README_WINDOWS.md

Windows 10/11

• Single .bat file for installation (if you do not skip any optional packages, takes about 9GB filled on disk).
• Recommend base Conda env, which allows for DocTR that requires pygobject that has otherwise no support (except mysys2 that cannot be used by h2oGPT).
• Also allows for the TTS package by Coqui, which is otherwise not currently enabled in the one-click installer.

Install

• Download Visual Studio 2022: Download Link
  • Run Installer, click ok to run, click Continue
  • Click on Individual Components
  • Search for these in the search bar and click on them:
    • Windows 11 SDK (e.g. 10.0.22000.0)
    • C++ Universal Windows Platform support (e.g. for v143 build tools)
    • MSVC VS 2022 C++ x64/x86 build tools (latest)
    • C++ CMake tools for Windows
    • 
  • Click Install, and follow through installation, and do not need to launch VS 2022 at end.
• Download the MinGW installer: MiniGW
  • Run Installer, Click Install, Continue, Install/Run to launch installation manager.
  • Select packages to install:
    • minigw32-base
    • mingw32-gcc-g++
    • 
  • Go to installation tab, then apply changes.
• Download and install Miniconda
• Run Miniconda shell (not powershell!) as Administrator
• Run: set path=%path%;c:\MinGW\msys\1.0\bin\ to get C++ in path. In some cases it may be instead correct to use set path=%path%;c:\MinGW\bin\
• Download latest nvidia driver for windows if one has old drivers before CUDA 11.8 supported
• Confirm can run nvidia-smi and see driver version
• Setup Conda Environment:
  • 

   conda create -n h2ogpt -y
   conda activate h2ogpt
   conda install python=3.10 -c conda-forge -y
   python --version  # should say python 3.10.xx
   python -c "import os, sys ; print('hello world')"  # should print "hello world"

• GPU Only: Install CUDA

   conda install cudatoolkit=11.8 -c conda-forge -y
   set CUDA_HOME=$CONDA_PREFIX

• Install Git:

   conda install -c conda-forge git

• Install h2oGPT:

   git clone https://github.com/h2oai/h2ogpt.git
   cd h2ogpt

• Prepare to install dependencies:

  set PIP_EXTRA_INDEX_URL=https://download.pytorch.org/whl/cu118 https://huggingface.github.io/autogptq-index/whl/cu118/
  

  Choose cu118+ for A100/H100+. Or for CPU set

  set PIP_EXTRA_INDEX_URL=https://download.pytorch.org/whl/cpu
  

• For non-CPU case, choose llama_cpp_python ARGS for your system according to llama_cpp_python backend documentation, e.g. for CUDA:

   set CMAKE_ARGS=-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=all
   set GGML_CUDA=1
   set FORCE_CMAKE=1
  

  Note for some reason things will fail with llama_cpp_python if don't add all cuda arches, and building with all those arches does take some time.
• Run `docs\windows_install.bat for full normal document Q/A installation. To allow all (GPL too) packages, run:

  set GPLOK=1
  docs\windows_install.bat
  

One can pick and choose different optional things to install instead by commenting them out in the shell script, or edit the script if any issues. See script for notes about installation.

See `docs\windows_install.bat for additional installation instructions for:

• Microsoft Word/Excel support
• Tesseract OCR support

Note models are stored in C:\Users\<user>\.cache\ for chroma, huggingface, selenium, torch, weaviate, etc. directories. For an absolute windows path, choose --user_path=C:\Users\YourUsername\h2ogpt or something similar for some user YourUsername. If the model is using the GPU, in nvidia-smi or some other GPU monitor program you should see python.exe using GPUs in C (Compute) mode and using GPU resources. Use set CUDA_VISIBLE_DEVICES=0 to pick first model, since llama.cpp models cannot choose which GPU otherwise.

See FAQ for how to run various models. See CPU and GPU for some other general aspects about using h2oGPT on CPU or GPU, such as which models to try, quantization, etc.

Possible Issues

• SSL Certification failure when connecting to Hugging Face.
  • Your org may be blocking HF
  • Try: https://stackoverflow.com/a/75111104
  • Or try: huggingface/transformers#17611 (comment)
  • Try using proxy.
• If you see import problems, then try setting PYTHONPATH in a .bat file:

  SET PYTHONPATH=.:src:$PYTHONPATH
  python generate.py ...

  for some options ...
• For easier handling of command line operations, consider using bash in windows with coreutils.

Control ENV

• In this Python code, set ENVs anywhere before main_h2ogpt() is called
  • E.g. os.environ['name'] = 'value', e.g. os.environ['n_jobs'] = '10' (must be always a string).
  • Environment variables can be changed, e.g.:
    • n_jobs: number of cores for various tasks
    • OMP_NUM_THREADS thread count for LLaMa
    • CUDA_VISIBLE_DEVICES which GPUs are used. Recommend set to single fast GPU, e.g. CUDA_VISIBLE_DEVICES=0 if have multiple GPUs. Note that UI cannot control which GPUs (or CPU mode) for LLaMa models.
    • Any CLI argument from python generate.py --help with environment variable set as h2ogpt_x, e.g. h2ogpt_h2ocolors to False.
    • Set env h2ogpt_server_name to actual IP address for LAN to see app, e.g. h2ogpt_server_name to 192.168.1.172 and allow access through firewall if have Windows Defender activated.
  • To terminate the app, go to System Tab and click Admin and click Shutdown h2oGPT.
    • If startup fails, run as console and check for errors, e.g. and kill any old Python processes.