GitHub - presenton/presenton: Open-Source AI Presentation Generator and API (Gamma, Canva, Beautiful AI, Decktopus, Presentations AI Alterna

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Open-Source AI Presentation Generator and API (Gamma, Canva, Beautiful AI, Decktopus, Presentations AI Alternative)

Discover what Presenton can do from AI-powered presentation generation to editing, exporting, and flexible model providers.

presenton.3.mp4

✨ Why Presenton

No SaaS lock-in · No forced subscriptions · Full control over models and data

What makes Presenton different?

• Use Fully self-hosted in Web through Docker Package

• Or Download Desktop App (Mac, Windows & Linux)

• Works with Ollama, LM Studio, OpenAI, Gemini, Vertex AI, Azure OpenAI, Amazon Bedrock, Fireworks, Together AI, Anthropic, or any other OpenAI compatible providers

• Comes with AI Presentation Generation API

• Fully open-source (Apache 2.0)

• Works with your own design/templates

• Fully editable PPTX export

Tip Star us! A ⭐ shows your support and encourages us to keep building! 😇

🎛 Features

Create presentations from a prompt, an uploaded document, or your own PowerPoint design. Choose from built-in templates, bring your preferred AI provider and API key, polish manually with drag-edit interface and export a fully editable deck.

🎨 In-Built AI Presentation Templates for PowerPoint

Browse in-built AI presentation templates for pitch decks, business reports, executive updates, educational presentations, and more. Preview each editable slide layout, choose a design, and use Presenton to generate fully editable PowerPoint ( .

pptx ) or PDF presentations from a prompt or document.

Momentum Business Presentation Template — sales reports, strategy decks, and data storytelling

Preview Momentum business template ↗

Dynamic Creative Presentation Template — proposals, visual stories, and high-impact decks

Preview Dynamic presentation template ↗

Executive PowerPoint Template — leadership updates, strategic plans, and decision-ready reports

Preview Executive PowerPoint template ↗

General Presentation Template — adaptable layouts for business, education, and everyday topics

Preview General presentation template ↗

Modern Pitch Deck Template — contemporary slides for startups, products, and portfolios

Preview Modern pitch deck template ↗

Standard Business Presentation Template — professional reports, proposals, and company decks

Preview Standard business template ↗

Browse all free AI presentation templates → · Create an AI-ready PowerPoint template from your PPTX →

💻 Presenton Desktop

Create AI-powered presentations using your own model provider (BYOK) or run everything locally on your own machine for full control and data privacy.

Available Platforms

Platform Architecture Package Download

macOS Apple Silicon / Intel .dmg Download ↗

Windows x64 .exe Download ↗

Linux x64 .deb Download ↗

Deploy to Cloud Providers

Presenton gives you complete control over your AI presentation workflow. Choose your models, customize your experience, and keep your data private.

• Custom Templates & Themes — Create unlimited presentation designs with HTML and Tailwind CSS

• AI Template Generation — Create presentation templates from existing Powerpoint documents.

• Flexible Generation — Build presentations from prompts or uploaded documents

Export Ready — Save as PowerPoint (PPTX) and PDF with professional formatting

• Built-In MCP Server — Generate presentations over Model Context Protocol

• Bring Your Own Key — Use your own API keys for OpenAI, Google Gemini, Vertex AI, Azure OpenAI, Anthropic Claude, or any compatible provider. Only pay for what you use, no hidden fees or subscriptions.

• Ollama Integration — Run open-source models locally with full privacy

• OpenAI API Compatible — Connect to any OpenAI-compatible endpoint with your own models

• Multi-Provider Support — Mix and match text and image generation providers

• Versatile Image Generation — Choose from DALL-E 3, Gemini Flash, Pexels, or Pixabay

• Rich Media Support — Icons, charts, and custom graphics for professional presentations

• Runs Locally — All processing happens on your device, no cloud dependencies

• API Deployment — Host as your own API service for your team

• Multi-User Workspaces — Give each user a private workspace and manage accounts from a built-in admin panel

• Fully Open-Source — Apache 2.0 licensed, inspect, modify, and contribute

Docker Ready — One-command deployment with GPU support for local models

• Electron Desktop App — Run Presenton as a native desktop application on Windows, macOS, and Linux (no browser required)

• Sign in with ChatGPT — Use your free or paid ChatGPT account to sign in and start creating presentations instantly — no separate API key required

☁️ Presenton Cloud

Run Presenton directly in your browser — no installation, no setup required. Start creating presentations instantly from anywhere.

🏢 Presenton Enterprise

Deploy and manage Presenton across your organization with versioned Helm charts for Kubernetes, detailed audit logs, and a centralized admin console. Enterprise authentication supports SSO and automated user provisioning through OAuth, OIDC, and SCIM.

⚡ Running Presenton

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 ).

- Setup (First Time)

cd electron

npm run setup:env

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

npm run dist

Output files are written to electron/dist (or as configured in your electron-builder settings).

For a public macOS DMG outside the Mac App Store, use

APPLE_KEYCHAIN_PROFILE="presenton-notary" npm run build:all:mac:signed

from electron/ after the one-time Developer ID and notarization setup in docs/macos/dev/direct-distribution.md .

Option 2

Docker

- Start Presenton Linux/MacOS (Bash/Zsh Shell):

docker run -it --name presenton -p 5001:80 -v "./app_data:/app_data" ghcr.io/presenton/presenton:latest

Windows (PowerShell):

docker run -it --name presenton -p 5001:80 -v "${PWD}\app_data:/app_data" ghcr.io/presenton/presenton:latest

- Open Presenton

Open http://localhost:5001 in the browser of your choice to use Presenton.

Note: You can replace 5001 with any other port number of your choice to run Presenton on a different port number. If you use

Docker Compose, set PRESENTON_HTTP_HOST_PORT , for example

PRESENTON_HTTP_HOST_PORT=8080 docker compose up production .

⚙️ Deployment Configurations

The tables 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

Variable Values / default Purpose

CAN_CHANGE_KEYS true / false

Set to false to keep API keys hidden and unmodifiable.

PRESENTON_PUBLIC_URL Optional URL Browser-reachable Presenton origin, such as http://localhost:5001 or https://slides.example.com . Generated download, edit, and preview links use this origin.

PRESENTATION_GENERATION_MODE both (default), standard , smart Controls the modes available in the UI and MCP server. A single-mode value hides the selector; smart also hides template features. See the presentation generation modes guide .

LLM openai , deepseek , google , vertex , azure , bedrock , openrouter , fireworks , together , cerebras , anthropic , litellm , lmstudio , ollama , custom , codex Selects the text LLM provider.

OPENAI_API_KEY Required for LLM=openai OpenAI API key.

OPENAI_MODEL gpt-4.1 (default) OpenAI model.

DEEPSEEK_API_KEY Required for LLM=deepseek DeepSeek API key.

DEEPSEEK_MODEL deepseek-chat (default) DeepSeek model.

DEEPSEEK_BASE_URL https://api.deepseek.com (default) DeepSeek base URL.

GOOGLE_API_KEY Required for LLM=google Google API key.

GOOGLE_MODEL models/gemini-2.0-flash (default) Google model.

VERTEX_MODEL gemini-2.5-flash (default) Vertex AI model.

VERTEX_API_KEY Optional Vertex Express API key authentication.

VERTEX_PROJECT / VERTEX_LOCATION Optional pair GCP project credential authentication; do not combine with VERTEX_API_KEY .

VERTEX_BASE_URL Optional URL Vertex gateway or base URL override.

AZURE_OPENAI_MODEL Required for LLM=azure Azure deployment or model name.

AZURE_OPENAI_API_KEY Required for LLM=azure Azure OpenAI API key.

AZURE_OPENAI_API_VERSION Required; for example 2024-10-21 Azure OpenAI API version.

AZURE_OPENAI_ENDPOINT / AZURE_OPENAI_BASE_URL At least one required Azure OpenAI endpoint.

AZURE_OPENAI_DEPLOYMENT Optional Azure deployment override.

BEDROCK_REGION us-east-1 (default) AWS Bedrock region.

BEDROCK_MODEL Required for LLM=bedrock Standard model ID or full inference-profile ARN, passed to Bedrock Converse as modelId . See the Amazon Bedrock guide .

BEDROCK_API_KEY Optional Bedrock API-key authentication; alternative to AWS keys.

BEDROCK_AWS_ACCESS_KEY_ID / BEDROCK_AWS_SECRET_ACCESS_KEY Required together when BEDROCK_API_KEY is unset AWS credential authentication for Bedrock.

BEDROCK_AWS_SESSION_TOKEN Optional AWS session token.

BEDROCK_PROFILE_NAME Optional AWS profile name.

OPENROUTER_API_KEY Required for LLM=openrouter OpenRouter API key.

OPENROUTER_MODEL openai/gpt-4o (default) OpenRouter model.

OPENROUTER_BASE_URL https://openrouter.ai/api/v1 (default) OpenRouter base URL.

OPENROUTER_PROVIDER_ORDER Optional comma-separated list Provider routing order.

OPENROUTER_ALLOW_FALLBACKS true / false Optional provider fallback override.

OPENROUTER_REQUIRE_PARAMETERS true / false Only route to providers supporting every request parameter.

OPENROUTER_DATA_COLLECTION allow / deny Optional data-collection policy.

OPENROUTER_ZDR true / false Optional zero-data-retention requirement.

FIREWORKS_API_KEY Required for LLM=fireworks Fireworks API key.

FIREWORKS_MODEL For example accounts/fireworks/models/llama-v3p1-8b-instruct Fireworks model.

FIREWORKS_BASE_URL https://api.fireworks.ai/inference/v1 (default) Fireworks base URL.

TOGETHER_API_KEY Required for LLM=together Together AI API key.

TOGETHER_MODEL For example openai/gpt-oss-20b Together AI model.

TOGETHER_BASE_URL https://api.together.ai/v1 (default) Together AI base URL.

CEREBRAS_API_KEY Required for LLM=cerebras Cerebras API key.

CEREBRAS_MODEL llama-3.3-70b (default) Cerebras model.

CEREBRAS_BASE_URL https://api.cerebras.ai/v1 (default) Cerebras base URL.

ANTHROPIC_API_KEY Required for LLM=anthropic Anthropic API key.

ANTHROPIC_MODEL claude-3-5-sonnet-20241022 (default) Anthropic model.

CODEX_MODEL Required for LLM=codex Codex model. The OAuth flow maps host port 1455 for its callback.

CUSTOM_LLM_URL Required for LLM=custom OpenAI-compatible base URL. The server must implement POST /v1/chat/completions ; a provider-specific completion endpoint is insufficient.

CUSTOM_LLM_API_KEY Provider-dependent Custom-provider API key.

CUSTOM_MODEL Required for LLM=custom Custom-provider model ID.

LITELLM_BASE_URL Required for LLM=litellm LiteLLM proxy or gateway base URL.

LITELLM_API_KEY Optional LiteLLM API key.

LITELLM_MODEL gpt-4.1 (default) LiteLLM model.

LMSTUDIO_BASE_URL http://localhost:1234/v1 (default) LM Studio base URL; /v1 is appended when omitted.

LMSTUDIO_API_KEY Optional LM Studio API key.

LMSTUDIO_MODEL For example openai/gpt-oss-20b LM Studio model.

DISABLE_THINKING true / false Disables thinking for providers that support it, including DeepSeek.

WEB_GROUNDING true / false Enables web search by default.

WEB_SEARCH_PROVIDER auto , native , searxng , tavily , exa Selects the search mode. auto uses native search for OpenAI, Google, and Anthropic and otherwise leaves search off unless an external provider is selected.

WEB_SEARCH_MAX_RESULTS 5 (default), maximum 10 Maximum external search results added to model context.

SEARXNG_BASE_URL Optional URL Self-hosted SearXNG base URL.

TAVILY_API_KEY , EXA_API_KEY Optional Credentials for hosted search providers.

EXTENDED_REASONING true / false Enables extended reasoning where supported.

LLM_GENERATION_PROFILE fast , balanced (default), deep , model_max Global generation profile.

LLM_MAX_OUTPUT_TOKENS Optional positive integer Output-token override for every text provider.

MAX_OUTLINE_WORDS 100 (default), positive integer Maximum words in each generated, edited, or slides_markdown slide outline.

LLM_REASONING_MODE auto , enabled , disabled Global reasoning-mode override.

LLM_REASONING_EFFORT default , none , minimal , low , medium , high , xhigh , max Reasoning-effort override.

LLM_REASONING_BUDGET_TOKENS Optional non-negative integer Reasoning token budget.

All advanced text-provider settings are optional. Use Reset advanced settings in Settings or onboarding to remove overrides and inherit application/provider defaults.

Ollama

Use when LLM is ollama :

Variable Values / default Purpose

OLLAMA_URL For example http://host.docker.internal:11434 from Docker Ollama HTTP API base URL.

OLLAMA_MODEL For example llama3.2:3b Ollama model name.

START_OLLAMA false (default), true Allows the container entrypoint ( start.js ) to install Ollama and run ollama serve .

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

Variable Values / default Purpose

DATABASE_URL Optional SQLAlchemy URL Configures the database; when unset, the app uses SQLite under app data.

MIGRATE_DATABASE_ON_STARTUP true in Compose Runs database migrations during 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).

Variable Values / default Purpose

DISABLE_IMAGE_GENERATION true / false Disables slide image generation.

ENABLE_PARALLEL_IMAGE_GENERATION true (default), false Allows concurrent image-provider requests. Set to false for providers with strict rate limits.

IMAGE_PROVIDER pexels , pixabay , gemini_flash , nanobanana_pro , dall-e-3 , gpt-image-1.5 , comfyui , open_webui , openai_compatible Selects the image backend.

PEXELS_API_KEY Required for IMAGE_PROVIDER=pexels Pexels stock-image API key.

PIXABAY_API_KEY Required for IMAGE_PROVIDER=pixabay Pixabay stock-image API key.

DALL_E_3_QUALITY standard (default), hd DALL-E 3 image quality.

GPT_IMAGE_1_5_QUALITY low , medium (default), high GPT Image 1.5 image quality.

COMFYUI_URL / COMFYUI_WORKFLOW Required for IMAGE_PROVIDER=comfyui Self-hosted ComfyUI endpoint and workflow JSON.

OPEN_WEBUI_IMAGE_URL / OPEN_WEBUI_IMAGE_API_KEY Required for IMAGE_PROVIDER=open_webui Open WebUI-compatible image endpoint and API key.

OPENAI_COMPAT_IMAGE_BASE_URL / OPENAI_COMPAT_IMAGE_API_KEY / OPENAI_COMPAT_IMAGE_MODEL Required for IMAGE_PROVIDER=openai_compatible Sends image requests to an OpenAI-compatible /v1/images/* endpoint such as LiteLLM, Azure, or a vLLM gateway.

The parallel image generation option applies everywhere images are generated: initial presentation generation, slide editing and regeneration, direct image requests, and assistant image tools.

Telemetry

Variable Values / default Purpose

DISABLE_ANONYMOUS_TRACKING true / false

Set to true to disable anonymous telemetry.

Multi-user authentication

Presenton supports multiple accounts with a private workspace for each user. The first account becomes the primary administrator and can create, reset, or remove other accounts from Admin → Users .

Existing single-user installations are upgraded automatically: the current account becomes the primary administrator, while its presentations, templates, tasks, and other owned data stay attached to the same account.

Set up the primary administrator

On a new installation, open Presenton and follow the account setup screen. For an unattended Docker deployment, you can create the primary administrator on first boot with environment variables:

docker run -it --name presenton \

-p 5001:80 \ -e AUTH_USERNAME=admin \ -e AUTH_PASSWORD=change-this-password \ -v " ./app_data:/app_data " \ ghcr.io/presenton/presenton:latest

Usernames must contain at least 3 characters, and new passwords must contain at least 8 characters. Older six- or seven-character passwords remain valid after an upgrade.

Authentication environment variables

Variable Purpose

AUTH_USERNAME Username used to create the primary administrator on first boot. It can also change the username during a rotation or recovery.

AUTH_PASSWORD Password used for first-time setup, rotation, or recovery. Required when using either flag below.

AUTH_OVERRIDE_FROM_ENV =[true/false] Replace the primary administrator's credentials from the environment on the next startup. Use this for a deployment-managed credential rotation.

RESET_AUTH =[true/false] Recover access to the existing primary administrator without replacing the account or its data.

Presenton Cloud provider

Presenton Cloud is an optional, installation-wide generation provider. It is not an authentication method for the self-hosted instance. Create or sign in to the local administrator account first, then connect Presenton from provider onboarding.

Only the local administrator can connect, replace, or disconnect the provider. The browser displays a short device code and opens the hosted Presenton approval page.

After approval, the delegated access and rotating refresh tokens are encrypted at rest and stored as one global provider credential; they are never returned to the browser or stored per local user.

Selecting Presenton as the text provider saves LLM=presenton . Presentation generation and document uploads then use the Presenton Cloud API and its token.

Connecting the provider alone does not change generation: when another provider is selected, the existing local generation pipeline remains unchanged. Disconnecting revokes and removes the global credentials and deselects Presenton.

No OAuth client registration, client secret, or environment configuration is required. Official builds contain the cloud URL and first-party public device-flow client ID.

To rotate credentials from the environment:

docker stop presenton

docker rm presenton

docker run -it --name presenton \

-p 5001:80 \ -e AUTH_USERNAME=admin \ -e AUTH_PASSWORD=new-secure-password \ -e AUTH_OVERRIDE_FROM_ENV=true \ -v " ./app_data:/app_data " \ ghcr.io/presenton/presenton:latest

For account recovery, use the same command with RESET_AUTH=true instead of

AUTH_OVERRIDE_FROM_ENV=true . Both operations preserve the administrator's user ID

and owned data, and invalidate existing browser sessions and API keys. Remove the one-time flag after the successful startup.

Important Do not remove authentication fields from app_data/userConfig.json to reset access. Presenton stores a hashed recovery copy of the primary administrator credentials and the session-signing secret there.

Use the recovery variables above to preserve the database account and its ownership links.

To sign out, open Settings → Other → Sign out .

API and MCP authentication

Presenton exposes a client-neutral MCP 2025-11-25 Streamable HTTP endpoint at /mcp . When authentication is enabled, REST API and MCP clients use the same administrator-provisioned, user-scoped API key. Browser JWT cookies are not accepted as MCP credentials.

- An administrator creates the target Presenton user, then calls POST /api/v1/admin/api-keys from an authenticated admin session with {"user_id":".","label":"My API client","expiry_days":90} . The response contains the new key.

Listing and revocation use GET /api/v1/admin/api-keys and POST /api/v1/admin/api-keys/{api_key_id}/revoke . An administrator can securely reveal a key again with GET /api/v1/admin/api-keys/{api_key_id}/token .

- Configure any Streamable HTTP MCP client to send the generated sk-presenton-... key on every request:

{ "servers" : { "presenton" : { "url" : " http://localhost:5001/mcp " , "type" : " http " , "headers" : { "Authorization" : " Bearer sk-presenton-0123456789abcdef.REPLACE_WITH_SECRET " } } }, "inputs" : [] }

Notes:

Streamable HTTP and bearer-header configuration in Open WebUI or any other conforming MCP client.

• This example uses VS Code's .vscode/mcp.json format. Use the equivalent

recoverable copy. They expire by default after 90 days and represent exactly the selected Presenton user. The same key authenticates general REST endpoints and MCP, but cannot sign in to the browser or change admin/provider settings.

• API keys retain an Argon2 authentication hash and an encrypted, admin-only

user session. The long-lived key is never forwarded to presentation APIs.

• The API key is exchanged inside the MCP process for a short-lived internal

• Revoking the key through the admin API takes effect immediately.

Poll get_job_status until completed or error ; template listing is immediate.

• Standard, Smart Mode, and template generation tools return an async task ID.

by get_job_status ) so Standard and Smart generation use the same job model.

• MCP exposes only the polling Smart workflow ( start_smart_presentation followed

single call, then returns the data needed by start_template_generation .

• upload_template_assets accepts one PPTX and its replacement fonts in a

user-scoped paths that can be passed unchanged to Standard or Smart generation.

• upload_files accepts reference documents and images as base64 and returns

• MCP is not available in the Electron desktop app ( PRESENTON_ELECTRON=true ). Electron runs with DISABLE_AUTH=true by default, and the MCP server is disabled there to avoid auth conflicts.

Note: LLM and image variables above are forwarded from docker-compose.yml when set in .env .

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 5001:80 -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 5001:80 -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 5001:80 -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 5001:80 -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 for inference profiles, IAM, and troubleshooting.

docker run -it --name presenton -p 5001:80 -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 5001:80 -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 5001:80 -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 5001:80 -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 5001:80 -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 5001:80 -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 5001:80 -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 5001:80 -e CAN_CHANGE

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