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python: fix CalledProcessError on Intel Macs since v2.8.0 (#3045)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
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Jared Van Bortel
GitHub
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commit
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@ -12,6 +12,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
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### Changed
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- Rebase llama.cpp on latest upstream as of September 26th ([#2998](https://github.com/nomic-ai/gpt4all/pull/2998))
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- Change the error message when a message is too long ([#3004](https://github.com/nomic-ai/gpt4all/pull/3004))
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- Fix CalledProcessError on Intel Macs since v2.8.0 ([#3045](https://github.com/nomic-ai/gpt4all/pull/3045))
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## [2.8.2] - 2024-08-14
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@ -3,7 +3,6 @@ from __future__ import annotations
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import ctypes
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import os
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import platform
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import re
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import subprocess
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import sys
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import textwrap
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@ -28,16 +27,25 @@ if TYPE_CHECKING:
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EmbeddingsType = TypeVar('EmbeddingsType', bound='list[Any]')
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cuda_found: bool = False
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# TODO(jared): use operator.call after we drop python 3.10 support
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def _operator_call(obj, /, *args, **kwargs):
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return obj(*args, **kwargs)
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# Detect Rosetta 2
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if platform.system() == "Darwin" and platform.processor() == "i386":
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if subprocess.run(
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"sysctl -n sysctl.proc_translated".split(), check=True, capture_output=True, text=True,
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).stdout.strip() == "1":
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raise RuntimeError(textwrap.dedent("""\
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Running GPT4All under Rosetta is not supported due to CPU feature requirements.
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Please install GPT4All in an environment that uses a native ARM64 Python interpreter.
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""").strip())
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@_operator_call
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def check_rosetta() -> None:
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if platform.system() == "Darwin" and platform.processor() == "i386":
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p = subprocess.run("sysctl -n sysctl.proc_translated".split(), capture_output=True, text=True)
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if p.returncode == 0 and p.stdout.strip() == "1":
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raise RuntimeError(textwrap.dedent("""\
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Running GPT4All under Rosetta is not supported due to CPU feature requirements.
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Please install GPT4All in an environment that uses a native ARM64 Python interpreter.
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""").strip())
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# Check for C++ runtime libraries
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if platform.system() == "Windows":
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@ -53,33 +61,35 @@ if platform.system() == "Windows":
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"""), file=sys.stderr)
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def _load_cuda(rtver: str, blasver: str) -> None:
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if platform.system() == "Linux":
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cudalib = f"lib/libcudart.so.{rtver}"
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cublaslib = f"lib/libcublas.so.{blasver}"
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else: # Windows
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cudalib = fr"bin\cudart64_{rtver.replace('.', '')}.dll"
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cublaslib = fr"bin\cublas64_{blasver}.dll"
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@_operator_call
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def find_cuda() -> None:
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global cuda_found
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# preload the CUDA libs so the backend can find them
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ctypes.CDLL(os.path.join(cuda_runtime.__path__[0], cudalib), mode=ctypes.RTLD_GLOBAL)
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ctypes.CDLL(os.path.join(cublas.__path__[0], cublaslib), mode=ctypes.RTLD_GLOBAL)
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def _load_cuda(rtver: str, blasver: str) -> None:
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if platform.system() == "Linux":
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cudalib = f"lib/libcudart.so.{rtver}"
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cublaslib = f"lib/libcublas.so.{blasver}"
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else: # Windows
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cudalib = fr"bin\cudart64_{rtver.replace('.', '')}.dll"
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cublaslib = fr"bin\cublas64_{blasver}.dll"
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# preload the CUDA libs so the backend can find them
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ctypes.CDLL(os.path.join(cuda_runtime.__path__[0], cudalib), mode=ctypes.RTLD_GLOBAL)
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ctypes.CDLL(os.path.join(cublas.__path__[0], cublaslib), mode=ctypes.RTLD_GLOBAL)
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# Find CUDA libraries from the official packages
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cuda_found = False
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if platform.system() in ("Linux", "Windows"):
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try:
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from nvidia import cuda_runtime, cublas
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except ImportError:
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pass # CUDA is optional
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else:
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for rtver, blasver in [("12", "12"), ("11.0", "11")]:
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try:
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_load_cuda(rtver, blasver)
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cuda_found = True
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except OSError: # dlopen() does not give specific error codes
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pass # try the next one
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# Find CUDA libraries from the official packages
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if platform.system() in ("Linux", "Windows"):
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try:
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from nvidia import cuda_runtime, cublas
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except ImportError:
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pass # CUDA is optional
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else:
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for rtver, blasver in [("12", "12"), ("11.0", "11")]:
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try:
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_load_cuda(rtver, blasver)
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cuda_found = True
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except OSError: # dlopen() does not give specific error codes
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pass # try the next one
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# TODO: provide a config file to make this more robust
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@ -121,6 +131,7 @@ class LLModelPromptContext(ctypes.Structure):
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("context_erase", ctypes.c_float),
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]
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class LLModelGPUDevice(ctypes.Structure):
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_fields_ = [
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("backend", ctypes.c_char_p),
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@ -131,6 +142,7 @@ class LLModelGPUDevice(ctypes.Structure):
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("vendor", ctypes.c_char_p),
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]
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# Define C function signatures using ctypes
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llmodel.llmodel_model_create.argtypes = [ctypes.c_char_p]
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llmodel.llmodel_model_create.restype = ctypes.c_void_p
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@ -540,7 +552,6 @@ class LLModel:
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ctypes.c_char_p(),
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)
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def prompt_model_streaming(
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self, prompt: str, prompt_template: str, callback: ResponseCallbackType = empty_response_callback, **kwargs
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) -> Iterable[str]:
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@ -589,16 +600,16 @@ class LLModel:
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decoded = []
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for byte in response:
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bits = "{:08b}".format(byte)
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(high_ones, _, _) = bits.partition('0')
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if len(high_ones) == 1:
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if len(high_ones) == 1:
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# continuation byte
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self.buffer.append(byte)
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self.buff_expecting_cont_bytes -= 1
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else:
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else:
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# beginning of a byte sequence
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if len(self.buffer) > 0:
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decoded.append(self.buffer.decode(errors='replace'))
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@ -608,18 +619,18 @@ class LLModel:
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self.buffer.append(byte)
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self.buff_expecting_cont_bytes = max(0, len(high_ones) - 1)
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if self.buff_expecting_cont_bytes <= 0:
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if self.buff_expecting_cont_bytes <= 0:
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# received the whole sequence or an out of place continuation byte
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decoded.append(self.buffer.decode(errors='replace'))
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self.buffer.clear()
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self.buff_expecting_cont_bytes = 0
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if len(decoded) == 0 and self.buff_expecting_cont_bytes > 0:
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# wait for more continuation bytes
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return True
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return callback(token_id, ''.join(decoded))
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return callback(token_id, ''.join(decoded))
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return _raw_callback
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@ -8,7 +8,6 @@ import os
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import platform
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import re
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import sys
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import time
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import warnings
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from contextlib import contextmanager
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from pathlib import Path
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