From e36569f11bf7df5c562c82a043b9dd9d77e2b7b4 Mon Sep 17 00:00:00 2001 From: c0sogi Date: Fri, 28 Jul 2023 16:33:37 +0900 Subject: [PATCH 01/10] [WIP] dependency solution --- .gitignore | 3 +- LICENSE.md | 9 + llama_api/modules/base.py | 3 +- llama_api/modules/exllama.py | 5 +- llama_api/modules/llama_cpp.py | 28 +- llama_api/modules/sentence_encoder.py | 7 + llama_api/modules/transformer.py | 7 +- llama_api/server/app_settings.py | 14 +- llama_api/server/pools/llama.py | 4 - llama_api/server/routers/v1.py | 2 +- llama_api/shared/config.py | 15 + llama_api/utils/concurrency.py | 7 + llama_api/utils/dependency.py | 259 +++ llama_api/utils/lazy_imports.py | 4 +- llama_api/utils/path.py | 61 +- llama_api/utils/system.py | 20 +- llama_api/utils/venv.py | 145 ++ model_definitions.py | 4 + poetry.lock | 2997 +++++++++++++++++++++++++ pyproject.toml | 49 + readme.md | 4 +- tests/conftest.py | 23 +- tests/test_ci.py | 24 + tests/test_process_pool.py | 2 +- tests/test_server.py | 4 +- 25 files changed, 3613 insertions(+), 87 deletions(-) create mode 100644 LICENSE.md create mode 100644 llama_api/shared/config.py create mode 100644 llama_api/utils/dependency.py create mode 100644 llama_api/utils/venv.py create mode 100644 poetry.lock create mode 100644 pyproject.toml create mode 100644 tests/test_ci.py diff --git a/.gitignore b/.gitignore index c6c4b43..b0082d5 100644 --- a/.gitignore +++ b/.gitignore @@ -7,4 +7,5 @@ models/gptq/* .vscode *.pyc PRIVATE_* -repositories \ No newline at end of file +repositories +tests/.venv \ No newline at end of file diff --git a/LICENSE.md b/LICENSE.md new file mode 100644 index 0000000..3a1d718 --- /dev/null +++ b/LICENSE.md @@ -0,0 +1,9 @@ +MIT License + +Copyright (c) 2023 Andrei Betlen + +Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \ No newline at end of file diff --git a/llama_api/modules/base.py b/llama_api/modules/base.py index 0310160..64d81d1 100644 --- a/llama_api/modules/base.py +++ b/llama_api/modules/base.py @@ -3,7 +3,6 @@ from typing import Any, Iterator, TypeVar from ..mixins.prompt_utils import PromptUtilsMixin -from ..mixins.waiter import WaiterMixin from ..schemas.api import ( APIChatMessage, ChatCompletion, @@ -24,7 +23,7 @@ class BaseLLMModel: max_total_tokens: int = 2048 -class BaseCompletionGenerator(ABC, PromptUtilsMixin, WaiterMixin): +class BaseCompletionGenerator(ABC, PromptUtilsMixin): """Base class for all completion generators.""" @abstractmethod diff --git a/llama_api/modules/exllama.py b/llama_api/modules/exllama.py index 2c9c192..eb387af 100644 --- a/llama_api/modules/exllama.py +++ b/llama_api/modules/exllama.py @@ -1,7 +1,9 @@ """Wrapper for exllama to generate text completions.""" # flake8: noqa +from ..utils.dependency import install_torch +install_torch() from contextlib import contextmanager from pathlib import Path from typing import TYPE_CHECKING, Iterator, Optional @@ -15,8 +17,9 @@ make_completion, make_completion_chunk, ) +from ..utils.dependency import import_repository from ..utils.logger import ApiLogger -from ..utils.path import import_repository, resolve_model_path_to_posix +from ..utils.path import resolve_model_path_to_posix from .base import BaseCompletionGenerator with import_repository( diff --git a/llama_api/modules/llama_cpp.py b/llama_api/modules/llama_cpp.py index d786160..48bc1da 100644 --- a/llama_api/modules/llama_cpp.py +++ b/llama_api/modules/llama_cpp.py @@ -15,29 +15,21 @@ convert_text_completion_chunks_to_chat, convert_text_completion_to_chat, ) +from ..utils.dependency import import_repository from ..utils.llama_cpp import build_shared_lib from ..utils.logger import ApiLogger -from ..utils.path import import_repository, resolve_model_path_to_posix +from ..utils.path import resolve_model_path_to_posix from .base import BaseCompletionGenerator logger = ApiLogger(__name__) logger.info("🦙 llama-cpp-python repository found!") build_shared_lib(logger=logger) -try: - with import_repository( - git_path="https://github.com/abetlen/llama-cpp-python", - disk_path="repositories/llama_cpp", - ): - from repositories.llama_cpp import llama_cpp - from repositories.llama_cpp.llama_cpp.llama_cpp import GGML_USE_CUBLAS -except ImportError: - logger.warning( - "🦙 llama-cpp-python repository not found. " - "Falling back to llama-cpp-python submodule." - ) - - import llama_cpp - from llama_cpp import GGML_USE_CUBLAS as GGML_USE_CUBLAS +with import_repository( + git_path="https://github.com/abetlen/llama-cpp-python", + disk_path="repositories/llama_cpp", +): + from repositories.llama_cpp import llama_cpp + from repositories.llama_cpp.llama_cpp.llama_cpp import GGML_USE_CUBLAS def _make_logit_bias_processor( @@ -96,7 +88,7 @@ def _create_completion( mirostat_mode=settings.mirostat_mode, mirostat_tau=settings.mirostat_tau, mirostat_eta=settings.mirostat_eta, - logits_processor=llama_cpp.LogitsProcessorList( # type: ignore + logits_processor=llama_cpp.LogitsProcessorList( [ _make_logit_bias_processor( client, @@ -134,7 +126,7 @@ def _create_chat_completion( mirostat_mode=settings.mirostat_mode, mirostat_tau=settings.mirostat_tau, mirostat_eta=settings.mirostat_eta, - logits_processor=llama_cpp.LogitsProcessorList( # type: ignore + logits_processor=llama_cpp.LogitsProcessorList( [ _make_logit_bias_processor( client, diff --git a/llama_api/modules/sentence_encoder.py b/llama_api/modules/sentence_encoder.py index ac17431..b17cd38 100644 --- a/llama_api/modules/sentence_encoder.py +++ b/llama_api/modules/sentence_encoder.py @@ -1,3 +1,10 @@ +"""Wrapper for sentence_encoder to generate text embeddings.""" +# flake8: noqa + +from ..utils.dependency import install_tensorflow + +install_tensorflow() + from typing import TYPE_CHECKING, Callable, Optional import numpy as np diff --git a/llama_api/modules/transformer.py b/llama_api/modules/transformer.py index 8b67cc9..c20b800 100644 --- a/llama_api/modules/transformer.py +++ b/llama_api/modules/transformer.py @@ -1,6 +1,11 @@ +"""Wrapper for transformer to generate text embeddings.""" +# flake8: noqa + +from ..utils.dependency import install_torch + +install_torch() from gc import collect from typing import Optional - from torch import Tensor, cuda from transformers.modeling_outputs import ( BaseModelOutputWithPoolingAndCrossAttentions, diff --git a/llama_api/server/app_settings.py b/llama_api/server/app_settings.py index b80bb9c..fba8ea4 100644 --- a/llama_api/server/app_settings.py +++ b/llama_api/server/app_settings.py @@ -1,3 +1,4 @@ +from logging import warn import platform from contextlib import asynccontextmanager from os import environ @@ -7,6 +8,11 @@ def ensure_packages_installed(): + """Install the packages in the requirements.txt file""" + warn( + "This function is deprecated. Use `install_dependencies` instead.", + DeprecationWarning, + ) subprocess.run( [ sys.executable, @@ -60,8 +66,14 @@ def set_priority(pid: Optional[int] = None, priority: str = "high"): def initialize_before_launch(install_packages: bool = False): """Initialize the app""" + from ..utils.dependency import install_poetry, install_dependencies + if install_packages: - ensure_packages_installed() + try: + import poetry # noqa: F401 + except ImportError: + install_poetry() + install_dependencies() if platform.system() == "Windows": set_priority(priority="high") diff --git a/llama_api/server/pools/llama.py b/llama_api/server/pools/llama.py index 9e72692..dd834f1 100644 --- a/llama_api/server/pools/llama.py +++ b/llama_api/server/pools/llama.py @@ -52,10 +52,7 @@ def completion_generator_manager( ): """Context manager for completion generators.""" completion_generator = get_completion_generator(body) - completion_generator.wait_until_available() - completion_generator.set_availability(False) yield completion_generator - completion_generator.set_availability(True) def get_model_names() -> list[str]: @@ -114,7 +111,6 @@ def get_completion_generator( # Before creating a new completion generator, check memory usage if completion_generators.maxlen == len(completion_generators): - completion_generators[-1].wait_until_available() free_memory_of_first_item_from_container( completion_generators, min_free_memory_mb=256, diff --git a/llama_api/server/routers/v1.py b/llama_api/server/routers/v1.py index ad9004e..bca4b21 100644 --- a/llama_api/server/routers/v1.py +++ b/llama_api/server/routers/v1.py @@ -62,7 +62,7 @@ @dataclass class WixMetadata: key: Optional[str] = None - semaphore: Semaphore = field(default_factory=lambda: Semaphore(1)) + semaphore: Semaphore = field(default_factory=lambda: Semaphore(10)) # Worker index (wix) is used to keep track of which worker is currently diff --git a/llama_api/shared/config.py b/llama_api/shared/config.py new file mode 100644 index 0000000..2d689aa --- /dev/null +++ b/llama_api/shared/config.py @@ -0,0 +1,15 @@ +from dataclasses import dataclass +from pathlib import Path +from typing import Tuple + + +@dataclass(frozen=True) +class Config: + """Configuration for the project""" + + project_root: Path = Path(__file__).parent.parent.parent + env_for_venv: Tuple[str, ...] = ("SYSTEMROOT", "CUDA_HOME", "CUDA_PATH") + cuda_version: str = "11.8" + torch_version: str = "==2.0.1" + torch_source: str = "https://download.pytorch.org/whl/torch_stable.html" + tensorflow_version: str = "==2.13.0" diff --git a/llama_api/utils/concurrency.py b/llama_api/utils/concurrency.py index 0de3e4c..1d61dff 100644 --- a/llama_api/utils/concurrency.py +++ b/llama_api/utils/concurrency.py @@ -32,6 +32,13 @@ def init_process_pool(env_vars: dict[str, str]) -> None: for key, value in env_vars.items(): environ[key] = value + cuda_home = environ.get("CUDA_HOME", None) + cuda_path = environ.get("CUDA_PATH", None) + if cuda_path is not None and cuda_home is None: + environ["CUDA_HOME"] = cuda_path + elif cuda_home is not None and cuda_path is None: + environ["CUDA_PATH"] = cuda_home + def pool() -> ProcessPool: """Get the process pool, and initialize it if it's not initialized yet""" diff --git a/llama_api/utils/dependency.py b/llama_api/utils/dependency.py new file mode 100644 index 0000000..0721e4a --- /dev/null +++ b/llama_api/utils/dependency.py @@ -0,0 +1,259 @@ +import os +import sys +from contextlib import contextmanager +from pathlib import Path +from subprocess import DEVNULL, call, check_call +from tempfile import mkstemp +from typing import List, Optional +from urllib.request import urlopen + +from ..shared.config import Config +from ..utils.logger import ApiLogger +from ..utils.system import get_cuda_version + +logger = ApiLogger(__name__) + + +def _get_proper_torch_cuda_version( + cuda_version: str, + source: str = Config.torch_source, + fallback_cuda_version: str = "11.8", +) -> str: + """Helper function that returns the proper CUDA version of torch.""" + if cuda_version == fallback_cuda_version: + return fallback_cuda_version + elif _check_if_torch_cuda_version_available( + cuda_version=cuda_version, source=source + ): + return cuda_version + else: + return fallback_cuda_version + + +def _check_if_torch_cuda_version_available( + cuda_version: str = Config.torch_version, + source: str = Config.torch_source, +) -> bool: + """Helper function that checks if the CUDA version of torch is available""" + try: + # Determine the version of python, CUDA, and platform + cuda_version = (f'cu{cuda_version.replace(".", "")}').encode() # type: ignore + python_version = ( + f"cp{sys.version_info.major}{sys.version_info.minor}" + ).encode() + platform = ("win" if sys.platform == "win32" else "linux").encode() + + # Check if the CUDA version of torch is available + for line in urlopen(source).read().splitlines(): + if ( + cuda_version in line + and python_version in line + and platform in line + ): + return True + return False + except Exception: + return False + + +def _parse_dependencies( + parse_dir: Path, excludes: Optional[List[str]] = None +) -> List[str]: + """Parse dependencies from pyproject.toml or requirements.txt. + e.g. torch==1.9.0, torchvision==0.10.0, etc.""" + try: + if (parse_dir / "pyproject.toml").exists(): + # Convert dependencies from pyproject.toml to requirements.txt + call( + [ + "poetry", + "export", + "-f", + "requirements.txt", + "--output", + "requirements.txt", + ], + cwd=parse_dir, + ) + except Exception: + pass + try: + with open(parse_dir / "requirements.txt", "r") as file: + return [ + line.split(";")[0].strip() + for line in file.readlines() + if ( + "==" in line + or ">=" in line + or "<=" in line + or "~=" in line + ) + and ( + excludes is None or not any(ex in line for ex in excludes) + ) + ] + except Exception: + return [] + + +@contextmanager +def import_repository(git_path: str, disk_path: str): + """ + Import a repository from git. The repository will be cloned to disk_path. + The dependencies will be installed from pyproject.toml or requirements.txt. + """ + + if not Path(disk_path).exists(): + # Clone the repository + check_call(["git", "clone", git_path, disk_path]) + + # Install dependencies + dependencies = _parse_dependencies(Path(disk_path), excludes=["torch"]) + if dependencies: + logger.info(f"Installing dependencies: {dependencies}") + check_call( + ["poetry", "add"] + dependencies, + ) + check_call( + ["poetry", "install"], + ) + else: + logger.warning("No dependencies information found.") + # Add the repository to the path so that it can be imported + sys.path.insert(0, str(disk_path)) + yield + sys.path.remove(str(disk_path)) + + +def install_poetry(): + """Install poetry.""" + logger.critical("Installing poetry...") + check_call( + [sys.executable, "-m", "pip", "install", "poetry"], stdout=DEVNULL + ) + logger.critical("Poetry installed.") + + +def install_torch( + torch_version: str = Config.torch_version, + cuda_version: Optional[str] = Config.cuda_version, + source: Optional[ + str + ] = Config.torch_source, # https://download.pytorch.org/whl/torch_stable.html +) -> bool: + """Try to install Pytorch. + If CUDA is available, install the CUDA version of torch. + Else, install the CPU version of torch. + Args: + torch_version (str): The version of torch. Defaults to Config.torch_version. + cuda_version (str): The version of CUDA. Defaults to Config.cuda_version. + source (Optional[str]): The source to install torch from. + Defaults to Config.torch_source. + Returns: + bool: True if CUDA is installed, False otherwise.""" + pip_install = [sys.executable, "-m", "pip", "install"] + fallback_cuda_version = Config.cuda_version + # If a source is specified, and if CUDA is available, + # install the CUDA version of torch + if source and get_cuda_version(): + # Check if the CUDA version of torch is available. + # If not, fallback to `Config.cuda_version`. + cuda_version = ( + _get_proper_torch_cuda_version( + cuda_version=cuda_version, + fallback_cuda_version=fallback_cuda_version, + ) + if cuda_version is not None + else fallback_cuda_version + ) + pip_install.append( + f'torch{torch_version}+cu{cuda_version.replace(".", "")}' + ) + # If a source is specified, add it to the pip install command + pip_install += ["-f", source] + elif source: + # If a source is specified, but CUDA is not available, + # install the CPU version of torch + pip_install.append(f"torch{torch_version}+cpu") + # If a source is specified, add it to the pip install command + pip_install += ["-f", source] + else: + # If source is not specified, install the canonical version of torch + pip_install.append(f"torch{torch_version}") + + # Install torch + logger.critical( + f"Installing PyTorch with command: {' '.join(pip_install)}" + ) + check_call(pip_install) + logger.critical("PyTorch installed.") + return cuda_version is not None + + +def install_tensorflow( + tensorflow_version: str = Config.tensorflow_version, + source: Optional[str] = None, +) -> None: + """Try to install TensorFlow. + + Args: + tensorflow_version (str): The version of TensorFlow. + Defaults to Config.tensorflow_version. + source (Optional[str]): The source to install TensorFlow from. + If not specified, TensorFlow will be installed from PyPi. + """ + pip_install = [ + sys.executable, + "-m", + "pip", + "install", + f"tensorflow{tensorflow_version}", + ] + + # If a source is specified, add it to the pip install command + if source: + pip_install += ["-f", source] + + # Install TensorFlow + logger.critical( + f"Installing TensorFlow with command: {' '.join(pip_install)}" + ) + check_call(pip_install) + logger.critical("TensorFlow installed.") + + +def install_dependencies(extras: Optional[List[str]] = None): + """Install dependencies.""" + logger.critical("Installing dependencies...") + command = ["poetry", "install"] + if extras: + command += ["--extras", " ".join(extras)] + check_call(command, cwd=Config.project_root) + + +def remove_all_dependencies(): + """Remove all dependencies. + To be used when cleaning up the environment.""" + logger.critical("Removing all dependencies...") + # Create a temporary file + fd, temp_path = mkstemp() + + try: + # Step 1: List out all installed packages + with open(temp_path, "w") as temp_file: + check_call(["pip", "freeze"], stdout=temp_file) + + # Step 2: Uninstall all packages listed in the temp file + with open(temp_path, "r") as temp_file: + packages = [line.strip() for line in temp_file if "-e" not in line] + + for package in packages: + # The "--yes" option automatically confirms the uninstallation + check_call( + [sys.executable, "-m", "pip", "uninstall", "--yes", package] + ) + finally: + # Close the file descriptor and remove the temporary file + os.close(fd) + os.remove(temp_path) + logger.critical("All dependencies removed.") diff --git a/llama_api/utils/lazy_imports.py b/llama_api/utils/lazy_imports.py index 25981d1..71fa5db 100644 --- a/llama_api/utils/lazy_imports.py +++ b/llama_api/utils/lazy_imports.py @@ -5,8 +5,8 @@ from functools import wraps from typing import Callable, TypeVar, Union -from .logger import ApiLogger +from .logger import ApiLogger T = TypeVar("T") logger = ApiLogger(__name__) @@ -34,7 +34,7 @@ def wrapper(*args, **kwargs) -> Union[T, Exception]: logger.info(f"🦙 Successfully imported {module_name}!") return result except Exception as e: - logger.error(f"🦙 Error importing {module_name}: {e}") + logger.exception(f"🦙 Error importing {module_name}: {e}") return e finally: # Add the module to the `logged_modules` set diff --git a/llama_api/utils/path.py b/llama_api/utils/path.py index 1dba0b0..62cc0fd 100644 --- a/llama_api/utils/path.py +++ b/llama_api/utils/path.py @@ -1,51 +1,34 @@ -from os import getcwd -from subprocess import run -import sys -from contextlib import contextmanager from pathlib import Path from typing import Optional +from ..shared.config import Config from ..utils.logger import ApiLogger logger = ApiLogger(__name__) -@contextmanager -def import_repository(git_path: str, disk_path: str): - if not Path(disk_path).exists(): - run(["git", "clone", git_path, disk_path]) - sys.path.insert(0, str(disk_path)) - yield - sys.path.remove(str(disk_path)) - - -@contextmanager -def relative_import(path: str): - sys.path.insert(0, str(path)) - yield - sys.path.remove(str(path)) - - -@contextmanager -def suppress_import_error(): - try: - yield - except ImportError as e: - logger.warning(f"ImportError: {e}") - - def resolve_model_path_to_posix( model_path: str, default_relative_directory: Optional[str] = None ) -> str: - """Resolve a model path to a POSIX path, relative to the BASE_DIR.""" - cwd = getcwd() + """Resolve a model path to a POSIX path.""" path = Path(model_path) - parent_directory: Path = ( - Path(cwd) / Path(default_relative_directory) - if default_relative_directory is not None - else Path(cwd) - if Path.cwd() == path.parent.resolve() - else path.parent.resolve() - ) - filename: str = path.name - return (parent_directory / filename).as_posix() + cwd = Path.cwd() + + # Try to find the model in all possible scenarios + parent_dir_candidates = [ + cwd, + Config.project_root, + Config.project_root / "models", + Config.project_root / "models" / "ggml", + Config.project_root / "models" / "gptq", + Config.project_root / "llama_api", + ] + if default_relative_directory is not None: + parent_dir_candidates.insert(0, cwd / Path(default_relative_directory)) + for parent_dir in parent_dir_candidates: + if (parent_dir / model_path).exists(): + logger.info(f"`{path.name}` found in {parent_dir}") + return (parent_dir / model_path).resolve().as_posix() + logger.warning(f"`{path.name}` not found in {parent_dir}") + logger.error(f"`{path.name}` not found in any of the above directories") + return model_path diff --git a/llama_api/utils/system.py b/llama_api/utils/system.py index 05098d5..60a37d9 100644 --- a/llama_api/utils/system.py +++ b/llama_api/utils/system.py @@ -1,7 +1,9 @@ +from collections import deque from gc import collect from logging import INFO, getLogger +from re import compile +from subprocess import PIPE, check_output, run from typing import TYPE_CHECKING, Any, Optional, Union -from collections import deque if TYPE_CHECKING: from asyncio import Queue as AsyncQueue @@ -11,12 +13,24 @@ ContainerLike = Union["deque", "Queue", "AsyncQueue", list, dict] +def get_cuda_version() -> Optional[str]: + """Returns the current CUDA version as a string. + Returns None if nvidia-smi is not available or CUDA is not installed.""" + try: + result = compile(r"CUDA Version: (\d+\.\d+)").search( + check_output(["nvidia-smi"]).decode("utf-8") + ) + if result is None: + return + return result.group(1) + except Exception: + return + + def get_vram_usages() -> Optional[list[int]]: """Returns a list of memory usage in MB for each GPU. Returns None if nvidia-smi is not available.""" try: - from subprocess import PIPE, run - result = run( [ "nvidia-smi", diff --git a/llama_api/utils/venv.py b/llama_api/utils/venv.py new file mode 100644 index 0000000..2ff8d1e --- /dev/null +++ b/llama_api/utils/venv.py @@ -0,0 +1,145 @@ +import os +import shutil +import subprocess +import sys +from pathlib import Path +from typing import Dict, Optional, Tuple, Union + +from ..shared.config import Config + + +class VirtualEnvironment: + def __init__(self, venv_path: Union[Path, str]) -> None: + self.venv_path = Path(venv_path).resolve() + self.env_for_venv = Config.env_for_venv + self._executable: Optional[Path] = None + self._env: Optional[Dict[str, str]] = None + + def remove(self) -> int: + """Remove the venv if it exists. + If successful, return 0. Otherwise, return 1.""" + try: + if self.venv_path.exists(): + shutil.rmtree(self.venv_path) + return 0 + except OSError: + return 1 + + def create(self) -> int: + """Create a virtual environment. + If successful, return 0. Otherwise, return non-zero exit code""" + assert ( + subprocess.check_call( + [ + sys.executable, + "-m", + "pip", + "install", + "--upgrade", + "pip", + "virtualenv", + ], + stdout=subprocess.DEVNULL, + ) + == 0 + ), "Failed to install virtualenv." + return subprocess.check_call( + [sys.executable, "-m", "virtualenv", self.venv_path.as_posix()], + stdout=subprocess.DEVNULL, + ) + + def recreate(self) -> int: + """Remove and create a virtual environment""" + self.remove() + return self.create() + + def get_settings(self) -> Tuple[Path, Dict[str, str]]: + """Return the path and the environment variables. + These will be used to run commands in the virtual environment.""" + + # Create the virtual environment if it does not exist. + if not self.venv_path.exists(): + self.create() + + # The name of the Python executable may vary across platforms. + python_executable = ( + "python.exe" if sys.platform == "win32" else "python" + ) + + # The name of the Python executable and the directory + # it resides in may vary across platforms. + if sys.platform == "win32": + python_executable = "python.exe" + executable_directory = "Scripts" + else: + python_executable = "python" + executable_directory = "bin" + + venv_python_path = ( + self.venv_path / executable_directory / python_executable + ) + + # Verify if the path is correct. + if not venv_python_path.exists(): + raise FileNotFoundError(f"{venv_python_path} does not exist.") + + # Create the environment variables. + # Copy only the environment variables that are needed. + # This is for security reasons. + env = { + "PATH": venv_python_path.parent.as_posix(), + "VIRTUAL_ENV": venv_python_path.parent.parent.as_posix(), + } + for var in self.env_for_venv: + if var in os.environ: + env[var] = os.environ[var] + + # Check if the virtual environment is correct. + check_command = [venv_python_path, "-c", "import sys; sys.executable"] + exit_code = subprocess.check_call( + check_command, env=env, stdout=subprocess.DEVNULL + ) + assert ( + exit_code == 0 + ), "The virtual environment is not configured correctly." + + # Return the path and the environment variables. + return venv_python_path, env + + def pip(self, *commands: str, stdout: Optional[int] = None) -> int: + """Run a pip command in the virtual environment. + Return the exit code.""" + original_env = os.environ.copy() + executable, env = self.get_settings() + original_env.update(env) + return subprocess.check_call( + [executable.as_posix(), "-m", "pip", *commands], + env=original_env, + stdout=stdout, + ) + + def run_script( + self, script_path: Union[Path, str] + ) -> subprocess.CompletedProcess[str]: + """Run a python script in the virtual environment. + Return the completed process object. + This contains the returncode, stdout, and stderr.""" + executable, env = self.get_settings() + return subprocess.run( + [executable.as_posix(), Path(script_path).as_posix()], + env=env, + text=True, + stdout=subprocess.PIPE, + ) + + @property + def executable(self) -> Path: + if self._executable is None: + self._executable = self.get_settings()[0] + return self._executable + + @property + def env(self) -> Dict[str, str]: + if self._env is None: + self._env = self.get_settings()[1] + return self._env diff --git a/model_definitions.py b/model_definitions.py index 3b2fc1b..8acef12 100644 --- a/model_definitions.py +++ b/model_definitions.py @@ -12,6 +12,10 @@ model_path="llama-2-13b-chat.ggmlv3.q4_K_M.bin", ) +test_vocab = LlamaCppModel( + max_total_tokens=4096, + model_path="repositories/llama_cpp/vendor/llama.cpp/models/ggml-vocab.bin", +) # ================== ExLLaMa models ================== # orca_mini_7b = ExllamaModel( diff --git a/poetry.lock b/poetry.lock new file mode 100644 index 0000000..ec643be --- /dev/null +++ b/poetry.lock @@ -0,0 +1,2997 @@ +# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. + +[[package]] +name = "absl-py" +version = "1.4.0" +description = "Abseil Python Common Libraries, see 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+authors = ["c0sogi "] +license = "MIT" +readme = "readme.md" +homepage = "https://github.com/c0sogi/llama-api" +repository = "https://github.com/c0sogi/llama-api" +packages = [{ include = "llama_api" }] +include = ["LICENSE.md"] + +[tool.poetry.dependencies] +python = ">=3.10.1,<3.12" +typing-extensions = ">=4.0.0" +fastapi = "^0.100" +orjson = "^3.9" +uvicorn = { extras = ["standard"], version = "^0.23" } +sse-starlette = "^1.6" +psutil = "^5.9" +scikit-build = "^0.17.6" +filelock = "^3.12" +transformers = "^4.31.0" +tensorflow-hub = "^0.14" +numpy = "^1.24.3" +tensorflow = { version = "2.13.0", optional = true } +torch = { version = "2.0.1", optional = true } + +# torch: 2.0.1+cu118 for GPU, 2.0.1+cpu for CPU + +# Other dependencies +safetensors = "0.3.1" +sentencepiece = ">=0.1.97" +ninja = "1.11.1" +diskcache = "5.6.1" + +[tool.poetry.group.dev.dependencies] +black = "^23.7.0" +twine = "^4.0.2" +mkdocs = "^1.4.3" +mkdocstrings = { extras = ["python"], version = "^0.22.0" } +mkdocs-material = "^9.1.19" +pytest = "^7.4.0" +pytest-asyncio = "^0.21.1" +httpx = "^0.24.1" + +[build-system] +requires = ["poetry-core>=1.0.0"] +build-backend = "poetry.core.masonry.api" diff --git a/readme.md b/readme.md index 5c86312..d62d888 100644 --- a/readme.md +++ b/readme.md @@ -18,9 +18,9 @@ You can use this server to run the models in your own application, or use it as 1. **Python 3.11** is required to run the server. You can download it from https://www.python.org/downloads/ -2. **CMake** is required to build llama.cpp shared library. You can download it from https://cmake.org/download/ +2. **llama.cpp**: To use llama.cpp, and if you are **Windows** user, download [CMake](https://cmake.org/download/) to compile library. -3. **CUDA 11.8** is required to build cuBLAS build of llama.cpp. You can download it from https://developer.nvidia.com/cuda-11-8-0-download-archive +3. **ExLlama**: To use ExLlama, install the prerequisites of this [repository](https://github.com/turboderp/exllama). Maybe **Windows** user needs to install both [MSVC 2022](https://visualstudio.microsoft.com/downloads/) and [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive). ## How to download the models diff --git a/tests/conftest.py b/tests/conftest.py index b18ead2..b1c400c 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,17 +1,17 @@ -from pathlib import Path import sys -import pytest +from pathlib import Path +import pytest -sys.path.insert(0, Path(__file__).parent.parent.as_posix()) -from llama_api.utils.concurrency import pool # noqa: E402 +# Insert the root directory into the path, so we can import the package +_root_dir = Path(__file__).parent.parent +sys.path.insert(0, _root_dir.as_posix()) @pytest.fixture(scope="session") def app(): - from llama_api.server.app_settings import ( - create_app_llama_cpp, - ) + from llama_api.server.app_settings import create_app_llama_cpp + from llama_api.utils.concurrency import pool try: yield create_app_llama_cpp() @@ -21,12 +21,15 @@ def app(): @pytest.fixture(scope="session") def ppool(): - from llama_api.utils.process_pool import ( - ProcessPool, - ) + from llama_api.utils.process_pool import ProcessPool with ProcessPool(max_workers=2) as pool: for wix in range(pool.max_workers): pool.worker_at_wix(wix) yield pool + + +@pytest.fixture(scope="session") +def root_dir(): + return _root_dir diff --git a/tests/test_ci.py b/tests/test_ci.py new file mode 100644 index 0000000..20f3711 --- /dev/null +++ b/tests/test_ci.py @@ -0,0 +1,24 @@ +from pathlib import Path + +test_output = "bar baz" + + +def foo(): + print(test_output) + + +def test_venv(): + from llama_api.utils.venv import VirtualEnvironment + + venv_name = ".venv" + venv = VirtualEnvironment(Path(__file__).parent / venv_name) + assert venv.recreate() == 0, "Failed to create virtual environment." + assert venv.pip("install", "requests") == 0, "Failed to install requests." + stdout = venv.run_script(__file__).stdout + assert ( + test_output in stdout + ), "Failed to run script in virtual environment." + + +if __name__ == "__main__": + foo() diff --git a/tests/test_process_pool.py b/tests/test_process_pool.py index 470980a..5df6941 100644 --- a/tests/test_process_pool.py +++ b/tests/test_process_pool.py @@ -7,7 +7,7 @@ from pathlib import Path from time import sleep, time -sys.path.insert(0, Path(__file__).parents[1].as_posix()) +sys.path.insert(0, Path(__file__).parent.parent.as_posix()) environ["MAX_WORKERS"] = "2" from llama_api.utils.concurrency import ( # noqa: E402 ProcessPool, diff --git a/tests/test_server.py b/tests/test_server.py index a649269..2d6a461 100644 --- a/tests/test_server.py +++ b/tests/test_server.py @@ -1,6 +1,7 @@ import re from asyncio import gather from pathlib import Path +import sys from typing import ( TYPE_CHECKING, Awaitable, @@ -15,7 +16,8 @@ import pytest from httpx import AsyncClient, Response -from llama_api.schemas.api import ( +sys.path.insert(0, Path(__file__).parent.parent.as_posix()) +from llama_api.schemas.api import ( # noqa: E402 ModelList, ChatCompletionChoice, CompletionChoice, From d54ef38c493a2fb21a50bd81f2e9332a4725aa0e Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sat, 29 Jul 2023 22:03:50 +0900 Subject: [PATCH 02/10] Auto dependency resolver --- llama_api/modules/exllama.py | 5 - llama_api/modules/llama_cpp.py | 6 - llama_api/modules/sentence_encoder.py | 6 - llama_api/modules/transformer.py | 5 - llama_api/server/app_settings.py | 57 +- llama_api/server/pools/llama.py | 2 +- llama_api/utils/concurrency.py | 4 +- llama_api/utils/dependency.py | 201 ++- llama_api/utils/llama_cpp.py | 2 +- poetry.lock | 1649 +++++++++++++++---------- pyproject.toml | 22 +- requirements-all.txt | 28 + requirements.txt | 107 +- 13 files changed, 1284 insertions(+), 810 deletions(-) create mode 100644 requirements-all.txt diff --git a/llama_api/modules/exllama.py b/llama_api/modules/exllama.py index eb387af..9b72f6d 100644 --- a/llama_api/modules/exllama.py +++ b/llama_api/modules/exllama.py @@ -1,9 +1,4 @@ """Wrapper for exllama to generate text completions.""" - -# flake8: noqa -from ..utils.dependency import install_torch - -install_torch() from contextlib import contextmanager from pathlib import Path from typing import TYPE_CHECKING, Iterator, Optional diff --git a/llama_api/modules/llama_cpp.py b/llama_api/modules/llama_cpp.py index 48bc1da..5c442db 100644 --- a/llama_api/modules/llama_cpp.py +++ b/llama_api/modules/llama_cpp.py @@ -29,7 +29,6 @@ disk_path="repositories/llama_cpp", ): from repositories.llama_cpp import llama_cpp - from repositories.llama_cpp.llama_cpp.llama_cpp import GGML_USE_CUBLAS def _make_logit_bias_processor( @@ -164,11 +163,6 @@ def __del__(self) -> None: del self.client self.client = None logger.info("🗑️ LlamaCppCompletionGenerator deleted!") - if GGML_USE_CUBLAS: - logger.warning( - "🗑️ Since you are using cuBLAS, unloading llama.cpp model" - "will cause VRAM leak." - ) @property def llm_model(self) -> "LlamaCppModel": diff --git a/llama_api/modules/sentence_encoder.py b/llama_api/modules/sentence_encoder.py index b17cd38..4ac5129 100644 --- a/llama_api/modules/sentence_encoder.py +++ b/llama_api/modules/sentence_encoder.py @@ -1,10 +1,4 @@ """Wrapper for sentence_encoder to generate text embeddings.""" -# flake8: noqa - -from ..utils.dependency import install_tensorflow - -install_tensorflow() - from typing import TYPE_CHECKING, Callable, Optional import numpy as np diff --git a/llama_api/modules/transformer.py b/llama_api/modules/transformer.py index c20b800..a0c9c9d 100644 --- a/llama_api/modules/transformer.py +++ b/llama_api/modules/transformer.py @@ -1,9 +1,4 @@ """Wrapper for transformer to generate text embeddings.""" -# flake8: noqa - -from ..utils.dependency import install_torch - -install_torch() from gc import collect from typing import Optional from torch import Tensor, cuda diff --git a/llama_api/server/app_settings.py b/llama_api/server/app_settings.py index fba8ea4..688de01 100644 --- a/llama_api/server/app_settings.py +++ b/llama_api/server/app_settings.py @@ -1,10 +1,25 @@ -from logging import warn +from pathlib import Path import platform +import subprocess +import sys from contextlib import asynccontextmanager +from logging import warn from os import environ -import sys -from typing import Optional -import subprocess +from typing import Dict, Optional, Union + + +from ..utils.dependency import ( + get_poetry_executable, + git_clone, + install_all_dependencies, + install_poetry, + install_tensorflow, + install_torch, + is_package_available, +) +from ..utils.logger import ApiLogger + +logger = ApiLogger(__name__) def ensure_packages_installed(): @@ -63,17 +78,29 @@ def set_priority(pid: Optional[int] = None, priority: str = "high"): p.nice(priorities[priority]) -def initialize_before_launch(install_packages: bool = False): +def initialize_before_launch( + git_and_disk_paths: Optional[Dict[str, Union[str, Path]]] = None, + install_packages: bool = False, +) -> None: """Initialize the app""" - from ..utils.dependency import install_poetry, install_dependencies + # Git clone the repositories + if git_and_disk_paths is not None: + for git_path, disk_path in git_and_disk_paths.items(): + git_clone(git_path=git_path, disk_path=disk_path) if install_packages: - try: - import poetry # noqa: F401 - except ImportError: + # Install the dependencies + poetry = get_poetry_executable() + if not poetry.exists(): + logger.warning(f"⚠️ Poetry not found: {poetry}") install_poetry() - install_dependencies() + if not is_package_available("torch"): + install_torch() + if not is_package_available("tensorflow"): + install_tensorflow() + project_paths = [Path(".")] + list(Path("repositories").glob("*")) + install_all_dependencies(project_paths=project_paths) if platform.system() == "Windows": set_priority(priority="high") @@ -86,7 +113,7 @@ async def lifespan(app): from ..utils.concurrency import pool from ..utils.logger import ApiLogger - ApiLogger.ccritical("🦙 LLaMA API server is running") + ApiLogger.cinfo("🦙 LLaMA API server is running") yield ApiLogger.ccritical("🦙 Shutting down LLaMA API server...") pool().kill() @@ -119,7 +146,13 @@ def run( port: int, max_workers: int = 1, ) -> None: - initialize_before_launch(install_packages=True) + initialize_before_launch( + git_and_disk_paths={ + "https://github.com/abetlen/llama-cpp-python": "repositories/llama_cpp", + "https://github.com/turboderp/exllama": "repositories/exllama", + }, + install_packages=True, + ) from uvicorn import Config, Server diff --git a/llama_api/server/pools/llama.py b/llama_api/server/pools/llama.py index dd834f1..2545e5c 100644 --- a/llama_api/server/pools/llama.py +++ b/llama_api/server/pools/llama.py @@ -33,7 +33,7 @@ logger = ApiLogger(__name__) -logger.critical(f"{current_process()} is initiated with PID: {getpid()}") +logger.info(f"🔧 {current_process()} is initiated with PID: {getpid()}") lazy = LazyImports() # lazy-loader of modules completion_generators: deque["BaseCompletionGenerator"] = deque(maxlen=1) diff --git a/llama_api/utils/concurrency.py b/llama_api/utils/concurrency.py index 1d61dff..5d4de6b 100644 --- a/llama_api/utils/concurrency.py +++ b/llama_api/utils/concurrency.py @@ -45,14 +45,14 @@ def pool() -> ProcessPool: global _pool if _pool is None: - logger.critical("Initializing process pool...") + logger.info("Initializing process pool...") _pool = ProcessPool( max_workers=int(environ.get("MAX_WORKERS", 1)), initializer=init_process_pool, initargs=(dict(environ),), ) elif not _pool.is_available: - logger.critical("Process pool died. Reinitializing process pool...") + logger.critical("🚨 Process pool died. Reinitializing process pool...") _pool = ProcessPool( max_workers=int(environ.get("MAX_WORKERS", 1)), initializer=init_process_pool, diff --git a/llama_api/utils/dependency.py b/llama_api/utils/dependency.py index 0721e4a..a9bc8e7 100644 --- a/llama_api/utils/dependency.py +++ b/llama_api/utils/dependency.py @@ -1,10 +1,12 @@ +from importlib.util import find_spec import os import sys from contextlib import contextmanager from pathlib import Path -from subprocess import DEVNULL, call, check_call +from re import compile +from subprocess import DEVNULL, call, check_call, run from tempfile import mkstemp -from typing import List, Optional +from typing import List, Optional, Union from urllib.request import urlopen from ..shared.config import Config @@ -14,7 +16,27 @@ logger = ApiLogger(__name__) -def _get_proper_torch_cuda_version( +def is_package_available(package: str) -> bool: + return True if find_spec(package) else False + + +def git_clone(git_path: str, disk_path: Union[Path, str]) -> None: + """Clone a git repository to a disk path.""" + if not Path(disk_path).exists(): + # Clone the repository + check_call(["git", "clone", git_path, disk_path]) + + +def get_poetry_executable() -> Path: + """Construct the path to the poetry executable within the virtual environment + Check the operating system to determine the correct location""" + if os.name == "nt": # Windows + return Path(sys.prefix) / "Scripts" / "poetry.exe" + else: # Linux or Mac + return Path(sys.prefix) / "bin" / "poetry" + + +def get_proper_torch_cuda_version( cuda_version: str, source: str = Config.torch_source, fallback_cuda_version: str = "11.8", @@ -22,7 +44,7 @@ def _get_proper_torch_cuda_version( """Helper function that returns the proper CUDA version of torch.""" if cuda_version == fallback_cuda_version: return fallback_cuda_version - elif _check_if_torch_cuda_version_available( + elif check_if_torch_cuda_version_available( cuda_version=cuda_version, source=source ): return cuda_version @@ -30,7 +52,7 @@ def _get_proper_torch_cuda_version( return fallback_cuda_version -def _check_if_torch_cuda_version_available( +def check_if_torch_cuda_version_available( cuda_version: str = Config.torch_version, source: str = Config.torch_source, ) -> bool: @@ -56,44 +78,87 @@ def _check_if_torch_cuda_version_available( return False -def _parse_dependencies( - parse_dir: Path, excludes: Optional[List[str]] = None +def parse_requirements( + requirements: str, + excludes: Optional[List[str]] = None, + include_version: bool = True, ) -> List[str]: - """Parse dependencies from pyproject.toml or requirements.txt. - e.g. torch==1.9.0, torchvision==0.10.0, etc.""" + """Parse requirements from a string. + Args: + requirements: The string of requirements.txt to parse. + excludes: A list of packages to exclude. + include_version: Whether to include the version in the parsed requirements. + Returns: + A list of parsed requirements. + """ + # Define the regular expression pattern + pattern = compile(r"([a-zA-Z0-9_\-\+]+)(==|>=|<=|~=|>|<|!=|===)([0-9\.]+)") + + # Use finditer to get all matches in the string + return [ + match.group() if include_version else match.group(1) + for match in pattern.finditer(requirements) + if not excludes or match.group(1) not in excludes + ] + + +def convert_toml_to_requirements_with_poetry(toml_path: Path) -> None: + """Convert dependencies from pyproject.toml to requirements.txt.""" try: - if (parse_dir / "pyproject.toml").exists(): + if toml_path.exists(): # Convert dependencies from pyproject.toml to requirements.txt call( [ - "poetry", + get_poetry_executable(), "export", "-f", "requirements.txt", "--output", "requirements.txt", + "--without-hashes", ], - cwd=parse_dir, + cwd=toml_path.parent, ) except Exception: pass - try: - with open(parse_dir / "requirements.txt", "r") as file: - return [ - line.split(";")[0].strip() - for line in file.readlines() - if ( - "==" in line - or ">=" in line - or "<=" in line - or "~=" in line - ) - and ( - excludes is None or not any(ex in line for ex in excludes) - ) - ] - except Exception: - return [] + + +# def parse_dependencies( +# parse_dir: Path, +# excludes: Optional[List[str]] = None, +# include_version: bool = True, +# ) -> List[str]: +# """Parse dependencies from pyproject.toml or requirements.txt. +# Then, convert the dependencies to a list of strings.""" +# try: +# if (parse_dir / "pyproject.toml").exists(): +# # Convert dependencies from pyproject.toml to requirements.txt +# call( +# [ +# get_poetry_executable(), +# "export", +# "-f", +# "requirements.txt", +# "--output", +# "requirements.txt", +# "--without-hashes", +# ], +# cwd=parse_dir, +# ) +# except Exception: +# pass +# try: +# with open(parse_dir / "requirements.txt", "r") as file: +# return [ +# dep +# for dep in parse_requirements( +# file.read(), +# excludes=excludes, +# include_version=include_version, +# ) +# ] +# except Exception: +# return [] @contextmanager @@ -103,22 +168,9 @@ def import_repository(git_path: str, disk_path: str): The dependencies will be installed from pyproject.toml or requirements.txt. """ - if not Path(disk_path).exists(): - # Clone the repository - check_call(["git", "clone", git_path, disk_path]) + # Clone the repository + git_clone(git_path=git_path, disk_path=disk_path) - # Install dependencies - dependencies = _parse_dependencies(Path(disk_path), excludes=["torch"]) - if dependencies: - logger.info(f"Installing dependencies: {dependencies}") - check_call( - ["poetry", "add"] + dependencies, - ) - check_call( - ["poetry", "install"], - ) - else: - logger.warning("No dependencies information found.") # Add the repository to the path so that it can be imported sys.path.insert(0, str(disk_path)) yield @@ -127,11 +179,11 @@ def import_repository(git_path: str, disk_path: str): def install_poetry(): """Install poetry.""" - logger.critical("Installing poetry...") + logger.info("📦 Installing poetry...") check_call( [sys.executable, "-m", "pip", "install", "poetry"], stdout=DEVNULL ) - logger.critical("Poetry installed.") + logger.info("✅ Poetry installed.") def install_torch( @@ -159,7 +211,7 @@ def install_torch( # Check if the CUDA version of torch is available. # If not, fallback to `Config.cuda_version`. cuda_version = ( - _get_proper_torch_cuda_version( + get_proper_torch_cuda_version( cuda_version=cuda_version, fallback_cuda_version=fallback_cuda_version, ) @@ -182,11 +234,9 @@ def install_torch( pip_install.append(f"torch{torch_version}") # Install torch - logger.critical( - f"Installing PyTorch with command: {' '.join(pip_install)}" - ) + logger.info(f"📦 Installing PyTorch with command: {' '.join(pip_install)}") check_call(pip_install) - logger.critical("PyTorch installed.") + logger.info("✅ PyTorch installed.") return cuda_version is not None @@ -215,20 +265,45 @@ def install_tensorflow( pip_install += ["-f", source] # Install TensorFlow - logger.critical( - f"Installing TensorFlow with command: {' '.join(pip_install)}" + logger.info( + f"📦 Installing TensorFlow with command: {' '.join(pip_install)}" ) check_call(pip_install) - logger.critical("TensorFlow installed.") + logger.info("✅ TensorFlow installed.") -def install_dependencies(extras: Optional[List[str]] = None): - """Install dependencies.""" - logger.critical("Installing dependencies...") - command = ["poetry", "install"] - if extras: - command += ["--extras", " ".join(extras)] - check_call(command, cwd=Config.project_root) +def install_all_dependencies( + project_paths: Optional[Union[List[Path], List[str]]] = None, +) -> None: + """Install every dependencies.""" + pip_install = [sys.executable, "-m", "pip", "install", "-r"] + for project_path in project_paths or []: + project_path = Path(project_path).resolve() + logger.info(f"📦 Installing dependencies for {project_path}...") + convert_toml_to_requirements_with_poetry( + project_path / "pyproject.toml" + ) + requirements_path = project_path / "requirements.txt" + if not requirements_path.exists(): + logger.warning( + f"⚠️ Could not find requirements.txt in {project_path}." + ) + continue + result = run( + pip_install + [requirements_path], + text=True, + stdout=DEVNULL, + stderr=DEVNULL, + ) + + if result.stderr or result.returncode != 0: + logger.error( + "❌ Error installing dependencies: " + + (result.stdout or "") + + (result.stderr or "") + ) + else: + logger.info("✅ Dependencies installed!") def remove_all_dependencies(): @@ -241,7 +316,9 @@ def remove_all_dependencies(): try: # Step 1: List out all installed packages with open(temp_path, "w") as temp_file: - check_call(["pip", "freeze"], stdout=temp_file) + check_call( + [sys.executable, "-m", "pip", "freeze"], stdout=temp_file + ) # Step 2: Uninstall all packages listed in the temp file with open(temp_path, "r") as temp_file: diff --git a/llama_api/utils/llama_cpp.py b/llama_api/utils/llama_cpp.py index 4a5a441..21f757d 100644 --- a/llama_api/utils/llama_cpp.py +++ b/llama_api/utils/llama_cpp.py @@ -138,7 +138,7 @@ def build_shared_lib( if environ.get("CMAKE_ARGS") is None: environ["CMAKE_ARGS"] = CMAKE_ARGS - logger.critical( + logger.info( f"🦙 Building llama.cpp libs with {environ['CMAKE_ARGS']}" ) subprocess.run([sys.executable, "-m", "pip", "install", "."]) diff --git a/poetry.lock b/poetry.lock index ec643be..e68cba6 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,14 +1,14 @@ # This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. [[package]] -name = "absl-py" -version = "1.4.0" -description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py." -optional = true -python-versions = ">=3.6" +name = "annotated-types" +version = "0.5.0" +description = "Reusable constraint types to use with typing.Annotated" +optional = false +python-versions = ">=3.7" files = [ - {file = "absl-py-1.4.0.tar.gz", hash = "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"}, - {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"}, + {file = "annotated_types-0.5.0-py3-none-any.whl", hash = "sha256:58da39888f92c276ad970249761ebea80ba544b77acddaa1a4d6cf78287d45fd"}, + {file = "annotated_types-0.5.0.tar.gz", hash = "sha256:47cdc3490d9ac1506ce92c7aaa76c579dc3509ff11e098fc867e5130ab7be802"}, ] [[package]] @@ -33,19 +33,22 @@ test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>= trio = ["trio (<0.22)"] [[package]] -name = "astunparse" -version = "1.6.3" -description = "An AST unparser for Python" -optional = true -python-versions = "*" +name = "attrs" +version = "23.1.0" +description = "Classes Without Boilerplate" +optional = false +python-versions = ">=3.7" files = [ - {file = "astunparse-1.6.3-py2.py3-none-any.whl", hash = "sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8"}, - {file = "astunparse-1.6.3.tar.gz", hash = "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872"}, + {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"}, + {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"}, ] -[package.dependencies] -six = ">=1.6.1,<2.0" -wheel = ">=0.23.0,<1.0" +[package.extras] +cov = ["attrs[tests]", "coverage[toml] (>=5.3)"] +dev = ["attrs[docs,tests]", "pre-commit"] +docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"] +tests = ["attrs[tests-no-zope]", "zope-interface"] +tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] [[package]] name = "black" @@ -111,16 +114,48 @@ webencodings = "*" css = ["tinycss2 (>=1.1.0,<1.2)"] [[package]] -name = "cachetools" -version = "5.3.1" -description = "Extensible memoizing collections and decorators" -optional = true -python-versions = ">=3.7" +name = "build" +version = "0.10.0" +description = "A simple, correct Python build frontend" +optional = false +python-versions = ">= 3.7" +files = [ + {file = "build-0.10.0-py3-none-any.whl", hash = "sha256:af266720050a66c893a6096a2f410989eeac74ff9a68ba194b3f6473e8e26171"}, + {file = "build-0.10.0.tar.gz", hash = "sha256:d5b71264afdb5951d6704482aac78de887c80691c52b88a9ad195983ca2c9269"}, +] + +[package.dependencies] +colorama = {version = "*", markers = "os_name == \"nt\""} +packaging = ">=19.0" +pyproject_hooks = "*" +tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""} + +[package.extras] +docs = ["furo (>=2021.08.31)", "sphinx (>=4.0,<5.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)"] +test = ["filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "toml (>=0.10.0)", "wheel (>=0.36.0)"] +typing = ["importlib-metadata (>=5.1)", "mypy (==0.991)", "tomli", "typing-extensions (>=3.7.4.3)"] +virtualenv = ["virtualenv (>=20.0.35)"] + +[[package]] +name = "cachecontrol" +version = "0.12.14" +description = "httplib2 caching for requests" +optional = false +python-versions = ">=3.6" files = [ - {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"}, - {file = "cachetools-5.3.1.tar.gz", hash = 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"zipp" version = "3.16.2" @@ -2994,4 +3277,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.10.1,<3.12" -content-hash = "1ee10634cc1982c4fea8574ec92f67ae8f3e119f7a0af448e8fd65de6bac828f" +content-hash = "d3894b312b097ea1b48461143caac21b3c917c1ed3ebfabdbe9f14fa3f3ebd0b" diff --git a/pyproject.toml b/pyproject.toml index aeb9f5c..079af08 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,10 +12,11 @@ include = ["LICENSE.md"] [tool.poetry.dependencies] python = ">=3.10.1,<3.12" -typing-extensions = ">=4.0.0" +poetry = "^1.5.1" + +uvicorn = { extras = ["standard"], version = "^0.23" } fastapi = "^0.100" orjson = "^3.9" -uvicorn = { extras = ["standard"], version = "^0.23" } sse-starlette = "^1.6" psutil = "^5.9" scikit-build = "^0.17.6" @@ -23,20 +24,19 @@ filelock = "^3.12" transformers = "^4.31.0" tensorflow-hub = "^0.14" numpy = "^1.24.3" -tensorflow = { version = "2.13.0", optional = true } -torch = { version = "2.0.1", optional = true } - -# torch: 2.0.1+cu118 for GPU, 2.0.1+cpu for CPU - -# Other dependencies -safetensors = "0.3.1" +safetensors = "^0.3.1" +ninja = "^1.11.1" +diskcache = "^5.6.1" +pydantic = "^2.0.0" +pydantic-settings = "^2.0.0" sentencepiece = ">=0.1.97" -ninja = "1.11.1" -diskcache = "5.6.1" +typing-extensions = ">=4.0.0" +# torch: 2.0.1+cu118 for GPU, 2.0.1+cpu for CPU [tool.poetry.group.dev.dependencies] black = "^23.7.0" twine = "^4.0.2" +flake8 = "^6.0.0" mkdocs = "^1.4.3" mkdocstrings = { extras = ["python"], version = "^0.22.0" } mkdocs-material = "^9.1.19" diff --git a/requirements-all.txt b/requirements-all.txt new file mode 100644 index 0000000..90cdedf --- /dev/null +++ b/requirements-all.txt @@ -0,0 +1,28 @@ +psutil +fastapi +uvicorn[standard] +transformers +orjson +llama_cpp_python[server] +safetensors==0.3.1 +sentencepiece>=0.1.97 +ninja==1.11.1 +--find-links https://download.pytorch.org/whl/torch_stable.html +torch==2.0.1+cu118 +numpy +scikit-learn +tensorflow>=2.0.0 +tensorflow-hub +scikit-build + + +# Dev +black +twine +flake8 +mkdocs +mkdocstrings +mkdocs-material +pytest +pytest-asyncio +httpx \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 456cc75..8a625ff 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,16 +1,91 @@ -psutil -fastapi -uvicorn[standard] -transformers -orjson -llama_cpp_python[server] -safetensors==0.3.1 -sentencepiece>=0.1.97 -ninja==1.11.1 ---find-links https://download.pytorch.org/whl/torch_stable.html -torch==2.0.1+cu118 -numpy -scikit-learn -tensorflow>=2.0.0 -tensorflow-hub -scikit-build \ No newline at end of file +annotated-types==0.5.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +anyio==3.7.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +attrs==23.1.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +build==0.10.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +cachecontrol[filecache]==0.12.14 ; python_full_version >= "3.10.1" and python_version < "3.12" +certifi==2023.7.22 ; python_full_version >= "3.10.1" and python_version < "3.12" +cffi==1.15.1 ; python_full_version >= "3.10.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") +charset-normalizer==3.2.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +cleo==2.0.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +click==8.1.6 ; python_full_version >= "3.10.1" and python_version < "3.12" +colorama==0.4.6 ; python_full_version >= "3.10.1" and python_version < "3.12" and (os_name == "nt" or platform_system == "Windows") +crashtest==0.4.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +cryptography==41.0.2 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "linux" +diskcache==5.6.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +distlib==0.3.7 ; python_full_version >= "3.10.1" and python_version < "3.12" +distro==1.8.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +dulwich==0.21.5 ; python_full_version >= "3.10.1" and python_version < "3.12" +exceptiongroup==1.1.2 ; python_full_version >= "3.10.1" and python_version < "3.11" +fastapi==0.100.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +filelock==3.12.2 ; python_full_version >= "3.10.1" and python_version < "3.12" +fsspec==2023.6.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +h11==0.14.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +html5lib==1.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +httptools==0.6.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +huggingface-hub==0.16.4 ; python_full_version >= "3.10.1" and python_version < "3.12" +idna==3.4 ; python_full_version >= "3.10.1" and python_version < "3.12" +importlib-metadata==6.8.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +installer==0.7.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +jaraco-classes==3.3.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +jeepney==0.8.0 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "linux" +jsonschema-specifications==2023.7.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +jsonschema==4.18.4 ; python_full_version >= "3.10.1" and python_version < "3.12" +keyring==23.13.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +lockfile==0.12.2 ; python_full_version >= "3.10.1" and python_version < "3.12" +more-itertools==10.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +msgpack==1.0.5 ; python_full_version >= "3.10.1" and python_version < "3.12" +ninja==1.11.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +numpy==1.25.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +orjson==3.9.2 ; python_full_version >= "3.10.1" and python_version < "3.12" +packaging==23.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +pexpect==4.8.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +pkginfo==1.9.6 ; python_full_version >= "3.10.1" and python_version < "3.12" +platformdirs==3.9.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +poetry-core==1.6.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +poetry-plugin-export==1.4.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +poetry==1.5.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +protobuf==4.23.4 ; python_full_version >= "3.10.1" and python_version < "3.12" +psutil==5.9.5 ; python_full_version >= "3.10.1" and python_version < "3.12" +ptyprocess==0.7.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +pycparser==2.21 ; python_full_version >= "3.10.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") +pydantic-core==2.4.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +pydantic-settings==2.0.2 ; python_full_version >= "3.10.1" and python_version < "3.12" +pydantic==2.1.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +pyproject-hooks==1.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +python-dotenv==1.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +pywin32-ctypes==0.2.2 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "win32" +pyyaml==6.0.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +rapidfuzz==2.15.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +referencing==0.30.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +regex==2023.6.3 ; python_full_version >= "3.10.1" and python_version < "3.12" +requests-toolbelt==1.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +requests==2.31.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +rpds-py==0.9.2 ; python_full_version >= "3.10.1" and python_version < "3.12" +safetensors==0.3.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +scikit-build==0.17.6 ; python_full_version >= "3.10.1" and python_version < "3.12" +secretstorage==3.3.3 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "linux" +sentencepiece==0.1.99 ; python_full_version >= "3.10.1" and python_version < "3.12" +setuptools==68.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +shellingham==1.5.0.post1 ; python_full_version >= "3.10.1" and python_version < "3.12" +six==1.16.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +sniffio==1.3.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +sse-starlette==1.6.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +starlette==0.27.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +tensorflow-hub==0.14.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +tokenizers==0.13.3 ; python_full_version >= "3.10.1" and python_version < "3.12" +tomli==2.0.1 ; python_full_version >= "3.10.1" and python_version < "3.11" +tomlkit==0.12.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +tqdm==4.65.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +transformers==4.31.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +trove-classifiers==2023.7.6 ; python_full_version >= "3.10.1" and python_version < "3.12" +typing-extensions==4.7.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +urllib3==1.26.16 ; python_full_version >= "3.10.1" and python_version < "3.12" +uvicorn[standard]==0.23.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +uvloop==0.17.0 ; (sys_platform != "win32" and sys_platform != "cygwin") and platform_python_implementation != "PyPy" and python_full_version >= "3.10.1" and python_version < "3.12" +virtualenv==20.24.2 ; python_full_version >= "3.10.1" and python_version < "3.12" +watchfiles==0.19.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +webencodings==0.5.1 ; python_full_version >= "3.10.1" and python_version < "3.12" +websockets==11.0.3 ; python_full_version >= "3.10.1" and python_version < "3.12" +wheel==0.41.0 ; python_full_version >= "3.10.1" and python_version < "3.12" +xattr==0.10.1 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "darwin" +zipp==3.16.2 ; python_full_version >= "3.10.1" and python_version < "3.12" From aa7d75c21ec4617482a4889373351ccc0f0c162b Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sun, 30 Jul 2023 01:14:59 +0900 Subject: [PATCH 03/10] Changed test module: pytest -> unittest --- tests/conftest.py | 66 ++++--- tests/test_ci.py | 2 +- tests/test_process_pool.py | 230 ++++++++++++------------ tests/test_server.py | 351 +++++++++++++++++++------------------ 4 files changed, 327 insertions(+), 322 deletions(-) diff --git a/tests/conftest.py b/tests/conftest.py index b1c400c..3f5a3a2 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,35 +1,33 @@ -import sys from pathlib import Path - -import pytest - -# Insert the root directory into the path, so we can import the package -_root_dir = Path(__file__).parent.parent -sys.path.insert(0, _root_dir.as_posix()) - - -@pytest.fixture(scope="session") -def app(): - from llama_api.server.app_settings import create_app_llama_cpp - from llama_api.utils.concurrency import pool - - try: - yield create_app_llama_cpp() - finally: - pool().shutdown(wait=False) - - -@pytest.fixture(scope="session") -def ppool(): - from llama_api.utils.process_pool import ProcessPool - - with ProcessPool(max_workers=2) as pool: - for wix in range(pool.max_workers): - pool.worker_at_wix(wix) - - yield pool - - -@pytest.fixture(scope="session") -def root_dir(): - return _root_dir +from typing import Dict, List +import unittest + +from llama_api.server.app_settings import create_app_llama_cpp +from llama_api.utils.concurrency import pool as concurrency_pool +from llama_api.utils.process_pool import ProcessPool +from llama_api.shared.config import Config + + +class TestLlamaAPI(unittest.TestCase): + ggml_model: str = "orca-mini-3b.ggmlv3.q4_1.bin" + ggml_path: Path = Config.project_root / Path(f"models/ggml/{ggml_model}") + + gptq_model: str = "orca_mini_7b" + gptq_path: Path = Config.project_root / Path(f"models/gptq/{gptq_model}") + + messages: List[Dict[str, str]] = [ + {"role": "user", "content": "Hello, there!"} + ] + prompt: str = "\n".join([f"{m['role']}: {m['content']}" for m in messages]) + + @classmethod + def setUpClass(cls): + cls.app = create_app_llama_cpp() + cls.ppool = ProcessPool(max_workers=2) + for wix in range(cls.ppool.max_workers): + cls.ppool.worker_at_wix(wix) + + @classmethod + def tearDownClass(cls): + concurrency_pool().shutdown(wait=False) + cls.ppool.shutdown() diff --git a/tests/test_ci.py b/tests/test_ci.py index 20f3711..65e76d2 100644 --- a/tests/test_ci.py +++ b/tests/test_ci.py @@ -10,7 +10,7 @@ def foo(): def test_venv(): from llama_api.utils.venv import VirtualEnvironment - venv_name = ".venv" + venv_name = ".test-venv" venv = VirtualEnvironment(Path(__file__).parent / venv_name) assert venv.recreate() == 0, "Failed to create virtual environment." assert venv.pip("install", "requests") == 0, "Failed to install requests." diff --git a/tests/test_process_pool.py b/tests/test_process_pool.py index 5df6941..daa4710 100644 --- a/tests/test_process_pool.py +++ b/tests/test_process_pool.py @@ -1,21 +1,17 @@ from asyncio import gather -from os import environ, getpid -import pytest from concurrent.futures import Future from functools import partial -import sys -from pathlib import Path +from os import getpid from time import sleep, time -sys.path.insert(0, Path(__file__).parent.parent.as_posix()) -environ["MAX_WORKERS"] = "2" -from llama_api.utils.concurrency import ( # noqa: E402 - ProcessPool, +from llama_api.utils.concurrency import ( + ProcessPool, # noqa: E402 awake_all_pool_workers, pool, run_in_processpool, run_in_processpool_with_wix, ) +from tests.conftest import TestLlamaAPI def simple_job(sleep_time: float) -> float: @@ -25,133 +21,131 @@ def simple_job(sleep_time: float) -> float: return sleep_time -def test_process_pool(ppool) -> None: - # We're recording the start time - start_time = time() - - # Submitting two jobs which will sleep for 1 second each - f1: Future = ppool.submit(simple_job, 1) - f2: Future = ppool.submit(simple_job, 1) - print("Submitted jobs at", time()) - - # Waiting for both jobs to complete - result1 = f1.result() # This will block until f1 is done - result2 = f2.result() # This will block until f2 is done - print("Jobs done:", result1, result2) - - # Recording the end time - end_time = time() - print("Elapsed time:", end_time - start_time) - - # Total elapsed time should be little more than 1 second, - # not 2 seconds, because jobs are expected to run in parallel. - assert end_time - start_time <= 2.0, f"{end_time - start_time}" - assert result1 == result2 == 1 - - -def test_process_pool_with_wix(ppool) -> None: - # We're recording the start time - start_time = time() - - # Submitting two jobs which will sleep for 1 second each - f1: Future = ppool.submit_with_wix(partial(simple_job, 1), wix=1) - f2: Future = ppool.submit_with_wix(partial(simple_job, 1), wix=1) - print("Submitted jobs") - - # Waiting for both jobs to complete - result1 = f1.result() # This will block until f1 is done - result2 = f2.result() # This will block until f2 is done - print("Jobs done:", result1, result2) - - # Recording the end time - end_time = time() - print("Elapsed time:", end_time - start_time) - - # Total elapsed time should be little more than 2 seconds, - # not 1 second, because jobs are expected to run in serial. - assert end_time - start_time >= 2.0, f"{end_time - start_time}" - assert result1 == result2 == 1 +class TestProcessPool(TestLlamaAPI): + def test_process_pool(self) -> None: + # We're recording the start time + start_time = time() + # Submitting two jobs which will sleep for 1 second each + f1: Future = self.ppool.submit(simple_job, 1) + f2: Future = self.ppool.submit(simple_job, 1) + print("Submitted jobs at", time()) -@pytest.mark.asyncio -async def test_process_pool_async(): - try: - awake_all_pool_workers() - sleep(2) # Give the pool some time to start up + # Waiting for both jobs to complete + result1 = f1.result() # This will block until f1 is done + result2 = f2.result() # This will block until f2 is done + print("Jobs done:", result1, result2) - start_time = time() - print("Submitting jobs...") - result_1, result_2 = await gather( - run_in_processpool(simple_job, 1), - run_in_processpool(simple_job, 1), # type: ignore - ) + # Recording the end time end_time = time() print("Elapsed time:", end_time - start_time) # Total elapsed time should be little more than 1 second, # not 2 seconds, because jobs are expected to run in parallel. - assert end_time - start_time <= 2.0, f"{end_time - start_time}" - assert result_1 == result_2 == 1 - finally: - _pool = pool() - _pool.join() - - -@pytest.mark.asyncio -async def test_process_pool_with_wix_async(): - try: - awake_all_pool_workers() - sleep(2) # Give the pool some time to start up + self.assertLessEqual( + end_time - start_time, 2.0, f"{end_time - start_time}" + ) + self.assertTrue(result1 == result2 == 1) + def test_process_pool_with_wix(self) -> None: + # We're recording the start time start_time = time() - print("Submitting jobs...") - result_1, result_2 = await gather( - run_in_processpool_with_wix(partial(simple_job, 1), wix=1), - run_in_processpool_with_wix(partial(simple_job, 1), wix=1), - ) - end_time = time() - print("Elapsed time:", end_time - start_time) - # Total elapsed time should be little more than 2 seconds, - # not 1 second, because jobs are expected to run in serial. - assert end_time - start_time >= 2.0, f"{end_time - start_time}" - assert result_1 == result_2 == 1 - finally: - _pool = pool() - _pool.join() - - -def test_process_pool_graceful_shutdown(): - timeout = None - with ProcessPool(max_workers=2) as executor: - f1 = executor.submit(simple_job, 1) - f2 = executor.submit(simple_job, 1) + # Submitting two jobs which will sleep for 1 second each + f1: Future = self.ppool.submit_with_wix(partial(simple_job, 1), wix=1) + f2: Future = self.ppool.submit_with_wix(partial(simple_job, 1), wix=1) print("Submitted jobs") - # Wait for the jobs to start - result1 = f1.result(timeout=timeout) - result2 = f2.result(timeout=timeout) + # Waiting for both jobs to complete + result1 = f1.result() # This will block until f1 is done + result2 = f2.result() # This will block until f2 is done print("Jobs done:", result1, result2) + # Recording the end time + end_time = time() + print("Elapsed time:", end_time - start_time) -def test_process_pool_map(): - timeout = 3.0 - with ProcessPool(max_workers=4) as executor: - results = iter( - executor.map( - simple_job, - [1, 1, 1, 1], - chunksize=2, - timeout=timeout, - ) + # Total elapsed time should be little more than 2 seconds, + # not 1 second, because jobs are expected to run in serial. + self.assertGreaterEqual( + end_time - start_time, 2.0, f"{end_time - start_time}" ) - print("Submitted jobs") + self.assertTrue(result1 == result2 == 1) + + async def test_process_pool_async(self): + try: + awake_all_pool_workers() + sleep(2) # Give the pool some time to start up + + start_time = time() + print("Submitting jobs...") + result_1, result_2 = await gather( + run_in_processpool(simple_job, 1), + run_in_processpool(simple_job, 1), # type: ignore + ) + end_time = time() + print("Elapsed time:", end_time - start_time) - # Wait for the jobs to start - result1 = next(results) - result2 = next(results) - print("Jobs done:", result1, result2) + # Total elapsed time should be little more than 1 second, + # not 2 seconds, because jobs are expected to run in parallel. + self.assertLessEqual( + end_time - start_time, 2.0, f"{end_time - start_time}" + ) + self.assertTrue(result_1 == result_2 == 1) + finally: + _pool = pool() + _pool.join() + + async def test_process_pool_with_wix_async(self): + try: + awake_all_pool_workers() + sleep(2) # Give the pool some time to start up + + start_time = time() + print("Submitting jobs...") + result_1, result_2 = await gather( + run_in_processpool_with_wix(partial(simple_job, 1), wix=1), + run_in_processpool_with_wix(partial(simple_job, 1), wix=1), + ) + end_time = time() + print("Elapsed time:", end_time - start_time) + # Total elapsed time should be little more than 2 seconds, + # not 1 second, because jobs are expected to run in serial. + self.assertGreaterEqual( + end_time - start_time, 2.0, f"{end_time - start_time}" + ) + self.assertTrue(result_1 == result_2 == 1) + finally: + _pool = pool() + _pool.join() + + def test_process_pool_graceful_shutdown(self): + timeout = None + with ProcessPool(max_workers=2) as executor: + f1 = executor.submit(simple_job, 1) + f2 = executor.submit(simple_job, 1) + print("Submitted jobs") + + # Wait for the jobs to start + result1 = f1.result(timeout=timeout) + result2 = f2.result(timeout=timeout) + print("Jobs done:", result1, result2) + + def test_process_pool_map(self): + timeout = 3.0 + with ProcessPool(max_workers=4) as executor: + results = iter( + executor.map( + simple_job, + [1, 1, 1, 1], + chunksize=2, + timeout=timeout, + ) + ) + print("Submitted jobs") -if __name__ == "__main__": - test_process_pool_map() + # Wait for the jobs to start + result1 = next(results) + result2 = next(results) + print("Jobs done:", result1, result2) diff --git a/tests/test_server.py b/tests/test_server.py index 2d6a461..0ef84cb 100644 --- a/tests/test_server.py +++ b/tests/test_server.py @@ -3,18 +3,20 @@ from pathlib import Path import sys from typing import ( - TYPE_CHECKING, Awaitable, + Dict, Iterable, List, Literal, Optional, Tuple, + Union, ) +import unittest from fastapi.testclient import TestClient -import pytest from httpx import AsyncClient, Response +from tests.conftest import TestLlamaAPI sys.path.insert(0, Path(__file__).parent.parent.as_posix()) from llama_api.schemas.api import ( # noqa: E402 @@ -23,190 +25,201 @@ CompletionChoice, ) -if TYPE_CHECKING: - from fastapi import FastAPI EndPoint = Literal["completions", "chat/completions"] -GGML_MODEL: str = "orca-mini-3b.ggmlv3.q4_1.bin" -GGML_PATH: Path = Path(__file__).parents[1] / Path(f"models/ggml/{GGML_MODEL}") -GPTQ_MODEL: str = "orca_mini_7b" -GPTQ_PATH: Path = Path(__file__).parents[1] / Path(f"models/gptq/{GPTQ_MODEL}") - -MESSAGES = [{"role": "user", "content": "Hello, there!"}] -PROMPT = "\n".join([f"{m['role']}: {m['content']}" for m in MESSAGES]) - - -async def _arequest_completion( - app: "FastAPI", - model_names: List[str] | Tuple[str, ...], - endpoints: EndPoint | Iterable[EndPoint], -): - _endpoints: Iterable[str] = ( - [endpoints] * len(model_names) - if isinstance(endpoints, str) - else endpoints - ) - async with AsyncClient( - app=app, base_url="http://localhost", timeout=None - ) as client: - # Get models using the API - model_resp: ModelList = (await client.get("/v1/models")).json() - models: list[str] = [] - for model_name in model_names: - model: Optional[str] = None - for model_data in model_resp["data"]: - if model_name in model_data["id"]: - model = re.sub(r"\(.*\)", "", model_data["id"]).strip() - break - assert model, f"Model {model_name} not found" - models.append(model) - - # Submit requests to the API - tasks: list[Awaitable] = [] - for model, endpoint in zip(models, _endpoints): - request = {"model": model, "max_tokens": 50} - request_message = ( - {"messages": MESSAGES} - if endpoint.startswith("chat") - else {"prompt": PROMPT} - ) - tasks.append( - client.post( - f"/v1/{endpoint}", - json=request | {"stream": False} | request_message, - headers={"Content-Type": "application/json"}, - timeout=None, - ) +class TestServer(TestLlamaAPI, unittest.IsolatedAsyncioTestCase): + def test_health(self): + with TestClient(app=self.app) as client: + response = client.get( + "/health", + headers={"Content-Type": "application/json"}, ) + self.assertEqual(response.status_code, 200) - # Wait for responses - cmpl_resps: list[Response] = await gather(*tasks) - results: list[str] = [] - for model, cmpl_resp in zip(models, cmpl_resps): - assert cmpl_resp.status_code == 200 - choice: CompletionChoice | ChatCompletionChoice = cmpl_resp.json()[ - "choices" - ][0] - if "message" in choice: - results.append(choice["message"]["content"]) # type: ignore - elif "text" in choice: - results.append(choice["text"]) - else: - raise ValueError(f"Unknown response: {cmpl_resp.json()}") - print(f"Result of {model}:", results[-1], end="\n\n", flush=True) - - assert len(results) == len(models) - - -def _request_completion( - app: "FastAPI", - model_names: List[str] | Tuple[str, ...], - endpoints: EndPoint | Iterable[EndPoint], -): - _endpoints: Iterable[str] = ( - [endpoints] * len(model_names) - if isinstance(endpoints, str) - else endpoints + @unittest.skipIf( + not TestLlamaAPI.ggml_path.exists(), + reason=f"No model in {TestLlamaAPI.ggml_path}", ) - with TestClient(app=app) as client: - # Get models using the API - model_resp = (client.get("/v1/models")).json() - models: list[str] = [] - for model_name in model_names: - model: Optional[str] = None - for model_data in model_resp["data"]: - if model_name in model_data["id"]: - model = re.sub(r"\(.*\)", "", model_data["id"]).strip() - break - assert model, f"Model {model_name} not found" - models.append(model) - - # Submit requests to the API - cmpl_resps: list[Response] = [] - for model, endpoint in zip(models, _endpoints): - request = {"model": model, "max_tokens": 50} - request_message = ( - {"messages": MESSAGES} - if endpoint.startswith("chat") - else {"prompt": PROMPT} - ) - cmpl_resps.append( - client.post( - f"/v1/{endpoint}", - json=request | {"stream": False} | request_message, - headers={"Content-Type": "application/json"}, - timeout=None, - ) - ) - - # Wait for responses - results: list[str] = [] - for model, cmpl_resp in zip(models, cmpl_resps): - assert cmpl_resp.status_code == 200 - choice: CompletionChoice | ChatCompletionChoice = cmpl_resp.json()[ - "choices" - ][0] - if "message" in choice: - results.append(choice["message"]["content"]) # type: ignore - elif "text" in choice: - results.append(choice["text"]) - else: - raise ValueError(f"Unknown response: {cmpl_resp.json()}") - print(f"Result of {model}:", results[-1], end="\n\n", flush=True) - - assert len(results) == len(models) - - -def test_health(app): - with TestClient(app=app) as client: - response = client.get( - "/health", - headers={"Content-Type": "application/json"}, + def test_llama_cpp(self): + self._request_completion( + model_names=(self.ggml_model,), endpoints="completions" + ) + self._request_completion( + model_names=(self.ggml_model,), endpoints="chat/completions" ) - assert response.status_code == 200 - -@pytest.mark.skipif(not GGML_PATH.exists(), reason=f"No model in {GGML_PATH}") -def test_llama_cpp(app): - _request_completion( - app, model_names=(GGML_MODEL,), endpoints="completions" - ) - _request_completion( - app, model_names=(GGML_MODEL,), endpoints="chat/completions" + @unittest.skipIf( + not TestLlamaAPI.gptq_path.exists(), + reason=f"No model in{TestLlamaAPI.gptq_path}", ) + def test_exllama(self): + self._request_completion( + model_names=(self.gptq_model,), endpoints="completions" + ) + self._request_completion( + model_names=(self.gptq_model,), endpoints="chat/completions" + ) + @unittest.skipIf( + not TestLlamaAPI.ggml_path.exists(), + reason=f"No model in {TestLlamaAPI.ggml_path}", + ) + async def test_llama_cpp_concurrency(self): + model_names: Tuple[str, ...] = (self.ggml_model, self.ggml_model) + await self._arequest_completion( + model_names=model_names, endpoints="completions" + ) -@pytest.mark.skipif(not GPTQ_PATH.exists(), reason=f"No model in{GPTQ_PATH}") -def test_exllama(app): - _request_completion( - app, model_names=(GPTQ_MODEL,), endpoints="completions" + @unittest.skipIf( + not TestLlamaAPI.gptq_path.exists(), + reason=f"No model in {TestLlamaAPI.gptq_path}", ) - _request_completion( - app, model_names=(GPTQ_MODEL,), endpoints="chat/completions" + async def test_exllama_concurrency(self): + model_names: Tuple[str, ...] = (self.gptq_model, self.gptq_model) + await self._arequest_completion( + model_names=model_names, endpoints="completions" + ) + + @unittest.skipIf( + (not TestLlamaAPI.ggml_path.exists()) + or (not TestLlamaAPI.gptq_path.exists()), + f"No model in {TestLlamaAPI.ggml_path} or {TestLlamaAPI.gptq_path}", ) + async def test_llama_mixed_concurrency(self): + model_names: Tuple[str, ...] = (self.ggml_model, self.gptq_model) + await self._arequest_completion( + model_names=model_names, endpoints="completions" + ) + async def _arequest_completion( + self, + model_names: Union[List[str], Tuple[str, ...]], + endpoints: Union[EndPoint, Iterable[EndPoint]], + ): + _endpoints: Iterable[str] = ( + [endpoints] * len(model_names) + if isinstance(endpoints, str) + else endpoints + ) + async with AsyncClient( + app=self.app, base_url="http://localhost", timeout=None + ) as client: + # Get models using the API + model_resp: ModelList = (await client.get("/v1/models")).json() + models: List[str] = [] + for model_name in model_names: + model: Optional[str] = None + for model_data in model_resp["data"]: + if model_name in model_data["id"]: + model = re.sub(r"\(.*\)", "", model_data["id"]).strip() + break + assert model, f"Model {model_name} not found" + models.append(model) + + # Submit requests to the API + tasks: List[Awaitable] = [] + for model, endpoint in zip(models, _endpoints): + request = {"model": model, "max_tokens": 50} + request_message = ( + {"messages": self.messages} + if endpoint.startswith("chat") + else {"prompt": self.prompt} + ) + tasks.append( + client.post( + f"/v1/{endpoint}", + json=_union( + request, {"stream": False}, request_message + ), + headers={"Content-Type": "application/json"}, + timeout=None, + ) + ) -@pytest.mark.asyncio -async def test_llama_cpp_concurrency(app): - model_names: Tuple[str, ...] = (GGML_MODEL, GGML_MODEL) - await _arequest_completion( - app, model_names=model_names, endpoints="completions" - ) + # Wait for responses + cmpl_resps: List[Response] = await gather(*tasks) + results: List[str] = [] + for model, cmpl_resp in zip(models, cmpl_resps): + assert cmpl_resp.status_code == 200 + choice: Union[ + CompletionChoice, ChatCompletionChoice + ] = cmpl_resp.json()["choices"][0] + if "message" in choice: + results.append(choice["message"]["content"]) + elif "text" in choice: + results.append(choice["text"]) + else: + raise ValueError(f"Unknown response: {cmpl_resp.json()}") + print( + f"Result of {model}:", results[-1], end="\n\n", flush=True + ) + + assert len(results) == len(models) + + def _request_completion( + self, + model_names: Union[List[str], Tuple[str, ...]], + endpoints: Union[EndPoint, Iterable[EndPoint]], + ): + _endpoints: Iterable[str] = ( + [endpoints] * len(model_names) + if isinstance(endpoints, str) + else endpoints + ) + with TestClient(app=self.app) as client: + # Get models using the API + model_resp = (client.get("/v1/models")).json() + models: List[str] = [] + for model_name in model_names: + model: Optional[str] = None + for model_data in model_resp["data"]: + if model_name in model_data["id"]: + model = re.sub(r"\(.*\)", "", model_data["id"]).strip() + break + assert model, f"Model {model_name} not found" + models.append(model) + + # Submit requests to the API + cmpl_resps: List[Response] = [] + for model, endpoint in zip(models, _endpoints): + request = {"model": model, "max_tokens": 50} + request_message = ( + {"messages": self.messages} + if endpoint.startswith("chat") + else {"prompt": self.prompt} + ) + cmpl_resps.append( + client.post( + f"/v1/{endpoint}", + json=_union( + request, {"stream": False}, request_message + ), + headers={"Content-Type": "application/json"}, + timeout=None, + ) + ) + # Wait for responses + results: List[str] = [] + for model, cmpl_resp in zip(models, cmpl_resps): + assert cmpl_resp.status_code == 200 + choice: Union[ + CompletionChoice, ChatCompletionChoice + ] = cmpl_resp.json()["choices"][0] + if "message" in choice: + results.append(choice["message"]["content"]) + elif "text" in choice: + results.append(choice["text"]) + else: + raise ValueError(f"Unknown response: {cmpl_resp.json()}") + print( + f"Result of {model}:", results[-1], end="\n\n", flush=True + ) -@pytest.mark.asyncio -async def test_exllama_concurrency(app): - model_names: Tuple[str, ...] = (GPTQ_MODEL, GPTQ_MODEL) - await _arequest_completion( - app, model_names=model_names, endpoints="completions" - ) + assert len(results) == len(models) -@pytest.mark.asyncio -async def test_llama_mixed_concurrency(app): - model_names: Tuple[str, ...] = (GGML_MODEL, GPTQ_MODEL) - await _arequest_completion( - app, model_names=model_names, endpoints="completions" - ) +def _union(*dicts: Dict) -> Dict: + return {k: v for d in dicts for k, v in d.items()} From 9ee4d5e38d6fdb41bb0289e0d30c30dfccf6e22b Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sun, 30 Jul 2023 01:15:13 +0900 Subject: [PATCH 04/10] Improved old python compatibility --- llama_api/mixins/prompt_utils.py | 9 +- llama_api/modules/base.py | 10 +- llama_api/modules/exllama.py | 39 +++--- llama_api/modules/llama_cpp.py | 32 ++--- llama_api/modules/sentence_encoder.py | 10 +- llama_api/modules/transformer.py | 16 ++- llama_api/schemas/api.py | 8 +- llama_api/schemas/function_calling.py | 26 ++-- llama_api/schemas/models.py | 4 +- llama_api/server/app_settings.py | 16 +-- llama_api/server/pools/llama.py | 48 ++++--- llama_api/server/routers/v1.py | 8 +- llama_api/shared/config.py | 8 +- llama_api/utils/concurrency.py | 4 +- llama_api/utils/dependency.py | 64 ++------- llama_api/utils/errors.py | 16 ++- llama_api/utils/llama_cpp.py | 10 +- llama_api/utils/logger.py | 4 +- llama_api/utils/process_pool.py | 4 +- llama_api/utils/system.py | 4 +- model_definitions.py | 3 +- poetry.lock | 23 +++- pyproject.toml | 2 +- readme.md | 2 + requirements-all.txt | 2 - requirements.txt | 182 +++++++++++++------------- tests/conftest.py | 2 + 27 files changed, 281 insertions(+), 275 deletions(-) diff --git a/llama_api/mixins/prompt_utils.py b/llama_api/mixins/prompt_utils.py index bec69e8..adc6194 100644 --- a/llama_api/mixins/prompt_utils.py +++ b/llama_api/mixins/prompt_utils.py @@ -1,3 +1,4 @@ +from typing import List from ..schemas.api import APIChatMessage, TextGenerationSettings @@ -9,7 +10,7 @@ class PromptUtilsMixin: ai_fallback_input_role: str = "Assistant" @staticmethod - def get_stop_strings(*roles: str) -> list[str]: + def get_stop_strings(*roles: str) -> List[str]: """A helper method to generate stop strings for a given set of roles. Stop strings are required to stop text completion API from generating text that does not belong to the current chat turn. @@ -33,7 +34,7 @@ def get_stop_strings(*roles: str) -> list[str]: @classmethod def convert_messages_into_prompt( - cls, messages: list[APIChatMessage], settings: TextGenerationSettings + cls, messages: List[APIChatMessage], settings: TextGenerationSettings ) -> str: """A helper method to convert list of messages into one text prompt.""" @@ -48,7 +49,7 @@ def convert_messages_into_prompt( input_role = ai_input_role = message.role chat_history += f"### {input_role}:{message.content}" - prompt_stop: list[str] = cls.get_stop_strings( + prompt_stop: List[str] = cls.get_stop_strings( cls.user_input_role, cls.system_input_role, ai_input_role ) if isinstance(settings.stop, str): @@ -61,7 +62,7 @@ def convert_messages_into_prompt( @staticmethod def is_possible_to_generate_stops( - decoded_text: str, stops: list[str] + decoded_text: str, stops: List[str] ) -> bool: """A helper method to check if the decoded text contains any of the stop tokens.""" diff --git a/llama_api/modules/base.py b/llama_api/modules/base.py index 64d81d1..6428137 100644 --- a/llama_api/modules/base.py +++ b/llama_api/modules/base.py @@ -1,6 +1,6 @@ from abc import ABC, abstractmethod from dataclasses import dataclass -from typing import Any, Iterator, TypeVar +from typing import Any, Iterator, List, TypeVar from ..mixins.prompt_utils import PromptUtilsMixin from ..schemas.api import ( @@ -56,14 +56,14 @@ def generate_completion_with_streaming( @abstractmethod def generate_chat_completion( - self, messages: list[APIChatMessage], settings: TextGenerationSettings + self, messages: List[APIChatMessage], settings: TextGenerationSettings ) -> ChatCompletion: """Generate a completion for a given prompt.""" ... @abstractmethod def generate_chat_completion_with_streaming( - self, messages: list[APIChatMessage], settings: TextGenerationSettings + self, messages: List[APIChatMessage], settings: TextGenerationSettings ) -> Iterator[ChatCompletionChunk]: """Generate a completion for a given prompt, yielding chunks of text as they are generated.""" @@ -91,9 +91,9 @@ def from_pretrained(cls, model_name: str) -> "BaseEmbeddingGenerator": @abstractmethod def generate_embeddings( self, - texts: list[str], + texts: List[str], **kwargs: Any, - ) -> list[list[float]]: + ) -> List[List[float]]: """Generate embeddings for a list of texts.""" ... diff --git a/llama_api/modules/exllama.py b/llama_api/modules/exllama.py index 9b72f6d..e3fc0b5 100644 --- a/llama_api/modules/exllama.py +++ b/llama_api/modules/exllama.py @@ -1,9 +1,9 @@ """Wrapper for exllama to generate text completions.""" from contextlib import contextmanager from pathlib import Path -from typing import TYPE_CHECKING, Iterator, Optional +from typing import TYPE_CHECKING, Dict, Iterator, List, Optional -from torch import IntTensor, cuda +from torch import IntTensor, Tensor, cuda from ..schemas.models import ExllamaModel from ..utils.completions import ( @@ -39,6 +39,15 @@ assert cuda.is_available(), "CUDA must be available to use ExLlama." +def _encode(tokenizer: ExLlamaTokenizer, text: str) -> Tensor: + """Encode a text string into a tensor.""" + result = tokenizer.encode(text) + if isinstance(result, tuple): + return result[0] + else: + return result + + def _make_config(llm_model: "ExllamaModel") -> ExLlamaConfig: """Create a config object for the ExLlama model.""" model_folder_path = Path( @@ -50,7 +59,7 @@ def _make_config(llm_model: "ExllamaModel") -> ExLlamaConfig: config = ExLlamaConfig((model_folder_path / "config.json").as_posix()) # Find the model checkpoint - model_file_found: list[Path] = [] + model_file_found: List[Path] = [] for ext in (".safetensors", ".pt", ".bin"): model_file_found.extend(model_folder_path.glob(f"*{ext}")) if model_file_found: @@ -105,7 +114,7 @@ class ExllamaCompletionGenerator(BaseCompletionGenerator): tokenizer: Optional[ExLlamaTokenizer] = None generator: Optional[ExLlamaGenerator] = None _llm_model: Optional["ExllamaModel"] = None - _completion_status: dict[ + _completion_status: Dict[ str, int ] = {} # key: completion_id, value: number of completion tokens @@ -270,7 +279,7 @@ def generate_completion_with_streaming( text=last_token if last_token is not None else "", finish_reason="length" if self._completion_status.get( - completion_id, self.tokenizer.encode(generated_text).shape[1] + completion_id, _encode(self.tokenizer, generated_text).shape[1] ) >= settings.max_tokens else "stop", @@ -282,9 +291,9 @@ def generate_completion( assert self.tokenizer is not None and self.config is not None completion_id: str = settings.completion_id generated_text: str = self._generate_text(prompt, settings=settings) - n_prompt_tokens: int = self.tokenizer.encode(prompt).shape[1] + n_prompt_tokens: int = _encode(self.tokenizer, prompt).shape[1] n_completion_tokens: int = self._completion_status.get( - completion_id, self.tokenizer.encode(generated_text).shape[1] + completion_id, _encode(self.tokenizer, generated_text).shape[1] ) return make_completion( id=completion_id, @@ -299,7 +308,7 @@ def generate_completion( def generate_chat_completion_with_streaming( self, - messages: list["APIChatMessage"], + messages: List["APIChatMessage"], settings: "TextGenerationSettings", ) -> Iterator["ChatCompletionChunk"]: assert self.config is not None and self.tokenizer is not None @@ -326,23 +335,23 @@ def generate_chat_completion_with_streaming( content=last_token if last_token is not None else "", finish_reason="length" if self._completion_status.get( - completion_id, self.tokenizer.encode(generated_text).shape[1] + completion_id, _encode(self.tokenizer, generated_text).shape[1] ) else "stop", ) def generate_chat_completion( self, - messages: list["APIChatMessage"], + messages: List["APIChatMessage"], settings: "TextGenerationSettings", ) -> "ChatCompletion": assert self.tokenizer is not None and self.config is not None completion_id: str = settings.completion_id prompt = self.convert_messages_into_prompt(messages, settings=settings) generated_text: str = self._generate_text(prompt, settings=settings) - prompt_tokens: int = self.tokenizer.encode(prompt).shape[1] + prompt_tokens: int = _encode(self.tokenizer, prompt).shape[1] completion_tokens: int = self._completion_status.get( - completion_id, self.tokenizer.encode(generated_text).shape[1] + completion_id, _encode(self.tokenizer, generated_text).shape[1] ) return make_chat_completion( id=completion_id, @@ -355,10 +364,10 @@ def generate_chat_completion( else "stop", ) - def encode(self, message: str, /) -> list[int]: + def encode(self, message: str, /) -> List[int]: assert self.tokenizer is not None, "Tokenizer is not initialized" - return self.tokenizer.encode(message).flatten().tolist() + return _encode(self.tokenizer, message).flatten().tolist() - def decode(self, tokens: list[int], /) -> str: + def decode(self, tokens: List[int], /) -> str: assert self.tokenizer is not None, "Tokenizer is not initialized" return str(self.tokenizer.decode(IntTensor(tokens))) diff --git a/llama_api/modules/llama_cpp.py b/llama_api/modules/llama_cpp.py index 5c442db..6932689 100644 --- a/llama_api/modules/llama_cpp.py +++ b/llama_api/modules/llama_cpp.py @@ -1,6 +1,6 @@ """Wrapper for llama_cpp to generate text completions.""" from inspect import signature -from typing import Iterator, Literal, Optional +from typing import Dict, Iterator, List, Literal, Optional, Union from ..schemas.api import ( APIChatMessage, @@ -33,14 +33,14 @@ def _make_logit_bias_processor( llama: llama_cpp.Llama, - logit_bias: dict[str, float], + logit_bias: Dict[str, float], logit_bias_type: Optional[Literal["input_ids", "tokens"]], ): """Create a logit bias processor to bias the logit scores.""" if logit_bias_type is None: logit_bias_type = "input_ids" - to_bias: dict[int, float] = {} + to_bias: Dict[int, float] = {} if logit_bias_type == "input_ids": for input_id_string, score in logit_bias.items(): to_bias[int(input_id_string)] = score @@ -53,10 +53,10 @@ def _make_logit_bias_processor( to_bias[input_id] = score def logit_bias_processor( - input_ids: list[int], - scores: list[float], - ) -> list[float]: - new_scores: list[float] = [0.0] * len(scores) + input_ids: List[int], + scores: List[float], + ) -> List[float]: + new_scores: List[float] = [0.0] * len(scores) for input_id, score in enumerate(scores): new_scores[input_id] = score + to_bias.get(input_id, 0.0) @@ -70,7 +70,7 @@ def _create_completion( prompt: str, stream: bool, settings: TextGenerationSettings, -) -> Completion | Iterator[CompletionChunk]: +) -> Union[Completion, Iterator[CompletionChunk]]: return client.create_completion( # type: ignore stream=stream, prompt=prompt, @@ -104,10 +104,10 @@ def _create_completion( def _create_chat_completion( client: llama_cpp.Llama, - messages: list[APIChatMessage], + messages: List[APIChatMessage], stream: bool, settings: TextGenerationSettings, -) -> ChatCompletion | Iterator[ChatCompletionChunk]: +) -> Union[ChatCompletion, Iterator[ChatCompletionChunk]]: prompt: str = LlamaCppCompletionGenerator.convert_messages_into_prompt( messages, settings=settings ) @@ -149,7 +149,9 @@ def _create_chat_completion( class LlamaCppCompletionGenerator(BaseCompletionGenerator): - generator: Optional[Iterator[CompletionChunk | ChatCompletionChunk]] = None + generator: Optional[ + Iterator[Union[CompletionChunk, ChatCompletionChunk]] + ] = None client: Optional[llama_cpp.Llama] = None _llm_model: Optional["LlamaCppModel"] = None @@ -260,7 +262,7 @@ def generate_completion_with_streaming( yield from completion_chunk_generator def generate_chat_completion( - self, messages: list[APIChatMessage], settings: TextGenerationSettings + self, messages: List[APIChatMessage], settings: TextGenerationSettings ) -> ChatCompletion: assert self.client is not None chat_completion = _create_chat_completion( @@ -273,7 +275,7 @@ def generate_chat_completion( return chat_completion def generate_chat_completion_with_streaming( - self, messages: list[APIChatMessage], settings: TextGenerationSettings + self, messages: List[APIChatMessage], settings: TextGenerationSettings ) -> Iterator[ChatCompletionChunk]: assert self.client is not None chat_completion_chunk_generator = _create_chat_completion( @@ -286,12 +288,12 @@ def generate_chat_completion_with_streaming( self.generator = chat_completion_chunk_generator yield from chat_completion_chunk_generator - def encode(self, text: str, add_bos: bool = True) -> list[int]: + def encode(self, text: str, add_bos: bool = True) -> List[int]: assert self.client is not None, "Client is not initialized" return self.client.tokenize( text.encode("utf-8", errors="ignore"), add_bos=add_bos ) - def decode(self, tokens: list[int]) -> str: + def decode(self, tokens: List[int]) -> str: assert self.client is not None, "Client is not initialized" return self.client.detokenize(tokens).decode("utf-8", errors="ignore") diff --git a/llama_api/modules/sentence_encoder.py b/llama_api/modules/sentence_encoder.py index 4ac5129..e9f8694 100644 --- a/llama_api/modules/sentence_encoder.py +++ b/llama_api/modules/sentence_encoder.py @@ -1,5 +1,5 @@ """Wrapper for sentence_encoder to generate text embeddings.""" -from typing import TYPE_CHECKING, Callable, Optional +from typing import TYPE_CHECKING, Callable, List, Optional import numpy as np import tensorflow_hub as hub @@ -18,7 +18,7 @@ class SentenceEncoderEmbeddingGenerator(BaseEmbeddingGenerator): automatically downloading the model from https://tfhub.dev/""" base_url: str = "https://tfhub.dev/google/" - model: Optional[Callable[[list[str]], "Tensor"]] = None + model: Optional[Callable[[List[str]], "Tensor"]] = None _model_name: Optional[str] = None def __del__(self) -> None: @@ -41,12 +41,12 @@ def from_pretrained( def generate_embeddings( self, - texts: list[str], + texts: List[str], batch_size: int = 100, **kwargs, - ) -> list[list[float]]: + ) -> List[List[float]]: assert self.model is not None, "Please load the model first." - embeddings: list["Tensor"] = [] + embeddings: List["Tensor"] = [] for batch_idx_start in range(0, len(texts), batch_size): batch_idx_end = batch_idx_start + batch_size batch_texts = texts[batch_idx_start:batch_idx_end] diff --git a/llama_api/modules/transformer.py b/llama_api/modules/transformer.py index a0c9c9d..c11fea0 100644 --- a/llama_api/modules/transformer.py +++ b/llama_api/modules/transformer.py @@ -1,6 +1,6 @@ """Wrapper for transformer to generate text embeddings.""" from gc import collect -from typing import Optional +from typing import List, Optional, Tuple, Union from torch import Tensor, cuda from transformers.modeling_outputs import ( BaseModelOutputWithPoolingAndCrossAttentions, @@ -25,7 +25,9 @@ class TransformerEmbeddingGenerator(BaseEmbeddingGenerator): automatically downloading the model from https://huggingface.co/""" model: Optional[PreTrainedModel] = None - tokenizer: Optional[PreTrainedTokenizer | PreTrainedTokenizerFast] = None + tokenizer: Optional[ + Union[PreTrainedTokenizer, PreTrainedTokenizerFast] + ] = None encoder: Optional[PreTrainedModel] = None _model_name: Optional[str] = None @@ -58,12 +60,12 @@ def from_pretrained( def generate_embeddings( self, - texts: list[str], + texts: List[str], context_length: int = 512, batch_size: int = 3, **kwargs, - ) -> list[list[float]]: - embeddings: list[list[float]] = [] + ) -> List[List[float]]: + embeddings: List[List[float]] = [] for batch_idx_start in range(0, len(texts), batch_size): batch_idx_end = batch_idx_start + batch_size batch_texts = texts[batch_idx_start:batch_idx_end] @@ -75,9 +77,9 @@ def generate_embeddings( def _generate_embeddings_and_n_tokens( self, - texts: list[str], + texts: List[str], context_length: int = 512, - ) -> tuple[list[list[float]], int]: + ) -> Tuple[List[List[float]], int]: assert self.model is not None and self.tokenizer is not None def average_pool( diff --git a/llama_api/schemas/api.py b/llama_api/schemas/api.py index f6f2514..45a08e3 100644 --- a/llama_api/schemas/api.py +++ b/llama_api/schemas/api.py @@ -101,7 +101,7 @@ class TextGenerationSettings(BaseModel): default=False, description="If True, the input is echoed back in the output.", ) - stop: Optional[str | list[str]] = Field( + stop: Optional[Union[str, List[str]]] = Field( default=None, description="A list of tokens at which to stop generation. If None, no stop tokens are used.", ) @@ -171,7 +171,7 @@ class TextGenerationSettings(BaseModel): mirostat_eta: float = Field( default=0.1, ge=0.001, le=1.0, description="Mirostat learning rate" ) - logit_bias: Optional[dict[str, float]] = Field( + logit_bias: Optional[Dict[str, float]] = Field( default=None, description=( "A dictionary of logit bias values to use for each token. The keys are the tokens" @@ -199,7 +199,7 @@ class TextGenerationSettings(BaseModel): class CreateEmbeddingRequest(BaseModel): model: str = Field(description="The model to use for embedding.") - input: Union[str, list[str]] = Field(description="The input to embed.") + input: Union[str, List[str]] = Field(description="The input to embed.") user: Optional[str] = Field(default=None, description="Not in use.") class Config: @@ -236,7 +236,7 @@ class CreateChatCompletionRequest(TextGenerationSettings): model: str = Field( default=..., description="The model to use for completion." ) - messages: list[APIChatMessage] = Field( + messages: List[APIChatMessage] = Field( default=[], description="A list of messages to generate completions for.", ) diff --git a/llama_api/schemas/function_calling.py b/llama_api/schemas/function_calling.py index d4ffee3..35c964f 100644 --- a/llama_api/schemas/function_calling.py +++ b/llama_api/schemas/function_calling.py @@ -2,7 +2,17 @@ from dataclasses import dataclass from types import NoneType -from typing import Any, Generic, Literal, Optional, Type, TypeVar, Union +from typing import ( + Any, + Dict, + Generic, + List, + Literal, + Optional, + Type, + TypeVar, + Union, +) from typing_extensions import NotRequired, TypedDict @@ -16,13 +26,13 @@ class ParameterProperty(TypedDict): type: str description: NotRequired[str] - enum: NotRequired[list[JsonTypes]] + enum: NotRequired[List[JsonTypes]] class ParameterDefinition(TypedDict): type: Literal["object"] - properties: dict[str, ParameterProperty] - required: NotRequired[list[str]] + properties: Dict[str, ParameterProperty] + required: NotRequired[List[str]] class FunctionProperty(TypedDict): @@ -38,9 +48,9 @@ class FunctionCallParameter(Generic[ParamType]): name: str type: Type[ParamType] description: Optional[str] = None - enum: Optional[list[ParamType]] = None + enum: Optional[List[ParamType]] = None - def to_dict(self) -> dict[str, ParameterProperty]: + def to_dict(self) -> Dict[str, ParameterProperty]: """Returns a dictionary representation of the parameter""" parameter_property: ParameterProperty = { "type": self._get_json_type(self.type) @@ -81,8 +91,8 @@ class FunctionCall: name: str description: Optional[str] = None - parameters: Optional[list[FunctionCallParameter[Any]]] = None - required: Optional[list[str]] = None + parameters: Optional[List[FunctionCallParameter[Any]]] = None + required: Optional[List[str]] = None def to_dict(self) -> FunctionProperty: """Returns a dictionary representation of the function""" diff --git a/llama_api/schemas/models.py b/llama_api/schemas/models.py index c44b6b8..cb326b8 100644 --- a/llama_api/schemas/models.py +++ b/llama_api/schemas/models.py @@ -1,5 +1,5 @@ from dataclasses import dataclass, field -from typing import Literal, Optional +from typing import List, Literal, Optional from ..modules.base import BaseLLMModel @@ -118,7 +118,7 @@ class ExllamaModel(BaseLLMModel): "RAM as a buffer for GPU to GPU transfers." }, ) - auto_map: Optional[list[float]] = field( + auto_map: Optional[List[float]] = field( default=None, metadata={ "description": "List of floats with memory allocation in GB, " diff --git a/llama_api/server/app_settings.py b/llama_api/server/app_settings.py index 688de01..a2c445a 100644 --- a/llama_api/server/app_settings.py +++ b/llama_api/server/app_settings.py @@ -1,13 +1,13 @@ -from pathlib import Path import platform import subprocess import sys from contextlib import asynccontextmanager from logging import warn from os import environ +from pathlib import Path from typing import Dict, Optional, Union - +from ..shared.config import Config from ..utils.dependency import ( get_poetry_executable, git_clone, @@ -147,19 +147,17 @@ def run( max_workers: int = 1, ) -> None: initialize_before_launch( - git_and_disk_paths={ - "https://github.com/abetlen/llama-cpp-python": "repositories/llama_cpp", - "https://github.com/turboderp/exllama": "repositories/exllama", - }, + git_and_disk_paths=Config.git_and_disk_paths, install_packages=True, ) - from uvicorn import Config, Server + from uvicorn import Config as UvicornConfig + from uvicorn import Server as UvicornServer environ["MAX_WORKERS"] = str(max_workers) - Server( - config=Config( + UvicornServer( + config=UvicornConfig( create_app_llama_cpp(), host="0.0.0.0", port=port, diff --git a/llama_api/server/pools/llama.py b/llama_api/server/pools/llama.py index 2545e5c..fd3d9b0 100644 --- a/llama_api/server/pools/llama.py +++ b/llama_api/server/pools/llama.py @@ -4,7 +4,7 @@ from os import getpid from queue import Queue from threading import Event -from typing import Iterator +from typing import Dict, Iterator, List, Union import model_definitions @@ -46,16 +46,18 @@ def init() -> None: @contextmanager def completion_generator_manager( - body: CreateCompletionRequest - | CreateChatCompletionRequest - | CreateEmbeddingRequest, + body: Union[ + CreateCompletionRequest, + CreateChatCompletionRequest, + CreateEmbeddingRequest, + ], ): """Context manager for completion generators.""" completion_generator = get_completion_generator(body) yield completion_generator -def get_model_names() -> list[str]: +def get_model_names() -> List[str]: return [ k + f"({v.model_path})" for k, v in model_definitions.__dict__.items() @@ -72,9 +74,11 @@ def get_model(model_name: str) -> "BaseLLMModel": def get_completion_generator( - body: CreateCompletionRequest - | CreateChatCompletionRequest - | CreateEmbeddingRequest, + body: Union[ + CreateCompletionRequest, + CreateChatCompletionRequest, + CreateEmbeddingRequest, + ], ) -> "BaseCompletionGenerator": """Get a completion generator for the given model. If the model is not cached, create a new one. @@ -82,7 +86,7 @@ def get_completion_generator( try: # Check if the model is an OpenAI model - openai_replacement_models: dict[str, str] = getattr( + openai_replacement_models: Dict[str, str] = getattr( model_definitions, "openai_replacement_models", {} ) if body.model in openai_replacement_models: @@ -200,7 +204,7 @@ def get_embedding_generator( def generate_completion_chunks( - body: CreateChatCompletionRequest | CreateCompletionRequest, + body: Union[CreateChatCompletionRequest, CreateCompletionRequest], queue: Queue, event: Event, ) -> None: @@ -208,7 +212,7 @@ def generate_completion_chunks( with completion_generator_manager(body=body) as cg: if isinstance(body, CreateChatCompletionRequest): _iterator: Iterator[ - ChatCompletionChunk | CompletionChunk + Union[ChatCompletionChunk, CompletionChunk] ] = cg.generate_chat_completion_with_streaming( messages=body.messages, settings=body, @@ -218,11 +222,13 @@ def generate_completion_chunks( prompt=body.prompt, settings=body, ) - first_response: ChatCompletionChunk | CompletionChunk = next( + first_response: Union[ChatCompletionChunk, CompletionChunk] = next( _iterator ) - def iterator() -> Iterator[ChatCompletionChunk | CompletionChunk]: + def iterator() -> ( + Iterator[Union[ChatCompletionChunk, CompletionChunk]] + ): yield first_response for chunk in _iterator: yield chunk @@ -235,18 +241,18 @@ def iterator() -> Iterator[ChatCompletionChunk | CompletionChunk]: def generate_completion( - body: CreateChatCompletionRequest | CreateCompletionRequest, + body: Union[CreateChatCompletionRequest, CreateCompletionRequest], queue: Queue, event: Event, ) -> None: with queue_event_manager(queue=queue, event=event): with completion_generator_manager(body=body) as cg: if isinstance(body, CreateChatCompletionRequest): - completion: ChatCompletion | Completion = ( - cg.generate_chat_completion( - messages=body.messages, - settings=body, - ) + completion: Union[ + ChatCompletion, Completion + ] = cg.generate_chat_completion( + messages=body.messages, + settings=body, ) elif isinstance(body, CreateCompletionRequest): completion = cg.generate_completion( @@ -275,8 +281,8 @@ def generate_embeddings( embedding_generator: "BaseEmbeddingGenerator" = ( get_embedding_generator(body) ) - embeddings: list[ - list[float] + embeddings: List[ + List[float] ] = embedding_generator.generate_embeddings( texts=body.input if isinstance(body.input, list) diff --git a/llama_api/server/routers/v1.py b/llama_api/server/routers/v1.py index bca4b21..d697f50 100644 --- a/llama_api/server/routers/v1.py +++ b/llama_api/server/routers/v1.py @@ -15,8 +15,10 @@ Callable, Iterator, Optional, + Tuple, Type, TypeVar, + Union, ) from anyio import ( @@ -68,7 +70,7 @@ class WixMetadata: # Worker index (wix) is used to keep track of which worker is currently # processing a request. This is used to prevent multiple requests from # creating multiple completion generators at the same time. -wixs: tuple[WixMetadata] = tuple(WixMetadata() for _ in range(MAX_WORKERS)) +wixs: Tuple[WixMetadata] = tuple(WixMetadata() for _ in range(MAX_WORKERS)) def validate_item_type(item: Any, type: Type[T]) -> T: @@ -197,7 +199,7 @@ async def create_chat_completion( queue, event = get_queue_and_event() producer: Callable[ [ - CreateChatCompletionRequest | CreateCompletionRequest, + Union[CreateChatCompletionRequest, CreateCompletionRequest], Queue, Event, ], @@ -260,7 +262,7 @@ async def create_completion( queue, event = get_queue_and_event() producer: Callable[ [ - CreateChatCompletionRequest | CreateCompletionRequest, + Union[CreateChatCompletionRequest, CreateCompletionRequest], Queue, Event, ], diff --git a/llama_api/shared/config.py b/llama_api/shared/config.py index 2d689aa..156f419 100644 --- a/llama_api/shared/config.py +++ b/llama_api/shared/config.py @@ -1,9 +1,7 @@ -from dataclasses import dataclass from pathlib import Path -from typing import Tuple +from typing import Dict, Tuple, Union -@dataclass(frozen=True) class Config: """Configuration for the project""" @@ -13,3 +11,7 @@ class Config: torch_version: str = "==2.0.1" torch_source: str = "https://download.pytorch.org/whl/torch_stable.html" tensorflow_version: str = "==2.13.0" + git_and_disk_paths: Dict[str, Union[Path, str]] = { + "https://github.com/abetlen/llama-cpp-python": "repositories/llama_cpp", + "https://github.com/turboderp/exllama": "repositories/exllama", + } diff --git a/llama_api/utils/concurrency.py b/llama_api/utils/concurrency.py index 5d4de6b..0ae4286 100644 --- a/llama_api/utils/concurrency.py +++ b/llama_api/utils/concurrency.py @@ -5,7 +5,7 @@ from os import environ from queue import Queue from threading import Event -from typing import Callable, Optional, ParamSpec, Tuple, TypeVar +from typing import Callable, Dict, Optional, ParamSpec, Tuple, TypeVar from fastapi.concurrency import run_in_threadpool @@ -21,7 +21,7 @@ _manager: Optional[SyncManager] = None -def init_process_pool(env_vars: dict[str, str]) -> None: +def init_process_pool(env_vars: Dict[str, str]) -> None: """Initialize the process pool, and set the environment variables for the child processes""" try: diff --git a/llama_api/utils/dependency.py b/llama_api/utils/dependency.py index a9bc8e7..c104961 100644 --- a/llama_api/utils/dependency.py +++ b/llama_api/utils/dependency.py @@ -28,7 +28,8 @@ def git_clone(git_path: str, disk_path: Union[Path, str]) -> None: def get_poetry_executable() -> Path: - """Construct the path to the poetry executable within the virtual environment + """Construct the path to the poetry executable + within the virtual environment. Check the operating system to determine the correct location""" if os.name == "nt": # Windows return Path(sys.prefix) / "Scripts" / "poetry.exe" @@ -59,19 +60,15 @@ def check_if_torch_cuda_version_available( """Helper function that checks if the CUDA version of torch is available""" try: # Determine the version of python, CUDA, and platform - cuda_version = (f'cu{cuda_version.replace(".", "")}').encode() # type: ignore - python_version = ( + cuda_ver = (f'cu{cuda_version.replace(".", "")}').encode() + python_ver = ( f"cp{sys.version_info.major}{sys.version_info.minor}" ).encode() platform = ("win" if sys.platform == "win32" else "linux").encode() # Check if the CUDA version of torch is available for line in urlopen(source).read().splitlines(): - if ( - cuda_version in line - and python_version in line - and platform in line - ): + if cuda_ver in line and python_ver in line and platform in line: return True return False except Exception: @@ -87,7 +84,8 @@ def parse_requirements( Args: requirements: The string of requirements.txt to parse. excludes: A list of packages to exclude. - include_version: Whether to include the version in the parsed requirements. + include_version: + Whether to include the version in the parsed requirements. Returns: A list of parsed requirements. """ @@ -123,44 +121,6 @@ def convert_toml_to_requirements_with_poetry(toml_path: Path) -> None: pass -# def parse_dependencies( -# parse_dir: Path, -# excludes: Optional[List[str]] = None, -# include_version: bool = True, -# ) -> List[str]: -# """Parse dependencies from pyproject.toml or requirements.txt. -# Then, convert the dependencies to a list of strings.""" -# try: -# if (parse_dir / "pyproject.toml").exists(): -# # Convert dependencies from pyproject.toml to requirements.txt -# call( -# [ -# get_poetry_executable(), -# "export", -# "-f", -# "requirements.txt", -# "--output", -# "requirements.txt", -# "--without-hashes", -# ], -# cwd=parse_dir, -# ) -# except Exception: -# pass -# try: -# with open(parse_dir / "requirements.txt", "r") as file: -# return [ -# dep -# for dep in parse_requirements( -# file.read(), -# excludes=excludes, -# include_version=include_version, -# ) -# ] -# except Exception: -# return [] - - @contextmanager def import_repository(git_path: str, disk_path: str): """ @@ -189,16 +149,16 @@ def install_poetry(): def install_torch( torch_version: str = Config.torch_version, cuda_version: Optional[str] = Config.cuda_version, - source: Optional[ - str - ] = Config.torch_source, # https://download.pytorch.org/whl/torch_stable.html + source: Optional[str] = Config.torch_source, ) -> bool: """Try to install Pytorch. If CUDA is available, install the CUDA version of torch. Else, install the CPU version of torch. Args: - torch_version (str): The version of torch. Defaults to Config.torch_version. - cuda_version (str): The version of CUDA. Defaults to Config.cuda_version. + torch_version (str): The version of torch. + Defaults to Config.torch_version. + cuda_version (str): The version of CUDA. + Defaults to Config.cuda_version. source (Optional[str]): The source to install torch from. Defaults to Config.torch_source. Returns: diff --git a/llama_api/utils/errors.py b/llama_api/utils/errors.py index bbe540c..2a5d21b 100644 --- a/llama_api/utils/errors.py +++ b/llama_api/utils/errors.py @@ -1,7 +1,7 @@ from os import getpid, kill from re import Match, compile from signal import SIGINT -from typing import Callable, Optional +from typing import Callable, Optional, Tuple, Union from fastapi import Request, Response from fastapi.responses import JSONResponse @@ -28,9 +28,9 @@ class ErrorResponse(TypedDict): class ErrorResponseCallbacks: @staticmethod def token_exceed_callback( - request: CreateCompletionRequest | CreateChatCompletionRequest, + request: Union[CreateCompletionRequest, CreateChatCompletionRequest], match: Match[str], - ) -> tuple[int, ErrorResponse]: + ) -> Tuple[int, ErrorResponse]: context_window = int(match.group(2)) prompt_tokens = int(match.group(1)) completion_tokens = request.max_tokens @@ -69,11 +69,13 @@ def wrap_error_message_as_openai( self, error: Exception, body: Optional[ - CreateCompletionRequest - | CreateChatCompletionRequest - | CreateEmbeddingRequest + Union[ + CreateCompletionRequest, + CreateChatCompletionRequest, + CreateEmbeddingRequest, + ] ] = None, - ) -> tuple[int, ErrorResponse]: + ) -> Tuple[int, ErrorResponse]: if body is None or isinstance(body, CreateEmbeddingRequest): return 500, ErrorResponse( message=str(error), diff --git a/llama_api/utils/llama_cpp.py b/llama_api/utils/llama_cpp.py index 21f757d..b23cbfb 100644 --- a/llama_api/utils/llama_cpp.py +++ b/llama_api/utils/llama_cpp.py @@ -5,7 +5,7 @@ import sys from logging import Logger, getLogger from pathlib import Path -from typing import Optional +from typing import List, Optional # You can set the CMAKE_ARGS environment variable to change the cmake args. # cuBLAS is default to ON, @@ -63,7 +63,7 @@ def _git_clone() -> None: subprocess.run(clone_command, cwd=cwd) -def _get_libs() -> list[str]: +def _get_libs() -> List[str]: # Determine the libs based on the platform if sys.platform.startswith("linux"): return [ @@ -82,16 +82,16 @@ def _get_libs() -> list[str]: raise RuntimeError("Unsupported platform") -def _get_lib_paths(base_path: Path) -> list[Path]: +def _get_lib_paths(base_path: Path) -> List[Path]: # Determine the lib paths based on the platform return [base_path / lib for lib in _get_libs()] def _copy_skbuild_libs_to_target( cmake_dir: Path, target_dir: Path -) -> list[Path]: +) -> List[Path]: # Copy the built libs to the target folder - source_libs: Optional[list[Path]] = None + source_libs: Optional[List[Path]] = None for dir in (cmake_dir / "_skbuild").glob("*"): if dir.is_dir(): print(f"~~~ Checking {dir}") diff --git a/llama_api/utils/logger.py b/llama_api/utils/logger.py index 40dcf72..7cfe2bf 100644 --- a/llama_api/utils/logger.py +++ b/llama_api/utils/logger.py @@ -3,7 +3,7 @@ import logging import os from dataclasses import dataclass -from typing import Optional +from typing import Dict, Optional from .colorama import Fore, Style @@ -38,7 +38,7 @@ def format(self, record: logging.LogRecord): class ApiLogger(logging.Logger): - _instances: dict[str, "ApiLogger"] = {} + _instances: Dict[str, "ApiLogger"] = {} def __new__( cls, name: str, logging_config: LoggingConfig = LoggingConfig() diff --git a/llama_api/utils/process_pool.py b/llama_api/utils/process_pool.py index 66aaf88..89df04e 100644 --- a/llama_api/utils/process_pool.py +++ b/llama_api/utils/process_pool.py @@ -405,7 +405,7 @@ def _job_manager_thread(self) -> None: """Manages dispatching jobs to processes, checking results, sending them to futures and restarting if they die""" while True: - busy_procs = [] # type: list[int] + busy_procs = [] # type: List[int] for wix, worker in enumerate(self._pool): if worker is None: continue @@ -440,7 +440,7 @@ def _job_manager_thread(self) -> None: idle_procs = [ wix for wix in range(self.max_workers) if wix not in busy_procs - ] # type: list[int] + ] # type: List[int] if not idle_procs: # All workers are busy, let's wait for one to become idle sleep(SLEEP_TICK) diff --git a/llama_api/utils/system.py b/llama_api/utils/system.py index 60a37d9..f2f4410 100644 --- a/llama_api/utils/system.py +++ b/llama_api/utils/system.py @@ -3,7 +3,7 @@ from logging import INFO, getLogger from re import compile from subprocess import PIPE, check_output, run -from typing import TYPE_CHECKING, Any, Optional, Union +from typing import TYPE_CHECKING, Any, List, Optional, Union if TYPE_CHECKING: from asyncio import Queue as AsyncQueue @@ -27,7 +27,7 @@ def get_cuda_version() -> Optional[str]: return -def get_vram_usages() -> Optional[list[int]]: +def get_vram_usages() -> Optional[List[int]]: """Returns a list of memory usage in MB for each GPU. Returns None if nvidia-smi is not available.""" try: diff --git a/model_definitions.py b/model_definitions.py index 8acef12..c35f99e 100644 --- a/model_definitions.py +++ b/model_definitions.py @@ -1,3 +1,4 @@ +from typing import Dict from llama_api.schemas.models import ExllamaModel, LlamaCppModel # ================== LLaMA.cpp models ================== # @@ -28,7 +29,7 @@ # Define a mapping from OpenAI model names to LLaMA models. # e.g. If you request API model "gpt-3.5-turbo", # the API will load the LLaMA model "orca_mini_3b" -openai_replacement_models: dict[str, str] = { +openai_replacement_models: Dict[str, str] = { "gpt-3.5-turbo": "orca_mini_3b", "gpt-4": "orca_mini_7b", } diff --git a/poetry.lock b/poetry.lock index e68cba6..8ce5cf5 100644 --- a/poetry.lock +++ b/poetry.lock @@ -88,6 +88,7 @@ packaging = ">=22.0" pathspec = ">=0.9.0" platformdirs = ">=2" tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""} +typing-extensions = {version = ">=3.10.0.0", markers = "python_version < \"3.10\""} [package.extras] colorama = ["colorama (>=0.4.3)"] @@ -1008,6 +1009,9 @@ files = [ {file = "Markdown-3.4.4.tar.gz", hash = "sha256:225c6123522495d4119a90b3a3ba31a1e87a70369e03f14799ea9c0d7183a3d6"}, ] +[package.dependencies] +importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""} + [package.extras] docs = ["mdx-gh-links (>=0.2)", "mkdocs (>=1.0)", "mkdocs-nature (>=0.4)"] testing = ["coverage", "pyyaml"] @@ -1143,6 +1147,7 @@ files = [ click = ">=7.0" colorama = {version = ">=0.4", markers = "platform_system == \"Windows\""} ghp-import = ">=1.0" +importlib-metadata = {version = ">=4.3", markers = "python_version < \"3.10\""} jinja2 = ">=2.11.1" markdown = ">=3.2.1" markupsafe = ">=2.0.1" @@ -1218,6 +1223,7 @@ files = [ ] [package.dependencies] +importlib-metadata = {version = ">=4.6", markers = "python_version < \"3.10\""} Jinja2 = ">=2.11.1" Markdown = ">=3.3" MarkupSafe = ">=1.1" @@ -1225,6 +1231,7 @@ mkdocs = ">=1.2" mkdocs-autorefs = ">=0.3.1" mkdocstrings-python = {version = ">=0.5.2", optional = true, markers = "extra == \"python\""} pymdown-extensions = ">=6.3" +typing-extensions = {version = ">=4.1", markers = "python_version < \"3.10\""} [package.extras] crystal = ["mkdocstrings-crystal (>=0.3.4)"] @@ -1510,18 +1517,18 @@ testing = ["pytest", "pytest-cov"] [[package]] name = "platformdirs" -version = "3.9.1" +version = "3.10.0" description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." optional = false python-versions = ">=3.7" files = [ - {file = "platformdirs-3.9.1-py3-none-any.whl", hash = "sha256:ad8291ae0ae5072f66c16945166cb11c63394c7a3ad1b1bc9828ca3162da8c2f"}, - {file = "platformdirs-3.9.1.tar.gz", hash = "sha256:1b42b450ad933e981d56e59f1b97495428c9bd60698baab9f3eb3d00d5822421"}, + {file = "platformdirs-3.10.0-py3-none-any.whl", hash = "sha256:d7c24979f292f916dc9cbf8648319032f551ea8c49a4c9bf2fb556a02070ec1d"}, + {file = "platformdirs-3.10.0.tar.gz", hash = "sha256:b45696dab2d7cc691a3226759c0d3b00c47c8b6e293d96f6436f733303f77f6d"}, ] [package.extras] -docs = ["furo (>=2023.5.20)", "proselint (>=0.13)", "sphinx (>=7.0.1)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"] -test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.3.1)", "pytest-cov (>=4.1)", "pytest-mock (>=3.10)"] +docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.1)", "sphinx-autodoc-typehints (>=1.24)"] +test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"] [[package]] name = "pluggy" @@ -1557,6 +1564,7 @@ crashtest = ">=0.4.1,<0.5.0" dulwich = ">=0.21.2,<0.22.0" filelock = ">=3.8.0,<4.0.0" html5lib = ">=1.0,<2.0" +importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""} installer = ">=0.7.0,<0.8.0" jsonschema = ">=4.10.0,<5.0.0" keyring = ">=23.9.0,<24.0.0" @@ -2665,6 +2673,7 @@ files = [ [package.dependencies] anyio = ">=3.4.0,<5" +typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""} [package.extras] full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyaml"] @@ -3276,5 +3285,5 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" -python-versions = ">=3.10.1,<3.12" -content-hash = "d3894b312b097ea1b48461143caac21b3c917c1ed3ebfabdbe9f14fa3f3ebd0b" +python-versions = ">=3.9.1,<3.12" +content-hash = "917c885df5367bbbde43b2d9d9979b48a7180374f21fc3df740d99c544550bfc" diff --git a/pyproject.toml b/pyproject.toml index 079af08..d39847c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,7 +11,7 @@ packages = [{ include = "llama_api" }] include = ["LICENSE.md"] [tool.poetry.dependencies] -python = ">=3.10.1,<3.12" +python = ">=3.9.1,<3.12" poetry = "^1.5.1" uvicorn = { extras = ["standard"], version = "^0.23" } diff --git a/readme.md b/readme.md index d62d888..e7824a0 100644 --- a/readme.md +++ b/readme.md @@ -13,6 +13,8 @@ You can use this server to run the models in your own application, or use it as 2. **Parallelism and Concurrency Enabled** - Due to the internal operation of the process pool, both parallelism and concurrency are secured. The `--max-workers $NUM_WORKERS` option needs to be provided when starting the server. This, however, only applies when requests are made simultaneously for different models. If requests are made for the same model, they will wait until a slot becomes available due to the semaphore. +3. **Auto Dependency Installation** + - The project automatically installs the required dependencies, including **pytorch** and **tensorflow**, when the server is started. This is done by checking the `pyproject.toml` or `requirements.txt` file in the root directory of this project or other repositories. `pyproject.toml` will be parsed into `requirements.txt` with `poetry`. If you want to add more dependencies, simply add them to the file. ## Before you start diff --git a/requirements-all.txt b/requirements-all.txt index 90cdedf..8e1425d 100644 --- a/requirements-all.txt +++ b/requirements-all.txt @@ -23,6 +23,4 @@ flake8 mkdocs mkdocstrings mkdocs-material -pytest -pytest-asyncio httpx \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 8a625ff..321cb67 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,91 +1,91 @@ -annotated-types==0.5.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -anyio==3.7.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -attrs==23.1.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -build==0.10.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -cachecontrol[filecache]==0.12.14 ; python_full_version >= "3.10.1" and python_version < "3.12" -certifi==2023.7.22 ; python_full_version >= "3.10.1" and python_version < "3.12" -cffi==1.15.1 ; python_full_version >= "3.10.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") -charset-normalizer==3.2.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -cleo==2.0.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -click==8.1.6 ; python_full_version >= "3.10.1" and python_version < "3.12" -colorama==0.4.6 ; python_full_version >= "3.10.1" and python_version < "3.12" and (os_name == "nt" or platform_system == "Windows") -crashtest==0.4.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -cryptography==41.0.2 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "linux" -diskcache==5.6.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -distlib==0.3.7 ; python_full_version >= "3.10.1" and python_version < "3.12" -distro==1.8.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -dulwich==0.21.5 ; python_full_version >= "3.10.1" and python_version < "3.12" -exceptiongroup==1.1.2 ; python_full_version >= "3.10.1" and python_version < "3.11" -fastapi==0.100.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -filelock==3.12.2 ; python_full_version >= "3.10.1" and python_version < "3.12" -fsspec==2023.6.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -h11==0.14.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -html5lib==1.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -httptools==0.6.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -huggingface-hub==0.16.4 ; python_full_version >= "3.10.1" and python_version < "3.12" -idna==3.4 ; python_full_version >= "3.10.1" and python_version < "3.12" -importlib-metadata==6.8.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -installer==0.7.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -jaraco-classes==3.3.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -jeepney==0.8.0 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "linux" -jsonschema-specifications==2023.7.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -jsonschema==4.18.4 ; python_full_version >= "3.10.1" and python_version < "3.12" -keyring==23.13.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -lockfile==0.12.2 ; python_full_version >= "3.10.1" and python_version < "3.12" -more-itertools==10.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -msgpack==1.0.5 ; python_full_version >= "3.10.1" and python_version < "3.12" -ninja==1.11.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -numpy==1.25.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -orjson==3.9.2 ; python_full_version >= "3.10.1" and python_version < "3.12" -packaging==23.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -pexpect==4.8.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -pkginfo==1.9.6 ; python_full_version >= "3.10.1" and python_version < "3.12" -platformdirs==3.9.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -poetry-core==1.6.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -poetry-plugin-export==1.4.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -poetry==1.5.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -protobuf==4.23.4 ; python_full_version >= "3.10.1" and python_version < "3.12" -psutil==5.9.5 ; python_full_version >= "3.10.1" and python_version < "3.12" -ptyprocess==0.7.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -pycparser==2.21 ; python_full_version >= "3.10.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") -pydantic-core==2.4.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -pydantic-settings==2.0.2 ; python_full_version >= "3.10.1" and python_version < "3.12" -pydantic==2.1.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -pyproject-hooks==1.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -python-dotenv==1.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -pywin32-ctypes==0.2.2 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "win32" -pyyaml==6.0.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -rapidfuzz==2.15.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -referencing==0.30.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -regex==2023.6.3 ; python_full_version >= "3.10.1" and python_version < "3.12" -requests-toolbelt==1.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -requests==2.31.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -rpds-py==0.9.2 ; python_full_version >= "3.10.1" and python_version < "3.12" -safetensors==0.3.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -scikit-build==0.17.6 ; python_full_version >= "3.10.1" and python_version < "3.12" -secretstorage==3.3.3 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "linux" -sentencepiece==0.1.99 ; python_full_version >= "3.10.1" and python_version < "3.12" -setuptools==68.0.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -shellingham==1.5.0.post1 ; python_full_version >= "3.10.1" and python_version < "3.12" -six==1.16.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -sniffio==1.3.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -sse-starlette==1.6.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -starlette==0.27.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -tensorflow-hub==0.14.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -tokenizers==0.13.3 ; python_full_version >= "3.10.1" and python_version < "3.12" -tomli==2.0.1 ; python_full_version >= "3.10.1" and python_version < "3.11" -tomlkit==0.12.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -tqdm==4.65.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -transformers==4.31.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -trove-classifiers==2023.7.6 ; python_full_version >= "3.10.1" and python_version < "3.12" -typing-extensions==4.7.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -urllib3==1.26.16 ; python_full_version >= "3.10.1" and python_version < "3.12" -uvicorn[standard]==0.23.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -uvloop==0.17.0 ; (sys_platform != "win32" and sys_platform != "cygwin") and platform_python_implementation != "PyPy" and python_full_version >= "3.10.1" and python_version < "3.12" -virtualenv==20.24.2 ; python_full_version >= "3.10.1" and python_version < "3.12" -watchfiles==0.19.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -webencodings==0.5.1 ; python_full_version >= "3.10.1" and python_version < "3.12" -websockets==11.0.3 ; python_full_version >= "3.10.1" and python_version < "3.12" -wheel==0.41.0 ; python_full_version >= "3.10.1" and python_version < "3.12" -xattr==0.10.1 ; python_full_version >= "3.10.1" and python_version < "3.12" and sys_platform == "darwin" -zipp==3.16.2 ; python_full_version >= "3.10.1" and python_version < "3.12" +annotated-types==0.5.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +anyio==3.7.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +attrs==23.1.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +build==0.10.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +cachecontrol[filecache]==0.12.14 ; python_full_version >= "3.9.1" and python_version < "3.12" +certifi==2023.7.22 ; python_full_version >= "3.9.1" and python_version < "3.12" +cffi==1.15.1 ; python_full_version >= "3.9.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") +charset-normalizer==3.2.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +cleo==2.0.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +click==8.1.6 ; python_full_version >= "3.9.1" and python_version < "3.12" +colorama==0.4.6 ; python_full_version >= "3.9.1" and python_version < "3.12" and (os_name == "nt" or platform_system == "Windows") +crashtest==0.4.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +cryptography==41.0.2 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "linux" +diskcache==5.6.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +distlib==0.3.7 ; python_full_version >= "3.9.1" and python_version < "3.12" +distro==1.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +dulwich==0.21.5 ; python_full_version >= "3.9.1" and python_version < "3.12" +exceptiongroup==1.1.2 ; python_full_version >= "3.9.1" and python_version < "3.11" +fastapi==0.100.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +filelock==3.12.2 ; python_full_version >= "3.9.1" and python_version < "3.12" +fsspec==2023.6.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +h11==0.14.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +html5lib==1.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +httptools==0.6.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +huggingface-hub==0.16.4 ; python_full_version >= "3.9.1" and python_version < "3.12" +idna==3.4 ; python_full_version >= "3.9.1" and python_version < "3.12" +importlib-metadata==6.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +installer==0.7.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +jaraco-classes==3.3.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +jeepney==0.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "linux" +jsonschema-specifications==2023.7.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +jsonschema==4.18.4 ; python_full_version >= "3.9.1" and python_version < "3.12" +keyring==23.13.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +lockfile==0.12.2 ; python_full_version >= "3.9.1" and python_version < "3.12" +more-itertools==10.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +msgpack==1.0.5 ; python_full_version >= "3.9.1" and python_version < "3.12" +ninja==1.11.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +numpy==1.25.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +orjson==3.9.2 ; python_full_version >= "3.9.1" and python_version < "3.12" +packaging==23.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +pexpect==4.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +pkginfo==1.9.6 ; python_full_version >= "3.9.1" and python_version < "3.12" +platformdirs==3.9.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +poetry-core==1.6.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +poetry-plugin-export==1.4.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +poetry==1.5.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +protobuf==4.23.4 ; python_full_version >= "3.9.1" and python_version < "3.12" +psutil==5.9.5 ; python_full_version >= "3.9.1" and python_version < "3.12" +ptyprocess==0.7.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +pycparser==2.21 ; python_full_version >= "3.9.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") +pydantic-core==2.4.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +pydantic-settings==2.0.2 ; python_full_version >= "3.9.1" and python_version < "3.12" +pydantic==2.1.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +pyproject-hooks==1.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +python-dotenv==1.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +pywin32-ctypes==0.2.2 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "win32" +pyyaml==6.0.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +rapidfuzz==2.15.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +referencing==0.30.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +regex==2023.6.3 ; python_full_version >= "3.9.1" and python_version < "3.12" +requests-toolbelt==1.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +requests==2.31.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +rpds-py==0.9.2 ; python_full_version >= "3.9.1" and python_version < "3.12" +safetensors==0.3.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +scikit-build==0.17.6 ; python_full_version >= "3.9.1" and python_version < "3.12" +secretstorage==3.3.3 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "linux" +sentencepiece==0.1.99 ; python_full_version >= "3.9.1" and python_version < "3.12" +setuptools==68.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +shellingham==1.5.0.post1 ; python_full_version >= "3.9.1" and python_version < "3.12" +six==1.16.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +sniffio==1.3.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +sse-starlette==1.6.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +starlette==0.27.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +tensorflow-hub==0.14.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +tokenizers==0.13.3 ; python_full_version >= "3.9.1" and python_version < "3.12" +tomli==2.0.1 ; python_full_version >= "3.9.1" and python_version < "3.11" +tomlkit==0.12.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +tqdm==4.65.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +transformers==4.31.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +trove-classifiers==2023.7.6 ; python_full_version >= "3.9.1" and python_version < "3.12" +typing-extensions==4.7.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +urllib3==1.26.16 ; python_full_version >= "3.9.1" and python_version < "3.12" +uvicorn[standard]==0.23.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +uvloop==0.17.0 ; (sys_platform != "win32" and sys_platform != "cygwin") and platform_python_implementation != "PyPy" and python_full_version >= "3.9.1" and python_version < "3.12" +virtualenv==20.24.2 ; python_full_version >= "3.9.1" and python_version < "3.12" +watchfiles==0.19.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +webencodings==0.5.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +websockets==11.0.3 ; python_full_version >= "3.9.1" and python_version < "3.12" +wheel==0.41.0 ; python_full_version >= "3.9.1" and python_version < "3.12" +xattr==0.10.1 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "darwin" +zipp==3.16.2 ; python_full_version >= "3.9.1" and python_version < "3.12" diff --git a/tests/conftest.py b/tests/conftest.py index 3f5a3a2..272027d 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,3 +1,4 @@ +from os import environ from pathlib import Path from typing import Dict, List import unittest @@ -26,6 +27,7 @@ def setUpClass(cls): cls.ppool = ProcessPool(max_workers=2) for wix in range(cls.ppool.max_workers): cls.ppool.worker_at_wix(wix) + environ["MAX_WORKERS"] = "2" @classmethod def tearDownClass(cls): From 14eac4cb9a7b10f8970ec6ef291ffd901e94b6f3 Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sun, 30 Jul 2023 14:38:14 +0900 Subject: [PATCH 05/10] dependency solution --- .gitignore | 10 +-- Dockerfile | 22 +++--- docker-compose.yml | 30 ++++++- llama_api/modules/llama_cpp.py | 2 - llama_api/server/app_settings.py | 82 +++++++++++-------- llama_api/server/routers/v1.py | 2 +- llama_api/utils/concurrency.py | 9 ++- llama_api/utils/dependency.py | 131 +++++++++++++++++++------------ llama_api/utils/errors.py | 4 +- main.py | 31 +++++++- poetry.lock | 32 ++++---- pyproject.toml | 2 +- readme.md | 23 +++++- requirements.txt | 2 +- tests/conftest.py | 16 +++- tests/test_process_pool.py | 14 +++- tests/test_server.py | 47 +++++++---- 17 files changed, 307 insertions(+), 152 deletions(-) diff --git a/.gitignore b/.gitignore index b0082d5..2b48ff4 100644 --- a/.gitignore +++ b/.gitignore @@ -2,10 +2,10 @@ models/ggml/* models/gptq/* !models/ggml/llama_cpp_models_here.txt !models/gptq/exllama_models_here.txt +repositories/ *.log -.venv -.vscode *.pyc -PRIVATE_* -repositories -tests/.venv \ No newline at end of file +.venv/ +.vscode/ +.test-venv/ +PRIVATE_* \ No newline at end of file diff --git a/Dockerfile b/Dockerfile index b7d020d..a56b85a 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,7 +1,7 @@ ### Dockerfile for Python 3.11.4 & CUDA 12.1.1 & Ubuntu 22.04 -### Approximately 7 ~ 10 minutes to build +### Approximately 5 ~ 10 minutes to build -# 필요한 CUDA 버전을 선택합니다. +# Select the required CUDA version. ARG CUDA_IMAGE="12.1.1-devel-ubuntu22.04" FROM nvidia/cuda:${CUDA_IMAGE} ENV PYTHON_VERSION="3.11.4" @@ -9,10 +9,13 @@ ENV PYTHON_VERSION_SHORT="3.11" ENV HOST 0.0.0.0 ENV PORT=8000 -# 필요한 파일들을 복사합니다. -COPY requirements.txt /tmp/requirements.txt +# Copy the necessary files. +COPY requirements.txt /app/requirements.txt +COPY pyproject.toml /app/pyproject.toml +COPY llama_api /app/llama_api -# Python 설치를 위한 종속성들을 설치하고, Python을 설치하고 설정합니다. +# Install the necessary applications, and then install Python. +# Then, install the necessary Python packages(Dependencies). RUN apt-get update && apt-get install -y --no-install-recommends \ build-essential \ zlib1g-dev \ @@ -34,11 +37,12 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ && update-alternatives --install /usr/bin/python python /usr/local/bin/python${PYTHON_VERSION_SHORT} 1 \ && update-alternatives --install /usr/bin/python3 python3 /usr/local/bin/python${PYTHON_VERSION_SHORT} 1 \ && python3 -m pip install --upgrade pip \ - && pip install --no-cache-dir -r /tmp/requirements.txt \ && rm -rf /var/lib/apt/lists/* \ && apt-get clean \ - && rm -rf /tmp/* + && rm -rf /tmp/* \ + && cd /app \ + && python3 -m llama_api.server.app_settings -# 작업 디렉토리를 설정하고, 서버를 실행합니다. +# Set the working directory and start the server. WORKDIR /app -ENTRYPOINT [ "python3", "-m", "main" "--port", "${PORT}" ] +ENTRYPOINT [ "python3", "-m", "main", "--port", "${PORT}" ] \ No newline at end of file diff --git a/docker-compose.yml b/docker-compose.yml index 03111e3..c87a432 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -2,9 +2,7 @@ version: '3' services: llama-api: - build: - context: . - dockerfile: Dockerfile + image: cosogi/llama-api:230730 entrypoint: ["python3", "-m", "main", "--port", "8000"] environment: - MAX_WORKERS=1 @@ -14,6 +12,7 @@ services: - ./model_definitions.py:/app/model_definitions.py - ./main.py:/app/main.py - ./requirements.txt:/app/requirements.txt + - ./pyproject.toml:/app/pyproject.toml ports: - 8000:8000 deploy: @@ -21,4 +20,27 @@ services: reservations: devices: - driver: nvidia - capabilities: [gpu] \ No newline at end of file + capabilities: [gpu] + +# services: + # llama-api: + # build: + # context: . + # dockerfile: Dockerfile + # entrypoint: ["python3", "-m", "main", "--port", "8000"] + # environment: + # - MAX_WORKERS=1 + # volumes: + # - ./models:/app/models + # - ./llama_api:/app/llama_api + # - ./model_definitions.py:/app/model_definitions.py + # - ./main.py:/app/main.py + # - ./requirements.txt:/app/requirements.txt + # ports: + # - 8000:8000 + # deploy: + # resources: + # reservations: + # devices: + # - driver: nvidia + # capabilities: [gpu] \ No newline at end of file diff --git a/llama_api/modules/llama_cpp.py b/llama_api/modules/llama_cpp.py index 6932689..afd1adb 100644 --- a/llama_api/modules/llama_cpp.py +++ b/llama_api/modules/llama_cpp.py @@ -16,14 +16,12 @@ convert_text_completion_to_chat, ) from ..utils.dependency import import_repository -from ..utils.llama_cpp import build_shared_lib from ..utils.logger import ApiLogger from ..utils.path import resolve_model_path_to_posix from .base import BaseCompletionGenerator logger = ApiLogger(__name__) logger.info("🦙 llama-cpp-python repository found!") -build_shared_lib(logger=logger) with import_repository( git_path="https://github.com/abetlen/llama-cpp-python", disk_path="repositories/llama_cpp", diff --git a/llama_api/server/app_settings.py b/llama_api/server/app_settings.py index a2c445a..13ef331 100644 --- a/llama_api/server/app_settings.py +++ b/llama_api/server/app_settings.py @@ -1,8 +1,5 @@ import platform -import subprocess -import sys from contextlib import asynccontextmanager -from logging import warn from os import environ from pathlib import Path from typing import Dict, Optional, Union @@ -12,37 +9,17 @@ get_poetry_executable, git_clone, install_all_dependencies, - install_poetry, + install_package, install_tensorflow, - install_torch, + install_pytorch, is_package_available, ) +from ..utils.llama_cpp import build_shared_lib from ..utils.logger import ApiLogger logger = ApiLogger(__name__) -def ensure_packages_installed(): - """Install the packages in the requirements.txt file""" - warn( - "This function is deprecated. Use `install_dependencies` instead.", - DeprecationWarning, - ) - subprocess.run( - [ - sys.executable, - "-m", - "pip", - "install", - "--trusted-host", - "pypi.python.org", - "-r", - "requirements.txt", - ], - env=environ.copy(), - ) - - def set_priority(pid: Optional[int] = None, priority: str = "high"): import platform from os import getpid @@ -81,6 +58,9 @@ def set_priority(pid: Optional[int] = None, priority: str = "high"): def initialize_before_launch( git_and_disk_paths: Optional[Dict[str, Union[str, Path]]] = None, install_packages: bool = False, + force_cuda: bool = False, + skip_pytorch_install: bool = False, + skip_tensorflow_install: bool = False, ) -> None: """Initialize the app""" @@ -90,18 +70,35 @@ def initialize_before_launch( git_clone(git_path=git_path, disk_path=disk_path) if install_packages: - # Install the dependencies + # Install all dependencies poetry = get_poetry_executable() if not poetry.exists(): + # Install poetry logger.warning(f"⚠️ Poetry not found: {poetry}") - install_poetry() - if not is_package_available("torch"): - install_torch() - if not is_package_available("tensorflow"): + install_package("poetry", force=True) + if not skip_pytorch_install or not is_package_available("torch"): + # Install pytorch + install_pytorch(force_cuda=force_cuda) + if not skip_tensorflow_install or not is_package_available( + "tensorflow" + ): + # Install tensorflow install_tensorflow() + + # Install all dependencies of our project and other repositories project_paths = [Path(".")] + list(Path("repositories").glob("*")) install_all_dependencies(project_paths=project_paths) + # Build the shared library of LLaMA C++ code + build_shared_lib(logger=logger) + else: + logger.warning( + "🏃‍♂️ Skipping package installation..." + "If any packages are missing, " + "use `--install-packages` option to install them." + ) + + # Set the priority of the process if platform.system() == "Windows": set_priority(priority="high") else: @@ -145,10 +142,17 @@ async def health(): def run( port: int, max_workers: int = 1, + install_packages: bool = False, + force_cuda: bool = False, + skip_pytorch_install: bool = False, + skip_tensorflow_install: bool = False, ) -> None: initialize_before_launch( git_and_disk_paths=Config.git_and_disk_paths, - install_packages=True, + install_packages=install_packages, + force_cuda=force_cuda, + skip_pytorch_install=skip_pytorch_install, + skip_tensorflow_install=skip_tensorflow_install, ) from uvicorn import Config as UvicornConfig @@ -164,3 +168,17 @@ def run( log_level="info", ) ).run() + + +if __name__ == "__main__": + # Git clone the repositories & install the dependencies. + # This is done before the server is launched to avoid + # the overhead of doing it when the server is running. + # Forcing CUDA is necessary when building the docker image + initialize_before_launch( + git_and_disk_paths=Config.git_and_disk_paths, + install_packages=True, + force_cuda=True, + skip_pytorch_install=False, + skip_tensorflow_install=False, + ) diff --git a/llama_api/server/routers/v1.py b/llama_api/server/routers/v1.py index d697f50..53ea12d 100644 --- a/llama_api/server/routers/v1.py +++ b/llama_api/server/routers/v1.py @@ -64,7 +64,7 @@ @dataclass class WixMetadata: key: Optional[str] = None - semaphore: Semaphore = field(default_factory=lambda: Semaphore(10)) + semaphore: Semaphore = field(default_factory=lambda: Semaphore(1)) # Worker index (wix) is used to keep track of which worker is currently diff --git a/llama_api/utils/concurrency.py b/llama_api/utils/concurrency.py index 0ae4286..44b20ee 100644 --- a/llama_api/utils/concurrency.py +++ b/llama_api/utils/concurrency.py @@ -3,13 +3,14 @@ from contextlib import contextmanager from multiprocessing.managers import SyncManager from os import environ +import platform from queue import Queue from threading import Event from typing import Callable, Dict, Optional, ParamSpec, Tuple, TypeVar from fastapi.concurrency import run_in_threadpool -from ..server.app_settings import initialize_before_launch +from ..server.app_settings import set_priority from ..utils.logger import ApiLogger from ..utils.process_pool import ProcessPool @@ -25,7 +26,11 @@ def init_process_pool(env_vars: Dict[str, str]) -> None: """Initialize the process pool, and set the environment variables for the child processes""" try: - initialize_before_launch(install_packages=False) + # Set the priority of the process + if platform.system() == "Windows": + set_priority(priority="high") + else: + set_priority(priority="normal") except Exception: pass diff --git a/llama_api/utils/dependency.py b/llama_api/utils/dependency.py index c104961..3e4c1d8 100644 --- a/llama_api/utils/dependency.py +++ b/llama_api/utils/dependency.py @@ -4,7 +4,7 @@ from contextlib import contextmanager from pathlib import Path from re import compile -from subprocess import DEVNULL, call, check_call, run +from subprocess import PIPE, check_call, run from tempfile import mkstemp from typing import List, Optional, Union from urllib.request import urlopen @@ -16,15 +16,47 @@ logger = ApiLogger(__name__) +def run_command( + command: List[str], + action: str, + name: str, + try_emoji: str = "📦", + success_emoji: str = "✅", + failure_emoji: str = "❌", + **kwargs, +) -> bool: + """Run a command and log the result. + Return True if the command was successful, False otherwise.""" + logger.info( + f"{try_emoji} {action}ing {name} with command: {' '.join(command)}" + ) + result = run(command, text=True, stdout=PIPE, stderr=PIPE, **kwargs) + if result.returncode != 0: + logger.error( + f"{failure_emoji} Failed to {action} {name}:\n" + + (result.stdout or "") + + (result.stderr or "") + ) + return False + else: + logger.info(f"{success_emoji} {name} installed.") + return True + + def is_package_available(package: str) -> bool: return True if find_spec(package) else False -def git_clone(git_path: str, disk_path: Union[Path, str]) -> None: +def git_clone(git_path: str, disk_path: Union[Path, str]) -> Optional[bool]: """Clone a git repository to a disk path.""" if not Path(disk_path).exists(): - # Clone the repository - check_call(["git", "clone", git_path, disk_path]) + return run_command( + ["git", "clone", git_path, str(disk_path)], + action="clone", + name=f"{git_path} to {disk_path}", + try_emoji="📥", + ) + return None def get_poetry_executable() -> Path: @@ -100,25 +132,27 @@ def parse_requirements( ] -def convert_toml_to_requirements_with_poetry(toml_path: Path) -> None: +def convert_toml_to_requirements_with_poetry( + toml_path: Path, + *args, + format: str = "requirements.txt", + output: str = "requirements.txt", +) -> Optional[bool]: """Convert dependencies from pyproject.toml to requirements.txt.""" + poetry = str(get_poetry_executable()) + command = [poetry, "export", "-f", format, "--output", output, *args] try: if toml_path.exists(): # Convert dependencies from pyproject.toml to requirements.txt - call( - [ - get_poetry_executable(), - "export", - "-f", - "requirements.txt", - "--output", - "requirements.txt", - "--without-hashes", - ], + return run_command( + command, + action="convert", + name="pyproject.toml to requirements.txt", + try_emoji="🔄", cwd=toml_path.parent, ) except Exception: - pass + return None @contextmanager @@ -137,19 +171,32 @@ def import_repository(git_path: str, disk_path: str): sys.path.remove(str(disk_path)) -def install_poetry(): +def install_package(package: str, force: bool = False) -> bool: + """Install a package with pip.""" + if not force and is_package_available(package): + return True + return run_command( + [sys.executable, "-m", "pip", "install", package], + action="install", + name=package, + ) + + +def install_poetry() -> bool: """Install poetry.""" logger.info("📦 Installing poetry...") - check_call( - [sys.executable, "-m", "pip", "install", "poetry"], stdout=DEVNULL + return run_command( + [sys.executable, "-m", "pip", "install", "poetry"], + action="install", + name="poetry", ) - logger.info("✅ Poetry installed.") -def install_torch( +def install_pytorch( torch_version: str = Config.torch_version, cuda_version: Optional[str] = Config.cuda_version, source: Optional[str] = Config.torch_source, + force_cuda: bool = False, ) -> bool: """Try to install Pytorch. If CUDA is available, install the CUDA version of torch. @@ -161,13 +208,14 @@ def install_torch( Defaults to Config.cuda_version. source (Optional[str]): The source to install torch from. Defaults to Config.torch_source. + force_cuda (bool): Whether to force install the CUDA version of torch. Returns: - bool: True if CUDA is installed, False otherwise.""" + bool: True if Pytorch is installed successfully, else False.""" pip_install = [sys.executable, "-m", "pip", "install"] fallback_cuda_version = Config.cuda_version # If a source is specified, and if CUDA is available, # install the CUDA version of torch - if source and get_cuda_version(): + if force_cuda or (source and get_cuda_version()): # Check if the CUDA version of torch is available. # If not, fallback to `Config.cuda_version`. cuda_version = ( @@ -194,16 +242,13 @@ def install_torch( pip_install.append(f"torch{torch_version}") # Install torch - logger.info(f"📦 Installing PyTorch with command: {' '.join(pip_install)}") - check_call(pip_install) - logger.info("✅ PyTorch installed.") - return cuda_version is not None + return run_command(pip_install, action="install", name="PyTorch") def install_tensorflow( tensorflow_version: str = Config.tensorflow_version, source: Optional[str] = None, -) -> None: +) -> bool: """Try to install TensorFlow. Args: @@ -211,6 +256,8 @@ def install_tensorflow( Defaults to Config.tensorflow_version. source (Optional[str]): The source to install TensorFlow from. If not specified, TensorFlow will be installed from PyPi. + Returns: + bool: True if TensorFlow is installed successfully, else False. """ pip_install = [ sys.executable, @@ -225,23 +272,19 @@ def install_tensorflow( pip_install += ["-f", source] # Install TensorFlow - logger.info( - f"📦 Installing TensorFlow with command: {' '.join(pip_install)}" - ) - check_call(pip_install) - logger.info("✅ TensorFlow installed.") + return run_command(pip_install, action="install", name="TensorFlow") def install_all_dependencies( project_paths: Optional[Union[List[Path], List[str]]] = None, -) -> None: +) -> Optional[bool]: """Install every dependencies.""" pip_install = [sys.executable, "-m", "pip", "install", "-r"] for project_path in project_paths or []: project_path = Path(project_path).resolve() logger.info(f"📦 Installing dependencies for {project_path}...") convert_toml_to_requirements_with_poetry( - project_path / "pyproject.toml" + project_path / "pyproject.toml", "--without-hashes" ) requirements_path = project_path / "requirements.txt" if not requirements_path.exists(): @@ -249,22 +292,12 @@ def install_all_dependencies( f"⚠️ Could not find requirements.txt in {project_path}." ) continue - result = run( - pip_install + [requirements_path], - text=True, - stdout=DEVNULL, - stderr=DEVNULL, + return run_command( + pip_install + [requirements_path.as_posix()], + action="install", + name="dependencies", ) - if result.stderr or result.returncode != 0: - logger.error( - "❌ Error installing dependencies: " - + (result.stdout or "") - + (result.stderr or "") - ) - else: - logger.info("✅ Dependencies installed!") - def remove_all_dependencies(): """Remove all dependencies. diff --git a/llama_api/utils/errors.py b/llama_api/utils/errors.py index 2a5d21b..6e52cc1 100644 --- a/llama_api/utils/errors.py +++ b/llama_api/utils/errors.py @@ -106,7 +106,7 @@ async def custom_route_handler(request: Request) -> Response: try: return await original_route_handler(request) except (OSError, MemoryError) as e: - logger.exception(f"Exception in llama-cpp: {e}") + logger.exception(f"Exception in llama api: {e}") if isinstance(e, MemoryError): error_msg = str(e) else: @@ -124,7 +124,7 @@ async def custom_route_handler(request: Request) -> Response: 500, ) except Exception as e: - logger.exception(f"Exception in llama-cpp: {e}") + logger.exception(f"Exception in llama api: {e}") json_body = await request.json() try: diff --git a/main.py b/main.py index 8456c5d..39687cb 100644 --- a/main.py +++ b/main.py @@ -8,17 +8,44 @@ "--port", type=int, default=8000, - help="Port to run the server on", + help="Port to run the server on; default is 8000", ) parser.add_argument( "--max-workers", type=int, default=1, - help="Maximum number of process workers to run", + help="Maximum number of process workers to run; default is 1", + ) + parser.add_argument( + "--install-pkgs", + action="store_true", + help="Install all required packages before running the server", + ) + parser.add_argument( + "--force-cuda", + action="store_true", + help=( + "Force CUDA version of pytorch to be used" + "when installing pytorch. e.g. torch==2.0.1+cu118" + ), + ) + parser.add_argument( + "--skip-torch-install", + action="store_true", + help="Skip installing pytorch, if `install-packages` is set", + ) + parser.add_argument( + "--skip-tf-install", + action="store_true", + help="Skip installing tensorflow, if `install-packages` is set", ) args = parser.parse_args() run( port=args.port, max_workers=args.max_workers, + install_packages=args.install_pkgs, + force_cuda=args.force_cuda, + skip_pytorch_install=args.skip_torch_install, + skip_tensorflow_install=args.skip_tf_install, ) diff --git a/poetry.lock b/poetry.lock index 8ce5cf5..3acd800 100644 --- a/poetry.lock +++ b/poetry.lock @@ -592,19 +592,19 @@ testing = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "diff-cover (>=7.5)", "p [[package]] name = "flake8" -version = "6.0.0" +version = "6.1.0" description = "the modular source code checker: pep8 pyflakes and co" optional = false python-versions = ">=3.8.1" files = [ - {file = "flake8-6.0.0-py2.py3-none-any.whl", hash = "sha256:3833794e27ff64ea4e9cf5d410082a8b97ff1a06c16aa3d2027339cd0f1195c7"}, - {file = "flake8-6.0.0.tar.gz", hash = "sha256:c61007e76655af75e6785a931f452915b371dc48f56efd765247c8fe68f2b181"}, + {file = "flake8-6.1.0-py2.py3-none-any.whl", hash = "sha256:ffdfce58ea94c6580c77888a86506937f9a1a227dfcd15f245d694ae20a6b6e5"}, + {file = "flake8-6.1.0.tar.gz", hash = "sha256:d5b3857f07c030bdb5bf41c7f53799571d75c4491748a3adcd47de929e34cd23"}, ] [package.dependencies] mccabe = ">=0.7.0,<0.8.0" -pycodestyle = ">=2.10.0,<2.11.0" -pyflakes = ">=3.0.0,<3.1.0" +pycodestyle = ">=2.11.0,<2.12.0" +pyflakes = ">=3.1.0,<3.2.0" [[package]] name = "fsspec" @@ -1673,13 +1673,13 @@ files = [ [[package]] name = "pycodestyle" -version = "2.10.0" +version = "2.11.0" description = "Python style guide checker" optional = false -python-versions = ">=3.6" +python-versions = ">=3.8" files = [ - {file = "pycodestyle-2.10.0-py2.py3-none-any.whl", hash = "sha256:8a4eaf0d0495c7395bdab3589ac2db602797d76207242c17d470186815706610"}, - {file = "pycodestyle-2.10.0.tar.gz", hash = "sha256:347187bdb476329d98f695c213d7295a846d1152ff4fe9bacb8a9590b8ee7053"}, + {file = "pycodestyle-2.11.0-py2.py3-none-any.whl", hash = "sha256:5d1013ba8dc7895b548be5afb05740ca82454fd899971563d2ef625d090326f8"}, + {file = "pycodestyle-2.11.0.tar.gz", hash = "sha256:259bcc17857d8a8b3b4a2327324b79e5f020a13c16074670f9c8c8f872ea76d0"}, ] [[package]] @@ -1842,13 +1842,13 @@ python-dotenv = ">=0.21.0" [[package]] name = "pyflakes" -version = "3.0.1" +version = "3.1.0" description = "passive checker of Python programs" optional = false -python-versions = ">=3.6" +python-versions = ">=3.8" files = [ - {file = "pyflakes-3.0.1-py2.py3-none-any.whl", hash = "sha256:ec55bf7fe21fff7f1ad2f7da62363d749e2a470500eab1b555334b67aa1ef8cf"}, - {file = "pyflakes-3.0.1.tar.gz", hash = "sha256:ec8b276a6b60bd80defed25add7e439881c19e64850afd9b346283d4165fd0fd"}, + {file = "pyflakes-3.1.0-py2.py3-none-any.whl", hash = "sha256:4132f6d49cb4dae6819e5379898f2b8cce3c5f23994194c24b77d5da2e36f774"}, + {file = "pyflakes-3.1.0.tar.gz", hash = "sha256:a0aae034c444db0071aa077972ba4768d40c830d9539fd45bf4cd3f8f6992efc"}, ] [[package]] @@ -2322,13 +2322,13 @@ idna2008 = ["idna"] [[package]] name = "rich" -version = "13.4.2" +version = "13.5.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false python-versions = ">=3.7.0" files = [ - {file = "rich-13.4.2-py3-none-any.whl", hash = "sha256:8f87bc7ee54675732fa66a05ebfe489e27264caeeff3728c945d25971b6485ec"}, - {file = "rich-13.4.2.tar.gz", hash = "sha256:d653d6bccede5844304c605d5aac802c7cf9621efd700b46c7ec2b51ea914898"}, + {file = "rich-13.5.0-py3-none-any.whl", hash = "sha256:996670a7618ccce27c55ba6fc0142e6e343773e11d34c96566a17b71b0e6f179"}, + {file = "rich-13.5.0.tar.gz", hash = "sha256:62c81e88dc078d2372858660e3d5566746870133e51321f852ccc20af5c7e7b2"}, ] [package.dependencies] diff --git a/pyproject.toml b/pyproject.toml index d39847c..fa8d41b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "llama-api" -version = "0.1.0" +version = "0.1.1" description = "An OpenAI-like LLaMA inference API" authors = ["c0sogi "] license = "MIT" diff --git a/readme.md b/readme.md index e7824a0..4a9c950 100644 --- a/readme.md +++ b/readme.md @@ -14,7 +14,7 @@ You can use this server to run the models in your own application, or use it as - Due to the internal operation of the process pool, both parallelism and concurrency are secured. The `--max-workers $NUM_WORKERS` option needs to be provided when starting the server. This, however, only applies when requests are made simultaneously for different models. If requests are made for the same model, they will wait until a slot becomes available due to the semaphore. 3. **Auto Dependency Installation** - - The project automatically installs the required dependencies, including **pytorch** and **tensorflow**, when the server is started. This is done by checking the `pyproject.toml` or `requirements.txt` file in the root directory of this project or other repositories. `pyproject.toml` will be parsed into `requirements.txt` with `poetry`. If you want to add more dependencies, simply add them to the file. + - The project automatically do git clones and installs the required dependencies, including **pytorch** and **tensorflow**, when the server is started. This is done by checking the `pyproject.toml` or `requirements.txt` file in the root directory of this project or other repositories. `pyproject.toml` will be parsed into `requirements.txt` with `poetry`. If you want to add more dependencies, simply add them to the file. ## Before you start @@ -64,11 +64,26 @@ Define llama.cpp & exllama models in `model_definitions.py`. You can define all ## How to run server -All required packages will be installed automatically. -Simply run the following command: +All required packages will be installed automatically with this command. ```bash -python -m main --port 8000 +python -m main --install-pkgs +``` + +If you already have all required packages installed, you can skip the installation with this command. +```bash +python -m main +``` +Options: +```b + -h, --help show this help message and exit + --port PORT Port to run the server on; default is 8000 + --max-workers MAX_WORKERS + Maximum number of process workers to run; default is 1 + --install-pkgs Install all required packages before running the server + --force-cuda Force CUDA version of pytorch to be used when installing pytorch. e.g. torch==2.0.1+cu118 + --skip-torch-install Skip installing pytorch, if `install-pkgs` is set + --skip-tf-install Skip installing tensorflow, if `install-pkgs` is set ``` ## Usage: Text Completion diff --git a/requirements.txt b/requirements.txt index 321cb67..29377de 100644 --- a/requirements.txt +++ b/requirements.txt @@ -40,7 +40,7 @@ orjson==3.9.2 ; python_full_version >= "3.9.1" and python_version < "3.12" packaging==23.1 ; python_full_version >= "3.9.1" and python_version < "3.12" pexpect==4.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" pkginfo==1.9.6 ; python_full_version >= "3.9.1" and python_version < "3.12" -platformdirs==3.9.1 ; python_full_version >= "3.9.1" and python_version < "3.12" +platformdirs==3.10.0 ; python_full_version >= "3.9.1" and python_version < "3.12" poetry-core==1.6.1 ; python_full_version >= "3.9.1" and python_version < "3.12" poetry-plugin-export==1.4.0 ; python_full_version >= "3.9.1" and python_version < "3.12" poetry==1.5.1 ; python_full_version >= "3.9.1" and python_version < "3.12" diff --git a/tests/conftest.py b/tests/conftest.py index 272027d..96c729a 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,12 +1,17 @@ +import importlib +import unittest from os import environ from pathlib import Path -from typing import Dict, List -import unittest +from typing import TYPE_CHECKING, Dict, List, Type # noqa: F401 from llama_api.server.app_settings import create_app_llama_cpp +from llama_api.shared.config import Config from llama_api.utils.concurrency import pool as concurrency_pool +from llama_api.utils.dependency import install_package, is_package_available from llama_api.utils.process_pool import ProcessPool -from llama_api.shared.config import Config + +if TYPE_CHECKING: + from httpx import AsyncClient # noqa: F401 class TestLlamaAPI(unittest.TestCase): @@ -23,6 +28,11 @@ class TestLlamaAPI(unittest.TestCase): @classmethod def setUpClass(cls): + if not is_package_available("httpx"): + install_package("httpx") + cls.AsyncClient = importlib.import_module( + "httpx" + ).AsyncClient # type: Type[AsyncClient] cls.app = create_app_llama_cpp() cls.ppool = ProcessPool(max_workers=2) for wix in range(cls.ppool.max_workers): diff --git a/tests/test_process_pool.py b/tests/test_process_pool.py index daa4710..e14cfed 100644 --- a/tests/test_process_pool.py +++ b/tests/test_process_pool.py @@ -3,9 +3,10 @@ from functools import partial from os import getpid from time import sleep, time +import unittest from llama_api.utils.concurrency import ( - ProcessPool, # noqa: E402 + ProcessPool, awake_all_pool_workers, pool, run_in_processpool, @@ -21,8 +22,11 @@ def simple_job(sleep_time: float) -> float: return sleep_time -class TestProcessPool(TestLlamaAPI): +class TestProcessPool(TestLlamaAPI, unittest.IsolatedAsyncioTestCase): + """Test that the process pool works as expected.""" + def test_process_pool(self) -> None: + """Test the basic functionality of the process pool.""" # We're recording the start time start_time = time() @@ -48,6 +52,7 @@ def test_process_pool(self) -> None: self.assertTrue(result1 == result2 == 1) def test_process_pool_with_wix(self) -> None: + """Test the worker-index-based scheduling functionality of the process pool.""" # We're recording the start time start_time = time() @@ -73,6 +78,7 @@ def test_process_pool_with_wix(self) -> None: self.assertTrue(result1 == result2 == 1) async def test_process_pool_async(self): + """Test the basic functionality of the process pool in an async context.""" try: awake_all_pool_workers() sleep(2) # Give the pool some time to start up @@ -97,6 +103,8 @@ async def test_process_pool_async(self): _pool.join() async def test_process_pool_with_wix_async(self): + """Test the worker-index-based scheduling functionality of the process pool + in an async context.""" try: awake_all_pool_workers() sleep(2) # Give the pool some time to start up @@ -121,6 +129,7 @@ async def test_process_pool_with_wix_async(self): _pool.join() def test_process_pool_graceful_shutdown(self): + """Test the graceful shutdown of the process pool.""" timeout = None with ProcessPool(max_workers=2) as executor: f1 = executor.submit(simple_job, 1) @@ -133,6 +142,7 @@ def test_process_pool_graceful_shutdown(self): print("Jobs done:", result1, result2) def test_process_pool_map(self): + """Test the map functionality of the process pool.""" timeout = 3.0 with ProcessPool(max_workers=4) as executor: results = iter( diff --git a/tests/test_server.py b/tests/test_server.py index 0ef84cb..010ed30 100644 --- a/tests/test_server.py +++ b/tests/test_server.py @@ -1,7 +1,5 @@ import re from asyncio import gather -from pathlib import Path -import sys from typing import ( Awaitable, Dict, @@ -14,12 +12,9 @@ ) import unittest from fastapi.testclient import TestClient - -from httpx import AsyncClient, Response from tests.conftest import TestLlamaAPI -sys.path.insert(0, Path(__file__).parent.parent.as_posix()) -from llama_api.schemas.api import ( # noqa: E402 +from llama_api.schemas.api import ( ModelList, ChatCompletionChoice, CompletionChoice, @@ -30,7 +25,11 @@ class TestServer(TestLlamaAPI, unittest.IsolatedAsyncioTestCase): + """Test the FastAPI server + with basic health checks & LLM completion requests (with concurrency)""" + def test_health(self): + """Test the health endpoint""" with TestClient(app=self.app) as client: response = client.get( "/health", @@ -38,11 +37,21 @@ def test_health(self): ) self.assertEqual(response.status_code, 200) + def test_v1_models(self): + """Test the v1/models endpoint""" + with TestClient(app=self.app) as client: + response = client.get( + "/v1/models", + headers={"Content-Type": "application/json"}, + ) + self.assertEqual(response.status_code, 200) + @unittest.skipIf( not TestLlamaAPI.ggml_path.exists(), reason=f"No model in {TestLlamaAPI.ggml_path}", ) def test_llama_cpp(self): + """Test the Llama CPP model completion endpoints""" self._request_completion( model_names=(self.ggml_model,), endpoints="completions" ) @@ -55,6 +64,7 @@ def test_llama_cpp(self): reason=f"No model in{TestLlamaAPI.gptq_path}", ) def test_exllama(self): + """Test the ExLLama model completion endpoints""" self._request_completion( model_names=(self.gptq_model,), endpoints="completions" ) @@ -67,6 +77,7 @@ def test_exllama(self): reason=f"No model in {TestLlamaAPI.ggml_path}", ) async def test_llama_cpp_concurrency(self): + """Test the Llama CPP model completion endpoints with concurrency""" model_names: Tuple[str, ...] = (self.ggml_model, self.ggml_model) await self._arequest_completion( model_names=model_names, endpoints="completions" @@ -77,6 +88,7 @@ async def test_llama_cpp_concurrency(self): reason=f"No model in {TestLlamaAPI.gptq_path}", ) async def test_exllama_concurrency(self): + """Test the ExLLama model completion endpoints with concurrency""" model_names: Tuple[str, ...] = (self.gptq_model, self.gptq_model) await self._arequest_completion( model_names=model_names, endpoints="completions" @@ -88,6 +100,7 @@ async def test_exllama_concurrency(self): f"No model in {TestLlamaAPI.ggml_path} or {TestLlamaAPI.gptq_path}", ) async def test_llama_mixed_concurrency(self): + """Test the Llama CPP & ExLLama model completion endpoints with concurrency""" model_names: Tuple[str, ...] = (self.ggml_model, self.gptq_model) await self._arequest_completion( model_names=model_names, endpoints="completions" @@ -103,7 +116,7 @@ async def _arequest_completion( if isinstance(endpoints, str) else endpoints ) - async with AsyncClient( + async with self.AsyncClient( app=self.app, base_url="http://localhost", timeout=None ) as client: # Get models using the API @@ -115,8 +128,8 @@ async def _arequest_completion( if model_name in model_data["id"]: model = re.sub(r"\(.*\)", "", model_data["id"]).strip() break - assert model, f"Model {model_name} not found" - models.append(model) + self.assertTrue(model, f"Model {model_name} not found") + models.append(str(model)) # Submit requests to the API tasks: List[Awaitable] = [] @@ -139,10 +152,10 @@ async def _arequest_completion( ) # Wait for responses - cmpl_resps: List[Response] = await gather(*tasks) + cmpl_resps: List = await gather(*tasks) results: List[str] = [] for model, cmpl_resp in zip(models, cmpl_resps): - assert cmpl_resp.status_code == 200 + self.assertEqual(cmpl_resp.status_code, 200) choice: Union[ CompletionChoice, ChatCompletionChoice ] = cmpl_resp.json()["choices"][0] @@ -156,7 +169,7 @@ async def _arequest_completion( f"Result of {model}:", results[-1], end="\n\n", flush=True ) - assert len(results) == len(models) + self.assertEqual(len(results), len(models)) def _request_completion( self, @@ -178,11 +191,11 @@ def _request_completion( if model_name in model_data["id"]: model = re.sub(r"\(.*\)", "", model_data["id"]).strip() break - assert model, f"Model {model_name} not found" - models.append(model) + self.assertTrue(model, f"Model {model_name} not found") + models.append(str(model)) # Submit requests to the API - cmpl_resps: List[Response] = [] + cmpl_resps: List = [] for model, endpoint in zip(models, _endpoints): request = {"model": model, "max_tokens": 50} request_message = ( @@ -204,7 +217,7 @@ def _request_completion( # Wait for responses results: List[str] = [] for model, cmpl_resp in zip(models, cmpl_resps): - assert cmpl_resp.status_code == 200 + self.assertEqual(cmpl_resp.status_code, 200) choice: Union[ CompletionChoice, ChatCompletionChoice ] = cmpl_resp.json()["choices"][0] @@ -218,7 +231,7 @@ def _request_completion( f"Result of {model}:", results[-1], end="\n\n", flush=True ) - assert len(results) == len(models) + self.assertEqual(len(results), len(models)) def _union(*dicts: Dict) -> Dict: From b77a709c4734d6af17885994b9cd92354d1de507 Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sun, 30 Jul 2023 15:24:58 +0900 Subject: [PATCH 06/10] fixed typos --- llama_api/utils/dependency.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/llama_api/utils/dependency.py b/llama_api/utils/dependency.py index 3e4c1d8..7a2e3db 100644 --- a/llama_api/utils/dependency.py +++ b/llama_api/utils/dependency.py @@ -39,7 +39,7 @@ def run_command( ) return False else: - logger.info(f"{success_emoji} {name} installed.") + logger.info(f"{success_emoji} Successfully {name} {action}ed.") return True @@ -280,6 +280,7 @@ def install_all_dependencies( ) -> Optional[bool]: """Install every dependencies.""" pip_install = [sys.executable, "-m", "pip", "install", "-r"] + result = True for project_path in project_paths or []: project_path = Path(project_path).resolve() logger.info(f"📦 Installing dependencies for {project_path}...") @@ -292,11 +293,12 @@ def install_all_dependencies( f"⚠️ Could not find requirements.txt in {project_path}." ) continue - return run_command( + result &= run_command( pip_install + [requirements_path.as_posix()], action="install", name="dependencies", ) + return result def remove_all_dependencies(): From a9c675d031e1fc4055c68efd38f921b207116bfe Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sun, 30 Jul 2023 16:49:15 +0900 Subject: [PATCH 07/10] CI workflow --- .github/workflows/ci.yml | 52 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 52 insertions(+) create mode 100644 .github/workflows/ci.yml diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..8dae7ce --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,52 @@ +# .github/workflows/ci.yml + +name: Continuous Integration + +on: + push: + branches: + - master + pull_request: + branches: + - master + +jobs: + build-and-test: + name: Build and Test + runs-on: ${{ matrix.os }} + strategy: + matrix: + os: [ubuntu-latest, windows-latest, macos-latest] + python-version: ['3.9', '3.10', '3.11'] + + steps: + - name: Check out code + uses: actions/checkout@v2 + + - name: Set up Python + uses: actions/setup-python@v2 + with: + python-version: ${{ matrix.python-version }} + + - name: Execute server & install minimum dependencies + run: python -m main --install-pkgs --skip-tf-install --skip-torch-install + + - name: Run tests + run: python -m unittest discover tests + + build-release: + needs: build-and-test + if: ${{ success() }} + name: Create Release + runs-on: ubuntu-latest + steps: + - name: Create Release + id: create_release + uses: actions/create-release@v1 + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + with: + tag_name: ${{ github.sha }} + release_name: master-${{ github.sha }} + draft: false + prerelease: false From 2ebe89ff77c4698fd0eaba7142a309951fe211dc Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sun, 30 Jul 2023 19:09:47 +0900 Subject: [PATCH 08/10] use binary cmake instead of scikit-build --- llama_api/utils/dependency.py | 38 +++++++---- llama_api/utils/llama_cpp.py | 119 ++++++++++++++++++---------------- pyproject.toml | 2 +- requirements.txt | 4 -- 4 files changed, 90 insertions(+), 73 deletions(-) diff --git a/llama_api/utils/dependency.py b/llama_api/utils/dependency.py index 7a2e3db..f94fbb2 100644 --- a/llama_api/utils/dependency.py +++ b/llama_api/utils/dependency.py @@ -23,24 +23,36 @@ def run_command( try_emoji: str = "📦", success_emoji: str = "✅", failure_emoji: str = "❌", + verbose: bool = True, **kwargs, ) -> bool: """Run a command and log the result. Return True if the command was successful, False otherwise.""" - logger.info( - f"{try_emoji} {action}ing {name} with command: {' '.join(command)}" - ) - result = run(command, text=True, stdout=PIPE, stderr=PIPE, **kwargs) - if result.returncode != 0: - logger.error( - f"{failure_emoji} Failed to {action} {name}:\n" - + (result.stdout or "") - + (result.stderr or "") - ) + try: + if verbose: + logger.info( + f"{try_emoji} {action}ing {name} with command: " + f"{' '.join(command)}" + ) + result = run(command, text=True, stdout=PIPE, stderr=PIPE, **kwargs) + if result.returncode != 0: + if verbose: + logger.error( + f"{failure_emoji} Failed to {action} {name}:\n" + + (result.stdout or "") + + (result.stderr or "") + ) + return False + else: + if verbose: + logger.info(f"{success_emoji} Successfully {name} {action}ed.") + return True + except Exception as e: + if verbose: + logger.error( + f"{failure_emoji} Failed to {action} {name}:\n" + str(e) + ) return False - else: - logger.info(f"{success_emoji} Successfully {name} {action}ed.") - return True def is_package_available(package: str) -> bool: diff --git a/llama_api/utils/llama_cpp.py b/llama_api/utils/llama_cpp.py index b23cbfb..b05505d 100644 --- a/llama_api/utils/llama_cpp.py +++ b/llama_api/utils/llama_cpp.py @@ -1,16 +1,18 @@ -from contextlib import contextmanager -from os import chdir, environ, getcwd -from shutil import copy +import shutil import subprocess import sys +from contextlib import contextmanager from logging import Logger, getLogger +from os import chdir, environ, getcwd from pathlib import Path -from typing import List, Optional +from typing import List, Optional, Union + +from ..utils.dependency import install_package, run_command # You can set the CMAKE_ARGS environment variable to change the cmake args. # cuBLAS is default to ON, # but if it fails to build, fall back to the default settings (CPU only) -CMAKE_ARGS: str = "-DLLAMA_STATIC=Off -DBUILD_SHARED_LIBS=ON -DLLAMA_CUBLAS=ON" +CMAKE_ARGS: str = "-DBUILD_SHARED_LIBS=ON -DLLAMA_CUBLAS=ON" LIB_BASE_NAME: str = "llama" REPOSITORY_FOLDER: str = "repositories" @@ -87,29 +89,59 @@ def _get_lib_paths(base_path: Path) -> List[Path]: return [base_path / lib for lib in _get_libs()] -def _copy_skbuild_libs_to_target( - cmake_dir: Path, target_dir: Path -) -> List[Path]: +def _copy_libs_to_target(cmake_dir: Path, target_dir: Path) -> None: + # Copy the built libs to the target folder + for lib_name in _get_libs(): + lib = cmake_dir / "build" / "bin" / "Release" / lib_name + if lib.exists(): + print(f"~~~ Found shared library: {lib}") + shutil.copy(lib, target_dir) + else: + print(f"~~~ Library {lib_name} not found") + + +def _cmake( + cmake_dir: Path, cmake_args: Union[str, List[str]], target_dir: Path +) -> None: + # Run cmake to build the shared lib + env = environ.copy() + build_dir = cmake_dir / "build" + if isinstance(cmake_args, str): + cmake_args = cmake_args.split(" ") + if "-DBUILD_SHARED_LIBS=ON" not in cmake_args: + cmake_args.append("-DBUILD_SHARED_LIBS=ON") + if build_dir.exists(): + # If the build folder exists, delete it + shutil.rmtree(build_dir) + + # Create the build folder + build_dir.mkdir(exist_ok=True) + + # Check if cmake is installed + if not run_command( + ["cmake"], action="check", name="cmake", env=env, verbose=False + ): + # If cmake is not installed, try to install it + install_package("cmake", force=True) + + # Build the shared lib + run_command( + ["cmake", *cmake_args, ".."], + action="build", + name="llama.cpp shared lib", + cwd=build_dir, + env=env, + ) + run_command( + ["cmake", "--build", ".", "--config", "Release"], + action="build", + name="llama.cpp shared lib", + cwd=build_dir, + env=env, + ) + # Copy the built libs to the target folder - source_libs: Optional[List[Path]] = None - for dir in (cmake_dir / "_skbuild").glob("*"): - if dir.is_dir(): - print(f"~~~ Checking {dir}") - source_libs = [ - source_lib - for source_lib in (dir / "cmake-install" / MODULE_NAME).glob( - "*" - ) - if source_lib.name in _get_libs() - ] - if source_libs: - print(f"~~~ Found {source_libs}") - break - assert source_libs is not None, "Could not find build libs" - - for source_lib in source_libs: - copy(source_lib, target_dir) - return source_libs + _copy_libs_to_target(cmake_dir=cmake_dir, target_dir=target_dir) def build_shared_lib( @@ -129,34 +161,11 @@ def build_shared_lib( if force_cmake or not any( lib_path.exists() for lib_path in _get_lib_paths(MODULE_PATH) ): - target_dir = MODULE_PATH - # Build the libs - with _temporary_change_cwd(PROJECT_PATH): - # Try to build the lib with cmake - environ["FORCE_CMAKE"] = "1" - if environ.get("CMAKE_ARGS") is None: - environ["CMAKE_ARGS"] = CMAKE_ARGS - - logger.info( - f"🦙 Building llama.cpp libs with {environ['CMAKE_ARGS']}" - ) - subprocess.run([sys.executable, "-m", "pip", "install", "."]) - - # Move the built libs to the target folder - source_libs = _copy_skbuild_libs_to_target( - cmake_dir=PROJECT_PATH, target_dir=target_dir + # Try to build the lib with cmake + cmake_dir = VENDOR_PATH + cmake_args = environ.get("CMAKE_ARGS", CMAKE_ARGS) + _cmake( + cmake_dir=cmake_dir, cmake_args=cmake_args, target_dir=MODULE_PATH ) - logger.info(f"🦙 llama.cpp libs built with `{environ['CMAKE_ARGS']}`") - for source_lib in source_libs: - logger.info(f"~~~ Moved {source_lib.name} to {target_dir}") return - - -if __name__ == "__main__": - root_path = Path(__file__).parent.parent.parent - sys.path.insert(0, root_path.as_posix()) - - from llama_api.utils.logger import ApiLogger - - build_shared_lib(force_cmake=True, logger=ApiLogger(__name__)) diff --git a/pyproject.toml b/pyproject.toml index fa8d41b..4dd6e71 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -19,7 +19,7 @@ fastapi = "^0.100" orjson = "^3.9" sse-starlette = "^1.6" psutil = "^5.9" -scikit-build = "^0.17.6" +cmake = {version = "^3.27.0", markers = "sys_platform == 'win32'"} filelock = "^3.12" transformers = "^4.31.0" tensorflow-hub = "^0.14" diff --git a/requirements.txt b/requirements.txt index 29377de..76b0328 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,7 +13,6 @@ crashtest==0.4.1 ; python_full_version >= "3.9.1" and python_version < "3.12" cryptography==41.0.2 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "linux" diskcache==5.6.1 ; python_full_version >= "3.9.1" and python_version < "3.12" distlib==0.3.7 ; python_full_version >= "3.9.1" and python_version < "3.12" -distro==1.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" dulwich==0.21.5 ; python_full_version >= "3.9.1" and python_version < "3.12" exceptiongroup==1.1.2 ; python_full_version >= "3.9.1" and python_version < "3.11" fastapi==0.100.1 ; python_full_version >= "3.9.1" and python_version < "3.12" @@ -62,10 +61,8 @@ requests-toolbelt==1.0.0 ; python_full_version >= "3.9.1" and python_version < " requests==2.31.0 ; python_full_version >= "3.9.1" and python_version < "3.12" rpds-py==0.9.2 ; python_full_version >= "3.9.1" and python_version < "3.12" safetensors==0.3.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -scikit-build==0.17.6 ; python_full_version >= "3.9.1" and python_version < "3.12" secretstorage==3.3.3 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "linux" sentencepiece==0.1.99 ; python_full_version >= "3.9.1" and python_version < "3.12" -setuptools==68.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" shellingham==1.5.0.post1 ; python_full_version >= "3.9.1" and python_version < "3.12" six==1.16.0 ; python_full_version >= "3.9.1" and python_version < "3.12" sniffio==1.3.0 ; python_full_version >= "3.9.1" and python_version < "3.12" @@ -86,6 +83,5 @@ virtualenv==20.24.2 ; python_full_version >= "3.9.1" and python_version < "3.12" watchfiles==0.19.0 ; python_full_version >= "3.9.1" and python_version < "3.12" webencodings==0.5.1 ; python_full_version >= "3.9.1" and python_version < "3.12" websockets==11.0.3 ; python_full_version >= "3.9.1" and python_version < "3.12" -wheel==0.41.0 ; python_full_version >= "3.9.1" and python_version < "3.12" xattr==0.10.1 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "darwin" zipp==3.16.2 ; python_full_version >= "3.9.1" and python_version < "3.12" From 5708e3aa8f5324615b51a6732a4a50beef74e30f Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sun, 30 Jul 2023 19:22:24 +0900 Subject: [PATCH 09/10] make build release with short name --- .github/workflows/ci.yml | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 8dae7ce..2c73edc 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -40,13 +40,16 @@ jobs: name: Create Release runs-on: ubuntu-latest steps: + - name: Shorten SHA + id: shorten_sha + run: echo "::set-output name=sha::$(echo ${GITHUB_SHA:0:7})" - name: Create Release id: create_release uses: actions/create-release@v1 env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} with: - tag_name: ${{ github.sha }} - release_name: master-${{ github.sha }} + tag_name: ${{ steps.shorten_sha.outputs.sha }} + release_name: master-${{ steps.shorten_sha.outputs.sha }} draft: false - prerelease: false + prerelease: false \ No newline at end of file From 6a0246527e98d0837434af0760241f888b0d4c89 Mon Sep 17 00:00:00 2001 From: c0sogi Date: Sun, 30 Jul 2023 19:51:03 +0900 Subject: [PATCH 10/10] ci fail resolve --- .github/workflows/ci.yml | 16 +-- Dockerfile | 2 +- llama_api/schemas/function_calling.py | 3 +- llama_api/server/app_settings.py | 62 +++++--- llama_api/server/pools/llama.py | 6 +- llama_api/shared/config.py | 2 +- llama_api/utils/concurrency.py | 16 ++- llama_api/utils/dependency.py | 66 +++++++-- llama_api/utils/errors.py | 2 +- llama_api/utils/lazy_imports.py | 4 +- llama_api/utils/llama_cpp.py | 107 +++++++++++--- llama_api/utils/process_pool.py | 16 ++- main.py | 4 +- model_definitions.py | 13 +- poetry.lock | 194 +++++++++++++------------- pyproject.toml | 4 +- readme.md | 2 +- requirements.txt | 177 +++++++++++------------ tests/conftest.py | 14 +- tests/test_ci.py | 24 ---- tests/test_process_pool.py | 187 +++++++------------------ tests/test_server.py | 47 ++++++- 22 files changed, 525 insertions(+), 443 deletions(-) delete mode 100644 tests/test_ci.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 2c73edc..b70babc 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -1,5 +1,3 @@ -# .github/workflows/ci.yml - name: Continuous Integration on: @@ -17,7 +15,7 @@ jobs: strategy: matrix: os: [ubuntu-latest, windows-latest, macos-latest] - python-version: ['3.9', '3.10', '3.11'] + python-version: ['3.8', '3.9', '3.10', '3.11'] steps: - name: Check out code @@ -28,15 +26,15 @@ jobs: with: python-version: ${{ matrix.python-version }} - - name: Execute server & install minimum dependencies - run: python -m main --install-pkgs --skip-tf-install --skip-torch-install - - - name: Run tests - run: python -m unittest discover tests + - name: Setup Python, install dependencies, and run tests + run: | + python -m pip install --upgrade pip + python -m llama_api.server.app_settings --install-pkgs + python -m unittest discover tests build-release: + if: github.event_name == 'push' && success() needs: build-and-test - if: ${{ success() }} name: Create Release runs-on: ubuntu-latest steps: diff --git a/Dockerfile b/Dockerfile index a56b85a..85ba958 100644 --- a/Dockerfile +++ b/Dockerfile @@ -41,7 +41,7 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ && apt-get clean \ && rm -rf /tmp/* \ && cd /app \ - && python3 -m llama_api.server.app_settings + && python3 -m llama_api.server.app_settings --force-cuda --install-pkgs # Set the working directory and start the server. WORKDIR /app diff --git a/llama_api/schemas/function_calling.py b/llama_api/schemas/function_calling.py index 35c964f..c45bcf2 100644 --- a/llama_api/schemas/function_calling.py +++ b/llama_api/schemas/function_calling.py @@ -1,7 +1,6 @@ """Helper classes for wrapping functions in OpenAI's API""" from dataclasses import dataclass -from types import NoneType from typing import ( Any, Dict, @@ -76,7 +75,7 @@ def _get_json_type(python_type: Type[JsonTypes]) -> str: return "object" elif python_type is list: return "array" - elif python_type is NoneType or python_type is None: + elif python_type is type(None) or python_type is None: return "null" else: raise ValueError( diff --git a/llama_api/server/app_settings.py b/llama_api/server/app_settings.py index 13ef331..deb39ca 100644 --- a/llama_api/server/app_settings.py +++ b/llama_api/server/app_settings.py @@ -1,3 +1,4 @@ +import argparse import platform from contextlib import asynccontextmanager from os import environ @@ -6,13 +7,13 @@ from ..shared.config import Config from ..utils.dependency import ( + get_installed_packages, get_poetry_executable, git_clone, install_all_dependencies, install_package, install_tensorflow, install_pytorch, - is_package_available, ) from ..utils.llama_cpp import build_shared_lib from ..utils.logger import ApiLogger @@ -76,12 +77,10 @@ def initialize_before_launch( # Install poetry logger.warning(f"⚠️ Poetry not found: {poetry}") install_package("poetry", force=True) - if not skip_pytorch_install or not is_package_available("torch"): + if not skip_pytorch_install: # Install pytorch install_pytorch(force_cuda=force_cuda) - if not skip_tensorflow_install or not is_package_available( - "tensorflow" - ): + if not skip_tensorflow_install: # Install tensorflow install_tensorflow() @@ -91,18 +90,20 @@ def initialize_before_launch( # Build the shared library of LLaMA C++ code build_shared_lib(logger=logger) + + # Get current packages installed + logger.info(f"📦 Installed packages: {get_installed_packages()}") else: logger.warning( "🏃‍♂️ Skipping package installation..." "If any packages are missing, " - "use `--install-packages` option to install them." + "use `--install-pkgs` option to install them." ) - - # Set the priority of the process - if platform.system() == "Windows": + try: + # Set the priority of the process set_priority(priority="high") - else: - set_priority(priority="normal") + except Exception: + pass @asynccontextmanager @@ -171,14 +172,37 @@ def run( if __name__ == "__main__": - # Git clone the repositories & install the dependencies. - # This is done before the server is launched to avoid - # the overhead of doing it when the server is running. - # Forcing CUDA is necessary when building the docker image + parser = argparse.ArgumentParser() + parser.add_argument( + "--install-pkgs", + action="store_true", + help="Install all required packages before running the server", + ) + parser.add_argument( + "--force-cuda", + action="store_true", + help=( + "Force CUDA version of pytorch to be used" + "when installing pytorch. e.g. torch==2.0.1+cu118" + ), + ) + parser.add_argument( + "--skip-torch-install", + action="store_true", + help="Skip installing pytorch, if `install-pkgs` is set", + ) + parser.add_argument( + "--skip-tf-install", + action="store_true", + help="Skip installing tensorflow, if `install-pkgs` is set", + ) + + args = parser.parse_args() + initialize_before_launch( git_and_disk_paths=Config.git_and_disk_paths, - install_packages=True, - force_cuda=True, - skip_pytorch_install=False, - skip_tensorflow_install=False, + install_packages=args.install_pkgs, + force_cuda=args.force_cuda, + skip_pytorch_install=args.skip_torch_install, + skip_tensorflow_install=args.skip_tf_install, ) diff --git a/llama_api/server/pools/llama.py b/llama_api/server/pools/llama.py index fd3d9b0..a7e3ca5 100644 --- a/llama_api/server/pools/llama.py +++ b/llama_api/server/pools/llama.py @@ -4,7 +4,7 @@ from os import getpid from queue import Queue from threading import Event -from typing import Dict, Iterator, List, Union +from typing import Deque, Dict, Iterator, List, Union import model_definitions @@ -36,8 +36,8 @@ logger.info(f"🔧 {current_process()} is initiated with PID: {getpid()}") lazy = LazyImports() # lazy-loader of modules -completion_generators: deque["BaseCompletionGenerator"] = deque(maxlen=1) -embedding_generators: deque["BaseEmbeddingGenerator"] = deque(maxlen=1) +completion_generators: Deque["BaseCompletionGenerator"] = deque(maxlen=1) +embedding_generators: Deque["BaseEmbeddingGenerator"] = deque(maxlen=1) def init() -> None: diff --git a/llama_api/shared/config.py b/llama_api/shared/config.py index 156f419..d45e567 100644 --- a/llama_api/shared/config.py +++ b/llama_api/shared/config.py @@ -12,6 +12,6 @@ class Config: torch_source: str = "https://download.pytorch.org/whl/torch_stable.html" tensorflow_version: str = "==2.13.0" git_and_disk_paths: Dict[str, Union[Path, str]] = { - "https://github.com/abetlen/llama-cpp-python": "repositories/llama_cpp", + "https://github.com/abetlen/llama-cpp-python": "repositories/llama_cpp", # noqa: E501 "https://github.com/turboderp/exllama": "repositories/exllama", } diff --git a/llama_api/utils/concurrency.py b/llama_api/utils/concurrency.py index 44b20ee..8fc517e 100644 --- a/llama_api/utils/concurrency.py +++ b/llama_api/utils/concurrency.py @@ -3,10 +3,10 @@ from contextlib import contextmanager from multiprocessing.managers import SyncManager from os import environ -import platform from queue import Queue +from sys import version_info from threading import Event -from typing import Callable, Dict, Optional, ParamSpec, Tuple, TypeVar +from typing import Callable, Dict, Optional, Tuple, TypeVar from fastapi.concurrency import run_in_threadpool @@ -14,6 +14,11 @@ from ..utils.logger import ApiLogger from ..utils.process_pool import ProcessPool +if version_info >= (3, 10): + from typing import ParamSpec +else: + from typing_extensions import ParamSpec + T = TypeVar("T") P = ParamSpec("P") @@ -27,10 +32,7 @@ def init_process_pool(env_vars: Dict[str, str]) -> None: and set the environment variables for the child processes""" try: # Set the priority of the process - if platform.system() == "Windows": - set_priority(priority="high") - else: - set_priority(priority="normal") + set_priority(priority="high") except Exception: pass @@ -82,7 +84,7 @@ def run_in_executor( func: Callable[P, T], *args: P.args, **kwargs: P.kwargs, -) -> Future[T]: +) -> "Future[T]": """Run a function in an executor, and return a future""" if loop.is_closed: diff --git a/llama_api/utils/dependency.py b/llama_api/utils/dependency.py index f94fbb2..a0cb6c3 100644 --- a/llama_api/utils/dependency.py +++ b/llama_api/utils/dependency.py @@ -1,8 +1,9 @@ -from importlib.util import find_spec import os import sys from contextlib import contextmanager +from importlib.util import find_spec from pathlib import Path +from platform import mac_ver from re import compile from subprocess import PIPE, check_call, run from tempfile import mkstemp @@ -71,6 +72,30 @@ def git_clone(git_path: str, disk_path: Union[Path, str]) -> Optional[bool]: return None +def get_mac_major_version_string(): + # platform.mac_ver() returns a tuple ('10.16', ('', '', ''), 'x86_64') + # Split the version string on '.' and take the first two components + major = mac_ver()[0].split(".")[0] + + # Join the components with '_' and prepend 'macosx_' + return "macosx_" + major + + +def get_installed_packages() -> List[str]: + """Return a list of installed packages""" + return [ + package.split("==")[0] + for package in run( + [sys.executable, "-m", "pip", "freeze"], + text=True, + stdout=PIPE, + stderr=PIPE, + ) + .stdout.strip() + .split("\n") + ] + + def get_poetry_executable() -> Path: """Construct the path to the poetry executable within the virtual environment. @@ -89,30 +114,40 @@ def get_proper_torch_cuda_version( """Helper function that returns the proper CUDA version of torch.""" if cuda_version == fallback_cuda_version: return fallback_cuda_version - elif check_if_torch_cuda_version_available( - cuda_version=cuda_version, source=source + elif check_if_torch_version_available( + version=f'cu{cuda_version.replace(".", "")}', source=source ): return cuda_version else: return fallback_cuda_version -def check_if_torch_cuda_version_available( - cuda_version: str = Config.torch_version, +def check_if_torch_version_available( + version: str = Config.torch_version, source: str = Config.torch_source, ) -> bool: - """Helper function that checks if the CUDA version of torch is available""" + """Helper function that checks if the version of torch is available""" try: # Determine the version of python, CUDA, and platform - cuda_ver = (f'cu{cuda_version.replace(".", "")}').encode() + canonical_version = compile(r"([0-9\.]+)").search(version) + if not canonical_version: + return False + package_ver = canonical_version.group().encode() python_ver = ( f"cp{sys.version_info.major}{sys.version_info.minor}" ).encode() - platform = ("win" if sys.platform == "win32" else "linux").encode() + if "win32" in sys.platform: + platform = "win_amd64".encode() + elif "linux" in sys.platform: + platform = "linux_x86_64".encode() + elif "darwin" in sys.platform: + platform = get_mac_major_version_string().encode() + else: + return False # Check if the CUDA version of torch is available for line in urlopen(source).read().splitlines(): - if cuda_ver in line and python_ver in line and platform in line: + if package_ver in line and python_ver in line and platform in line: return True return False except Exception: @@ -245,8 +280,17 @@ def install_pytorch( pip_install += ["-f", source] elif source: # If a source is specified, but CUDA is not available, - # install the CPU version of torch - pip_install.append(f"torch{torch_version}+cpu") + + if check_if_torch_version_available( + version=f"{torch_version}+cpu", + source=source, + ): + # install the CPU version of torch if available + pip_install.append(f"torch{torch_version}+cpu") + else: + # else, install the canonical version of torch + pip_install.append(f"torch{torch_version}") + # If a source is specified, add it to the pip install command pip_install += ["-f", source] else: diff --git a/llama_api/utils/errors.py b/llama_api/utils/errors.py index 6e52cc1..5086ce5 100644 --- a/llama_api/utils/errors.py +++ b/llama_api/utils/errors.py @@ -29,7 +29,7 @@ class ErrorResponseCallbacks: @staticmethod def token_exceed_callback( request: Union[CreateCompletionRequest, CreateChatCompletionRequest], - match: Match[str], + match: "Match[str]", ) -> Tuple[int, ErrorResponse]: context_window = int(match.group(2)) prompt_tokens = int(match.group(1)) diff --git a/llama_api/utils/lazy_imports.py b/llama_api/utils/lazy_imports.py index 71fa5db..19be2ea 100644 --- a/llama_api/utils/lazy_imports.py +++ b/llama_api/utils/lazy_imports.py @@ -4,13 +4,13 @@ from functools import wraps -from typing import Callable, TypeVar, Union +from typing import Callable, Set, TypeVar, Union from .logger import ApiLogger T = TypeVar("T") logger = ApiLogger(__name__) -logged_modules: set[str] = set() +logged_modules: Set[str] = set() def try_import(module_name: str): diff --git a/llama_api/utils/llama_cpp.py b/llama_api/utils/llama_cpp.py index b05505d..d49e416 100644 --- a/llama_api/utils/llama_cpp.py +++ b/llama_api/utils/llama_cpp.py @@ -8,11 +8,15 @@ from typing import List, Optional, Union from ..utils.dependency import install_package, run_command +from ..utils.system import get_cuda_version # You can set the CMAKE_ARGS environment variable to change the cmake args. -# cuBLAS is default to ON, -# but if it fails to build, fall back to the default settings (CPU only) -CMAKE_ARGS: str = "-DBUILD_SHARED_LIBS=ON -DLLAMA_CUBLAS=ON" +# cuBLAS is default to ON if CUDA is installed. +# CPU inference is default if CUDA is not installed. +if get_cuda_version() is None: + CMAKE_ARGS: str = "-DBUILD_SHARED_LIBS=ON" +else: + CMAKE_ARGS = "-DBUILD_SHARED_LIBS=ON -DLLAMA_CUBLAS=ON" LIB_BASE_NAME: str = "llama" REPOSITORY_FOLDER: str = "repositories" @@ -67,7 +71,7 @@ def _git_clone() -> None: def _get_libs() -> List[str]: # Determine the libs based on the platform - if sys.platform.startswith("linux"): + if "linux" in sys.platform: return [ f"lib{LIB_BASE_NAME}.so", ] @@ -89,7 +93,18 @@ def _get_lib_paths(base_path: Path) -> List[Path]: return [base_path / lib for lib in _get_libs()] -def _copy_libs_to_target(cmake_dir: Path, target_dir: Path) -> None: +def _copy_make_libs_to_target(make_dir: Path, target_dir: Path) -> None: + # Copy the built libs to the target folder + for lib_name in _get_libs(): + lib = make_dir / lib_name + if lib.exists(): + print(f"~~~ Found shared library: {lib}") + shutil.copy(lib, target_dir) + else: + print(f"~~~ Library {lib_name} not found") + + +def _copy_cmake_libs_to_target(cmake_dir: Path, target_dir: Path) -> None: # Copy the built libs to the target folder for lib_name in _get_libs(): lib = cmake_dir / "build" / "bin" / "Release" / lib_name @@ -100,16 +115,59 @@ def _copy_libs_to_target(cmake_dir: Path, target_dir: Path) -> None: print(f"~~~ Library {lib_name} not found") -def _cmake( - cmake_dir: Path, cmake_args: Union[str, List[str]], target_dir: Path -) -> None: - # Run cmake to build the shared lib - env = environ.copy() - build_dir = cmake_dir / "build" +def _get_cmake_args(cmake_args: Union[str, List[str]]) -> List[str]: if isinstance(cmake_args, str): cmake_args = cmake_args.split(" ") if "-DBUILD_SHARED_LIBS=ON" not in cmake_args: cmake_args.append("-DBUILD_SHARED_LIBS=ON") + return cmake_args + + +def _cmake_args_to_make_args(cmake_args: List[str]) -> List[str]: + # initialize an empty list to store the converted parts + result: List[str] = [] + # loop through each part + for cmake_arg in cmake_args: + # capitalize all letters + cmake_arg = cmake_arg.upper() + + # replace `ON` with `1` and `OFF` with `0` + cmake_arg = cmake_arg.replace("=ON", "=1").replace("=OFF", "=0") + + # remove the `-D` flag + if cmake_arg.startswith("-D"): + cmake_arg = cmake_arg[2:] + + # append the converted part to the result list + result.append(cmake_arg) + return result + + +def _make(make_dir: Path, make_args: List[str], target_dir: Path) -> None: + # Run make to build the shared lib + + # Build the shared lib + run_command( + ["make", *make_args], + action="build", + name="llama.cpp shared lib", + cwd=make_dir, + ) + for lib in _get_libs(): + run_command( + ["make", lib], + action="build", + name="llama.cpp shared lib", + cwd=make_dir, + ) + + # Copy the built libs to the target folder + _copy_make_libs_to_target(make_dir=make_dir, target_dir=target_dir) + + +def _cmake(cmake_dir: Path, cmake_args: List[str], target_dir: Path) -> None: + # Run cmake to build the shared lib + build_dir = cmake_dir / "build" if build_dir.exists(): # If the build folder exists, delete it shutil.rmtree(build_dir) @@ -118,9 +176,7 @@ def _cmake( build_dir.mkdir(exist_ok=True) # Check if cmake is installed - if not run_command( - ["cmake"], action="check", name="cmake", env=env, verbose=False - ): + if not run_command(["cmake"], action="check", name="cmake", verbose=False): # If cmake is not installed, try to install it install_package("cmake", force=True) @@ -130,18 +186,16 @@ def _cmake( action="build", name="llama.cpp shared lib", cwd=build_dir, - env=env, ) run_command( ["cmake", "--build", ".", "--config", "Release"], action="build", name="llama.cpp shared lib", cwd=build_dir, - env=env, ) # Copy the built libs to the target folder - _copy_libs_to_target(cmake_dir=cmake_dir, target_dir=target_dir) + _copy_cmake_libs_to_target(cmake_dir=cmake_dir, target_dir=target_dir) def build_shared_lib( @@ -164,8 +218,19 @@ def build_shared_lib( # Build the libs # Try to build the lib with cmake cmake_dir = VENDOR_PATH - cmake_args = environ.get("CMAKE_ARGS", CMAKE_ARGS) - _cmake( - cmake_dir=cmake_dir, cmake_args=cmake_args, target_dir=MODULE_PATH - ) + cmake_args_str = environ.get("CMAKE_ARGS", CMAKE_ARGS) + if sys.platform == "win32": + _cmake( + cmake_dir=cmake_dir, + cmake_args=_get_cmake_args(cmake_args_str), + target_dir=MODULE_PATH, + ) + else: + _make( + make_dir=cmake_dir, + make_args=_cmake_args_to_make_args( + _get_cmake_args(cmake_args_str) + ), + target_dir=MODULE_PATH, + ) return diff --git a/llama_api/utils/process_pool.py b/llama_api/utils/process_pool.py index 89df04e..ecaed7a 100644 --- a/llama_api/utils/process_pool.py +++ b/llama_api/utils/process_pool.py @@ -16,13 +16,17 @@ Iterable, List, Optional, - ParamSpec, Tuple, Type, TypeVar, Union, ) +if sys.version_info >= (3, 10): + from typing import ParamSpec +else: + from typing_extensions import ParamSpec + class _WrappedWorkerException(Exception): # type: ignore def __init__( @@ -94,7 +98,7 @@ def _chunked_fn(fn: Callable[..., T], *args: Tuple[Any, ...]) -> List[T]: def _process_chunk( fn: Callable[..., T], chunk: Iterable[Tuple[Any, ...]] -) -> List[partial[List[T]]]: +) -> "List[partial[List[T]]]": """Processes a chunk of an iterable passed to map. Runs the function passed to map() on a chunk of the @@ -217,6 +221,10 @@ def __init__( ) self.process.start() + @property + def is_alive(self) -> bool: + return self.process.is_alive() + def send(self, job: Job) -> None: partialed_func, _, future = job @@ -542,9 +550,9 @@ def map( # Create multiple partial functions so that we can send # multiple arguments to map - chunked_funcs: List[partial[List]] = _process_chunk( + chunked_funcs = _process_chunk( fn, chunk=_get_chunks(*iterables, chunksize=chunksize) - ) + ) # type: List[partial[List]] # Submit all the partial functions to the pool chunked_futures: List[Future[List]] = [ diff --git a/main.py b/main.py index 39687cb..c6c34e7 100644 --- a/main.py +++ b/main.py @@ -32,12 +32,12 @@ parser.add_argument( "--skip-torch-install", action="store_true", - help="Skip installing pytorch, if `install-packages` is set", + help="Skip installing pytorch, if `install-pkgs` is set", ) parser.add_argument( "--skip-tf-install", action="store_true", - help="Skip installing tensorflow, if `install-packages` is set", + help="Skip installing tensorflow, if `install-pkgs` is set", ) args = parser.parse_args() diff --git a/model_definitions.py b/model_definitions.py index c35f99e..c14c8d2 100644 --- a/model_definitions.py +++ b/model_definitions.py @@ -24,12 +24,21 @@ max_total_tokens=4096, compress_pos_emb=2.0, ) +stable_beluga_13b = ExllamaModel( + model_path="stable_beluga_13b", # model_path here + max_total_tokens=4096, +) +nous_hermes_llama_2_13b = ExllamaModel( + model_path="nous_hermes_llama_2_13b", # model_path here + max_total_tokens=8192, + compress_pos_emb=2.0, +) # Define a mapping from OpenAI model names to LLaMA models. # e.g. If you request API model "gpt-3.5-turbo", # the API will load the LLaMA model "orca_mini_3b" openai_replacement_models: Dict[str, str] = { - "gpt-3.5-turbo": "orca_mini_3b", - "gpt-4": "orca_mini_7b", + "gpt-3.5-turbo": "stable_beluga_13b", + "gpt-4": "nous_hermes_llama_2_13b", } diff --git 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(>=0.7)", "cython (>=0.25.1)", "importlib-metadata", "pytest (>=6.0.0)", "pytest-mock (>=1.10.4)", "requests", "virtualenv"] - [[package]] name = "secretstorage" version = "3.3.3" @@ -2597,22 +2631,6 @@ files = [ {file = "sentencepiece-0.1.99.tar.gz", hash = "sha256:189c48f5cb2949288f97ccdb97f0473098d9c3dcf5a3d99d4eabe719ec27297f"}, ] -[[package]] -name = "setuptools" -version = "68.0.0" -description = "Easily download, build, install, upgrade, and uninstall Python packages" -optional = false -python-versions = ">=3.7" -files = [ - {file = "setuptools-68.0.0-py3-none-any.whl", hash = "sha256:11e52c67415a381d10d6b462ced9cfb97066179f0e871399e006c4ab101fc85f"}, - {file = "setuptools-68.0.0.tar.gz", hash = "sha256:baf1fdb41c6da4cd2eae722e135500da913332ab3f2f5c7d33af9b492acb5235"}, -] - -[package.extras] -docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"] -testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"] -testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"] - [[package]] name = "shellingham" version = "1.5.0.post1" @@ -3170,20 +3188,6 @@ files = [ {file = "websockets-11.0.3.tar.gz", hash = "sha256:88fc51d9a26b10fc331be344f1781224a375b78488fc343620184e95a4b27016"}, ] -[[package]] -name = "wheel" -version = "0.41.0" -description = "A built-package format for Python" -optional = false -python-versions = ">=3.7" -files = [ - {file = "wheel-0.41.0-py3-none-any.whl", hash = "sha256:7e9be3bbd0078f6147d82ed9ed957e323e7708f57e134743d2edef3a7b7972a9"}, - {file = "wheel-0.41.0.tar.gz", hash = "sha256:55a0f0a5a84869bce5ba775abfd9c462e3a6b1b7b7ec69d72c0b83d673a5114d"}, -] - -[package.extras] -test = ["pytest (>=6.0.0)", "setuptools (>=65)"] - [[package]] name = "xattr" version = "0.10.1" @@ -3285,5 +3289,5 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" -python-versions = ">=3.9.1,<3.12" -content-hash = "917c885df5367bbbde43b2d9d9979b48a7180374f21fc3df740d99c544550bfc" +python-versions = ">=3.8.1,<3.12" +content-hash = "aa1a41ec0841ea5edb99dec7e07806ec94342aa67c3d26e3061f1f101c34cf7b" diff --git a/pyproject.toml b/pyproject.toml index 4dd6e71..a88a9f5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,7 +11,7 @@ packages = [{ include = "llama_api" }] include = ["LICENSE.md"] [tool.poetry.dependencies] -python = ">=3.9.1,<3.12" +python = ">=3.8.1,<3.12" poetry = "^1.5.1" uvicorn = { extras = ["standard"], version = "^0.23" } @@ -19,7 +19,7 @@ fastapi = "^0.100" orjson = "^3.9" sse-starlette = "^1.6" psutil = "^5.9" -cmake = {version = "^3.27.0", markers = "sys_platform == 'win32'"} +cmake = ">=3.18.0" filelock = "^3.12" transformers = "^4.31.0" tensorflow-hub = "^0.14" diff --git a/readme.md b/readme.md index 4a9c950..fb86b39 100644 --- a/readme.md +++ b/readme.md @@ -18,7 +18,7 @@ You can use this server to run the models in your own application, or use it as ## Before you start -1. **Python 3.11** is required to run the server. You can download it from https://www.python.org/downloads/ +1. **Python 3.8 / 3.9 / 3.10 / 3.11** is required to run the server. You can download it from https://www.python.org/downloads/ 2. **llama.cpp**: To use llama.cpp, and if you are **Windows** user, download [CMake](https://cmake.org/download/) to compile library. diff --git a/requirements.txt b/requirements.txt index 76b0328..2c76573 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,87 +1,90 @@ -annotated-types==0.5.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -anyio==3.7.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -attrs==23.1.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -build==0.10.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -cachecontrol[filecache]==0.12.14 ; python_full_version >= "3.9.1" and python_version < "3.12" -certifi==2023.7.22 ; python_full_version >= "3.9.1" and python_version < "3.12" -cffi==1.15.1 ; python_full_version >= "3.9.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") -charset-normalizer==3.2.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -cleo==2.0.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -click==8.1.6 ; python_full_version >= "3.9.1" and python_version < "3.12" -colorama==0.4.6 ; python_full_version >= "3.9.1" and python_version < "3.12" and (os_name == "nt" or platform_system == "Windows") -crashtest==0.4.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -cryptography==41.0.2 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "linux" -diskcache==5.6.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -distlib==0.3.7 ; python_full_version >= "3.9.1" and python_version < "3.12" -dulwich==0.21.5 ; python_full_version >= "3.9.1" and python_version < "3.12" -exceptiongroup==1.1.2 ; python_full_version >= "3.9.1" and python_version < "3.11" -fastapi==0.100.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -filelock==3.12.2 ; python_full_version >= "3.9.1" and python_version < "3.12" -fsspec==2023.6.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -h11==0.14.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -html5lib==1.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -httptools==0.6.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -huggingface-hub==0.16.4 ; python_full_version >= "3.9.1" and python_version < "3.12" -idna==3.4 ; python_full_version >= "3.9.1" and python_version < "3.12" -importlib-metadata==6.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -installer==0.7.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -jaraco-classes==3.3.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -jeepney==0.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "linux" -jsonschema-specifications==2023.7.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -jsonschema==4.18.4 ; python_full_version >= "3.9.1" and python_version < "3.12" -keyring==23.13.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -lockfile==0.12.2 ; python_full_version >= "3.9.1" and python_version < "3.12" -more-itertools==10.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -msgpack==1.0.5 ; python_full_version >= "3.9.1" and python_version < "3.12" -ninja==1.11.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -numpy==1.25.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -orjson==3.9.2 ; python_full_version >= "3.9.1" and python_version < "3.12" -packaging==23.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -pexpect==4.8.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -pkginfo==1.9.6 ; python_full_version >= "3.9.1" and python_version < "3.12" -platformdirs==3.10.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -poetry-core==1.6.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -poetry-plugin-export==1.4.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -poetry==1.5.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -protobuf==4.23.4 ; python_full_version >= "3.9.1" and python_version < "3.12" -psutil==5.9.5 ; python_full_version >= "3.9.1" and python_version < "3.12" -ptyprocess==0.7.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -pycparser==2.21 ; python_full_version >= "3.9.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") -pydantic-core==2.4.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -pydantic-settings==2.0.2 ; python_full_version >= "3.9.1" and python_version < "3.12" -pydantic==2.1.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -pyproject-hooks==1.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -python-dotenv==1.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -pywin32-ctypes==0.2.2 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "win32" -pyyaml==6.0.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -rapidfuzz==2.15.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -referencing==0.30.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -regex==2023.6.3 ; python_full_version >= "3.9.1" and python_version < "3.12" -requests-toolbelt==1.0.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -requests==2.31.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -rpds-py==0.9.2 ; python_full_version >= "3.9.1" and python_version < "3.12" -safetensors==0.3.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -secretstorage==3.3.3 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "linux" -sentencepiece==0.1.99 ; python_full_version >= "3.9.1" and python_version < "3.12" -shellingham==1.5.0.post1 ; python_full_version >= "3.9.1" and python_version < "3.12" -six==1.16.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -sniffio==1.3.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -sse-starlette==1.6.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -starlette==0.27.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -tensorflow-hub==0.14.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -tokenizers==0.13.3 ; python_full_version >= "3.9.1" and python_version < "3.12" -tomli==2.0.1 ; python_full_version >= "3.9.1" and python_version < "3.11" -tomlkit==0.12.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -tqdm==4.65.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -transformers==4.31.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -trove-classifiers==2023.7.6 ; python_full_version >= "3.9.1" and python_version < "3.12" -typing-extensions==4.7.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -urllib3==1.26.16 ; python_full_version >= "3.9.1" and python_version < "3.12" -uvicorn[standard]==0.23.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -uvloop==0.17.0 ; (sys_platform != "win32" and sys_platform != "cygwin") and platform_python_implementation != "PyPy" and python_full_version >= "3.9.1" and python_version < "3.12" -virtualenv==20.24.2 ; python_full_version >= "3.9.1" and python_version < "3.12" -watchfiles==0.19.0 ; python_full_version >= "3.9.1" and python_version < "3.12" -webencodings==0.5.1 ; python_full_version >= "3.9.1" and python_version < "3.12" -websockets==11.0.3 ; python_full_version >= "3.9.1" and python_version < "3.12" -xattr==0.10.1 ; python_full_version >= "3.9.1" and python_version < "3.12" and sys_platform == "darwin" -zipp==3.16.2 ; python_full_version >= "3.9.1" and python_version < "3.12" +annotated-types==0.5.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +anyio==3.7.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +attrs==23.1.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +build==0.10.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +cachecontrol[filecache]==0.12.14 ; python_full_version >= "3.8.1" and python_version < "3.12" +certifi==2023.7.22 ; python_full_version >= "3.8.1" and python_version < "3.12" +cffi==1.15.1 ; python_full_version >= "3.8.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") +charset-normalizer==3.2.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +cleo==2.0.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +click==8.1.6 ; python_full_version >= "3.8.1" and python_version < "3.12" +cmake==3.27.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +colorama==0.4.6 ; python_full_version >= "3.8.1" and python_version < "3.12" and (os_name == "nt" or platform_system == "Windows") +crashtest==0.4.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +cryptography==41.0.2 ; python_full_version >= "3.8.1" and python_version < "3.12" and sys_platform == "linux" +diskcache==5.6.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +distlib==0.3.7 ; python_full_version >= "3.8.1" and python_version < "3.12" +dulwich==0.21.5 ; python_full_version >= "3.8.1" and python_version < "3.12" +exceptiongroup==1.1.2 ; python_full_version >= "3.8.1" and python_version < "3.11" +fastapi==0.100.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +filelock==3.12.2 ; python_full_version >= "3.8.1" and python_version < "3.12" +fsspec==2023.6.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +h11==0.14.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +html5lib==1.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +httptools==0.6.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +huggingface-hub==0.16.4 ; python_full_version >= "3.8.1" and python_version < "3.12" +idna==3.4 ; python_full_version >= "3.8.1" and python_version < "3.12" +importlib-metadata==6.8.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +importlib-resources==6.0.0 ; python_full_version >= "3.8.1" and python_version < "3.9" +installer==0.7.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +jaraco-classes==3.3.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +jeepney==0.8.0 ; python_full_version >= "3.8.1" and python_version < "3.12" and sys_platform == "linux" +jsonschema-specifications==2023.7.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +jsonschema==4.18.4 ; python_full_version >= "3.8.1" and python_version < "3.12" +keyring==23.13.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +lockfile==0.12.2 ; python_full_version >= "3.8.1" and python_version < "3.12" +more-itertools==10.0.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +msgpack==1.0.5 ; python_full_version >= "3.8.1" and python_version < "3.12" +ninja==1.11.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +numpy==1.24.4 ; python_full_version >= "3.8.1" and python_version < "3.12" +orjson==3.9.2 ; python_full_version >= "3.8.1" and python_version < "3.12" +packaging==23.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +pexpect==4.8.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +pkginfo==1.9.6 ; python_full_version >= "3.8.1" and python_version < "3.12" +pkgutil-resolve-name==1.3.10 ; python_full_version >= "3.8.1" and python_version < "3.9" +platformdirs==3.10.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +poetry-core==1.6.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +poetry-plugin-export==1.4.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +poetry==1.5.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +protobuf==4.23.4 ; python_full_version >= "3.8.1" and python_version < "3.12" +psutil==5.9.5 ; python_full_version >= "3.8.1" and python_version < "3.12" +ptyprocess==0.7.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +pycparser==2.21 ; python_full_version >= "3.8.1" and python_version < "3.12" and (sys_platform == "darwin" or sys_platform == "linux") +pydantic-core==2.4.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +pydantic-settings==2.0.2 ; python_full_version >= "3.8.1" and python_version < "3.12" +pydantic==2.1.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +pyproject-hooks==1.0.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +python-dotenv==1.0.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +pywin32-ctypes==0.2.2 ; python_full_version >= "3.8.1" and python_version < "3.12" and sys_platform == "win32" +pyyaml==6.0.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +rapidfuzz==2.15.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +referencing==0.30.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +regex==2023.6.3 ; python_full_version >= "3.8.1" and python_version < "3.12" +requests-toolbelt==1.0.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +requests==2.31.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +rpds-py==0.9.2 ; python_full_version >= "3.8.1" and python_version < "3.12" +safetensors==0.3.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +secretstorage==3.3.3 ; python_full_version >= "3.8.1" and python_version < "3.12" and sys_platform == "linux" +sentencepiece==0.1.99 ; python_full_version >= "3.8.1" and python_version < "3.12" +shellingham==1.5.0.post1 ; python_full_version >= "3.8.1" and python_version < "3.12" +six==1.16.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +sniffio==1.3.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +sse-starlette==1.6.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +starlette==0.27.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +tensorflow-hub==0.14.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +tokenizers==0.13.3 ; python_full_version >= "3.8.1" and python_version < "3.12" +tomli==2.0.1 ; python_full_version >= "3.8.1" and python_version < "3.11" +tomlkit==0.12.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +tqdm==4.65.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +transformers==4.31.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +trove-classifiers==2023.7.6 ; python_full_version >= "3.8.1" and python_version < "3.12" +typing-extensions==4.7.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +urllib3==1.26.16 ; python_full_version >= "3.8.1" and python_version < "3.12" +uvicorn[standard]==0.23.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +uvloop==0.17.0 ; (sys_platform != "win32" and sys_platform != "cygwin") and platform_python_implementation != "PyPy" and python_full_version >= "3.8.1" and python_version < "3.12" +virtualenv==20.24.2 ; python_full_version >= "3.8.1" and python_version < "3.12" +watchfiles==0.19.0 ; python_full_version >= "3.8.1" and python_version < "3.12" +webencodings==0.5.1 ; python_full_version >= "3.8.1" and python_version < "3.12" +websockets==11.0.3 ; python_full_version >= "3.8.1" and python_version < "3.12" +xattr==0.10.1 ; python_full_version >= "3.8.1" and python_version < "3.12" and sys_platform == "darwin" +zipp==3.16.2 ; python_full_version >= "3.8.1" and python_version < "3.12" diff --git a/tests/conftest.py b/tests/conftest.py index 96c729a..e276030 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -6,11 +6,11 @@ from llama_api.server.app_settings import create_app_llama_cpp from llama_api.shared.config import Config -from llama_api.utils.concurrency import pool as concurrency_pool from llama_api.utils.dependency import install_package, is_package_available -from llama_api.utils.process_pool import ProcessPool +from llama_api.utils.concurrency import _pool if TYPE_CHECKING: + from fastapi.testclient import TestClient # noqa: F401 from httpx import AsyncClient # noqa: F401 @@ -33,13 +33,13 @@ def setUpClass(cls): cls.AsyncClient = importlib.import_module( "httpx" ).AsyncClient # type: Type[AsyncClient] + cls.TestClient = importlib.import_module( + "fastapi.testclient" + ).TestClient # type: Type[TestClient] cls.app = create_app_llama_cpp() - cls.ppool = ProcessPool(max_workers=2) - for wix in range(cls.ppool.max_workers): - cls.ppool.worker_at_wix(wix) environ["MAX_WORKERS"] = "2" @classmethod def tearDownClass(cls): - concurrency_pool().shutdown(wait=False) - cls.ppool.shutdown() + if _pool is not None: + _pool.shutdown(wait=True) diff --git a/tests/test_ci.py b/tests/test_ci.py deleted file mode 100644 index 65e76d2..0000000 --- a/tests/test_ci.py +++ /dev/null @@ -1,24 +0,0 @@ -from pathlib import Path - -test_output = "bar baz" - - -def foo(): - print(test_output) - - -def test_venv(): - from llama_api.utils.venv import VirtualEnvironment - - venv_name = ".test-venv" - venv = VirtualEnvironment(Path(__file__).parent / venv_name) - assert venv.recreate() == 0, "Failed to create virtual environment." - assert venv.pip("install", "requests") == 0, "Failed to install requests." - stdout = venv.run_script(__file__).stdout - assert ( - test_output in stdout - ), "Failed to run script in virtual environment." - - -if __name__ == "__main__": - foo() diff --git a/tests/test_process_pool.py b/tests/test_process_pool.py index e14cfed..41416b1 100644 --- a/tests/test_process_pool.py +++ b/tests/test_process_pool.py @@ -1,161 +1,74 @@ -from asyncio import gather from concurrent.futures import Future +from contextlib import contextmanager from functools import partial from os import getpid from time import sleep, time -import unittest +from typing import Tuple -from llama_api.utils.concurrency import ( - ProcessPool, - awake_all_pool_workers, - pool, - run_in_processpool, - run_in_processpool_with_wix, -) +from llama_api.utils.process_pool import ProcessPool from tests.conftest import TestLlamaAPI -def simple_job(sleep_time: float) -> float: - print("> Input sleep time:", sleep_time, "PID:", getpid()) +@contextmanager +def process_pool(max_workers: int): + with ProcessPool(max_workers=max_workers) as executor: + alive_workers = [False] * max_workers + while not all(alive_workers): + for wix in range(executor.max_workers): + # This will run in the worker + # at the specified worker-index(wix). + # We're just checking if the worker is alive. + alive_workers[wix] = executor.worker_at_wix(wix).is_alive + print("- Waiting for workers to start...", alive_workers) + sleep(0.25) # Wait for the pool to start + print("- Workers started.") + yield executor + + +def simple_job(sleep_time: float) -> Tuple[float, float]: + """A simple job that sleeps for a given time + and returns the start and end times.""" + start_time = time() + print("> Starting at:", start_time, "PID:", getpid()) sleep(sleep_time) - print("> Job done at", time(), "PID:", getpid()) - return sleep_time + end_time = time() + print("> Ending at", end_time, "PID:", getpid()) + return start_time, end_time -class TestProcessPool(TestLlamaAPI, unittest.IsolatedAsyncioTestCase): +class TestProcessPool(TestLlamaAPI): """Test that the process pool works as expected.""" def test_process_pool(self) -> None: """Test the basic functionality of the process pool.""" # We're recording the start time - start_time = time() + with process_pool(max_workers=2) as executor: + # Submitting two jobs which will sleep for 1 second each + f1: Future = executor.submit(simple_job, 1) + f2: Future = executor.submit(simple_job, 1) + print("Submitted jobs at", time()) - # Submitting two jobs which will sleep for 1 second each - f1: Future = self.ppool.submit(simple_job, 1) - f2: Future = self.ppool.submit(simple_job, 1) - print("Submitted jobs at", time()) + # Waiting for both jobs to complete + _, e1 = f1.result() # This will block until f1 is done + s2, _ = f2.result() # This will block until f2 is done - # Waiting for both jobs to complete - result1 = f1.result() # This will block until f1 is done - result2 = f2.result() # This will block until f2 is done - print("Jobs done:", result1, result2) - - # Recording the end time - end_time = time() - print("Elapsed time:", end_time - start_time) - - # Total elapsed time should be little more than 1 second, - # not 2 seconds, because jobs are expected to run in parallel. - self.assertLessEqual( - end_time - start_time, 2.0, f"{end_time - start_time}" - ) - self.assertTrue(result1 == result2 == 1) + # Assert that the second job started before the first job ended + self.assertLess(s2, e1) def test_process_pool_with_wix(self) -> None: - """Test the worker-index-based scheduling functionality of the process pool.""" + """Test the worker-index-based scheduling functionality + of the process pool.""" # We're recording the start time - start_time = time() - - # Submitting two jobs which will sleep for 1 second each - f1: Future = self.ppool.submit_with_wix(partial(simple_job, 1), wix=1) - f2: Future = self.ppool.submit_with_wix(partial(simple_job, 1), wix=1) - print("Submitted jobs") - - # Waiting for both jobs to complete - result1 = f1.result() # This will block until f1 is done - result2 = f2.result() # This will block until f2 is done - print("Jobs done:", result1, result2) - - # Recording the end time - end_time = time() - print("Elapsed time:", end_time - start_time) - - # Total elapsed time should be little more than 2 seconds, - # not 1 second, because jobs are expected to run in serial. - self.assertGreaterEqual( - end_time - start_time, 2.0, f"{end_time - start_time}" - ) - self.assertTrue(result1 == result2 == 1) - - async def test_process_pool_async(self): - """Test the basic functionality of the process pool in an async context.""" - try: - awake_all_pool_workers() - sleep(2) # Give the pool some time to start up - - start_time = time() - print("Submitting jobs...") - result_1, result_2 = await gather( - run_in_processpool(simple_job, 1), - run_in_processpool(simple_job, 1), # type: ignore - ) - end_time = time() - print("Elapsed time:", end_time - start_time) - - # Total elapsed time should be little more than 1 second, - # not 2 seconds, because jobs are expected to run in parallel. - self.assertLessEqual( - end_time - start_time, 2.0, f"{end_time - start_time}" - ) - self.assertTrue(result_1 == result_2 == 1) - finally: - _pool = pool() - _pool.join() - - async def test_process_pool_with_wix_async(self): - """Test the worker-index-based scheduling functionality of the process pool - in an async context.""" - try: - awake_all_pool_workers() - sleep(2) # Give the pool some time to start up - - start_time = time() - print("Submitting jobs...") - result_1, result_2 = await gather( - run_in_processpool_with_wix(partial(simple_job, 1), wix=1), - run_in_processpool_with_wix(partial(simple_job, 1), wix=1), - ) - end_time = time() - print("Elapsed time:", end_time - start_time) - - # Total elapsed time should be little more than 2 seconds, - # not 1 second, because jobs are expected to run in serial. - self.assertGreaterEqual( - end_time - start_time, 2.0, f"{end_time - start_time}" - ) - self.assertTrue(result_1 == result_2 == 1) - finally: - _pool = pool() - _pool.join() - - def test_process_pool_graceful_shutdown(self): - """Test the graceful shutdown of the process pool.""" - timeout = None - with ProcessPool(max_workers=2) as executor: - f1 = executor.submit(simple_job, 1) - f2 = executor.submit(simple_job, 1) - print("Submitted jobs") - # Wait for the jobs to start - result1 = f1.result(timeout=timeout) - result2 = f2.result(timeout=timeout) - print("Jobs done:", result1, result2) + with process_pool(max_workers=2) as executor: + # Submitting two jobs which will sleep for 1 second each + f1: Future = executor.submit_with_wix(partial(simple_job, 1), wix=0) + f2: Future = executor.submit_with_wix(partial(simple_job, 1), wix=0) + print("Submitted jobs at", time()) - def test_process_pool_map(self): - """Test the map functionality of the process pool.""" - timeout = 3.0 - with ProcessPool(max_workers=4) as executor: - results = iter( - executor.map( - simple_job, - [1, 1, 1, 1], - chunksize=2, - timeout=timeout, - ) - ) - print("Submitted jobs") + # Waiting for both jobs to complete + _, e1 = f1.result() # This will block until f1 is done + s2, _ = f2.result() # This will block until f2 is done - # Wait for the jobs to start - result1 = next(results) - result2 = next(results) - print("Jobs done:", result1, result2) + # Assert that the second job started before the first job ended + self.assertGreater(s2, e1) diff --git a/tests/test_server.py b/tests/test_server.py index 010ed30..8255b4a 100644 --- a/tests/test_server.py +++ b/tests/test_server.py @@ -11,7 +11,7 @@ Union, ) import unittest -from fastapi.testclient import TestClient +from llama_api.utils.system import get_cuda_version from tests.conftest import TestLlamaAPI from llama_api.schemas.api import ( @@ -30,16 +30,52 @@ class TestServer(TestLlamaAPI, unittest.IsolatedAsyncioTestCase): def test_health(self): """Test the health endpoint""" - with TestClient(app=self.app) as client: + with self.TestClient(app=self.app) as client: response = client.get( "/health", headers={"Content-Type": "application/json"}, ) self.assertEqual(response.status_code, 200) + def test_import_llama_cpp(self): + try: + from llama_api.modules.llama_cpp import ( # noqa: F401 + LlamaCppCompletionGenerator, + ) + except ImportError as e: + self.fail(f"Failed to import module: {e}") + + @unittest.skipIf( + get_cuda_version() is None, + reason="No CUDA found on this system", + ) + def test_import_exllama(self): + try: + from llama_api.modules.exllama import ( # noqa: F401 + ExllamaCompletionGenerator, + ) + except ImportError as e: + self.fail(f"Failed to import module: {e}") + + def test_import_sentence_encoder(self): + try: + from llama_api.modules.sentence_encoder import ( # noqa: F401 + SentenceEncoderEmbeddingGenerator, + ) + except ImportError as e: + self.fail(f"Failed to import module: {e}") + + def test_import_transformer(self): + try: + from llama_api.modules.transformer import ( # noqa: F401 + TransformerEmbeddingGenerator, + ) + except ImportError as e: + self.fail(f"Failed to import module: {e}") + def test_v1_models(self): """Test the v1/models endpoint""" - with TestClient(app=self.app) as client: + with self.TestClient(app=self.app) as client: response = client.get( "/v1/models", headers={"Content-Type": "application/json"}, @@ -100,7 +136,8 @@ async def test_exllama_concurrency(self): f"No model in {TestLlamaAPI.ggml_path} or {TestLlamaAPI.gptq_path}", ) async def test_llama_mixed_concurrency(self): - """Test the Llama CPP & ExLLama model completion endpoints with concurrency""" + """Test the Llama CPP & ExLLama model completion endpoints + with concurrency""" model_names: Tuple[str, ...] = (self.ggml_model, self.gptq_model) await self._arequest_completion( model_names=model_names, endpoints="completions" @@ -181,7 +218,7 @@ def _request_completion( if isinstance(endpoints, str) else endpoints ) - with TestClient(app=self.app) as client: + with self.TestClient(app=self.app) as client: # Get models using the API model_resp = (client.get("/v1/models")).json() models: List[str] = []