/create — Save new presentation (returns ID)
  • GET /ppt/outlines/stream/{id} — Stream outline JSON (SSE)
  • POST /ppt/presentation/prepare — Assign layouts and structure
  • GET /ppt/presentation/stream/{id} — Stream slide content (SSE)
  • POST /ppt/presentation/export — Export to PPTX or PDF
  • POST /ppt/pptx-slides/process — Analyze uploaded PPTX (extract slides, fonts, XML)
  • POST /ppt/slide-to-html/ — Convert PPTX slide to HTML

MCP Server:

  • http://localhost:5000/mcp — FastMCP HTTP endpoint for Claude Desktop integration

Swagger UI: http://localhost:5000/docs

Known Issues

Git

  • Remote: https://github.com/presenton/presenton.git
  • Latest commits: Recent work includes new templates refactor, MCP OpenAI spec fixes, Ukrainian language support, GPT-Image-1.5 integration, local ComfyUI image provider support, and NanoBanana integration
  • License: Apache 2.0

Additional Resources

  • Architecture & Design: See docs/project/architecture.md for detailed data flows and component interactions

Sessions

2026-04-14 – Project catalogued

Done: Added to Obsidian second brain.

Change Log

Date Requested Changed Files
2026-04-14 Initial setup Note created —

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