代码拉取完成,页面将自动刷新
from typing import List, Tuple
import setuptools
import platform
import subprocess
import os
from enum import Enum
import urllib.request
from urllib.parse import urlparse, quote
import re
import shutil
from setuptools import find_packages
with open("README.md", mode="r", encoding="utf-8") as fh:
long_description = fh.read()
BUILD_NO_CACHE = os.getenv("BUILD_NO_CACHE", "true").lower() == "true"
LLAMA_CPP_GPU_ACCELERATION = (
os.getenv("LLAMA_CPP_GPU_ACCELERATION", "true").lower() == "true"
)
def parse_requirements(file_name: str) -> List[str]:
with open(file_name) as f:
return [
require.strip()
for require in f
if require.strip() and not require.startswith("#")
]
def get_latest_version(package_name: str, index_url: str, default_version: str):
command = [
"python",
"-m",
"pip",
"index",
"versions",
package_name,
"--index-url",
index_url,
]
result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
if result.returncode != 0:
print("Error executing command.")
print(result.stderr.decode())
return default_version
output = result.stdout.decode()
lines = output.split("\n")
for line in lines:
if "Available versions:" in line:
available_versions = line.split(":")[1].strip()
latest_version = available_versions.split(",")[0].strip()
return latest_version
return default_version
def encode_url(package_url: str) -> str:
parsed_url = urlparse(package_url)
encoded_path = quote(parsed_url.path)
safe_url = parsed_url._replace(path=encoded_path).geturl()
return safe_url, parsed_url.path
def cache_package(package_url: str, package_name: str, is_windows: bool = False):
safe_url, parsed_url = encode_url(package_url)
if BUILD_NO_CACHE:
return safe_url
from pip._internal.utils.appdirs import user_cache_dir
filename = os.path.basename(parsed_url)
cache_dir = os.path.join(user_cache_dir("pip"), "http", "wheels", package_name)
os.makedirs(cache_dir, exist_ok=True)
local_path = os.path.join(cache_dir, filename)
if not os.path.exists(local_path):
temp_path = local_path + ".tmp"
if os.path.exists(temp_path):
os.remove(temp_path)
try:
print(f"Download {safe_url} to {local_path}")
urllib.request.urlretrieve(safe_url, temp_path)
shutil.move(temp_path, local_path)
finally:
if os.path.exists(temp_path):
os.remove(temp_path)
return f"file:///{local_path}" if is_windows else f"file://{local_path}"
class SetupSpec:
def __init__(self) -> None:
self.extras: dict = {}
self.install_requires: List[str] = []
setup_spec = SetupSpec()
class AVXType(Enum):
BASIC = "basic"
AVX = "AVX"
AVX2 = "AVX2"
AVX512 = "AVX512"
@staticmethod
def of_type(avx: str):
for item in AVXType:
if item._value_ == avx:
return item
return None
class OSType(Enum):
WINDOWS = "win"
LINUX = "linux"
DARWIN = "darwin"
OTHER = "other"
def get_cpu_avx_support() -> Tuple[OSType, AVXType]:
system = platform.system()
os_type = OSType.OTHER
cpu_avx = AVXType.BASIC
env_cpu_avx = AVXType.of_type(os.getenv("DBGPT_LLAMA_CPP_AVX"))
if "windows" in system.lower():
os_type = OSType.WINDOWS
output = "avx2"
print("Current platform is windows, use avx2 as default cpu architecture")
elif system == "Linux":
os_type = OSType.LINUX
result = subprocess.run(
["lscpu"], stdout=subprocess.PIPE, stderr=subprocess.PIPE
)
output = result.stdout.decode()
elif system == "Darwin":
os_type = OSType.DARWIN
result = subprocess.run(
["sysctl", "-a"], stdout=subprocess.PIPE, stderr=subprocess.PIPE
)
output = result.stdout.decode()
else:
os_type = OSType.OTHER
print("Unsupported OS to get cpu avx, use default")
return os_type, env_cpu_avx if env_cpu_avx else cpu_avx
if "avx512" in output.lower():
cpu_avx = AVXType.AVX512
elif "avx2" in output.lower():
cpu_avx = AVXType.AVX2
elif "avx " in output.lower():
# cpu_avx = AVXType.AVX
pass
return os_type, env_cpu_avx if env_cpu_avx else cpu_avx
def get_cuda_version_from_torch():
try:
import torch
return torch.version.cuda
except:
return None
def get_cuda_version_from_nvcc():
try:
output = subprocess.check_output(["nvcc", "--version"])
version_line = [
line for line in output.decode("utf-8").split("\n") if "release" in line
][0]
return version_line.split("release")[-1].strip().split(",")[0]
except:
return None
def get_cuda_version_from_nvidia_smi():
try:
output = subprocess.check_output(["nvidia-smi"]).decode("utf-8")
match = re.search(r"CUDA Version:\s+(\d+\.\d+)", output)
if match:
return match.group(1)
else:
return None
except:
return None
def get_cuda_version() -> str:
try:
cuda_version = get_cuda_version_from_torch()
if not cuda_version:
cuda_version = get_cuda_version_from_nvcc()
if not cuda_version:
cuda_version = get_cuda_version_from_nvidia_smi()
return cuda_version
except Exception:
return None
def torch_requires(
torch_version: str = "2.0.1",
torchvision_version: str = "0.15.2",
torchaudio_version: str = "2.0.2",
):
torch_pkgs = [
f"torch=={torch_version}",
f"torchvision=={torchvision_version}",
f"torchaudio=={torchaudio_version}",
]
torch_cuda_pkgs = []
os_type, _ = get_cpu_avx_support()
if os_type != OSType.DARWIN:
cuda_version = get_cuda_version()
if cuda_version:
supported_versions = ["11.7", "11.8"]
if cuda_version not in supported_versions:
print(
f"PyTorch version {torch_version} supported cuda version: {supported_versions}, replace to {supported_versions[-1]}"
)
cuda_version = supported_versions[-1]
cuda_version = "cu" + cuda_version.replace(".", "")
py_version = "cp310"
os_pkg_name = "linux_x86_64" if os_type == OSType.LINUX else "win_amd64"
torch_url = f"https://download.pytorch.org/whl/{cuda_version}/torch-{torch_version}+{cuda_version}-{py_version}-{py_version}-{os_pkg_name}.whl"
torchvision_url = f"https://download.pytorch.org/whl/{cuda_version}/torchvision-{torchvision_version}+{cuda_version}-{py_version}-{py_version}-{os_pkg_name}.whl"
torch_url_cached = cache_package(
torch_url, "torch", os_type == OSType.WINDOWS
)
torchvision_url_cached = cache_package(
torchvision_url, "torchvision", os_type == OSType.WINDOWS
)
torch_cuda_pkgs = [
f"torch @ {torch_url_cached}",
f"torchvision @ {torchvision_url_cached}",
f"torchaudio=={torchaudio_version}",
]
setup_spec.extras["torch"] = torch_pkgs
setup_spec.extras["torch_cpu"] = torch_pkgs
setup_spec.extras["torch_cuda"] = torch_cuda_pkgs
def llama_cpp_python_cuda_requires():
cuda_version = get_cuda_version()
device = "cpu"
if not cuda_version:
print("CUDA not support, use cpu version")
return
if not LLAMA_CPP_GPU_ACCELERATION:
print("Disable GPU acceleration")
return
# Supports GPU acceleration
device = "cu" + cuda_version.replace(".", "")
os_type, cpu_avx = get_cpu_avx_support()
print(f"OS: {os_type}, cpu avx: {cpu_avx}")
supported_os = [OSType.WINDOWS, OSType.LINUX]
if os_type not in supported_os:
print(
f"llama_cpp_python_cuda just support in os: {[r._value_ for r in supported_os]}"
)
return
cpu_device = ""
if cpu_avx == AVXType.AVX2 or cpu_avx == AVXType.AVX512:
cpu_device = "avx"
else:
cpu_device = "basic"
device += cpu_device
base_url = "https://github.com/jllllll/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui"
llama_cpp_version = "0.2.10"
py_version = "cp310"
os_pkg_name = "manylinux_2_31_x86_64" if os_type == OSType.LINUX else "win_amd64"
extra_index_url = f"{base_url}/llama_cpp_python_cuda-{llama_cpp_version}+{device}-{py_version}-{py_version}-{os_pkg_name}.whl"
extra_index_url, _ = encode_url(extra_index_url)
print(f"Install llama_cpp_python_cuda from {extra_index_url}")
setup_spec.extras["llama_cpp"].append(f"llama_cpp_python_cuda @ {extra_index_url}")
def core_requires():
"""
pip install db-gpt or pip install "db-gpt[core]"
"""
setup_spec.extras["core"] = [
"aiohttp==3.8.4",
"chardet==5.1.0",
"importlib-resources==5.12.0",
"psutil==5.9.4",
"python-dotenv==1.0.0",
"colorama==0.4.6",
"prettytable",
"cachetools",
]
setup_spec.extras["framework"] = [
"fschat",
"coloredlogs",
"httpx",
"sqlparse==0.4.4",
"seaborn",
# https://github.com/eosphoros-ai/DB-GPT/issues/551
"pandas==2.0.3",
"auto-gpt-plugin-template",
"gTTS==2.3.1",
"langchain>=0.0.286",
"SQLAlchemy==2.0.22",
"fastapi==0.98.0",
"pymysql",
"duckdb==0.8.1",
"duckdb-engine",
"jsonschema",
# TODO move transformers to default
"transformers>=4.31.0",
"alembic==1.12.0",
# for excel
"openpyxl",
]
def knowledge_requires():
"""
pip install "db-gpt[knowledge]"
"""
setup_spec.extras["knowledge"] = [
"spacy==3.5.3",
"chromadb==0.4.10",
"markdown",
"bs4",
"python-pptx",
"python-docx",
"pypdf",
"python-multipart",
]
def llama_cpp_requires():
"""
pip install "db-gpt[llama_cpp]"
"""
setup_spec.extras["llama_cpp"] = ["llama-cpp-python"]
llama_cpp_python_cuda_requires()
def quantization_requires():
pkgs = []
os_type, _ = get_cpu_avx_support()
if os_type != OSType.WINDOWS:
pkgs = ["bitsandbytes"]
else:
latest_version = get_latest_version(
"bitsandbytes",
"https://jllllll.github.io/bitsandbytes-windows-webui",
"0.41.1",
)
extra_index_url = f"https://github.com/jllllll/bitsandbytes-windows-webui/releases/download/wheels/bitsandbytes-{latest_version}-py3-none-win_amd64.whl"
local_pkg = cache_package(
extra_index_url, "bitsandbytes", os_type == OSType.WINDOWS
)
pkgs = [f"bitsandbytes @ {local_pkg}"]
print(pkgs)
# For chatglm2-6b-int4
pkgs += ["cpm_kernels"]
setup_spec.extras["quantization"] = pkgs
def all_vector_store_requires():
"""
pip install "db-gpt[vstore]"
"""
setup_spec.extras["vstore"] = [
"grpcio==1.47.5", # maybe delete it
"pymilvus==2.2.1",
"weaviate-client",
]
def all_datasource_requires():
"""
pip install "db-gpt[datasource]"
"""
setup_spec.extras["datasource"] = ["pymssql", "pymysql", "pyspark", "psycopg2"]
def openai_requires():
"""
pip install "db-gpt[openai]"
"""
setup_spec.extras["openai"] = ["openai", "tiktoken"]
setup_spec.extras["openai"] += setup_spec.extras["framework"]
setup_spec.extras["openai"] += setup_spec.extras["knowledge"]
def gpt4all_requires():
"""
pip install "db-gpt[gpt4all]"
"""
setup_spec.extras["gpt4all"] = ["gpt4all"]
def vllm_requires():
"""
pip install "db-gpt[vllm]"
"""
setup_spec.extras["vllm"] = ["vllm"]
# def chat_scene():
# setup_spec.extras["chat"] = [
# ""
# ]
def default_requires():
"""
pip install "db-gpt[default]"
"""
setup_spec.extras["default"] = [
"tokenizers==0.13.3",
"accelerate>=0.20.3",
"sentence-transformers",
"protobuf==3.20.3",
"zhipuai",
"dashscope",
"chardet",
"GitPython",
]
setup_spec.extras["default"] += setup_spec.extras["framework"]
setup_spec.extras["default"] += setup_spec.extras["knowledge"]
setup_spec.extras["default"] += setup_spec.extras["torch"]
setup_spec.extras["default"] += setup_spec.extras["quantization"]
def all_requires():
requires = set()
for _, pkgs in setup_spec.extras.items():
for pkg in pkgs:
requires.add(pkg)
setup_spec.extras["all"] = list(requires)
def init_install_requires():
setup_spec.install_requires += setup_spec.extras["core"]
print(f"Install requires: \n{','.join(setup_spec.install_requires)}")
core_requires()
torch_requires()
knowledge_requires()
llama_cpp_requires()
quantization_requires()
all_vector_store_requires()
all_datasource_requires()
openai_requires()
gpt4all_requires()
vllm_requires()
# must be last
default_requires()
all_requires()
init_install_requires()
setuptools.setup(
name="db-gpt",
packages=find_packages(exclude=("tests", "*.tests", "*.tests.*", "examples")),
version="0.4.0",
author="csunny",
author_email="cfqcsunny@gmail.com",
description="DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment."
" With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure.",
long_description=long_description,
long_description_content_type="text/markdown",
install_requires=setup_spec.install_requires,
url="https://github.com/eosphoros-ai/DB-GPT",
license="https://opensource.org/license/mit/",
python_requires=">=3.10",
extras_require=setup_spec.extras,
entry_points={
"console_scripts": [
"dbgpt=pilot.scripts.cli_scripts:main",
],
},
)
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