InvokeAI/docs/installation/INSTALL_MANUAL.md

title
Manual Installation

# :fontawesome-brands-linux: Linux | :fontawesome-brands-apple: macOS | :fontawesome-brands-windows: Windows

!!! warning "This is for advanced Users"

who are already expirienced with using conda or pip

Introduction

You have two choices for manual installation, the first one based on the Anaconda3 package manager (conda), and a second one which uses basic Python virtual environment (venv) commands and the PIP package manager. Both methods require you to enter commands on the terminal, also known as the "console".

On Windows systems you are encouraged to install and use the Powershell, which provides compatibility with Linux and Mac shells and nice features such as command-line completion.

Conda method

1. Check that your system meets the hardware requirements and has the appropriate GPU drivers installed. In particular, if you are a Linux user with an AMD GPU installed, you may need to install the ROCm driver.

   InvokeAI does not yet support Windows machines with AMD GPUs due to the lack of ROCm driver support on this platform.

   To confirm that the appropriate drivers are installed, run nvidia-smi on NVIDIA/CUDA systems, and rocm-smi on AMD systems. These should return information about the installed video card.

   Macintosh users with MPS acceleration, or anybody with a CPU-only system, can skip this step.

2. You will need to install Anaconda3 and Git if they are not already available. Use your operating system's preferred package manager, or download the installers manually. You can find them here:

   • Anaconda3
   • git

3. Clone the InvokeAI source code from GitHub:

   git clone https://github.com/invoke-ai/InvokeAI.git
   

   This will create InvokeAI folder where you will follow the rest of the steps.

4. Enter the newly-created InvokeAI folder:

   cd InvokeAI
   

   From this step forward make sure that you are working in the InvokeAI directory!

5. Select the appropriate environment file:

   We have created a series of environment files suited for different operating systems and GPU hardware. They are located in the environments-and-requirements directory:

   filename	OS
   environment-lin-amd.yml	Linux with an AMD (ROCm) GPU
   environment-lin-cuda.yml	Linux with an NVIDIA CUDA GPU
   environment-mac.yml	Macintosh
   environment-win-cuda.yml	Windows with an NVIDA CUDA GPU

   Choose the appropriate environment file for your system and link or copy it to environment.yml in InvokeAI's top-level directory. To do so, run following command from the repository-root:

   !!! Example ""

   === "Macintosh and Linux"
   
       !!! todo "Replace `xxx` and `yyy` with the appropriate OS and GPU codes as seen in the table above"
   
       ```bash
       ln -sf environments-and-requirements/environment-xxx-yyy.yml environment.yml
       ```
   
       When this is done, confirm that a file `environment.yml` has been linked in
       the InvokeAI root directory and that it points to the correct file in the
       `environments-and-requirements`.
   
       ```bash
       ls -la
       ```
   
   === "Windows"
   
       !!! todo " Since it requires admin privileges to create links, we will use the copy command to create your `environment.yml`"
   
       ```cmd
       copy environments-and-requirements\environment-win-cuda.yml environment.yml
       ```
   
       Afterwards verify that the file `environment.yml` has been created, either via the
       explorer or by using the command `dir` from the terminal
   
       ```cmd
       dir
       ```
   

   !!! warning "Do not try to run conda on directly on the subdirectory environments file. This won't work. Instead, copy or link it to the top-level directory as shown."

6. Create the conda environment:

   conda env update
   

   This will create a new environment named invokeai and install all InvokeAI dependencies into it. If something goes wrong you should take a look at troubleshooting.

7. Activate the invokeai environment:

   In order to use the newly created environment you will first need to activate it

   conda activate invokeai
   

   Your command-line prompt should change to indicate that invokeai is active by prepending (invokeai).

8. Pre-Load the model weights files:

   !!! tip

   If you have already downloaded the weights file(s) for another Stable
   Diffusion distribution, you may skip this step (by selecting "skip" when
   prompted) and configure InvokeAI to use the previously-downloaded files. The
   process for this is described in [here](INSTALLING_MODELS.md).
   

   python scripts/preload_models.py
   

   The script preload_models.py will interactively guide you through the process of downloading and installing the weights files needed for InvokeAI. Note that the main Stable Diffusion weights file is protected by a license agreement that you have to agree to. The script will list the steps you need to take to create an account on the site that hosts the weights files, accept the agreement, and provide an access token that allows InvokeAI to legally download and install the weights files.

   If you get an error message about a module not being installed, check that the invokeai environment is active and if not, repeat step 5.

9. Run the command-line- or the web- interface:

   !!! example ""

   !!! warning "Make sure that the conda environment is activated, which should create `(invokeai)` in front of your prompt!"
   
   === "CLI"
   
       ```bash
       python scripts/invoke.py
       ```
   
   === "local Webserver"
   
       ```bash
       python scripts/invoke.py --web
       ```
   
   === "Public Webserver"
   
       ```bash
       python scripts/invoke.py --web --host 0.0.0.0
       ```
   
   If you choose the run the web interface, point your browser at
   http://localhost:9090 in order to load the GUI.
   

10. Render away!

    Browse the features section to learn about all the things you can do with InvokeAI.

    Note that some GPUs are slow to warm up. In particular, when using an AMD card with the ROCm driver, you may have to wait for over a minute the first time you try to generate an image. Fortunately, after the warm up period rendering will be fast.

11. Subsequently, to relaunch the script, be sure to run "conda activate invokeai", enter the InvokeAI directory, and then launch the invoke script. If you forget to activate the 'invokeai' environment, the script will fail with multiple ModuleNotFound errors.

Updating to newer versions of the script

This distribution is changing rapidly. If you used the git clone method (step 5) to download the InvokeAI directory, then to update to the latest and greatest version, launch the Anaconda window, enter InvokeAI and type:

git pull
conda env update
python scripts/preload_models.py --no-interactive  #optional

This will bring your local copy into sync with the remote one. The last step may be needed to take advantage of new features or released models. The --no-interactive flag will prevent the script from prompting you to download the big Stable Diffusion weights files.

pip Install

To install InvokeAI with only the PIP package manager, please follow these steps:

1. Make sure you are using Python 3.9 or higher. The rest of the install procedure depends on this:

   python -V
   

2. Install the virtualenv tool if you don't have it already:

   pip install virtualenv
   

3. From within the InvokeAI top-level directory, create and activate a virtual environment named invokeai:

   virtualenv invokeai
   source invokeai/bin/activate
   

4. Pick the correct requirements*.txt file for your hardware and operating system.

   We have created a series of environment files suited for different operating systems and GPU hardware. They are located in the environments-and-requirements directory:

   filename	OS
   requirements-lin-amd.txt	Linux with an AMD (ROCm) GPU
   requirements-lin-arm64.txt	Linux running on arm64 systems
   requirements-lin-cuda.txt	Linux with an NVIDIA (CUDA) GPU
   requirements-mac-mps-cpu.txt	Macintoshes with MPS acceleration
   requirements-lin-win-colab-cuda.txt	Windows with an NVIDA (CUDA) GPU (supports Google Colab too)

   Select the appropriate requirements file, and make a link to it from requirements.txt in the top-level InvokeAI directory. The command to do this from the top-level directory is:

   !!! example ""

   === "Macintosh and Linux"
   
       !!! info "Replace `xxx` and `yyy` with the appropriate OS and GPU codes."
   
       ```bash
       ln -sf environments-and-requirements/requirements-xxx-yyy.txt requirements.txt
       ```
   
   === "Windows"
   
       !!! info "on Windows, admin privileges are required to make links, so we use the copy command instead"
   
       ```cmd
       copy environments-and-requirements\requirements-lin-win-colab-cuda.txt requirements.txt
       ```
   
   !!! warning
   
       Please do not link or copy `environments-and-requirements/requirements-base.txt`.
       This is a base requirements file that does not have the platform-specific
       libraries. Also, be sure to link or copy the platform-specific file to
   a top-level file named `requirements.txt` as shown here. Running pip on
   a requirements file in a subdirectory will not work as expected.
   

   When this is done, confirm that a file named requirements.txt has been created in the InvokeAI root directory and that it points to the correct file in environments-and-requirements.

5. Run PIP

   Be sure that the invokeai environment is active before doing this:

   pip install --prefer-binary -r requirements.txt
   

---

Troubleshooting

Here are some common issues and their suggested solutions.

Conda

Conda fails before completing conda update

The usual source of these errors is a package incompatibility. While we have tried to minimize these, over time packages get updated and sometimes introduce incompatibilities.

We suggest that you search Issues or the "bugs-and-support" channel of the InvokeAI Discord.

You may also try to install the broken packages manually using PIP. To do this, activate the invokeai environment, and run pip install with the name and version of the package that is causing the incompatibility. For example:

pip install test-tube==0.7.5

You can keep doing this until all requirements are satisfied and the invoke.py script runs without errors. Please report to Issues what you were able to do to work around the problem so that others can benefit from your investigation.

Create Conda Environment fails on MacOS

If conda create environment fails with lmdb error, this is most likely caused by Clang. Run brew config to see which Clang is installed on your Mac. If Clang isn't installed, that's causing the error. Start by installing additional XCode command line tools, followed by brew install llvm.

xcode-select --install
brew install llvm

If brew config has Clang installed, update to the latest llvm and try creating the environment again.

preload_models.py or invoke.py crashes at an early stage

This is usually due to an incomplete or corrupted Conda install. Make sure you have linked to the correct environment file and run conda update again.

If the problem persists, a more extreme measure is to clear Conda's caches and remove the invokeai environment:

conda deactivate
conda env remove -n invokeai
conda clean -a
conda update

This removes all cached library files, including ones that may have been corrupted somehow. (This is not supposed to happen, but does anyway).

invoke.py crashes at a later stage

If the CLI or web site had been working ok, but something unexpected happens later on during the session, you've encountered a code bug that is probably unrelated to an install issue. Please search Issues, file a bug report, or ask for help on Discord

My renders are running very slowly

You may have installed the wrong torch (machine learning) package, and the system is running on CPU rather than the GPU. To check, look at the log messages that appear when invoke.py is first starting up. One of the earlier lines should say Using device type cuda. On AMD systems, it will also say "cuda", and on Macintoshes, it should say "mps". If instead the message says it is running on "cpu", then you may need to install the correct torch library.

You may be able to fix this by installing a different torch library. Here are the magic incantations for Conda and PIP.

!!! todo "For CUDA systems"

- conda

  ```bash
  conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
  ```

- pip

  ```bash
  pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116
  ```

!!! todo "For AMD systems"

- conda

  ```bash
  conda activate invokeai
  pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
  ```

- pip

  ```bash
  pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
  ```

More information and troubleshooting tips can be found at https://pytorch.org.