import argparse import glob import os import re import site import subprocess import sys script_dir = os.getcwd() conda_env_path = os.path.join(script_dir, "installer_files", "env") # Command-line flags if "OOBABOOGA_FLAGS" in os.environ: CMD_FLAGS = os.environ["OOBABOOGA_FLAGS"] print("The following flags have been taken from the environment variable 'OOBABOOGA_FLAGS':") print(CMD_FLAGS) print("To use the CMD_FLAGS Inside webui.py, unset 'OOBABOOGA_FLAGS'.\n") else: cmd_flags_path = os.path.join(script_dir, "CMD_FLAGS.txt") if os.path.exists(cmd_flags_path): with open(cmd_flags_path, 'r') as f: CMD_FLAGS = ' '.join(line.strip() for line in f.read().splitlines() if line.strip()) else: CMD_FLAGS = '--chat' # Remove the '# ' from the following lines as needed for your AMD GPU on Linux # os.environ["ROCM_PATH"] = '/opt/rocm' # os.environ["HSA_OVERRIDE_GFX_VERSION"] = '10.3.0' # os.environ["HCC_AMDGPU_TARGET"] = 'gfx1030' def print_big_message(message): message = message.strip() lines = message.split('\n') print("\n\n*******************************************************************") for line in lines: if line.strip() != '': print("*", line) print("*******************************************************************\n\n") def run_cmd(cmd, assert_success=False, environment=False, capture_output=False, env=None): # Use the conda environment if environment: if sys.platform.startswith("win"): conda_bat_path = os.path.join(script_dir, "installer_files", "conda", "condabin", "conda.bat") cmd = "\"" + conda_bat_path + "\" activate \"" + conda_env_path + "\" >nul && " + cmd else: conda_sh_path = os.path.join(script_dir, "installer_files", "conda", "etc", "profile.d", "conda.sh") cmd = ". \"" + conda_sh_path + "\" && conda activate \"" + conda_env_path + "\" && " + cmd # Run shell commands result = subprocess.run(cmd, shell=True, capture_output=capture_output, env=env) # Assert the command ran successfully if assert_success and result.returncode != 0: print("Command '" + cmd + "' failed with exit status code '" + str(result.returncode) + "'. Exiting...") sys.exit() return result def check_env(): # If we have access to conda, we are probably in an environment conda_exist = run_cmd("conda", environment=True, capture_output=True).returncode == 0 if not conda_exist: print("Conda is not installed. Exiting...") sys.exit() # Ensure this is a new environment and not the base environment if os.environ["CONDA_DEFAULT_ENV"] == "base": print("Create an environment for this project and activate it. Exiting...") sys.exit() def clear_cache(): run_cmd("conda clean -a -y", environment=True) run_cmd("python -m pip cache purge", environment=True) def install_dependencies(): # Select your GPU or, choose to run in CPU mode print("What is your GPU") print() print("A) NVIDIA") print("B) AMD (Linux/MacOS only. Requires ROCm SDK 5.4.2/5.4.3 on Linux)") print("C) Apple M Series") print("D) None (I want to run models in CPU mode)") print() gpuchoice = input("Input> ").lower() if gpuchoice == "d": print_big_message("Once the installation ends, make sure to open CMD_FLAGS.txt with\na text editor and add the --cpu flag.") # Install the version of PyTorch needed if gpuchoice == "a": run_cmd('conda install -y -k cuda ninja git -c nvidia/label/cuda-11.7.0 -c nvidia && python -m pip install torch==2.0.1+cu117 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117', assert_success=True, environment=True) elif gpuchoice == "b" and not sys.platform.startswith("darwin"): if sys.platform.startswith("linux"): run_cmd('conda install -y -k ninja git && python -m pip install torch==2.0.1+rocm5.4.2 torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.4.2', assert_success=True, environment=True) else: print("AMD GPUs are only supported on Linux. Exiting...") sys.exit() elif (gpuchoice == "c" or gpuchoice == "b") and sys.platform.startswith("darwin"): run_cmd("conda install -y -k ninja git && python -m pip install torch torchvision torchaudio", assert_success=True, environment=True) elif gpuchoice == "d" or gpuchoice == "c": if sys.platform.startswith("linux"): run_cmd("conda install -y -k ninja git && python -m pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu", assert_success=True, environment=True) else: run_cmd("conda install -y -k ninja git && python -m pip install torch torchvision torchaudio", assert_success=True, environment=True) else: print("Invalid choice. Exiting...") sys.exit() # Clone webui to our computer run_cmd("git clone https://github.com/oobabooga/text-generation-webui.git", assert_success=True, environment=True) # Install the webui dependencies update_dependencies(initial_installation=True) def update_dependencies(initial_installation=False): os.chdir("text-generation-webui") run_cmd("git pull", assert_success=True, environment=True) # Workaround for git+ packages not updating properly Also store requirements.txt for later use with open("requirements.txt") as f: textgen_requirements = f.read() git_requirements = [req for req in textgen_requirements.splitlines() if req.startswith("git+")] # Loop through each "git+" requirement and uninstall it for req in git_requirements: # Extract the package name from the "git+" requirement url = req.replace("git+", "") package_name = url.split("/")[-1].split("@")[0] # Uninstall the package using pip run_cmd("python -m pip uninstall -y " + package_name, environment=True) print(f"Uninstalled {package_name}") # Installs/Updates the project dependencies run_cmd("python -m pip install -r requirements.txt --upgrade", assert_success=True, environment=True) # Installs the extensions dependencies (only on the first install) if initial_installation: extensions = next(os.walk("extensions"))[1] for extension in extensions: if extension in ['superbooga']: # No wheels available for dependencies continue extension_req_path = os.path.join("extensions", extension, "requirements.txt") if os.path.exists(extension_req_path): run_cmd("python -m pip install -r " + extension_req_path + " --upgrade", assert_success=True, environment=True) # The following dependencies are for CUDA, not CPU # Parse output of 'pip show torch' to determine torch version torver_cmd = run_cmd("python -m pip show torch", assert_success=True, environment=True, capture_output=True) torver = [v.split()[1] for v in torver_cmd.stdout.decode('utf-8').splitlines() if 'Version:' in v][0] # Check for '+cu' or '+rocm' in version string to determine if torch uses CUDA or ROCm check for pytorch-cuda as well for backwards compatibility if '+cu' not in torver and '+rocm' not in torver and run_cmd("conda list -f pytorch-cuda | grep pytorch-cuda", environment=True, capture_output=True).returncode == 1: clear_cache() return # Get GPU CUDA/compute support if '+cu' in torver: nvcc_device_query = "__nvcc_device_query" if not sys.platform.startswith("win") else "__nvcc_device_query.exe" compute_array = run_cmd(os.path.join(conda_env_path, "bin", nvcc_device_query), environment=True, capture_output=True) else: compute_array = type('obj', (object,), {'stdout': b'', 'returncode': 1}) # Fix a bitsandbytes compatibility issue with Linux # if sys.platform.startswith("linux"): # shutil.copy(os.path.join(site_packages_path, "bitsandbytes", "libbitsandbytes_cuda117.so"), os.path.join(site_packages_path, "bitsandbytes", "libbitsandbytes_cpu.so")) if not os.path.exists("repositories/"): os.mkdir("repositories") os.chdir("repositories") # Install or update exllama as needed if not os.path.exists("exllama/"): run_cmd("git clone https://github.com/turboderp/exllama.git", environment=True) else: os.chdir("exllama") run_cmd("git pull", environment=True) os.chdir("..") # Pre-installed exllama module does not support AMD GPU if '+rocm' in torver: run_cmd("python -m pip uninstall -y exllama", environment=True) # Get download URL for latest exllama ROCm wheel exllama_rocm = run_cmd('curl -s https://api.github.com/repos/jllllll/exllama/releases/latest | grep browser_download_url | grep rocm5.4.2-cp310-cp310-linux_x86_64.whl | cut -d : -f 2,3 | tr -d \'"\'', environment=True, capture_output=True).stdout.decode('utf-8') if 'rocm5.4.2-cp310-cp310-linux_x86_64.whl' in exllama_rocm: run_cmd("python -m pip install " + exllama_rocm, environment=True) # Fix build issue with exllama in Linux/WSL if sys.platform.startswith("linux") and not os.path.exists(f"{conda_env_path}/lib64"): run_cmd(f'ln -s "{conda_env_path}/lib" "{conda_env_path}/lib64"', environment=True) # oobabooga fork requires min compute of 6.0 gptq_min_compute = 60 gptq_min_compute_check = any(int(compute) >= gptq_min_compute for compute in compute_array.stdout.decode('utf-8').split(',')) if compute_array.returncode == 0 else False # Install GPTQ-for-LLaMa which enables 4bit CUDA quantization if not os.path.exists("GPTQ-for-LLaMa/"): # Install oobabooga fork if min compute met or if failed to check if '+rocm' in torver: run_cmd("git clone https://github.com/WapaMario63/GPTQ-for-LLaMa-ROCm.git GPTQ-for-LLaMa -b rocm", assert_success=True, environment=True) elif gptq_min_compute_check or compute_array.returncode != 0: run_cmd("git clone https://github.com/oobabooga/GPTQ-for-LLaMa.git -b cuda", assert_success=True, environment=True) else: run_cmd("git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa.git -b cuda", assert_success=True, environment=True) # On some Linux distributions, g++ may not exist or be the wrong version to compile GPTQ-for-LLaMa if sys.platform.startswith("linux"): gxx_output = run_cmd("g++ -dumpfullversion -dumpversion", environment=True, capture_output=True) if gxx_output.returncode != 0 or int(gxx_output.stdout.strip().split(b".")[0]) > 11: # Install the correct version of g++ run_cmd("conda install -y -k conda-forge::gxx_linux-64=11.2.0", environment=True) # Install/Update ROCm AutoGPTQ for AMD GPUs if '+rocm' in torver: if run_cmd("[ -d ./AutoGPTQ-rocm ] && rm -rfd ./AutoGPTQ-rocm; git clone https://github.com/jllllll/AutoGPTQ.git ./AutoGPTQ-rocm -b rocm && cp ./AutoGPTQ-rocm/setup_rocm.py ./AutoGPTQ-rocm/setup.py && python -m pip install ./AutoGPTQ-rocm --force-reinstall --no-deps", environment=True).returncode != 0: print_big_message("WARNING: AutoGPTQ kernel compilation failed!\n The installer will proceed to install a pre-compiled wheel.") if run_cmd("python -m pip install https://github.com/jllllll/GPTQ-for-LLaMa-Wheels/raw/Linux-x64/ROCm-5.4.2/auto_gptq-0.3.2%2Brocm5.4.2-cp310-cp310-linux_x86_64.whl --force-reinstall --no-deps", environment=True).returncode != 0: print_big_message("ERROR: AutoGPTQ wheel installation failed!\n You will not be able to use GPTQ-based models with AutoGPTQ.") # Install GPTQ-for-LLaMa dependencies os.chdir("GPTQ-for-LLaMa") run_cmd("git pull", environment=True) # Finds the path to your dependencies for sitedir in site.getsitepackages(): if "site-packages" in sitedir: site_packages_path = sitedir break # This path is critical to installing the following dependencies if site_packages_path is None: print("Could not find the path to your Python packages. Exiting...") sys.exit() # Compile and install GPTQ-for-LLaMa if '+rocm' in torver: if os.path.exists('setup_rocm.py'): os.replace("setup_rocm.py", "setup.py") elif os.path.exists('setup_cuda.py'): os.rename("setup_cuda.py", "setup.py") build_gptq = run_cmd("python -m pip install .", environment=True).returncode == 0 # Wheel installation can fail while in the build directory of a package with the same name os.chdir("..") # If the path does not exist or if command returncode is not 0, then the install failed or was potentially installed outside env quant_cuda_path_regex = os.path.join(site_packages_path, "quant_cuda*/") quant_cuda_path = glob.glob(quant_cuda_path_regex) if not build_gptq: # Attempt installation via alternative, Windows/Linux-specific method if sys.platform.startswith("win") or sys.platform.startswith("linux") and not quant_cuda_path: print_big_message("WARNING: GPTQ-for-LLaMa compilation failed, but this is FINE and can be ignored!\nThe installer will proceed to install a pre-compiled wheel.") if '+rocm' in torver: wheel = 'ROCm-5.4.2/quant_cuda-0.0.0-cp310-cp310-linux_x86_64.whl' else: wheel = f"{'' if gptq_min_compute_check or compute_array.returncode != 0 else '832e220d6dbf11bec5eaa8b221a52c1c854d2a25/'}quant_cuda-0.0.0-cp310-cp310-{'linux_x86_64' if sys.platform.startswith('linux') else 'win_amd64'}.whl" url = f"https://github.com/jllllll/GPTQ-for-LLaMa-Wheels/raw/{'Linux-x64' if sys.platform.startswith('linux') else 'main'}/" + wheel result = run_cmd("python -m pip install " + url, environment=True) if result.returncode == 0 and glob.glob(quant_cuda_path_regex): print("Wheel installation success!") else: print("ERROR: GPTQ wheel installation failed. You will not be able to use GPTQ-based models.") elif quant_cuda_path: print_big_message("WARNING: GPTQ-for-LLaMa compilation failed, but this is FINE and can be ignored!\nquant_cuda has already been installed.") else: print("ERROR: GPTQ CUDA kernel compilation failed.") print("You will not be able to use GPTQ-based models with GPTQ-for-LLaMa.") print("Continuing with install..") clear_cache() def download_model(): os.chdir("text-generation-webui") run_cmd("python download-model.py", environment=True) def launch_webui(): os.chdir("text-generation-webui") run_cmd(f"python server.py {CMD_FLAGS}", environment=True) if __name__ == "__main__": # Verifies we are in a conda environment check_env() parser = argparse.ArgumentParser() parser.add_argument('--update', action='store_true', help='Update the web UI.') args = parser.parse_args() if args.update: update_dependencies() else: # If webui has already been installed, skip and run if not os.path.exists("text-generation-webui/"): install_dependencies() os.chdir(script_dir) # Check if a model has been downloaded yet if len([item for item in glob.glob('text-generation-webui/models/*') if not item.endswith(('.txt', '.yaml'))]) == 0: print_big_message("WARNING: You haven't downloaded any model yet.\nOnce the web UI launches, head over to the \"Model\" tab and download one.") # Workaround for llama-cpp-python loading paths in CUDA env vars even if they do not exist conda_path_bin = os.path.join(conda_env_path, "bin") if not os.path.exists(conda_path_bin): os.mkdir(conda_path_bin) # Launch the webui launch_webui()