text-generation-webui/webui.py

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import argparse
import glob
import re
import os
import site
import subprocess
import sys
script_dir = os.getcwd()
conda_env_path = os.path.join(script_dir, "installer_files", "env")
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# Use this to set your command-line flags. For the full list, see:
# https://github.com/oobabooga/text-generation-webui/#starting-the-web-ui
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# Example: CMD_FLAGS = '--chat --listen'
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CMD_FLAGS = '--chat'
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# Allows users to set flags in "OOBABOOGA_FLAGS" environment variable
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")
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# 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")
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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
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result = subprocess.run(cmd, shell=True, capture_output=capture_output, env=env)
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# 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()
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return result
def check_env():
# If we have access to conda, we are probably in an environment
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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 install_dependencies():
# Select your GPU or, choose to run in CPU mode
print("What is your GPU")
print()
print("A) NVIDIA")
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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 in CPU mode)")
print()
gpuchoice = input("Input> ").lower()
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if gpuchoice == "d":
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print_big_message("Once the installation ends, make sure to open webui.py with a text editor\nand add the --cpu flag to CMD_FLAGS.")
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# 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)
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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)
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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
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run_cmd("git clone https://github.com/oobabooga/text-generation-webui.git", assert_success=True, environment=True)
# Install the webui dependencies
update_dependencies()
def update_dependencies():
os.chdir("text-generation-webui")
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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+")]
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# 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]
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# Uninstall the package using pip
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run_cmd("python -m pip uninstall -y " + package_name, environment=True)
print(f"Uninstalled {package_name}")
# Installs/Updates dependencies from all requirements.txt
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run_cmd("python -m pip install -r requirements.txt --upgrade", assert_success=True, environment=True)
extensions = next(os.walk("extensions"))[1]
for extension in extensions:
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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):
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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]
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# 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:
return
# Get GPU CUDA/compute support
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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")
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# 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("..")
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# 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)
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# 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)
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# 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
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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 gxx_linux-64=11.2.0 -c conda-forge", environment=True)
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# 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()
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# Compile and install GPTQ-for-LLaMa
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if '+rocm' in torver:
if os.path.exists('setup_rocm.py'):
os.replace("setup_rocm.py", "setup.py")
# Skip compile for AMD GPU if wheel is successfully installed
if rocm_gptq:
return
elif os.path.exists('setup_cuda.py'):
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os.rename("setup_cuda.py", "setup.py")
build_gptq = run_cmd("python -m pip install .", environment=True).returncode == 0
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# Wheel installation can fail while in the build directory of a package with the same name
os.chdir("..")
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# 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
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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.")
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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)
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if result.returncode == 0 and glob.glob(quant_cuda_path_regex):
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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.")
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else:
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print("ERROR: GPTQ CUDA kernel compilation failed.")
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print("You will not be able to use GPTQ-based models with GPTQ-for-LLaMa.")
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print("Continuing with install..")
def download_model():
os.chdir("text-generation-webui")
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run_cmd("python download-model.py", environment=True)
def launch_webui():
os.chdir("text-generation-webui")
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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 bottom of 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()