Anil-matcha/Open-Generative-AIPublic

Unrestricted Open-source alternative to AI video platforms — Free AI image & video generation studio with 600+ models (Flux, Midjourney, Kling, Sora, Veo). No content filters. Self-hosted, MIT licensed.

AI summary: An open-source hub for generative AI resources, models, and practical implementations.

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JavaScriptMITCreated May 9, 2023Last push 1d agoLatest release v2.0.0+413 stars this week+1.9K this month

Quick answers

What is Open-Generative-AI?
An open-source hub for generative AI resources, models, and practical implementations.
What does Open-Generative-AI do?
This repository acts as a comprehensive, open-source resource center for understanding and implementing generative AI technologies. It aggregates functional code examples, architectural diagrams, and Jupyter notebooks focused on various AI domains, including Large Language Models and diffusion networks. The project provides hands-on implementations for advanced techniques like Retrieval-Augmented Generation (RAG) and model fine-tuning. By offering transparent, runnable code, it demystifies complex AI concepts and provides a practical starting point for building custom applications. The repository is actively maintained to keep pace with the rapid developments in the open-source AI ecosystem.
Who is Open-Generative-AI for?
This repository is intended for software developers, data scientists, and AI enthusiasts looking to build practical generative AI applications. Familiarity with Python and basic machine learning concepts is recommended.
How do I get started with Open-Generative-AI?
git clone https://github.com/Anil-matcha/Open-Generative-AI.git
How popular is Open-Generative-AI on GitHub?
Anil-matcha/Open-Generative-AI has 29,577 stars and 5,421 forks on GitHub, and gained 413 stars in the last 7 days.
What license does Open-Generative-AI use?
Anil-matcha/Open-Generative-AI is released under the MIT license.

Star history

since Jul 28, 2026
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29.6K stars as of Oct 3, 2026. Measured daily since Jul 28, 2026; GitHub no longer exposes earlier star timestamps.

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Signals and awards

derived from tracked data
  • Widely adopted

    29,577 stars

  • Actively maintained

    Pushed within 48 hours

  • Permissive license

    MIT

  • Repeat trending

    4 trending appearances

What Open-Generative-AI does

This repository acts as a comprehensive, open-source resource center for understanding and implementing generative AI technologies. It aggregates functional code examples, architectural diagrams, and Jupyter notebooks focused on various AI domains, including Large Language Models and diffusion networks. The project provides hands-on implementations for advanced techniques like Retrieval-Augmented Generation (RAG) and model fine-tuning. By offering transparent, runnable code, it demystifies complex AI concepts and provides a practical starting point for building custom applications. The repository is actively maintained to keep pace with the rapid developments in the open-source AI ecosystem.

This repository is intended for software developers, data scientists, and AI enthusiasts looking to build practical generative AI applications. Familiarity with Python and basic machine learning concepts is recommended.

  • Practical Implementations: Provides working code examples for building complete generative AI applications from scratch.
  • Interactive Notebooks: Includes ready-to-run Jupyter notebooks that allow developers to experiment with models locally.
  • RAG Architecture Guides: Offers detailed, step-by-step walkthroughs on implementing robust Retrieval-Augmented Generation pipelines.
  • Fine-Tuning Strategies: Demonstrates how to efficiently fine-tune open-source models for specialized domain tasks.
  • Curated AI Resources: Aggregates essential reading materials, research papers, and best practices in a structured format.

Where teams use it

Application Prototyping

Software engineers referencing the provided RAG examples to quickly build a custom document-querying chatbot.

Skill Development

Developers transitioning into AI roles using the interactive notebooks to understand transformer architectures hands-on.

Model Fine-Tuning

Data scientists following the repository's guides to adapt a foundational open-source LLM to specific company data.

Academic Reference

Students and researchers utilizing the curated resources and code snippets as a baseline for experimental AI projects.

Getting started: git clone https://github.com/Anil-matcha/Open-Generative-AI.git

README

main branch

Open Generative AI — Unrestricted Open-Source Alternative to AI Video Platforms

Powered by MuAPI

The free, open-source alternative to AI Video Platforms. Generate AI images and videos using 400+ state-of-the-art models across 14 studios — no content filters, no closed ecosystem, no subscription fees.

Community: Join Discord for discussions and support

▶ Watch: Best Free Uncensored AI Models 2026 (No GPU)

Awesome Generative AI Apps

🎨 Explore 50+ more open-source AI apps →

💰 Turn This Into Your Own Product — White Label & Resell

Want to launch this as your own branded AI studio and charge your own customers for it? MuAPI White Label lets you spin up a fully white-labeled version of this app — your logo, your colors, your custom domain, your own pricing — with zero infra to manage. You keep the markup on every generation; MuAPI handles the models, the queue, and the billing plumbing underneath.

  • Your branding — logo, color theme, and a custom domain (e.g. studio.yourbrand.com)
  • Your pricing — set your own credit/subscription prices for end users, keep the margin
  • No infra — no servers, workers, or model hosting to run yourself
  • All studios included — Image, Video, Audio, Lip Sync, Cinema, Workflows, and more, depending on plan

Plans start at $49/mo. Get started with White Label →

What similar AI studios charge their users

Consumer AI image/video platforms almost all run on paid monthly subscriptions — this is the same playbook you'd run under your own brand:

Platform Typical subscription range
Midjourney ~$10–$120/mo (Basic → Mega)
Runway ~$12–$76/mo (Standard → Unlimited), custom Enterprise
Kling AI ~$10–$92/mo across Standard → Premier tiers
Luma Dream Machine ~$10–$100+/mo
Pika ~$8–$58/mo

(Figures are approximate, general-market ranges and change over time — check each platform's current pricing page before quoting them.) With MuAPI White Label, you set these numbers yourself for your own end users — the subscription revenue is yours.


API examples and model references

Related Projects

This is a curated set of high-value hubs, popular distribution tools, and model-specific integrations rather than a directory of every related repository.

🌐 Try it Online — No Install Required

Hosted version: https://muapi.ai/open-generative-ai?utm_source=github&utm_medium=readme&utm_campaign=open-generative-ai

Use all studios (Image, Video, Audio, AI Clipping, Vibe Motion, Lip Sync, Cinema, Marketing, Workflows, Agents, Design Agent, Apps, MCP & CLI) directly in your browser — no Node.js, no setup. Sign up for a free account to start generating. The hosted version is always up to date with the latest models.

Follow the creator for updates


⬇️ Download Desktop App

One-click installers — no Node.js or terminal required.

Platform Download
macOS Apple Silicon (M1/M2/M3/M4) Open Generative AI-1.0.9-arm64.dmg
macOS Intel (x64) Open Generative AI-1.0.9.dmg
Windows (x64) Open Generative AI Setup 1.0.9.exe
Linux (Ubuntu x64) v1.0.9 release (.AppImage / .deb), or build locally with npm run electron:build:linux.

All releases: github.com/Anil-matcha/Open-Generative-AI/releases

macOS Installation Guide

Because the app is not notarized by Apple, macOS Gatekeeper will block it on first launch. Follow these steps:

Step 1 — Mount the DMG and drag the app to /Applications

Step 2 — Open Terminal and run:

xattr -cr "/Applications/Open Generative AI.app"

Step 3 — Right-click the app in /Applications → click Open → click Open again on the dialog

You only need to do this once. After that, the app opens normally.

Alternative (no Terminal):

  1. Try to open the app — macOS will block it
  2. Go to System Settings → Privacy & Security
  3. Scroll down to find "Open Generative AI was blocked"
  4. Click Open Anyway → Open

Windows Installation — SmartScreen warning fix

Windows SmartScreen may show a warning because the installer is not code-signed:

  1. Click More info on the SmartScreen dialog
  2. Click Run anyway

The app will install silently to %LocalAppData% with a Start Menu shortcut.

Ubuntu / Linux Installation

Linux artifacts are available when building with Electron Builder:

# Build Linux installers (AppImage + .deb)
npm run electron:build:linux

Generated files are written to the release/ folder:

  • AppImage — portable, run directly after making executable:
    chmod +x "release/Open Generative AI-*.AppImage"
    ./release/Open\ Generative\ AI-*.AppImage
  • .deb — install on Debian/Ubuntu:
    sudo apt install ./release/open-generative-ai_*_amd64.deb

If AppImage fails to start on older systems, install libfuse2:

sudo apt install libfuse2
Ubuntu 24.04+ / AppArmor sandbox restriction

Ubuntu 24.04 and later enable a kernel security policy (apparmor_restrict_unprivileged_userns) that blocks Chromium's user-namespace sandbox. If the app fails to start silently or crashes immediately, you have two options:

Option A — Recommended: install the .deb instead. The .deb package ships an AppArmor profile that grants the required permission automatically on install with no system-wide changes.

Option B — Temporary system fix (AppImage users):

sudo sysctl -w kernel.apparmor_restrict_unprivileged_userns=0

This lasts until next reboot. To make it permanent:

echo 'kernel.apparmor_restrict_unprivileged_userns=0' | sudo tee /etc/sysctl.d/99-userns.conf

Open Generative AI is a free, open-source AI image, video, cinema, and lip sync studio that brings creative workflows to everyone. No content filters, no prompt rejections, no guardrails — just full creative freedom. Powered by Muapi.ai, it supports text-to-image, image-to-image, text-to-video, image-to-video, and audio-driven lip sync generation across models like Flux, Nano Banana, Midjourney, Kling, Sora, Veo, Seedream, Infinite Talk, LTX Lipsync, Wan 2.2, and more — all from a sleek, modern interface you can self-host and customize.

Why Open Generative AI instead of other AI Video Platforms?

  • No filters — no content filters, no nanny guardrails, no prompt rejections
  • Free & open-source — no subscription, no vendor lock-in
  • Self-hosted — your data stays on your machine, full creative control
  • 200+ models — text-to-image, image-to-image, text-to-video, image-to-video, lip sync
  • Multi-image input — feed up to 14 reference images into compatible models
  • Lip Sync Studio — animate portraits or sync lips to any audio with 9 dedicated models
  • Extensible — add your own models, modify the UI, build on top of it

For a deep dive into the technical architecture and the philosophy behind the "Infinite Budget" cinema workflow, see our comprehensive guide and roadmap.

⚡ Local Model Inference (Desktop App Only)

The desktop app supports two independent local engines. Pick whichever fits the machine you actually run on:

Engine What it is Best for
sd.cpp (bundled) C++ engine from stable-diffusion.cpp, runs on the same machine as the app. Metal GPU on Apple Silicon, CUDA/Vulkan/ROCm on Linux/Windows. Image-only models. Works on Mac M-series.
Wan2GP (BYO server) HTTP client to a user-run Wan2GP server. The server runs Python + PyTorch on a CUDA/ROCm GPU; the desktop app only sends prompts and receives results. Video models (Wan 2.2, Hunyuan, LTX) and large image models (Flux, Qwen-Image). NVIDIA/AMD GPU required on the server; the desktop app itself can run on a Mac.

Both engines share the same UI: open Settings → Local Models to configure each.

Engine 1 — sd.cpp (bundled)

Model Type Size Notes
Z-Image Turbo ⚡ Diffusion Transformer 2.5 GB + 2.7 GB aux 8-step turbo. Heavy on memory.
Z-Image Base ⚡ Diffusion Transformer 3.5 GB + 2.7 GB aux 50-step high-quality. Heavy on memory.
Dreamshaper 8 SD 1.5 2.1 GB 20-step versatile. Lightest tested option on Mac.
Realistic Vision v5.1 SD 1.5 2.1 GB 25-step photorealistic
Anything v5 SD 1.5 2.1 GB 20-step anime/illustration
SDXL Base 1.0 SDXL 6.9 GB 30-step high-res

Z-Image models require two shared auxiliary files (downloaded once, shared across both models):

  • Qwen3-4B Text Encoder — 2.4 GB
  • FLUX VAE — 335 MB

How to use:

  1. Open Settings → Local Models in the desktop app
  2. Install the sd.cpp inference engine (one click — auto-downloaded)
  3. Download your chosen model (and auxiliary files for Z-Image)
  4. In Image Studio, click the ⚡ Local toggle next to the model selector
  5. Select your local model and generate — no API key needed

All downloads happen inside the app. Nothing is installed system-wide.

By default, sd.cpp stores the engine, model weights, and temporary downloads under Electron's app data directory. Common paths are:

  • macOS: ~/Library/Application Support/open-generative-ai/local-ai
  • Windows: %APPDATA%\open-generative-ai\local-ai
  • Linux: ~/.config/open-generative-ai/local-ai

To keep multi-GB model weights on another drive, set OPEN_GENERATIVE_AI_LOCAL_AI_DIR before launching the desktop app. The app will create bin/, models/, and tmp/ inside that directory, and Settings -> Local Models shows the resolved model folder. Local engine output and download errors are written to the app process console, so launch from Terminal or PowerShell when you need troubleshooting logs.

Engine 2 — Wan2GP (remote Gradio server)

The app does not bundle Python or model weights for Wan2GP. You run Wan2GP yourself on a machine with a CUDA or ROCm GPU and point the desktop app at its URL.

# On your GPU machine
git clone https://github.com/deepbeepmeep/Wan2GP
cd Wan2GP
./install.sh                          # or install.bat on Windows
python wgp.py --listen --server-name 0.0.0.0   # binds to all interfaces

Then in the desktop app: Settings → Local Models → Wan2GP server, paste the URL (e.g. http://192.168.1.42:7860), click Test, then Save. The Wan2GP models become available — image models in Image Studio, video models reachable via the same generation API (Image Studio rejects video output explicitly; full Video Studio wiring is on the roadmap).

Model Type Notes
Flux.1 Dev Image 1024px, 28 steps
Qwen Image Image 1024px, 30 steps
Wan 2.2 (T2V / I2V) Video Slow on consumer GPUs
Hunyuan Video Video High-quality T2V
LTX Video Video Fastest video option

Why a separate server? Wan2GP's runtime (Sage attention, flash-attn, AWQ/GGUF kernels) is CUDA-only — there is no MPS / Apple Silicon path. Treating it as a remote server lets a Mac-only user keep the desktop app while offloading inference to a Linux/Windows GPU box, a gaming PC on the LAN, or a rented RunPod/vast.ai instance.

Local inference is only available in the desktop app. The hosted web version always uses cloud APIs.

Hardware Notes

  • sd.cpp runs on CPU (all platforms) and Metal GPU on Apple Silicon (M1/M2/M3/M4); CUDA/Vulkan/ROCm on Linux/Windows.
  • Metal GPU acceleration is built into the macOS desktop binary — significantly faster than CPU-only.
  • Recommended for sd.cpp Z-Image: 16 GB RAM (7.4 GB weights + 2.4 GB compute buffer). On a base 8 GB M-series Mac, Z-Image is known to hang the system — stick to SD 1.5 there.
  • For SD 1.5 on M2: expect ~1–2 s/step with the Metal dylib active. If you see ~10 s/step instead, the binary may have fallen back to CPU — see verification below.

Verifying the SD 1.5 path (the fastest sanity test on Mac)

If you want to confirm sd.cpp is installed correctly without going through the UI, you can drive sd-cli directly. This is the same binary the app uses.

# 1. App data layout (created on first app launch)
APP_DATA="${OPEN_GENERATIVE_AI_LOCAL_AI_DIR:-$HOME/Library/Application Support/open-generative-ai/local-ai}"
ls "$APP_DATA/bin"     # sd-cli, libstable-diffusion.dylib
ls "$APP_DATA/models"  # whatever you've downloaded

# 2. Grab a small SD 1.5 model directly (Dreamshaper 8, ~2 GB)
curl -L --fail --progress-bar \
  -o "$APP_DATA/models/DreamShaper_8_pruned.safetensors" \
  "https://huggingface.co/Lykon/DreamShaper/resolve/main/DreamShaper_8_pruned.safetensors"

# 3. Run a single 512x512 / 12-step inference
DYLD_LIBRARY_PATH="$APP_DATA/bin" "$APP_DATA/bin/sd-cli" \
  -m "$APP_DATA/models/DreamShaper_8_pruned.safetensors" \
  -p "a serene mountain lake at sunrise, oil painting" \
  -o /tmp/sd15-test.png \
  --steps 12 -H 512 -W 512 --cfg-scale 7.5 --seed 42 \
  --sampling-method euler_a

A healthy run on Apple Silicon prints total params memory size = 1969.78MB (VRAM 1969.78MB, RAM 0.00MB) (Metal-backed) and produces a coherent 512×512 PNG. If VRAM is 0.00MB instead, the dylib is CPU-only — check otool -L "$APP_DATA/bin/libstable-diffusion.dylib" | grep -i metal and reinstall the engine from Settings → Local Models if Metal is missing.


✨ Features

  • Image Studio — Generate images from text prompts (50+ text-to-image models) or transform existing images (55+ image-to-image models). Switches model set automatically based on whether a reference image is provided. Quality and resolution controls visible for models that support them.
  • Local Inference — Two engines: sd.cpp (bundled, runs on Mac/Win/Linux with Metal/CUDA/Vulkan/ROCm) for SD 1.5, SDXL, and Z-Image; and Wan2GP (BYO Gradio server) for Flux, Qwen-Image, and video models (Wan 2.2, Hunyuan, LTX). Configure both in Settings → Local Models.
  • Multi-Image Input — Upload up to 14 reference images for compatible edit models (Nano Banana 2 Edit, Flux Kontext Dev, GPT-4o Edit, and more). Multi-select picker with order badges, batch upload, and a "Use Selected" confirmation flow.
  • Video Studio — Generate videos from text prompts (40+ text-to-video models) or animate a start-frame image (60+ image-to-video models). Same intelligent mode switching as Image Studio.
  • Audio Studio — Generate and edit AI audio/music from text prompts.
  • AI Clipping — Auto-clip and extract highlights from longer video content.
  • Vibe Motion Studio — Motion/animation generation studio for stylized video effects.
  • Lip Sync Studio — Animate portrait images or sync lips on existing videos using audio. 9 dedicated models across two modes: portrait image + audio → talking video, and video + audio → lipsync video.
  • Body Swap (Recast) Studio — Swap/recast a subject's body or appearance in an image or video.
  • Cinema Studio — Interface for photorealistic cinematic shots with pro camera controls (Lens, Focal Length, Aperture)
  • Marketing Studio — Generate ad and marketing-ready creative variations from a single input.
  • Workflow Studio — Build and run multi-step AI pipelines visually. Chain image, video, and audio models into automated flows. Browse community templates, create your own with a node-based editor, and run them via an interactive playground.
  • Agent Studio — Multi-turn creative agent that plans and executes generation tasks conversationally.
  • Design Agent Studio — Canvas-based autonomous design agent for iterative visual work.
  • Explore Apps — Directory of app templates and use-cases built on the same model catalog.
  • AI Influencer Studio — Tools for creating and managing consistent AI persona/influencer content.
  • Upload History — Reference images are uploaded once and stored locally. A picker panel lets you reuse any previously uploaded image across sessions — no re-uploading.
  • Smart Controls — Dynamic aspect ratio, resolution/quality, and duration pickers that adapt to each model's capabilities (including t2i models with resolution or quality options)
  • Generation History — Browse, revisit, and download all past generations (persisted in browser storage)
  • Image & Video Download — One-click download of generated outputs in full resolution
  • API Key Management — Secure API key storage in browser localStorage (never sent to any server except Muapi)
  • Responsive Design — Works seamlessly on desktop and mobile with dark glassmorphism UI

🖼️ Image Studio — Dual Mode

The Image Studio automatically switches between two model sets:

Mode Trigger Models Prompt
Text-to-Image Default (no image) 50+ t2i models (Flux, Nano Banana 2, Seedream 5.0, Ideogram, GPT-4o, Midjourney…) Required
Image-to-Image Reference image uploaded 55+ i2i models (Kontext, Nano Banana 2 Edit, Seedream 5.0 Edit, Seededit, Upscaler…) Optional
Newly Added Models
Model Type Key Features
Nano Banana 2 Text-to-Image Google Gemini 3.1 Flash Image · Resolution 1K/2K/4K · Google Search enhancement · aspect ratio auto
Nano Banana 2 Edit Image-to-Image Up to 14 reference images · Resolution 1K/2K/4K · Google Search enhancement
Seedream 5.0 Text-to-Image ByteDance · Quality basic/high · 8 aspect ratios · up to 4K
Seedream 5.0 Edit Image-to-Image ByteDance · Natural language style transfer · Quality basic/high
MiniMax Image 01 Text-to-Image MiniMax · 8 aspect ratios · up to 4 images per request · 1500 char prompt
Multi-Image Input

Models that accept multiple reference images expose a multi-select picker when active:

Model Max Images
Nano Banana 2 Edit 14
Nano Banana Edit 10
Flux Kontext Dev I2I 10
Kling O1 Edit Image 10
GPT-4o Edit / GPT Image 1.5 Edit 10
Bytedance Seedream Edit v4 / v4.5 10
Vidu Q2 Reference to Image 7
Flux 2 Flex/Pro Edit 8
Nano Banana Pro Edit 8
Flux Kontext Pro/Max I2I 2
Wan 2.5/2.6 Image Edit 2–3
Qwen Image Edit Plus / 2511 3
GPT-4o Image to Image 5
Flux 2 Klein 4b/9b Edit 4

When a multi-image model is selected the upload trigger switches to multi-select mode:

  • Checkboxes with order numbers — images are sent to the model in the order you select them
  • Batch upload — pick multiple files at once from your file dialog
  • Count badge on the trigger shows how many images are active; a + badge appears when more slots are available
  • "Use Selected" button confirms and closes the picker

🎬 Video Studio — Dual Mode

The Video Studio follows the same pattern:

Mode Trigger Models Prompt
Text-to-Video Default (no image) 40+ t2v models (Kling, Sora, Veo, Wan, Seedance 2.0, Hailuo, Runway…) Required
Image-to-Video Start frame uploaded 60+ i2v models (Kling I2V, Veo3 I2V, Runway I2V, Wan I2V, Seedance 2.0 I2V, Midjourney I2V…) Optional
Newly Added Models
Model Type Key Features
Seedance 2.0 Text-to-Video ByteDance · Aspect ratios 16:9 / 9:16 / 4:3 / 3:4 · Duration 5 / 10 / 15s · Quality basic/high
Seedance 2.0 I2V Image-to-Video ByteDance · Animate images into video · Up to 9 reference images · Aspect ratios 16:9 / 9:16 / 4:3 / 3:4 · Duration 5 / 10 / 15s · Quality basic/high
Seedance 2.0 Extend Video Extension ByteDance · Seamlessly continue any Seedance 2.0 generation · Preserves style, motion & audio · Optional continuation prompt · Duration 5 / 10 / 15s · Quality basic/high
Grok Imagine T2V Text-to-Video xAI · Duration 6 / 10 / 15s · Modes: fun / normal / spicy · Aspect ratios 9:16 / 16:9 / 2:3 / 3:2 / 1:1
Grok Imagine I2V Image-to-Video xAI · Duration 6 / 10 / 15s · Modes: fun / normal / spicy · Cinematic motion from still images
MiniMax Hailuo 02 / 2.3 Standard & Pro Text-to-Video / Image-to-Video MiniMax · Full HD video · Multiple aspect ratios · Fast variant included

🎙️ Lip Sync Studio

The Lip Sync Studio generates audio-driven talking videos using 9 models across two input modes:

Mode Trigger Description
Portrait Image Default Upload a portrait image + audio file → animated talking video
Video Switch to Video mode Upload an existing video + audio file → lipsync video
Image-based Models (Portrait Image + Audio → Video)
Model Endpoint Resolutions Prompt
Infinite Talk infinitetalk-image-to-video 480p, 720p Optional
Wan 2.2 Speech to Video wan2.2-speech-to-video 480p, 720p Optional
LTX 2.3 Lipsync ltx-2.3-lipsync 480p, 720p, 1080p Optional
LTX 2 19B Lipsync ltx-2-19b-lipsync 480p, 720p, 1080p Optional
Video-based Models (Video + Audio → Lipsync Video)
Model Endpoint Resolutions Prompt
Sync Lipsync sync-lipsync — —
LatentSync latentsync-video — —
Creatify Lipsync creatify-lipsync — —
Veed Lipsync veed-lipsync — —
Infinite Talk V2V infinitetalk-video-to-video 480p, 720p Optional

How it works:

  1. Select Portrait Image or Video mode using the toggle
  2. Upload your portrait image (or video) using the image/video upload button
  3. Upload your audio file using the audio upload button
  4. Optionally enter a prompt to guide the motion style
  5. Select a model and resolution (where supported), then click Generate

Generation history is saved separately in lipsync_history and pending jobs resume automatically on page reload.

🔀 Workflow Studio

The Workflow Studio lets you build and run multi-step AI pipelines without writing code.

Key capabilities:

  • Templates — Start from pre-built workflows (image chains, video pipelines, and more)
  • My Workflows — Save and manage your own custom pipelines
  • Community — Browse and run workflows published by other users
  • Node-based Builder — Drag-and-drop visual editor to connect models and route outputs between steps
  • Playground — Run any workflow interactively with a form UI; results render inline
  • API execution — Every workflow is also callable via the Muapi API

💡 Want to add workflows to your own app? Check out Vibe Workflow — the open-source workflow engine powering this feature. Drop it into any project.

🎥 Cinema Studio Controls

The Cinema Studio offers precise control over the virtual camera, translating your choices into optimized prompt modifiers:

Category Available Options
Cameras Modular 8K Digital, Full-Frame Cine Digital, Grand Format 70mm Film, Studio Digital S35, Classic 16mm Film, Premium Large Format Digital
Lenses Creative Tilt, Compact Anamorphic, Extreme Macro, 70s Cinema Prime, Classic Anamorphic, Premium Modern Prime, Warm Cinema Prime, Swirl Bokeh Portrait, Vintage Prime, Halation Diffusion, Clinical Sharp Prime
Focal Lengths 8mm (Ultra-Wide), 14mm, 24mm, 35mm (Human Eye), 50mm (Portrait), 85mm (Tight Portrait)
Apertures f/1.4 (Shallow DoF), f/4 (Balanced), f/11 (Deep Focus)

📁 Upload History & Picker

Every image you upload is saved locally (URL + thumbnail) so you never upload the same file twice:

  • Click the upload button to open the reference image picker
  • Previously uploaded images appear in a 3-column grid with thumbnails
  • Single-image models — click a thumbnail to instantly select and close
  • Multi-image models — toggle multiple thumbnails (shown with order numbers), then click Use Selected
  • Upload new images with the Upload files button (supports multi-file selection in multi-image mode)
  • Remove individual images from history with the ✕ button
  • History persists across browser sessions (stored in localStorage)

🚀 Quick Start

Prerequisites

Setup

Most users want the desktop app, not this dev path. If you just want to run Open Generative AI on your machine, download a prebuilt installer instead — no Node.js required. The instructions below are for contributors building from source.

Pick the entry point that matches your goal:

  • Desktop app (Electron) → npm run electron:dev
  • Hosted web version (Next.js) → npm run dev
# Clone the repository (with submodules — required for the workflow + agent packages)
git clone --recurse-submodules https://github.com/Anil-matcha/Open-Generative-AI.git
cd Open-Generative-AI

# If you already cloned without --recurse-submodules, run this once:
# git submodule update --init --recursive

# Install dependencies + build workspace packages (studio, workflow, agents).
# This step is REQUIRED — `npm install` alone is not enough; the workspaces
# need to be built before either dev script will work.
npm run setup

# Then start ONE of:
npm run electron:dev   # Desktop app (Electron + Vite) — recommended
npm run dev            # Hosted web version (Next.js) → http://localhost:3000

You'll be prompted to enter your Muapi API key on first use (skip the key if you only plan to use local models).

Troubleshooting — Couldn't find a 'pages' directory: this means Next.js can't see the app/ folder. Confirm you're running npm run dev from the repo root (the directory that contains app/, package.json, and next.config.mjs), and that you cloned with submodules. Re-run npm run setup if packages/Vibe-Workflow or packages/agents are empty.

Production Build

npm run build
npm run start

Desktop App Build

Build native desktop apps with Electron:

# macOS (DMG — Intel + Apple Silicon)
npm run electron:build

# Windows (NSIS installer — x64 + ARM64)
npm run electron:build:win

# Linux (AppImage + DEB — x64)
npm run electron:build:linux

# Both platforms in one pass
npm run electron:build:all

Installers are output to the release/ folder. Pre-built binaries are also available on the Releases page.

🏗️ Architecture

The app is a Next.js monorepo with a shared packages/studio component library.

Open-Generative-AI/
├── app/                        # Next.js App Router
│   ├── layout.js               # Root layout (Tailwind, fonts)
│   ├── page.js                 # Redirects → /studio
│   └── studio/
│       └── page.js             # Studio page — renders StandaloneShell
├── components/
│   ├── StandaloneShell.js      # Tab nav + BYOK (API key from localStorage)
│   └── ApiKeyModal.js          # API key entry modal
├── packages/
│   └── studio/                 # Shared React component library
│       └── src/
│           ├── index.js        # Exports: ImageStudio, VideoStudio, AudioStudio, ClippingStudio, VibeMotionStudio, LipSyncStudio, RecastStudio, CinemaStudio, MarketingStudio, WorkflowStudio, AgentStudio, DesignAgentStudio, AppsStudio, AiInfluencerStudio, McpCliStudio
│           ├── models.js       # 400+ model definitions (single source of truth)
│           ├── muapi.js        # API client (named exports, apiKey as first param)
│           └── components/
│               ├── ImageStudio.jsx    # Dual-mode t2i/i2i studio
│               ├── VideoStudio.jsx    # Dual-mode t2v/i2v studio
│               ├── LipSyncStudio.jsx  # Portrait/video + audio → talking video
│               ├── CinemaStudio.jsx   # Pro studio with camera controls
│               └── WorkflowStudio.jsx # Multi-step pipeline builder & playground
├── next.config.mjs             # transpilePackages: ['studio']
├── tailwind.config.js
└── package.json                # workspaces: ["packages/studio"]

The packages/studio library is also consumed by the hosted version on muapi.ai — model updates made in packages/studio/src/models.js apply to both the self-hosted app and the hosted version automatically.

🔌 API Integration

The app communicates with Muapi.ai using a two-step pattern:

  1. Submit — POST /api/v1/{model-endpoint} with prompt and parameters
  2. Poll — GET /api/v1/predictions/{request_id}/result until status is completed

Authentication uses the x-api-key header. During development, a Vite proxy handles CORS by routing /api requests to https://api.muapi.ai.

File uploads use POST /api/v1/upload_file (multipart/form-data) and return a hosted URL that is passed to image-conditioned models. For multi-image models the full images_list array is forwarded to the API in one request.

Lip sync jobs use the same two-step pattern: a dedicated processLipSync() method accepts image_url or video_url alongside audio_url, dispatches to the model's endpoint, and polls until the output video URL is available.

🎨 Supported Model Categories

Category Count Examples
Text-to-Image 70+ Flux Dev, Nano Banana 2, Seedream 5.0, Ideogram v3, Midjourney v7, GPT-4o, SDXL
Image-to-Image 70+ Nano Banana 2 Edit (×14), Flux Kontext Pro, GPT-4o Edit, Seededit v3, Upscaler, Background Remover
Text-to-Video 85+ Kling v3, Sora 2, Veo 3, Wan 2.6, Seedance 2.0, Seedance 2.0 Extend, Seedance Pro, Hailuo 2.3, Runway Gen-3
Image-to-Video 120+ Kling v2.1 I2V, Veo3 I2V, Runway I2V, Seedance 2.0 I2V, Midjourney v7 I2V, Hunyuan I2V, Wan2.2 I2V
Video-to-Video 35+ Video effects, AI Clipping, Vibe Motion, video-conditioned edits
Lip Sync 15 Infinite Talk I2V, Wan 2.2 Speech to Video, LTX 2.3 Lipsync, LTX 2 19B Lipsync, Sync, LatentSync, Creatify, Veed, Infinite Talk V2V
Body Swap / Recast 3 Subject/appearance recast across image and video
Audio 15+ Text-to-music, remix, and audio editing models

(Counts verified against packages/studio/src/models.js — total 420+ models across these 8 categories, plus additional models surfaced through Marketing, Agent, and Design Agent studios.)

🛠️ Tech Stack

  • Next.js 14 — App Router, server components, fast dev server
  • React 18 — Studio UI components
  • Tailwind CSS v3 — Utility-first styling
  • npm workspaces — Monorepo with shared packages/studio library
  • Muapi.ai — AI model API gateway

🤔 How is this different from other AI Video Platforms?

Open Generative AI is a community-driven, open-source alternative that provides similar creative capabilities without the closed ecosystem:

Other providers Open Generative AI
Cost Subscription-based Free (open-source)
Content filters Yes — prompts blocked or altered None
Restrictions Platform guardrails enforced Full creative freedom
Models Proprietary 400+ open & commercial models
Multi-image input Limited Up to 14 images per request
Lip sync No 9 models, image & video modes
Hosted version Subscription Free at muapi.ai/open-generative-ai
Self-hosting No Yes
Customizable No Fully hackable
Data privacy Cloud-based Your data stays local
Source code Closed MIT licensed

📄 License

MIT

🙏 Credits

Built with Muapi.ai — the unified API for AI image and video generation models.


Deep Dive: For more details on the "AI Influencer" engine, upcoming "Popcorn" storyboarding features, and the future of this project, read the full technical overview.


Looking for a free, open-source AI Video Platform? Open Generative AI is an open-source AI image and video generation studio — with no content filters that you can self-host, customize, and extend.

View on GitHub

Recent activity

commits and pull requests

Releases and announcements

13 total
  1. ## What's New in v2.0.0 ### New Features - **Audio Studio** — dedicated audio generation tab - **Vibe Motion** — new motion effect capability - **Clipping Tab** — video clipping workflow - **Design Agent** — AI-powered design assistant integration - **EN/ZH Language Switcher** — internationalization across all studio components - **Interactive Command Generator Playground** — MCP CLI studio improvement - **Custom Local-AI Storage Directory** — choose where local models are stored ### Fixes & Improvements - **Wan2GP:** keep default endpoints available without metadata; endpoint fallback support - **Studio:** re-prompt for API key on 401/403 responses and harden header visibility - **Models:** correct Z-Image Base download URL filename casing - **McpCliStudio:** remove duplicated helpers and orphan code that broke Vite build - **Local-AI:** include model name and ID in download error messages - **Linux:** bundled local inference packaging for Linux builds - **Workflow/Design Agent:** updated UI components and Tailwind/jsconfig paths ## Downloads - **Windows:** Open.Generative.AI.Setup.2.0.0.exe - **macOS (Apple Silicon):** Open.Generative.AI-2.0.0-arm64.dmg - **macOS (Intel):** O

  2. ## Fix - **Video Studio:** the end-frame picker (for FLF image-to-video models like kling / veo / seedance) no longer triggers the API-key modal when a Wan2GP local model is selected. It now mirrors the start-frame picker's local-aware gating — routing uploads through Wan2GP and bypassing the auth prompt for local models. ## Downloads - **Windows:** `Open.Generative.AI.Setup.1.0.11.exe` - **macOS (Apple Silicon):** `Open.Generative.AI-1.0.11-arm64.dmg` - **macOS (Intel):** `Open.Generative.AI-1.0.11.dmg` - **Linux (AppImage):** `Open.Generative.AI-1.0.11.AppImage` - **Linux (Debian/Ubuntu):** `open-generative-ai_1.0.11_amd64.deb`

  3. ## What's new - **fix(lipsync):** Infinite Talk image-to-video (and the other `hasPrompt: true` lipsync models — Wan 2.2 s2v, LTX 2.3, LTX 2 19B, Infinite Talk v2v) no longer fail with `field "prompt" failed nullable validation: Value is not nullable; got null` when the prompt textarea is left blank. The client now always sends a `prompt` field (defaulting to an empty string) for those models so the backend never forwards `null` to the underlying API. ## Downloads - **macOS (Apple Silicon):** `Open Generative AI-1.0.10-arm64.dmg` - **macOS (Intel):** `Open Generative AI-1.0.10.dmg` - **Windows (x64):** `Open Generative AI Setup 1.0.10.exe` - **Linux (AppImage):** `Open Generative AI-1.0.10.AppImage` - **Linux (Debian/Ubuntu):** `open-generative-ai_1.0.10_amd64.deb` **Full changelog:** https://github.com/Anil-matcha/Open-Generative-AI/compare/v1.0.9...v1.0.10

  4. v1.0.9 — Local Wan2GP video generationv1.0.9Apr 27, 202690.9K downloads

    ## What's new Closes #126 — local Wan2GP users could not upload reference media or generate video locally even with WanGP installed, hitting "Not authorized: missing or invalid credentials" because every Video Studio upload was hard-wired to the Muapi-hosted endpoint. ### Fix - **Wan2GP upload bridge** (`wan2gp:upload-file` IPC) — pushes files to the configured Wan2GP server's `/upload` endpoint and rehydrates them into Gradio `FileData` descriptors at generation time. - **Local Video Studio** — Wan 2.2 t2v / Wan 2.2 i2v / Hunyuan / LTX models now appear in the Video Studio model picker when running in the desktop app. - **Auth gate bypassed for local models** — generating with a Wan2GP model no longer requires a Muapi API key. - **Generation routing** — Video Studio's t2v and i2v paths call `localAI.generate(...)` for Wan2GP models and surface step progress in the Generate button. ### Setup for local video 1. Run a Wan2GP server (`https://github.com/deepbeepmeep/Wan2GP`) on a machine with a CUDA or ROCm GPU. 2. In Settings → Local Models, set the server URL (e.g. `http://localhost:7860`). 3. Pick a Wan2GP entry from the Video Studio model dropdown. If your Wan2GP build exposes

  5. ## What's new - **Windows build restored.** v1.0.7 shipped Mac-only because the root `tailwindcss` was on v4 while workspace packages were on v3 — the v3/v4 mismatch broke the Windows electron build. v1.0.8 completes the revert to Tailwind v3 across the root app (CSS directives, vite config, postcss config) so the Windows installer builds and runs again. ## Downloads - **Windows (x64)** — `Open Generative AI Setup 1.0.8.exe` (unsigned NSIS installer; click *More info → Run anyway* on the SmartScreen warning) - macOS users: stay on [v1.0.7](https://github.com/Anil-matcha/Open-Generative-AI/releases/tag/v1.0.7) — there are no macOS-affecting changes in v1.0.8. ## Notes The Windows installer is **not code-signed**. SmartScreen will warn on first install — this is expected.

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When work happens

weekday and hour
SunMonTueWedThuFriSat036912151821Sun 0:00 — 4 commitsSun 1:00 — 3 commitsSun 2:00 — 5 commitsSun 3:00 — 0 commitsSun 4:00 — 0 commitsSun 5:00 — 1 commitsSun 6:00 — 6 commitsSun 7:00 — 3 commitsSun 8:00 — 0 commitsSun 9:00 — 0 commitsSun 10:00 — 3 commitsSun 11:00 — 1 commitsSun 12:00 — 1 commitsSun 13:00 — 0 commitsSun 14:00 — 0 commitsSun 15:00 — 2 commitsSun 16:00 — 0 commitsSun 17:00 — 2 commitsSun 18:00 — 1 commitsSun 19:00 — 0 commitsSun 20:00 — 2 commitsSun 21:00 — 0 commitsSun 22:00 — 0 commitsSun 23:00 — 2 commitsMon 0:00 — 3 commitsMon 1:00 — 0 commitsMon 2:00 — 0 commitsMon 3:00 — 0 commitsMon 4:00 — 0 commitsMon 5:00 — 3 commitsMon 6:00 — 0 commitsMon 7:00 — 0 commitsMon 8:00 — 1 commitsMon 9:00 — 0 commitsMon 10:00 — 5 commitsMon 11:00 — 2 commitsMon 12:00 — 1 commitsMon 13:00 — 1 commitsMon 14:00 — 2 commitsMon 15:00 — 4 commitsMon 16:00 — 6 commitsMon 17:00 — 0 commitsMon 18:00 — 0 commitsMon 19:00 — 4 commitsMon 20:00 — 1 commitsMon 21:00 — 1 commitsMon 22:00 — 0 commitsMon 23:00 — 6 commitsTue 0:00 — 0 commitsTue 1:00 — 0 commitsTue 2:00 — 5 commitsTue 3:00 — 2 commitsTue 4:00 — 1 commitsTue 5:00 — 0 commitsTue 6:00 — 0 commitsTue 7:00 — 0 commitsTue 8:00 — 0 commitsTue 9:00 — 2 commitsTue 10:00 — 2 commitsTue 11:00 — 1 commitsTue 12:00 — 13 commitsTue 13:00 — 8 commitsTue 14:00 — 3 commitsTue 15:00 — 2 commitsTue 16:00 — 0 commitsTue 17:00 — 3 commitsTue 18:00 — 3 commitsTue 19:00 — 4 commitsTue 20:00 — 3 commitsTue 21:00 — 2 commitsTue 22:00 — 2 commitsTue 23:00 — 4 commitsWed 0:00 — 10 commitsWed 1:00 — 1 commitsWed 2:00 — 1 commitsWed 3:00 — 0 commitsWed 4:00 — 1 commitsWed 5:00 — 0 commitsWed 6:00 — 1 commitsWed 7:00 — 0 commitsWed 8:00 — 0 commitsWed 9:00 — 0 commitsWed 10:00 — 2 commitsWed 11:00 — 6 commitsWed 12:00 — 9 commitsWed 13:00 — 7 commitsWed 14:00 — 5 commitsWed 15:00 — 5 commitsWed 16:00 — 3 commitsWed 17:00 — 4 commitsWed 18:00 — 3 commitsWed 19:00 — 4 commitsWed 20:00 — 5 commitsWed 21:00 — 4 commitsWed 22:00 — 2 commitsWed 23:00 — 4 commitsThu 0:00 — 0 commitsThu 1:00 — 3 commitsThu 2:00 — 3 commitsThu 3:00 — 0 commitsThu 4:00 — 1 commitsThu 5:00 — 1 commitsThu 6:00 — 0 commitsThu 7:00 — 0 commitsThu 8:00 — 1 commitsThu 9:00 — 2 commitsThu 10:00 — 4 commitsThu 11:00 — 1 commitsThu 12:00 — 0 commitsThu 13:00 — 2 commitsThu 14:00 — 3 commitsThu 15:00 — 0 commitsThu 16:00 — 2 commitsThu 17:00 — 4 commitsThu 18:00 — 3 commitsThu 19:00 — 0 commitsThu 20:00 — 3 commitsThu 21:00 — 3 commitsThu 22:00 — 2 commitsThu 23:00 — 3 commitsFri 0:00 — 1 commitsFri 1:00 — 0 commitsFri 2:00 — 0 commitsFri 3:00 — 2 commitsFri 4:00 — 0 commitsFri 5:00 — 4 commitsFri 6:00 — 0 commitsFri 7:00 — 0 commitsFri 8:00 — 0 commitsFri 9:00 — 5 commitsFri 10:00 — 3 commitsFri 11:00 — 0 commitsFri 12:00 — 4 commitsFri 13:00 — 11 commitsFri 14:00 — 4 commitsFri 15:00 — 8 commitsFri 16:00 — 4 commitsFri 17:00 — 6 commitsFri 18:00 — 5 commitsFri 19:00 — 12 commitsFri 20:00 — 8 commitsFri 21:00 — 3 commitsFri 22:00 — 3 commitsFri 23:00 — 3 commitsSat 0:00 — 0 commitsSat 1:00 — 2 commitsSat 2:00 — 2 commitsSat 3:00 — 0 commitsSat 4:00 — 0 commitsSat 5:00 — 0 commitsSat 6:00 — 2 commitsSat 7:00 — 0 commitsSat 8:00 — 0 commitsSat 9:00 — 0 commitsSat 10:00 — 8 commitsSat 11:00 — 2 commitsSat 12:00 — 1 commitsSat 13:00 — 1 commitsSat 14:00 — 5 commitsSat 15:00 — 4 commitsSat 16:00 — 2 commitsSat 17:00 — 1 commitsSat 18:00 — 3 commitsSat 19:00 — 4 commitsSat 20:00 — 4 commitsSat 21:00 — 3 commitsSat 22:00 — 1 commitsSat 23:00 — 1 commits
Commit volume by weekday and hour (UTC). Larger dots mean more commits.

Who is committing

last 52 weeks
Maintainer commits307 (66%)
Community commits158 (34%)

465 commits in total over the last year.

DateListRankStars gained
May 18, 2026daily#23+43
May 17, 2026daily#15+121
Apr 25, 2026daily#19+162
Apr 24, 2026daily#22+101
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