presenton/presenton
GitHub: presenton/presenton
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You can run Presenton in two ways: Docker for a one-command setup without installing a local dev stack, or the Electron desktop app for a native app experience (ideal for development or offline use).
**Option 1: Electron (Desktop App)**Run Presenton as a native desktop application. LLM and image provider (API keys, etc.) can be configured in the app. The same environment variables used for Docker apply when running the bundled backend.
Prerequisites: Node.js (LTS), npm, Python 3.11, and
uv
(for the shared FastAPI backend in servers/fastapi).
cd electron
This installs Node dependencies, runs uv sync in the FastAPI
server, and installs Next.js dependencies.
- Run in Development
npm run dev
This compiles TypeScript and starts Electron. The backend and UI run locally
inside the desktop window.
- Build Distributable (Optional)
To create installers for Windows, macOS, or Linux:
npm run build:all
Output files are written to electron/dist
(or as configured in your electron-builder settings).
**Option 2: Docker**
- Start Presenton
Linux/MacOS (Bash/Zsh Shell):
docker run -it --name presenton -p 5000:80 -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
Windows (PowerShell):
docker run -it --name presenton -p 5000:80 -v "${PWD}\app_data:/app_data" ghcr.io/presenton/presenton:latest
- Open Presenton
Open http://localhost:5000 in the 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
The lists below match the environment variables forwarded in this repository’s **`docker-compose.yml`** (`production`, `production-gpu`, `development`, and `development-gpu`). Put values in a `.env` file next to the compose file, or export them before `docker compose up`. The Electron app backend can read the same names when run outside Docker.
Other optional variables exist in code (for example advanced Mem0 paths, LiteParse runners, or `FAST_API_INTERNAL_URL` when Next.js and FastAPI are not same-origin); they are **not** wired in `docker-compose.yml`. Supported names are discoverable from `servers/fastapi/utils/get_env.py` and the Next.js server utilities under `servers/nextjs/`.
#### LLM and API keys
- **CAN_CHANGE_KEYS**=[true/false]: Set to **false** if you want to keep API keys hidden and make them unmodifiable.
- **LLM**=[openai/google/vertex/azure/bedrock/anthropic/lmstudio/ollama/custom/codex]: Select the text **LLM**.
- **OPENAI_API_KEY**: Required if **LLM** is **openai**.
- **OPENAI_MODEL**: Required if **LLM** is **openai** (default: `gpt-4.1`).
- **GOOGLE_API_KEY**: Required if **LLM** is **google**.
- **GOOGLE_MODEL**: Required if **LLM** is **google** (default: `models/gemini-2.0-flash`).
- **VERTEX_MODEL**: Required if **LLM** is **vertex** (default: `gemini-2.5-flash`).
- **VERTEX_API_KEY**: Optional auth path for **LLM=vertex** (Vertex Express).
- **VERTEX_PROJECT** / **VERTEX_LOCATION**: Optional auth path for **LLM=vertex** when using GCP project credentials (do not combine with `VERTEX_API_KEY`).
- **VERTEX_BASE_URL**: Optional Vertex gateway/base URL override.
- **AZURE_OPENAI_MODEL**: Required if **LLM** is **azure** (deployment/model name).
- **AZURE_OPENAI_API_KEY**: Required if **LLM** is **azure**.
- **AZURE_OPENAI_API_VERSION**: Required if **LLM** is **azure** (for example `2024-10-21`).
- **AZURE_OPENAI_ENDPOINT** / **AZURE_OPENAI_BASE_URL**: At least one is required if **LLM** is **azure**.
- **AZURE_OPENAI_DEPLOYMENT**: Optional deployment override for **LLM** is **azure**.
- **BEDROCK_REGION**: Optional if **LLM** is **bedrock** (default: `us-east-1`).
- **BEDROCK_MODEL**: Required if **LLM** is **bedrock**. Use a standard model ID (example: `us.anthropic.claude-3-5-haiku-20241022-v1:0`) or a full **inference profile ARN** for newer models (example: Claude Sonnet 4.6). Passed through to Bedrock Converse as `modelId`. See **[Amazon Bedrock guide](docs/amazon-bedrock.md)**.
- **BEDROCK_API_KEY**: Optional if **LLM** is **bedrock** (API key auth; alternative to AWS keys).
- **BEDROCK_AWS_ACCESS_KEY_ID** / **BEDROCK_AWS_SECRET_ACCESS_KEY**: Required together if **LLM** is **bedrock** and `BEDROCK_API_KEY` is not set.
- **BEDROCK_AWS_SESSION_TOKEN**: Optional session token for **LLM** is **bedrock**.
- **BEDROCK_PROFILE_NAME**: Optional AWS profile name for **LLM** is **bedrock**.
- **FIREWORKS_API_KEY**: Required if **LLM** is **fireworks**.
- **FIREWORKS_MODEL**: Required if **LLM** is **fireworks** (example: `accounts/fireworks/models/llama-v3p1-8b-instruct`).
- **FIREWORKS_BASE_URL**: Optional if **LLM** is **fireworks** (default: `https://api.fireworks.ai/inference/v1`).
- **TOGETHER_API_KEY**: Required if **LLM** is **together**.
- **TOGETHER_MODEL**: Required if **LLM** is **together** (example: `openai/gpt-oss-20b`).
- **TOGETHER_BASE_URL**: Optional if **LLM** is **together** (default: `https://api.together.ai/v1`).
- **ANTHROPIC_API_KEY**: Required if **LLM** is **anthropic**.
- **ANTHROPIC_MODEL**: Required if **LLM** is **anthropic** (default: `claude-3-5-sonnet-20241022`).
- **CODEX_MODEL**: Required if **LLM** is **codex** (Codex OAuth flow; compose maps host port **1455** for the callback).
- **CUSTOM_LLM_URL**: OpenAI-compatible base URL if **LLM** is **custom**.
- **CUSTOM_LLM_API_KEY**: API key if **LLM** is **custom**.
- **CUSTOM_MODEL**: Model id if **LLM** is **custom**.
- **LMSTUDIO_BASE_URL**: Optional LM Studio base URL if **LLM** is **lmstudio** (default: `http://localhost:1234/v1`; `/v1` is auto-appended when omitted).
- **LMSTUDIO_API_KEY**: Optional API key if **LLM** is **lmstudio**.
- **LMSTUDIO_MODEL**: Required if **LLM** is **lmstudio** (example: `openai/gpt-oss-20b`).
- **DISABLE_THINKING**=[true/false]: If **true**, disables “thinking” on the custom LLM.
- **WEB_GROUNDING**=[true/false]: If **true**, enables web search for OpenAI, Google, and Anthropic models.
- **EXTENDED_REASONING**=[true/false]: Enables extended reasoning where supported by the configured stack.
#### Ollama
Use when **LLM** is **ollama**:
- **OLLAMA_URL**: Base URL of the Ollama HTTP API (e.g. `http://host.docker.internal:11434` from Docker).
- **OLLAMA_MODEL**: Model name in Ollama (e.g. `llama3.2:3b`).
- **START_OLLAMA**=[true/false]: Container entrypoint (`start.js`): optional install + `ollama serve`. Default **false** (`development` / `production` compose).
#### Presentation memory (Mem0 OSS)
Mem0 uses local Qdrant + SQLite (OSS); memory is scoped per presentation.
By default the Docker runtime now points Mem0 at a local Ollama-compatible LLM endpoint, so it no longer needs an OpenAI key just to initialize. If you want to use OpenAI instead, set `MEM0_LLM_BASE_URL`/`MEM0_LLM_API_KEY` to your OpenAI-compatible endpoint and key.
Docker images install the default spaCy model (`en_core_web_sm`) during build so Mem0 can start without extra setup on each run.
| Variable | Purpose |
| ---------------------------- | ---------------------------------------------------------------------------------------------------------------- |
| **MEM0_ENABLED** | **true**/false (compose default **true**). |
| **MEM0_LLM_MODEL** | Mem0 LLM model name (compose default **`llama3.1:latest`** or `OLLAMA_MODEL`). |
| **MEM0_LLM_API_KEY** | Mem0 LLM API key placeholder for OpenAI-compatible clients (compose default **`ollama`**). |
| **MEM0_LLM_BASE_URL** | Mem0 LLM base URL (compose default **`OLLAMA_URL`** or `http://host.docker.internal:11434`). |
| **MEM0_DIR** | Root directory (compose default **`/app_data/mem0`**). |
| **MEM0_EMBEDDER_PROVIDER** | Embedder backend (compose default **`fastembed`**). |
| **MEM0_EMBEDDER_MODEL** | Model id (compose default **`BAAI/bge-small-en-v1.5`**). |
| **MEM0_EMBEDDING_DIMS** | Vector size (compose default **384**). |
| **MEM0_SPACY_MODEL** | Optional spaCy model override (default **`en_core_web_sm`**). |
| **MEM0_REQUIRE_SPACY_MODEL** | Keep as **true** (default). Set to false only if you intentionally want Mem0 to run without spaCy lemmatization. |
#### Document parsing (LiteParse)
| Variable | Purpose |
| ------------------------- | ----------------------------------------- |
| **LITEPARSE_DPI** | OCR render DPI (compose default **120**). |
| **LITEPARSE_NUM_WORKERS** | Worker count (compose default **1**). |
#### Database
- **DATABASE_URL**: SQLAlchemy URL; if unset, the app falls back to SQLite under app data.
- **MIGRATE_DATABASE_ON_STARTUP**: Compose sets **`true`** for all services so migrations run on startup.
#### Image generation
These variables match `docker-compose.yml`. **`IMAGE_PROVIDER`** selects the backend (`pexels`, `pixabay`, `gemini_flash`, `nanobanana_pro`, `dall-e-3`, `gpt-image-1.5`, `comfyui`, `open_webui`). Use **OPENAI_API_KEY** for OpenAI image modes and **GOOGLE_API_KEY** for Gemini image modes (same keys as the LLM section).
- **DISABLE_IMAGE_GENERATION**=[true/false]: Disable slide image generation.
- **IMAGE_PROVIDER**: Provider id (see enum above).
- **PEXELS_API_KEY**: Pexels stock images.
- **PIXABAY_API_KEY**: Pixabay stock images.
- **DALL_E_3_QUALITY**=[standard/hd]: Optional for **dall-e-3** (default `standard`).
- **GPT_IMAGE_1_5_QUALITY**=[low/medium/high]: Optional for **gpt-image-1.5** (default `medium`).
- **COMFYUI_URL** / **COMFYUI_WORKFLOW**: Self-hosted ComfyUI workflow JSON.
- **OPEN_WEBUI_IMAGE_URL** / **OPEN_WEBUI_IMAGE_API_KEY**: Open WebUI–compatible image endpoint.
- **OPENAI_COMPAT_IMAGE_BASE_URL** / **OPENAI_COMPAT_IMAGE_API_KEY** / **OPENAI_COMPAT_IMAGE_MODEL**: Required if using **openai_compatible** to send image requests to any OpenAI-compatible `/v1/images/*` endpoint (LiteLLM, Azure, vLLM Gateways, etc.).
#### Telemetry
- **DISABLE_ANONYMOUS_TRACKING**=[true/false]: Set to **true** to disable anonymous telemetry.
#### Authentication (web login)
Presenton uses a **single admin account** per instance. Credentials live in `app_data` (hashed; see `userConfig.json`). Pass these with `-e` or via `.env` for compose:
- **AUTH_USERNAME** / **AUTH_PASSWORD** — Preseed the admin login on first boot (password at least 6 characters). Ignored if a user already exists unless **AUTH_OVERRIDE_FROM_ENV** is set.
- **AUTH_OVERRIDE_FROM_ENV**=[true/false] — If **true**, replace stored credentials from the env vars on every FastAPI startup and rotate the session signing secret (invalidates existing sessions). Remove after a one-off rotation.
- **RESET_AUTH**=[true/false] — If **true**, clear stored credentials on startup. Use for a **single** boot to recover access, then unset.
**Examples**
docker run -it --name presenton -p 5000:80 -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
docker run -it --name presenton -p 5000:80 -e AUTH_USERNAME=admin -e AUTH_PASSWORD=changeme123 -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
docker run -it --name presenton -p 5000:80 -e AUTH_USERNAME=admin -e AUTH_PASSWORD=changeme123 -v "${PWD}\app_data:/app_data" ghcr.io/presenton/presenton:latest
docker stop presenton && docker rm presenton && docker run -it --name presenton -p 5000:80 -e AUTH_USERNAME=admin -e AUTH_PASSWORD=newcred456 -e AUTH_OVERRIDE_FROM_ENV=true -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
docker stop presenton && docker rm presenton && docker run -it --name presenton -p 5000:80 -e RESET_AUTH=true -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
docker stop presenton && docker rm presenton && docker run -it --name presenton -p 5000:80 -e AUTH_USERNAME=admin -e AUTH_PASSWORD=changeme123 -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
**Manual reset:** stop the container, edit `./app_data/userConfig.json`, delete `AUTH_USERNAME`, `AUTH_PASSWORD_HASH`, and `AUTH_SECRET_KEY`, save, and start again.
Sign out from the app: **Settings → Other → Sign out**.
**Docker Run Examples by Provider**
Same variables as compose; use `-e` instead of `.env` when running `docker run` directly.
- Using OpenAI
docker run -it --name presenton -p 5000:80 -e LLM="openai" -e OPENAI_API_KEY="******" -e IMAGE_PROVIDER="dall-e-3" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Google
docker run -it --name presenton -p 5000:80 -e LLM="google" -e GOOGLE_API_KEY="******" -e IMAGE_PROVIDER="gemini_flash" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Vertex AI (API key mode)
docker run -it --name presenton -p 5000:80 -e LLM="vertex" -e VERTEX_API_KEY="******" -e VERTEX_MODEL="gemini-2.5-flash" -e IMAGE_PROVIDER="gemini_flash" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Azure OpenAI
docker run -it --name presenton -p 5000:80 -e LLM="azure" -e AZURE_OPENAI_API_KEY="******" -e AZURE_OPENAI_MODEL="gpt-4.1" -e AZURE_OPENAI_API_VERSION="2024-10-21" -e AZURE_OPENAI_ENDPOINT="https://YOUR-RESOURCE.openai.azure.com" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Amazon Bedrock (on-demand model ID) — see **[docs/amazon-bedrock.md](docs/amazon-bedrock.md)** for inference profiles, IAM, and troubleshooting.
docker run -it --name presenton -p 5000:80 -e LLM="bedrock" -e BEDROCK_REGION="us-east-1" -e BEDROCK_AWS_ACCESS_KEY_ID="******" -e BEDROCK_AWS_SECRET_ACCESS_KEY="******" -e BEDROCK_MODEL="us.anthropic.claude-3-5-haiku-20241022-v1:0" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Amazon Bedrock (inference profile ARN, e.g. Claude Sonnet 4.6)
docker run -it --name presenton -p 5000:80 -e LLM="bedrock" -e BEDROCK_REGION="us-east-1" -e BEDROCK_AWS_ACCESS_KEY_ID="******" -e BEDROCK_AWS_SECRET_ACCESS_KEY="******" -e BEDROCK_MODEL="arn:aws:bedrock:us-east-1:YOUR_ACCOUNT_ID:inference-profile/us.anthropic.claude-sonnet-4-6" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Fireworks
docker run -it --name presenton -p 5000:80 -e LLM="fireworks" -e FIREWORKS_API_KEY="******" -e FIREWORKS_MODEL="accounts/fireworks/models/llama-v3p1-8b-instruct" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Together AI
docker run -it --name presenton -p 5000:80 -e LLM="together" -e TOGETHER_API_KEY="******" -e TOGETHER_MODEL="openai/gpt-oss-20b" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Ollama
docker run -it --name presenton -p 5000:80 -e LLM="ollama" -e OLLAMA_MODEL="llama3.2:3b" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="*******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using Anthropic
docker run -it --name presenton -p 5000:80 -e LLM="anthropic" -e ANTHROPIC_API_KEY="******" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using LM Studio (local)
docker run -it --name presenton -p 5000:80 -e LLM="lmstudio" -e LMSTUDIO_BASE_URL="http://host.docker.internal:1234" -e LMSTUDIO_MODEL="openai/gpt-oss-20b" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using OpenAI Compatible LLM 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" -e IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="********" -v "./app_data:/app_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 IMAGE_PROVIDER="pexels" -e PEXELS_API_KEY="*******" -e CAN_CHANGE_KEYS="false" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
- Using an OpenAI-Compatible Image Provider
This routes all slide image requests through your OpenAI-compatible gateway (LiteLLM, Azure, vLLM, etc.) while keeping the text LLM configuration independent:
docker run -it --name presenton -p 5000:80 -e IMAGE_PROVIDER="openai_compatible" -e OPENAI_COMPAT_IMAGE_BASE_URL="https://proxy.example.com/v1" -e OPENAI_COMPAT_IMAGE_API_KEY="******" -e OPENAI_COMPAT_IMAGE_MODEL="gpt-image-1" -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest
#
### ✨ Generate Presentation via API
**Generate Presentation**
Endpoint: /api/v1/ppt/presentation/generate
Method: POST
Content-Type: application/json
Authentication (HTTP Basic):
All /api/v1/ routes except /api/v1/auth/* require authentication. Send your Presenton admin username and password (same as the web UI, or AUTH_USERNAME / AUTH_PASSWORD when preseeding Docker). With curl, put them right after -u as -u USERNAME:PASSWORD — that is HTTP Basic auth and sets Authorization: Basic … for you. Replace the sample username:password below with your real credentials.
**Request Body**
Parameter
Type
Required
Description
contentstring
Yes
Main content used to generate the presentation.
slides_markdownstring[] | null
No
Provide custom slide markdown instead of auto-generation.
instructionsstring | null
No
Additional generation instructions.
tonestring
No
Text tone (default: "default").
Options: default, casual, professional,
funny, educational, sales_pitch
verbositystring
No
Content density (default: "standard").
Options: concise, standard, text-heavy
web_searchboolean
No
Enable web search grounding (default: false).
n_slidesinteger
No
Number of slides to generate (default: 8).
languagestring
No
Presentation language (default: "English").
templatestring
No
Template name (default: "general").
include_table_of_contentsboolean
No
Include table of contents slide (default: false).
include_title_slideboolean
No
Include title slide (default: true).
filesstring[] | null
No
Files to use in generation.
Upload first via /api/v1/ppt/files/upload.
export_asstring
No
Export format (default: "pptx").
Options: pptx, pdf
**Response**
{
"presentation_id": "string",
"path": "string",
"edit_path": "string"
**Example (curl + HTTP Basic auth with -u)**
curl -u username:password \
-X POST http://localhost:5000/api/v1/ppt/presentation/generate \
-H "Content-Type: application/json" \
-d '{
"content": "Introduction to Machine Learning",
"n_slides": 5,
"language": "English",
"template": "general",
"export_as": "pptx"
**Example Response**
{
"presentation_id": "d3000f96-096c-4768-b67b-e99aed029b57",
"path": "/app_data/d3000f96-096c-4768-b67b-e99aed029b57/Introduction_to_Machine_Learning.pptx",
"edit_path": "/presentation?id=d3000f96-096c-4768-b67b-e99aed029b57"
Note:
Prepend your server’s root URL to path and
edit_path to construct valid links.
**Documentation & Tutorials**
#
### 🚀 Roadmap
Track the public roadmap on GitHub Projects: [https://github.com/orgs/presenton/projects/2](https://github.com/orgs/presenton/projects/2)
标签：自动化攻击