diff --git a/.gitattributes b/.gitattributes index e6b57dd8aa3a017f4741130af12ddfae59fa37fc..c52c9b5a435bfb59b08f02c0a2b7dd9070529090 100644 --- a/.gitattributes +++ b/.gitattributes @@ -175,3 +175,4 @@ env-llmeval/lib/python3.10/site-packages/pandas/_libs/interval.cpython-310-x86_6 env-llmeval/lib/python3.10/site-packages/pandas/_libs/tslibs/offsets.cpython-310-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text env-llmeval/lib/python3.10/site-packages/pandas/_libs/algos.cpython-310-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text env-llmeval/lib/python3.10/site-packages/pandas/_libs/groupby.cpython-310-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text +env-llmeval/lib/python3.10/site-packages/regex/_regex.cpython-310-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text diff --git a/env-llmeval/lib/python3.10/site-packages/_yaml/__init__.py b/env-llmeval/lib/python3.10/site-packages/_yaml/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..7baa8c4b68127d5cdf0be9a799429e61347c2694 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/_yaml/__init__.py @@ -0,0 +1,33 @@ +# This is a stub package designed to roughly emulate the _yaml +# extension module, which previously existed as a standalone module +# and has been moved into the `yaml` package namespace. +# It does not perfectly mimic its old counterpart, but should get +# close enough for anyone who's relying on it even when they shouldn't. +import yaml + +# in some circumstances, the yaml module we imoprted may be from a different version, so we need +# to tread carefully when poking at it here (it may not have the attributes we expect) +if not getattr(yaml, '__with_libyaml__', False): + from sys import version_info + + exc = ModuleNotFoundError if version_info >= (3, 6) else ImportError + raise exc("No module named '_yaml'") +else: + from yaml._yaml import * + import warnings + warnings.warn( + 'The _yaml extension module is now located at yaml._yaml' + ' and its location is subject to change. To use the' + ' LibYAML-based parser and emitter, import from `yaml`:' + ' `from yaml import CLoader as Loader, CDumper as Dumper`.', + DeprecationWarning + ) + del warnings + # Don't `del yaml` here because yaml is actually an existing + # namespace member of _yaml. + +__name__ = '_yaml' +# If the module is top-level (i.e. not a part of any specific package) +# then the attribute should be set to ''. +# https://docs.python.org/3.8/library/types.html +__package__ = '' diff --git a/env-llmeval/lib/python3.10/site-packages/_yaml/__pycache__/__init__.cpython-310.pyc b/env-llmeval/lib/python3.10/site-packages/_yaml/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..54a8fc778eb6225e49d54ea42954037c45ab74a6 Binary files /dev/null and b/env-llmeval/lib/python3.10/site-packages/_yaml/__pycache__/__init__.cpython-310.pyc differ diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/__main__.py 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b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/api.py new file mode 100644 index 0000000000000000000000000000000000000000..0ba08e3a50ba6d61e75f3f31772eb4dfdd3f8f05 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/api.py @@ -0,0 +1,626 @@ +import logging +from os import PathLike +from typing import BinaryIO, List, Optional, Set, Union + +from .cd import ( + coherence_ratio, + encoding_languages, + mb_encoding_languages, + merge_coherence_ratios, +) +from .constant import IANA_SUPPORTED, TOO_BIG_SEQUENCE, TOO_SMALL_SEQUENCE, TRACE +from .md import mess_ratio +from .models import CharsetMatch, CharsetMatches +from .utils import ( + any_specified_encoding, + cut_sequence_chunks, + iana_name, + identify_sig_or_bom, + is_cp_similar, + is_multi_byte_encoding, + should_strip_sig_or_bom, +) + +# Will most likely be controversial +# logging.addLevelName(TRACE, "TRACE") +logger = logging.getLogger("charset_normalizer") +explain_handler = logging.StreamHandler() +explain_handler.setFormatter( + logging.Formatter("%(asctime)s | %(levelname)s | %(message)s") +) + + +def from_bytes( + sequences: Union[bytes, bytearray], + steps: int = 5, + chunk_size: int = 512, + threshold: float = 0.2, + cp_isolation: Optional[List[str]] = None, + cp_exclusion: Optional[List[str]] = None, + preemptive_behaviour: bool = True, + explain: bool = False, + language_threshold: float = 0.1, + enable_fallback: bool = True, +) -> CharsetMatches: + """ + Given a raw bytes sequence, return the best possibles charset usable to render str objects. + If there is no results, it is a strong indicator that the source is binary/not text. + By default, the process will extract 5 blocks of 512o each to assess the mess and coherence of a given sequence. + And will give up a particular code page after 20% of measured mess. Those criteria are customizable at will. + + The preemptive behavior DOES NOT replace the traditional detection workflow, it prioritize a particular code page + but never take it for granted. Can improve the performance. + + You may want to focus your attention to some code page or/and not others, use cp_isolation and cp_exclusion for that + purpose. + + This function will strip the SIG in the payload/sequence every time except on UTF-16, UTF-32. + By default the library does not setup any handler other than the NullHandler, if you choose to set the 'explain' + toggle to True it will alter the logger configuration to add a StreamHandler that is suitable for debugging. + Custom logging format and handler can be set manually. + """ + + if not isinstance(sequences, (bytearray, bytes)): + raise TypeError( + "Expected object of type bytes or bytearray, got: {0}".format( + type(sequences) + ) + ) + + if explain: + previous_logger_level: int = logger.level + logger.addHandler(explain_handler) + logger.setLevel(TRACE) + + length: int = len(sequences) + + if length == 0: + logger.debug("Encoding detection on empty bytes, assuming utf_8 intention.") + if explain: + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level or logging.WARNING) + return CharsetMatches([CharsetMatch(sequences, "utf_8", 0.0, False, [], "")]) + + if cp_isolation is not None: + logger.log( + TRACE, + "cp_isolation is set. use this flag for debugging purpose. " + "limited list of encoding allowed : %s.", + ", ".join(cp_isolation), + ) + cp_isolation = [iana_name(cp, False) for cp in cp_isolation] + else: + cp_isolation = [] + + if cp_exclusion is not None: + logger.log( + TRACE, + "cp_exclusion is set. use this flag for debugging purpose. " + "limited list of encoding excluded : %s.", + ", ".join(cp_exclusion), + ) + cp_exclusion = [iana_name(cp, False) for cp in cp_exclusion] + else: + cp_exclusion = [] + + if length <= (chunk_size * steps): + logger.log( + TRACE, + "override steps (%i) and chunk_size (%i) as content does not fit (%i byte(s) given) parameters.", + steps, + chunk_size, + length, + ) + steps = 1 + chunk_size = length + + if steps > 1 and length / steps < chunk_size: + chunk_size = int(length / steps) + + is_too_small_sequence: bool = len(sequences) < TOO_SMALL_SEQUENCE + is_too_large_sequence: bool = len(sequences) >= TOO_BIG_SEQUENCE + + if is_too_small_sequence: + logger.log( + TRACE, + "Trying to detect encoding from a tiny portion of ({}) byte(s).".format( + length + ), + ) + elif is_too_large_sequence: + logger.log( + TRACE, + "Using lazy str decoding because the payload is quite large, ({}) byte(s).".format( + length + ), + ) + + prioritized_encodings: List[str] = [] + + specified_encoding: Optional[str] = ( + any_specified_encoding(sequences) if preemptive_behaviour else None + ) + + if specified_encoding is not None: + prioritized_encodings.append(specified_encoding) + logger.log( + TRACE, + "Detected declarative mark in sequence. Priority +1 given for %s.", + specified_encoding, + ) + + tested: Set[str] = set() + tested_but_hard_failure: List[str] = [] + tested_but_soft_failure: List[str] = [] + + fallback_ascii: Optional[CharsetMatch] = None + fallback_u8: Optional[CharsetMatch] = None + fallback_specified: Optional[CharsetMatch] = None + + results: CharsetMatches = CharsetMatches() + + sig_encoding, sig_payload = identify_sig_or_bom(sequences) + + if sig_encoding is not None: + prioritized_encodings.append(sig_encoding) + logger.log( + TRACE, + "Detected a SIG or BOM mark on first %i byte(s). Priority +1 given for %s.", + len(sig_payload), + sig_encoding, + ) + + prioritized_encodings.append("ascii") + + if "utf_8" not in prioritized_encodings: + prioritized_encodings.append("utf_8") + + for encoding_iana in prioritized_encodings + IANA_SUPPORTED: + if cp_isolation and encoding_iana not in cp_isolation: + continue + + if cp_exclusion and encoding_iana in cp_exclusion: + continue + + if encoding_iana in tested: + continue + + tested.add(encoding_iana) + + decoded_payload: Optional[str] = None + bom_or_sig_available: bool = sig_encoding == encoding_iana + strip_sig_or_bom: bool = bom_or_sig_available and should_strip_sig_or_bom( + encoding_iana + ) + + if encoding_iana in {"utf_16", "utf_32"} and not bom_or_sig_available: + logger.log( + TRACE, + "Encoding %s won't be tested as-is because it require a BOM. Will try some sub-encoder LE/BE.", + encoding_iana, + ) + continue + if encoding_iana in {"utf_7"} and not bom_or_sig_available: + logger.log( + TRACE, + "Encoding %s won't be tested as-is because detection is unreliable without BOM/SIG.", + encoding_iana, + ) + continue + + try: + is_multi_byte_decoder: bool = is_multi_byte_encoding(encoding_iana) + except (ModuleNotFoundError, ImportError): + logger.log( + TRACE, + "Encoding %s does not provide an IncrementalDecoder", + encoding_iana, + ) + continue + + try: + if is_too_large_sequence and is_multi_byte_decoder is False: + str( + sequences[: int(50e4)] + if strip_sig_or_bom is False + else sequences[len(sig_payload) : int(50e4)], + encoding=encoding_iana, + ) + else: + decoded_payload = str( + sequences + if strip_sig_or_bom is False + else sequences[len(sig_payload) :], + encoding=encoding_iana, + ) + except (UnicodeDecodeError, LookupError) as e: + if not isinstance(e, LookupError): + logger.log( + TRACE, + "Code page %s does not fit given bytes sequence at ALL. %s", + encoding_iana, + str(e), + ) + tested_but_hard_failure.append(encoding_iana) + continue + + similar_soft_failure_test: bool = False + + for encoding_soft_failed in tested_but_soft_failure: + if is_cp_similar(encoding_iana, encoding_soft_failed): + similar_soft_failure_test = True + break + + if similar_soft_failure_test: + logger.log( + TRACE, + "%s is deemed too similar to code page %s and was consider unsuited already. Continuing!", + encoding_iana, + encoding_soft_failed, + ) + continue + + r_ = range( + 0 if not bom_or_sig_available else len(sig_payload), + length, + int(length / steps), + ) + + multi_byte_bonus: bool = ( + is_multi_byte_decoder + and decoded_payload is not None + and len(decoded_payload) < length + ) + + if multi_byte_bonus: + logger.log( + TRACE, + "Code page %s is a multi byte encoding table and it appear that at least one character " + "was encoded using n-bytes.", + encoding_iana, + ) + + max_chunk_gave_up: int = int(len(r_) / 4) + + max_chunk_gave_up = max(max_chunk_gave_up, 2) + early_stop_count: int = 0 + lazy_str_hard_failure = False + + md_chunks: List[str] = [] + md_ratios = [] + + try: + for chunk in cut_sequence_chunks( + sequences, + encoding_iana, + r_, + chunk_size, + bom_or_sig_available, + strip_sig_or_bom, + sig_payload, + is_multi_byte_decoder, + decoded_payload, + ): + md_chunks.append(chunk) + + md_ratios.append( + mess_ratio( + chunk, + threshold, + explain is True and 1 <= len(cp_isolation) <= 2, + ) + ) + + if md_ratios[-1] >= threshold: + early_stop_count += 1 + + if (early_stop_count >= max_chunk_gave_up) or ( + bom_or_sig_available and strip_sig_or_bom is False + ): + break + except ( + UnicodeDecodeError + ) as e: # Lazy str loading may have missed something there + logger.log( + TRACE, + "LazyStr Loading: After MD chunk decode, code page %s does not fit given bytes sequence at ALL. %s", + encoding_iana, + str(e), + ) + early_stop_count = max_chunk_gave_up + lazy_str_hard_failure = True + + # We might want to check the sequence again with the whole content + # Only if initial MD tests passes + if ( + not lazy_str_hard_failure + and is_too_large_sequence + and not is_multi_byte_decoder + ): + try: + sequences[int(50e3) :].decode(encoding_iana, errors="strict") + except UnicodeDecodeError as e: + logger.log( + TRACE, + "LazyStr Loading: After final lookup, code page %s does not fit given bytes sequence at ALL. %s", + encoding_iana, + str(e), + ) + tested_but_hard_failure.append(encoding_iana) + continue + + mean_mess_ratio: float = sum(md_ratios) / len(md_ratios) if md_ratios else 0.0 + if mean_mess_ratio >= threshold or early_stop_count >= max_chunk_gave_up: + tested_but_soft_failure.append(encoding_iana) + logger.log( + TRACE, + "%s was excluded because of initial chaos probing. Gave up %i time(s). " + "Computed mean chaos is %f %%.", + encoding_iana, + early_stop_count, + round(mean_mess_ratio * 100, ndigits=3), + ) + # Preparing those fallbacks in case we got nothing. + if ( + enable_fallback + and encoding_iana in ["ascii", "utf_8", specified_encoding] + and not lazy_str_hard_failure + ): + fallback_entry = CharsetMatch( + sequences, encoding_iana, threshold, False, [], decoded_payload + ) + if encoding_iana == specified_encoding: + fallback_specified = fallback_entry + elif encoding_iana == "ascii": + fallback_ascii = fallback_entry + else: + fallback_u8 = fallback_entry + continue + + logger.log( + TRACE, + "%s passed initial chaos probing. Mean measured chaos is %f %%", + encoding_iana, + round(mean_mess_ratio * 100, ndigits=3), + ) + + if not is_multi_byte_decoder: + target_languages: List[str] = encoding_languages(encoding_iana) + else: + target_languages = mb_encoding_languages(encoding_iana) + + if target_languages: + logger.log( + TRACE, + "{} should target any language(s) of {}".format( + encoding_iana, str(target_languages) + ), + ) + + cd_ratios = [] + + # We shall skip the CD when its about ASCII + # Most of the time its not relevant to run "language-detection" on it. + if encoding_iana != "ascii": + for chunk in md_chunks: + chunk_languages = coherence_ratio( + chunk, + language_threshold, + ",".join(target_languages) if target_languages else None, + ) + + cd_ratios.append(chunk_languages) + + cd_ratios_merged = merge_coherence_ratios(cd_ratios) + + if cd_ratios_merged: + logger.log( + TRACE, + "We detected language {} using {}".format( + cd_ratios_merged, encoding_iana + ), + ) + + results.append( + CharsetMatch( + sequences, + encoding_iana, + mean_mess_ratio, + bom_or_sig_available, + cd_ratios_merged, + decoded_payload, + ) + ) + + if ( + encoding_iana in [specified_encoding, "ascii", "utf_8"] + and mean_mess_ratio < 0.1 + ): + logger.debug( + "Encoding detection: %s is most likely the one.", encoding_iana + ) + if explain: + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + return CharsetMatches([results[encoding_iana]]) + + if encoding_iana == sig_encoding: + logger.debug( + "Encoding detection: %s is most likely the one as we detected a BOM or SIG within " + "the beginning of the sequence.", + encoding_iana, + ) + if explain: + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + return CharsetMatches([results[encoding_iana]]) + + if len(results) == 0: + if fallback_u8 or fallback_ascii or fallback_specified: + logger.log( + TRACE, + "Nothing got out of the detection process. Using ASCII/UTF-8/Specified fallback.", + ) + + if fallback_specified: + logger.debug( + "Encoding detection: %s will be used as a fallback match", + fallback_specified.encoding, + ) + results.append(fallback_specified) + elif ( + (fallback_u8 and fallback_ascii is None) + or ( + fallback_u8 + and fallback_ascii + and fallback_u8.fingerprint != fallback_ascii.fingerprint + ) + or (fallback_u8 is not None) + ): + logger.debug("Encoding detection: utf_8 will be used as a fallback match") + results.append(fallback_u8) + elif fallback_ascii: + logger.debug("Encoding detection: ascii will be used as a fallback match") + results.append(fallback_ascii) + + if results: + logger.debug( + "Encoding detection: Found %s as plausible (best-candidate) for content. With %i alternatives.", + results.best().encoding, # type: ignore + len(results) - 1, + ) + else: + logger.debug("Encoding detection: Unable to determine any suitable charset.") + + if explain: + logger.removeHandler(explain_handler) + logger.setLevel(previous_logger_level) + + return results + + +def from_fp( + fp: BinaryIO, + steps: int = 5, + chunk_size: int = 512, + threshold: float = 0.20, + cp_isolation: Optional[List[str]] = None, + cp_exclusion: Optional[List[str]] = None, + preemptive_behaviour: bool = True, + explain: bool = False, + language_threshold: float = 0.1, + enable_fallback: bool = True, +) -> CharsetMatches: + """ + Same thing than the function from_bytes but using a file pointer that is already ready. + Will not close the file pointer. + """ + return from_bytes( + fp.read(), + steps, + chunk_size, + threshold, + cp_isolation, + cp_exclusion, + preemptive_behaviour, + explain, + language_threshold, + enable_fallback, + ) + + +def from_path( + path: Union[str, bytes, PathLike], # type: ignore[type-arg] + steps: int = 5, + chunk_size: int = 512, + threshold: float = 0.20, + cp_isolation: Optional[List[str]] = None, + cp_exclusion: Optional[List[str]] = None, + preemptive_behaviour: bool = True, + explain: bool = False, + language_threshold: float = 0.1, + enable_fallback: bool = True, +) -> CharsetMatches: + """ + Same thing than the function from_bytes but with one extra step. Opening and reading given file path in binary mode. + Can raise IOError. + """ + with open(path, "rb") as fp: + return from_fp( + fp, + steps, + chunk_size, + threshold, + cp_isolation, + cp_exclusion, + preemptive_behaviour, + explain, + language_threshold, + enable_fallback, + ) + + +def is_binary( + fp_or_path_or_payload: Union[PathLike, str, BinaryIO, bytes], # type: ignore[type-arg] + steps: int = 5, + chunk_size: int = 512, + threshold: float = 0.20, + cp_isolation: Optional[List[str]] = None, + cp_exclusion: Optional[List[str]] = None, + preemptive_behaviour: bool = True, + explain: bool = False, + language_threshold: float = 0.1, + enable_fallback: bool = False, +) -> bool: + """ + Detect if the given input (file, bytes, or path) points to a binary file. aka. not a string. + Based on the same main heuristic algorithms and default kwargs at the sole exception that fallbacks match + are disabled to be stricter around ASCII-compatible but unlikely to be a string. + """ + if isinstance(fp_or_path_or_payload, (str, PathLike)): + guesses = from_path( + fp_or_path_or_payload, + steps=steps, + chunk_size=chunk_size, + threshold=threshold, + cp_isolation=cp_isolation, + cp_exclusion=cp_exclusion, + preemptive_behaviour=preemptive_behaviour, + explain=explain, + language_threshold=language_threshold, + enable_fallback=enable_fallback, + ) + elif isinstance( + fp_or_path_or_payload, + ( + bytes, + bytearray, + ), + ): + guesses = from_bytes( + fp_or_path_or_payload, + steps=steps, + chunk_size=chunk_size, + threshold=threshold, + cp_isolation=cp_isolation, + cp_exclusion=cp_exclusion, + preemptive_behaviour=preemptive_behaviour, + explain=explain, + language_threshold=language_threshold, + enable_fallback=enable_fallback, + ) + else: + guesses = from_fp( + fp_or_path_or_payload, + steps=steps, + chunk_size=chunk_size, + threshold=threshold, + cp_isolation=cp_isolation, + cp_exclusion=cp_exclusion, + preemptive_behaviour=preemptive_behaviour, + explain=explain, + language_threshold=language_threshold, + enable_fallback=enable_fallback, + ) + + return not guesses diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/cli/__init__.py b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/cli/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..d95fedfe5723713337f1a94ec8f0a00b6ca7816a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/cli/__init__.py @@ -0,0 +1,6 @@ +from .__main__ import cli_detect, query_yes_no + +__all__ = ( + "cli_detect", + "query_yes_no", +) diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/cli/__main__.py b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/cli/__main__.py new file mode 100644 index 0000000000000000000000000000000000000000..f4bcbaac049b542a004918a0b1499122fcca9cc0 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/cli/__main__.py @@ -0,0 +1,296 @@ +import argparse +import sys +from json import dumps +from os.path import abspath, basename, dirname, join, realpath +from platform import python_version +from typing import List, Optional +from unicodedata import unidata_version + +import charset_normalizer.md as md_module +from charset_normalizer import from_fp +from charset_normalizer.models import CliDetectionResult +from charset_normalizer.version import __version__ + + +def query_yes_no(question: str, default: str = "yes") -> bool: + """Ask a yes/no question via input() and return their answer. + + "question" is a string that is presented to the user. + "default" is the presumed answer if the user just hits . + It must be "yes" (the default), "no" or None (meaning + an answer is required of the user). + + The "answer" return value is True for "yes" or False for "no". + + Credit goes to (c) https://stackoverflow.com/questions/3041986/apt-command-line-interface-like-yes-no-input + """ + valid = {"yes": True, "y": True, "ye": True, "no": False, "n": False} + if default is None: + prompt = " [y/n] " + elif default == "yes": + prompt = " [Y/n] " + elif default == "no": + prompt = " [y/N] " + else: + raise ValueError("invalid default answer: '%s'" % default) + + while True: + sys.stdout.write(question + prompt) + choice = input().lower() + if default is not None and choice == "": + return valid[default] + elif choice in valid: + return valid[choice] + else: + sys.stdout.write("Please respond with 'yes' or 'no' " "(or 'y' or 'n').\n") + + +def cli_detect(argv: Optional[List[str]] = None) -> int: + """ + CLI assistant using ARGV and ArgumentParser + :param argv: + :return: 0 if everything is fine, anything else equal trouble + """ + parser = argparse.ArgumentParser( + description="The Real First Universal Charset Detector. " + "Discover originating encoding used on text file. " + "Normalize text to unicode." + ) + + parser.add_argument( + "files", type=argparse.FileType("rb"), nargs="+", help="File(s) to be analysed" + ) + parser.add_argument( + "-v", + "--verbose", + action="store_true", + default=False, + dest="verbose", + help="Display complementary information about file if any. " + "Stdout will contain logs about the detection process.", + ) + parser.add_argument( + "-a", + "--with-alternative", + action="store_true", + default=False, + dest="alternatives", + help="Output complementary possibilities if any. Top-level JSON WILL be a list.", + ) + parser.add_argument( + "-n", + "--normalize", + action="store_true", + default=False, + dest="normalize", + help="Permit to normalize input file. If not set, program does not write anything.", + ) + parser.add_argument( + "-m", + "--minimal", + action="store_true", + default=False, + dest="minimal", + help="Only output the charset detected to STDOUT. Disabling JSON output.", + ) + parser.add_argument( + "-r", + "--replace", + action="store_true", + default=False, + dest="replace", + help="Replace file when trying to normalize it instead of creating a new one.", + ) + parser.add_argument( + "-f", + "--force", + action="store_true", + default=False, + dest="force", + help="Replace file without asking if you are sure, use this flag with caution.", + ) + parser.add_argument( + "-t", + "--threshold", + action="store", + default=0.2, + type=float, + dest="threshold", + help="Define a custom maximum amount of chaos allowed in decoded content. 0. <= chaos <= 1.", + ) + parser.add_argument( + "--version", + action="version", + version="Charset-Normalizer {} - Python {} - Unicode {} - SpeedUp {}".format( + __version__, + python_version(), + unidata_version, + "OFF" if md_module.__file__.lower().endswith(".py") else "ON", + ), + help="Show version information and exit.", + ) + + args = parser.parse_args(argv) + + if args.replace is True and args.normalize is False: + print("Use --replace in addition of --normalize only.", file=sys.stderr) + return 1 + + if args.force is True and args.replace is False: + print("Use --force in addition of --replace only.", file=sys.stderr) + return 1 + + if args.threshold < 0.0 or args.threshold > 1.0: + print("--threshold VALUE should be between 0. AND 1.", file=sys.stderr) + return 1 + + x_ = [] + + for my_file in args.files: + matches = from_fp(my_file, threshold=args.threshold, explain=args.verbose) + + best_guess = matches.best() + + if best_guess is None: + print( + 'Unable to identify originating encoding for "{}". {}'.format( + my_file.name, + "Maybe try increasing maximum amount of chaos." + if args.threshold < 1.0 + else "", + ), + file=sys.stderr, + ) + x_.append( + CliDetectionResult( + abspath(my_file.name), + None, + [], + [], + "Unknown", + [], + False, + 1.0, + 0.0, + None, + True, + ) + ) + else: + x_.append( + CliDetectionResult( + abspath(my_file.name), + best_guess.encoding, + best_guess.encoding_aliases, + [ + cp + for cp in best_guess.could_be_from_charset + if cp != best_guess.encoding + ], + best_guess.language, + best_guess.alphabets, + best_guess.bom, + best_guess.percent_chaos, + best_guess.percent_coherence, + None, + True, + ) + ) + + if len(matches) > 1 and args.alternatives: + for el in matches: + if el != best_guess: + x_.append( + CliDetectionResult( + abspath(my_file.name), + el.encoding, + el.encoding_aliases, + [ + cp + for cp in el.could_be_from_charset + if cp != el.encoding + ], + el.language, + el.alphabets, + el.bom, + el.percent_chaos, + el.percent_coherence, + None, + False, + ) + ) + + if args.normalize is True: + if best_guess.encoding.startswith("utf") is True: + print( + '"{}" file does not need to be normalized, as it already came from unicode.'.format( + my_file.name + ), + file=sys.stderr, + ) + if my_file.closed is False: + my_file.close() + continue + + dir_path = dirname(realpath(my_file.name)) + file_name = basename(realpath(my_file.name)) + + o_: List[str] = file_name.split(".") + + if args.replace is False: + o_.insert(-1, best_guess.encoding) + if my_file.closed is False: + my_file.close() + elif ( + args.force is False + and query_yes_no( + 'Are you sure to normalize "{}" by replacing it ?'.format( + my_file.name + ), + "no", + ) + is False + ): + if my_file.closed is False: + my_file.close() + continue + + try: + x_[0].unicode_path = join(dir_path, ".".join(o_)) + + with open(x_[0].unicode_path, "w", encoding="utf-8") as fp: + fp.write(str(best_guess)) + except IOError as e: + print(str(e), file=sys.stderr) + if my_file.closed is False: + my_file.close() + return 2 + + if my_file.closed is False: + my_file.close() + + if args.minimal is False: + print( + dumps( + [el.__dict__ for el in x_] if len(x_) > 1 else x_[0].__dict__, + ensure_ascii=True, + indent=4, + ) + ) + else: + for my_file in args.files: + print( + ", ".join( + [ + el.encoding or "undefined" + for el in x_ + if el.path == abspath(my_file.name) + ] + ) + ) + + return 0 + + +if __name__ == "__main__": + cli_detect() diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/cli/__pycache__/__init__.cpython-310.pyc b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/cli/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 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b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/constant.py @@ -0,0 +1,1995 @@ +# -*- coding: utf-8 -*- +from codecs import BOM_UTF8, BOM_UTF16_BE, BOM_UTF16_LE, BOM_UTF32_BE, BOM_UTF32_LE +from encodings.aliases import aliases +from re import IGNORECASE, compile as re_compile +from typing import Dict, List, Set, Union + +# Contain for each eligible encoding a list of/item bytes SIG/BOM +ENCODING_MARKS: Dict[str, Union[bytes, List[bytes]]] = { + "utf_8": BOM_UTF8, + "utf_7": [ + b"\x2b\x2f\x76\x38", + b"\x2b\x2f\x76\x39", + b"\x2b\x2f\x76\x2b", + b"\x2b\x2f\x76\x2f", + b"\x2b\x2f\x76\x38\x2d", + ], + "gb18030": b"\x84\x31\x95\x33", + "utf_32": [BOM_UTF32_BE, BOM_UTF32_LE], + "utf_16": [BOM_UTF16_BE, BOM_UTF16_LE], +} + +TOO_SMALL_SEQUENCE: int = 32 +TOO_BIG_SEQUENCE: int = int(10e6) + +UTF8_MAXIMAL_ALLOCATION: int = 1_112_064 + +# Up-to-date Unicode ucd/15.0.0 +UNICODE_RANGES_COMBINED: Dict[str, range] = { + "Control character": range(32), + "Basic Latin": range(32, 128), + "Latin-1 Supplement": range(128, 256), + "Latin Extended-A": range(256, 384), + "Latin Extended-B": range(384, 592), + "IPA Extensions": range(592, 688), + "Spacing Modifier Letters": range(688, 768), + "Combining Diacritical Marks": range(768, 880), + "Greek and Coptic": range(880, 1024), + "Cyrillic": range(1024, 1280), + "Cyrillic Supplement": range(1280, 1328), + "Armenian": range(1328, 1424), + "Hebrew": range(1424, 1536), + "Arabic": range(1536, 1792), + "Syriac": range(1792, 1872), + "Arabic Supplement": range(1872, 1920), + "Thaana": range(1920, 1984), + "NKo": range(1984, 2048), + "Samaritan": range(2048, 2112), + "Mandaic": range(2112, 2144), + "Syriac Supplement": range(2144, 2160), + "Arabic Extended-B": range(2160, 2208), + "Arabic Extended-A": range(2208, 2304), + "Devanagari": range(2304, 2432), + "Bengali": range(2432, 2560), + "Gurmukhi": range(2560, 2688), + "Gujarati": range(2688, 2816), + "Oriya": range(2816, 2944), + "Tamil": range(2944, 3072), + "Telugu": range(3072, 3200), + "Kannada": range(3200, 3328), + "Malayalam": range(3328, 3456), + "Sinhala": range(3456, 3584), + "Thai": range(3584, 3712), + "Lao": range(3712, 3840), + "Tibetan": range(3840, 4096), + "Myanmar": range(4096, 4256), + "Georgian": range(4256, 4352), + "Hangul Jamo": range(4352, 4608), + "Ethiopic": range(4608, 4992), + "Ethiopic Supplement": range(4992, 5024), + "Cherokee": range(5024, 5120), + "Unified Canadian Aboriginal Syllabics": range(5120, 5760), + "Ogham": range(5760, 5792), + "Runic": range(5792, 5888), + "Tagalog": range(5888, 5920), + "Hanunoo": range(5920, 5952), + "Buhid": range(5952, 5984), + "Tagbanwa": range(5984, 6016), + "Khmer": range(6016, 6144), + "Mongolian": range(6144, 6320), + "Unified Canadian Aboriginal Syllabics Extended": range(6320, 6400), + "Limbu": range(6400, 6480), + "Tai Le": range(6480, 6528), + "New Tai Lue": range(6528, 6624), + "Khmer Symbols": range(6624, 6656), + "Buginese": range(6656, 6688), + "Tai Tham": range(6688, 6832), + "Combining Diacritical Marks Extended": range(6832, 6912), + "Balinese": range(6912, 7040), + "Sundanese": range(7040, 7104), + "Batak": range(7104, 7168), + "Lepcha": range(7168, 7248), + "Ol Chiki": range(7248, 7296), + "Cyrillic Extended-C": range(7296, 7312), + "Georgian Extended": range(7312, 7360), + "Sundanese Supplement": range(7360, 7376), + "Vedic Extensions": range(7376, 7424), + "Phonetic Extensions": range(7424, 7552), + "Phonetic Extensions Supplement": range(7552, 7616), + "Combining Diacritical Marks Supplement": range(7616, 7680), + "Latin Extended Additional": range(7680, 7936), + "Greek Extended": range(7936, 8192), + "General Punctuation": range(8192, 8304), + "Superscripts and Subscripts": range(8304, 8352), + "Currency Symbols": range(8352, 8400), + "Combining Diacritical Marks for Symbols": range(8400, 8448), + "Letterlike Symbols": range(8448, 8528), + "Number Forms": range(8528, 8592), + "Arrows": range(8592, 8704), + "Mathematical Operators": range(8704, 8960), + "Miscellaneous Technical": range(8960, 9216), + "Control Pictures": range(9216, 9280), + "Optical Character Recognition": range(9280, 9312), + "Enclosed Alphanumerics": range(9312, 9472), + "Box Drawing": range(9472, 9600), + "Block Elements": range(9600, 9632), + "Geometric Shapes": range(9632, 9728), + "Miscellaneous Symbols": range(9728, 9984), + "Dingbats": range(9984, 10176), + "Miscellaneous Mathematical Symbols-A": range(10176, 10224), + "Supplemental Arrows-A": range(10224, 10240), + "Braille Patterns": range(10240, 10496), + "Supplemental Arrows-B": range(10496, 10624), + "Miscellaneous Mathematical Symbols-B": range(10624, 10752), + "Supplemental Mathematical Operators": range(10752, 11008), + "Miscellaneous Symbols and Arrows": range(11008, 11264), + "Glagolitic": range(11264, 11360), + "Latin Extended-C": range(11360, 11392), + "Coptic": range(11392, 11520), + "Georgian Supplement": range(11520, 11568), + "Tifinagh": range(11568, 11648), + "Ethiopic Extended": range(11648, 11744), + "Cyrillic Extended-A": range(11744, 11776), + "Supplemental Punctuation": range(11776, 11904), + "CJK Radicals Supplement": range(11904, 12032), + "Kangxi Radicals": range(12032, 12256), + "Ideographic Description Characters": range(12272, 12288), + "CJK Symbols and Punctuation": range(12288, 12352), + "Hiragana": range(12352, 12448), + "Katakana": range(12448, 12544), + "Bopomofo": range(12544, 12592), + "Hangul Compatibility Jamo": range(12592, 12688), + "Kanbun": range(12688, 12704), + "Bopomofo Extended": range(12704, 12736), + "CJK Strokes": range(12736, 12784), + "Katakana Phonetic Extensions": range(12784, 12800), + "Enclosed CJK Letters and Months": range(12800, 13056), + "CJK Compatibility": range(13056, 13312), + "CJK Unified Ideographs Extension A": range(13312, 19904), + "Yijing Hexagram Symbols": range(19904, 19968), + "CJK Unified Ideographs": range(19968, 40960), + "Yi Syllables": range(40960, 42128), + "Yi Radicals": range(42128, 42192), + "Lisu": range(42192, 42240), + "Vai": range(42240, 42560), + "Cyrillic Extended-B": range(42560, 42656), + "Bamum": range(42656, 42752), + "Modifier Tone Letters": range(42752, 42784), + "Latin Extended-D": range(42784, 43008), + "Syloti Nagri": range(43008, 43056), + "Common Indic Number Forms": range(43056, 43072), + "Phags-pa": range(43072, 43136), + "Saurashtra": range(43136, 43232), + "Devanagari Extended": range(43232, 43264), + "Kayah Li": range(43264, 43312), + "Rejang": range(43312, 43360), + "Hangul Jamo Extended-A": range(43360, 43392), + "Javanese": range(43392, 43488), + "Myanmar Extended-B": range(43488, 43520), + "Cham": range(43520, 43616), + "Myanmar Extended-A": range(43616, 43648), + "Tai Viet": range(43648, 43744), + "Meetei Mayek Extensions": range(43744, 43776), + "Ethiopic Extended-A": range(43776, 43824), + "Latin Extended-E": range(43824, 43888), + "Cherokee Supplement": range(43888, 43968), + "Meetei Mayek": range(43968, 44032), + "Hangul Syllables": range(44032, 55216), + "Hangul Jamo Extended-B": range(55216, 55296), + "High Surrogates": range(55296, 56192), + "High Private Use Surrogates": range(56192, 56320), + "Low Surrogates": range(56320, 57344), + "Private Use Area": range(57344, 63744), + "CJK Compatibility Ideographs": range(63744, 64256), + "Alphabetic Presentation Forms": range(64256, 64336), + "Arabic Presentation Forms-A": range(64336, 65024), + "Variation Selectors": range(65024, 65040), + "Vertical Forms": range(65040, 65056), + "Combining Half Marks": range(65056, 65072), + "CJK Compatibility Forms": range(65072, 65104), + "Small Form Variants": range(65104, 65136), + "Arabic Presentation Forms-B": range(65136, 65280), + "Halfwidth and Fullwidth Forms": range(65280, 65520), + "Specials": range(65520, 65536), + "Linear B Syllabary": range(65536, 65664), + "Linear B Ideograms": range(65664, 65792), + "Aegean Numbers": range(65792, 65856), + "Ancient Greek Numbers": range(65856, 65936), + "Ancient Symbols": range(65936, 66000), + "Phaistos Disc": range(66000, 66048), + "Lycian": range(66176, 66208), + "Carian": range(66208, 66272), + "Coptic Epact Numbers": range(66272, 66304), + "Old Italic": range(66304, 66352), + "Gothic": range(66352, 66384), + "Old Permic": range(66384, 66432), + "Ugaritic": range(66432, 66464), + "Old Persian": range(66464, 66528), + "Deseret": range(66560, 66640), + "Shavian": range(66640, 66688), + "Osmanya": range(66688, 66736), + "Osage": range(66736, 66816), + "Elbasan": range(66816, 66864), + "Caucasian Albanian": range(66864, 66928), + "Vithkuqi": range(66928, 67008), + "Linear A": range(67072, 67456), + "Latin Extended-F": range(67456, 67520), + "Cypriot Syllabary": range(67584, 67648), + "Imperial Aramaic": range(67648, 67680), + "Palmyrene": range(67680, 67712), + "Nabataean": range(67712, 67760), + "Hatran": range(67808, 67840), + "Phoenician": range(67840, 67872), + "Lydian": range(67872, 67904), + "Meroitic Hieroglyphs": range(67968, 68000), + "Meroitic Cursive": range(68000, 68096), + "Kharoshthi": range(68096, 68192), + "Old South Arabian": range(68192, 68224), + "Old North Arabian": range(68224, 68256), + "Manichaean": range(68288, 68352), + "Avestan": range(68352, 68416), + "Inscriptional Parthian": range(68416, 68448), + "Inscriptional Pahlavi": range(68448, 68480), + "Psalter Pahlavi": range(68480, 68528), + "Old Turkic": range(68608, 68688), + "Old Hungarian": range(68736, 68864), + "Hanifi Rohingya": range(68864, 68928), + "Rumi Numeral Symbols": range(69216, 69248), + "Yezidi": range(69248, 69312), + "Arabic Extended-C": range(69312, 69376), + "Old Sogdian": range(69376, 69424), + "Sogdian": range(69424, 69488), + "Old Uyghur": range(69488, 69552), + "Chorasmian": range(69552, 69600), + "Elymaic": range(69600, 69632), + "Brahmi": range(69632, 69760), + "Kaithi": range(69760, 69840), + "Sora Sompeng": range(69840, 69888), + "Chakma": range(69888, 69968), + "Mahajani": range(69968, 70016), + "Sharada": range(70016, 70112), + "Sinhala Archaic Numbers": range(70112, 70144), + "Khojki": range(70144, 70224), + "Multani": range(70272, 70320), + "Khudawadi": range(70320, 70400), + "Grantha": range(70400, 70528), + "Newa": range(70656, 70784), + "Tirhuta": range(70784, 70880), + "Siddham": range(71040, 71168), + "Modi": range(71168, 71264), + "Mongolian Supplement": range(71264, 71296), + "Takri": range(71296, 71376), + "Ahom": range(71424, 71504), + "Dogra": range(71680, 71760), + "Warang Citi": range(71840, 71936), + "Dives Akuru": range(71936, 72032), + "Nandinagari": range(72096, 72192), + "Zanabazar Square": range(72192, 72272), + "Soyombo": range(72272, 72368), + "Unified Canadian Aboriginal Syllabics Extended-A": range(72368, 72384), + "Pau Cin Hau": range(72384, 72448), + "Devanagari Extended-A": range(72448, 72544), + "Bhaiksuki": range(72704, 72816), + "Marchen": range(72816, 72896), + "Masaram Gondi": range(72960, 73056), + "Gunjala Gondi": range(73056, 73136), + "Makasar": range(73440, 73472), + "Kawi": range(73472, 73568), + "Lisu Supplement": range(73648, 73664), + "Tamil Supplement": range(73664, 73728), + "Cuneiform": range(73728, 74752), + "Cuneiform Numbers and Punctuation": range(74752, 74880), + "Early Dynastic Cuneiform": range(74880, 75088), + "Cypro-Minoan": range(77712, 77824), + "Egyptian Hieroglyphs": range(77824, 78896), + "Egyptian Hieroglyph Format Controls": range(78896, 78944), + "Anatolian Hieroglyphs": range(82944, 83584), + "Bamum Supplement": range(92160, 92736), + "Mro": range(92736, 92784), + "Tangsa": range(92784, 92880), + "Bassa Vah": range(92880, 92928), + "Pahawh Hmong": range(92928, 93072), + "Medefaidrin": range(93760, 93856), + "Miao": range(93952, 94112), + "Ideographic Symbols and Punctuation": range(94176, 94208), + "Tangut": range(94208, 100352), + "Tangut Components": range(100352, 101120), + "Khitan Small Script": range(101120, 101632), + "Tangut Supplement": range(101632, 101760), + "Kana Extended-B": range(110576, 110592), + "Kana Supplement": range(110592, 110848), + "Kana Extended-A": range(110848, 110896), + "Small Kana Extension": range(110896, 110960), + "Nushu": range(110960, 111360), + "Duployan": range(113664, 113824), + "Shorthand Format Controls": range(113824, 113840), + "Znamenny Musical Notation": range(118528, 118736), + "Byzantine Musical Symbols": range(118784, 119040), + "Musical Symbols": range(119040, 119296), + "Ancient Greek Musical Notation": range(119296, 119376), + "Kaktovik Numerals": range(119488, 119520), + "Mayan Numerals": range(119520, 119552), + "Tai Xuan Jing Symbols": range(119552, 119648), + "Counting Rod Numerals": range(119648, 119680), + "Mathematical Alphanumeric Symbols": range(119808, 120832), + "Sutton SignWriting": range(120832, 121520), + "Latin Extended-G": range(122624, 122880), + "Glagolitic Supplement": range(122880, 122928), + "Cyrillic Extended-D": range(122928, 123024), + "Nyiakeng Puachue Hmong": range(123136, 123216), + "Toto": range(123536, 123584), + "Wancho": range(123584, 123648), + "Nag Mundari": range(124112, 124160), + "Ethiopic Extended-B": range(124896, 124928), + "Mende Kikakui": range(124928, 125152), + "Adlam": range(125184, 125280), + "Indic Siyaq Numbers": range(126064, 126144), + "Ottoman Siyaq Numbers": range(126208, 126288), + "Arabic Mathematical Alphabetic Symbols": range(126464, 126720), + "Mahjong Tiles": range(126976, 127024), + "Domino Tiles": range(127024, 127136), + "Playing Cards": range(127136, 127232), + "Enclosed Alphanumeric Supplement": range(127232, 127488), + "Enclosed Ideographic Supplement": range(127488, 127744), + "Miscellaneous Symbols and Pictographs": range(127744, 128512), + "Emoticons range(Emoji)": range(128512, 128592), + "Ornamental Dingbats": range(128592, 128640), + "Transport and Map Symbols": range(128640, 128768), + "Alchemical Symbols": range(128768, 128896), + "Geometric Shapes Extended": range(128896, 129024), + "Supplemental Arrows-C": range(129024, 129280), + "Supplemental Symbols and Pictographs": range(129280, 129536), + "Chess Symbols": range(129536, 129648), + "Symbols and Pictographs Extended-A": range(129648, 129792), + "Symbols for Legacy Computing": range(129792, 130048), + "CJK Unified Ideographs Extension B": range(131072, 173792), + "CJK Unified Ideographs Extension C": range(173824, 177984), + "CJK Unified Ideographs Extension D": range(177984, 178208), + "CJK Unified Ideographs Extension E": range(178208, 183984), + "CJK Unified Ideographs Extension F": range(183984, 191472), + "CJK Compatibility Ideographs Supplement": range(194560, 195104), + "CJK Unified Ideographs Extension G": range(196608, 201552), + "CJK Unified Ideographs Extension H": range(201552, 205744), + "Tags": range(917504, 917632), + "Variation Selectors Supplement": range(917760, 918000), + "Supplementary Private Use Area-A": range(983040, 1048576), + "Supplementary Private Use Area-B": range(1048576, 1114112), +} + + +UNICODE_SECONDARY_RANGE_KEYWORD: List[str] = [ + "Supplement", + "Extended", + "Extensions", + "Modifier", + "Marks", + "Punctuation", + "Symbols", + "Forms", + "Operators", + "Miscellaneous", + "Drawing", + "Block", + "Shapes", + "Supplemental", + "Tags", +] + +RE_POSSIBLE_ENCODING_INDICATION = re_compile( + r"(?:(?:encoding)|(?:charset)|(?:coding))(?:[\:= ]{1,10})(?:[\"\']?)([a-zA-Z0-9\-_]+)(?:[\"\']?)", + IGNORECASE, +) + +IANA_NO_ALIASES = [ + "cp720", + "cp737", + "cp856", + "cp874", + "cp875", + "cp1006", + "koi8_r", + "koi8_t", + "koi8_u", +] + +IANA_SUPPORTED: List[str] = sorted( + filter( + lambda x: x.endswith("_codec") is False + and x not in {"rot_13", "tactis", "mbcs"}, + list(set(aliases.values())) + IANA_NO_ALIASES, + ) +) + +IANA_SUPPORTED_COUNT: int = len(IANA_SUPPORTED) + +# pre-computed code page that are similar using the function cp_similarity. +IANA_SUPPORTED_SIMILAR: Dict[str, List[str]] = { + "cp037": ["cp1026", "cp1140", "cp273", "cp500"], + "cp1026": ["cp037", "cp1140", "cp273", "cp500"], + "cp1125": ["cp866"], + "cp1140": ["cp037", "cp1026", "cp273", "cp500"], + "cp1250": ["iso8859_2"], + "cp1251": ["kz1048", "ptcp154"], + "cp1252": ["iso8859_15", "iso8859_9", "latin_1"], + "cp1253": ["iso8859_7"], + "cp1254": ["iso8859_15", "iso8859_9", "latin_1"], + "cp1257": ["iso8859_13"], + "cp273": ["cp037", "cp1026", "cp1140", "cp500"], + "cp437": ["cp850", "cp858", "cp860", "cp861", "cp862", "cp863", "cp865"], + "cp500": ["cp037", "cp1026", "cp1140", "cp273"], + "cp850": ["cp437", "cp857", "cp858", "cp865"], + "cp857": ["cp850", "cp858", "cp865"], + "cp858": ["cp437", "cp850", "cp857", "cp865"], + "cp860": ["cp437", "cp861", "cp862", "cp863", "cp865"], + "cp861": ["cp437", "cp860", "cp862", "cp863", "cp865"], + "cp862": ["cp437", "cp860", "cp861", "cp863", "cp865"], + "cp863": ["cp437", "cp860", "cp861", "cp862", "cp865"], + "cp865": ["cp437", "cp850", "cp857", "cp858", "cp860", "cp861", "cp862", "cp863"], + "cp866": ["cp1125"], + "iso8859_10": ["iso8859_14", "iso8859_15", "iso8859_4", "iso8859_9", "latin_1"], + "iso8859_11": ["tis_620"], + "iso8859_13": ["cp1257"], + "iso8859_14": [ + "iso8859_10", + "iso8859_15", + "iso8859_16", + "iso8859_3", + "iso8859_9", + "latin_1", + ], + "iso8859_15": [ + "cp1252", + "cp1254", + "iso8859_10", + "iso8859_14", + "iso8859_16", + "iso8859_3", + "iso8859_9", + "latin_1", + ], + "iso8859_16": [ + "iso8859_14", + "iso8859_15", + "iso8859_2", + "iso8859_3", + "iso8859_9", + "latin_1", + ], + "iso8859_2": ["cp1250", "iso8859_16", "iso8859_4"], + "iso8859_3": ["iso8859_14", "iso8859_15", "iso8859_16", "iso8859_9", "latin_1"], + "iso8859_4": ["iso8859_10", "iso8859_2", "iso8859_9", "latin_1"], + "iso8859_7": ["cp1253"], + "iso8859_9": [ + "cp1252", + "cp1254", + "cp1258", + "iso8859_10", + "iso8859_14", + "iso8859_15", + "iso8859_16", + "iso8859_3", + "iso8859_4", + "latin_1", + ], + "kz1048": ["cp1251", "ptcp154"], + "latin_1": [ + "cp1252", + "cp1254", + "cp1258", + "iso8859_10", + "iso8859_14", + "iso8859_15", + "iso8859_16", + "iso8859_3", + "iso8859_4", + "iso8859_9", + ], + "mac_iceland": ["mac_roman", "mac_turkish"], + "mac_roman": ["mac_iceland", "mac_turkish"], + "mac_turkish": ["mac_iceland", "mac_roman"], + "ptcp154": ["cp1251", "kz1048"], + "tis_620": ["iso8859_11"], +} + + +CHARDET_CORRESPONDENCE: Dict[str, str] = { + "iso2022_kr": "ISO-2022-KR", + "iso2022_jp": "ISO-2022-JP", + "euc_kr": "EUC-KR", + "tis_620": "TIS-620", + "utf_32": "UTF-32", + "euc_jp": "EUC-JP", + "koi8_r": "KOI8-R", + "iso8859_1": "ISO-8859-1", + "iso8859_2": "ISO-8859-2", + "iso8859_5": "ISO-8859-5", + "iso8859_6": "ISO-8859-6", + "iso8859_7": "ISO-8859-7", + "iso8859_8": "ISO-8859-8", + "utf_16": "UTF-16", + "cp855": "IBM855", + "mac_cyrillic": "MacCyrillic", + "gb2312": "GB2312", + "gb18030": "GB18030", + "cp932": "CP932", + "cp866": "IBM866", + "utf_8": "utf-8", + "utf_8_sig": "UTF-8-SIG", + "shift_jis": "SHIFT_JIS", + "big5": "Big5", + "cp1250": "windows-1250", + "cp1251": "windows-1251", + "cp1252": "Windows-1252", + "cp1253": "windows-1253", + "cp1255": "windows-1255", + "cp1256": "windows-1256", + "cp1254": "Windows-1254", + "cp949": "CP949", +} + + +COMMON_SAFE_ASCII_CHARACTERS: Set[str] = { + "<", + ">", + "=", + ":", + "/", + "&", + ";", + "{", + "}", + "[", + "]", + ",", + "|", + '"', + "-", +} + + +KO_NAMES: Set[str] = {"johab", "cp949", "euc_kr"} +ZH_NAMES: Set[str] = {"big5", "cp950", "big5hkscs", "hz"} + +# Logging LEVEL below DEBUG +TRACE: int = 5 + + +# Language label that contain the em dash "—" +# character are to be considered alternative seq to origin +FREQUENCIES: Dict[str, List[str]] = { + "English": [ + "e", + "a", + "t", + "i", + "o", + "n", + "s", + "r", + "h", + "l", + "d", + "c", + "u", + "m", + "f", + "p", + "g", + "w", + "y", + "b", + "v", + "k", + "x", + "j", + "z", + "q", + ], + "English—": [ + "e", + "a", + "t", + "i", + "o", + "n", + "s", + "r", + "h", + "l", + "d", + "c", + "m", + "u", + "f", + "p", + "g", + "w", + "b", + "y", + "v", + "k", + "j", + "x", + "z", + "q", + ], + "German": [ + "e", + "n", + "i", + "r", + "s", + "t", + "a", + "d", + "h", + "u", + "l", + "g", + "o", + "c", + "m", + "b", + "f", + "k", + "w", + "z", + "p", + "v", + "ü", + "ä", + "ö", + "j", + ], + "French": [ + "e", + "a", + "s", + "n", + "i", + "t", + "r", + "l", + "u", + "o", + "d", + "c", + "p", + "m", + "é", + "v", + "g", + "f", + "b", + "h", + "q", + "à", + "x", + "è", + "y", + "j", + ], + "Dutch": [ + "e", + "n", + "a", + "i", + "r", + "t", + "o", + "d", + "s", + "l", + "g", + "h", + "v", + "m", + "u", + "k", + "c", + "p", + "b", + "w", + "j", + "z", + "f", + "y", + "x", + "ë", + ], + "Italian": [ + "e", + "i", + "a", + "o", + "n", + "l", + "t", + "r", + "s", + "c", + "d", + "u", + "p", + "m", + "g", + "v", + "f", + "b", + "z", + "h", + "q", + "è", + "à", + "k", + "y", + "ò", + ], + "Polish": [ + "a", + "i", + "o", + "e", + "n", + "r", + "z", + "w", + "s", + "c", + "t", + "k", + "y", + "d", + "p", + "m", + "u", + "l", + "j", + "ł", + "g", + "b", + "h", + "ą", + "ę", + "ó", + ], + "Spanish": [ + "e", + "a", + "o", + "n", + "s", + "r", + "i", + "l", + "d", + "t", + "c", + "u", + "m", + "p", + "b", + "g", + "v", + "f", + "y", + "ó", + "h", + "q", + "í", + "j", + "z", + "á", + ], + "Russian": [ + "о", + "а", + "е", + "и", + "н", + "с", + "т", + "р", + "в", + "л", + "к", + "м", + "д", + "п", + "у", + "г", + "я", + "ы", + "з", + "б", + "й", + "ь", + "ч", + "х", + "ж", + "ц", + ], + # Jap-Kanji + "Japanese": [ + "人", + "一", + "大", + "亅", + "丁", + "丨", + "竹", + "笑", + "口", + "日", + "今", + "二", + "彳", + "行", + "十", + "土", + "丶", + "寸", + "寺", + "時", + "乙", + "丿", + "乂", + "气", + "気", + "冂", + "巾", + "亠", + "市", + "目", + "儿", + "見", + "八", + "小", + "凵", + "県", + "月", + "彐", + "門", + "間", + "木", + "東", + "山", + "出", + "本", + "中", + "刀", + "分", + "耳", + "又", + "取", + "最", + "言", + "田", + "心", + "思", + "刂", + "前", + "京", + "尹", + "事", + "生", + "厶", + "云", + "会", + "未", + "来", + "白", + "冫", + "楽", + "灬", + "馬", + "尸", + "尺", + "駅", + "明", + "耂", + "者", + "了", + "阝", + "都", + "高", + "卜", + "占", + "厂", + "广", + "店", + "子", + "申", + "奄", + "亻", + "俺", + "上", + "方", + "冖", + "学", + "衣", + "艮", + "食", + "自", + ], + # Jap-Katakana + "Japanese—": [ + "ー", + "ン", + "ス", + "・", + "ル", + "ト", + "リ", + "イ", + "ア", + "ラ", + "ッ", + "ク", + "ド", + "シ", + "レ", + "ジ", + "タ", + "フ", + "ロ", + "カ", + "テ", + "マ", + "ィ", + "グ", + "バ", + "ム", + "プ", + "オ", + "コ", + "デ", + "ニ", + "ウ", + "メ", + "サ", + "ビ", + "ナ", + "ブ", + "ャ", + "エ", + "ュ", + "チ", + "キ", + "ズ", + "ダ", + "パ", + "ミ", + "ェ", + "ョ", + "ハ", + "セ", + "ベ", + "ガ", + "モ", + "ツ", + "ネ", + "ボ", + "ソ", + "ノ", + "ァ", + "ヴ", + "ワ", + "ポ", + "ペ", + "ピ", + "ケ", + "ゴ", + "ギ", + "ザ", + "ホ", + "ゲ", + "ォ", + "ヤ", + "ヒ", + "ユ", + "ヨ", + "ヘ", + "ゼ", + "ヌ", + "ゥ", + "ゾ", + "ヶ", + "ヂ", + "ヲ", + "ヅ", + "ヵ", + "ヱ", + "ヰ", + "ヮ", + "ヽ", + "゠", + "ヾ", + "ヷ", + "ヿ", + "ヸ", + "ヹ", + "ヺ", + ], + # Jap-Hiragana + "Japanese——": [ + "の", + "に", + "る", + "た", + "と", + "は", + "し", + "い", + "を", + "で", + "て", + "が", + "な", + "れ", + "か", + "ら", + "さ", + "っ", + "り", + "す", + "あ", + "も", + "こ", + "ま", + "う", + "く", + "よ", + "き", + "ん", + "め", + "お", + "け", + "そ", + "つ", + "だ", + "や", + "え", + "ど", + "わ", + "ち", + "み", + "せ", + "じ", + "ば", + "へ", + "び", + "ず", + "ろ", + "ほ", + "げ", + "む", + "べ", + "ひ", + "ょ", + "ゆ", + "ぶ", + "ご", + "ゃ", + "ね", + "ふ", + "ぐ", + "ぎ", + "ぼ", + "ゅ", + "づ", + "ざ", + "ぞ", + "ぬ", + "ぜ", + "ぱ", + "ぽ", + "ぷ", + "ぴ", + "ぃ", + "ぁ", + "ぇ", + "ぺ", + "ゞ", + "ぢ", + "ぉ", + "ぅ", + "ゐ", + "ゝ", + "ゑ", + "゛", + "゜", + "ゎ", + "ゔ", + "゚", + "ゟ", + "゙", + "ゕ", + "ゖ", + ], + "Portuguese": [ + "a", + "e", + "o", + "s", + "i", + "r", + "d", + "n", + "t", + "m", + "u", + "c", + "l", + "p", + "g", + "v", + "b", + "f", + "h", + "ã", + "q", + "é", + "ç", + "á", + "z", + "í", + ], + "Swedish": [ + "e", + "a", + "n", + "r", + "t", + "s", + "i", + "l", + "d", + "o", + "m", + "k", + "g", + "v", + "h", + "f", + "u", + "p", + "ä", + "c", + "b", + "ö", + "å", + "y", + "j", + "x", + ], + "Chinese": [ + "的", + "一", + "是", + "不", + "了", + "在", + "人", + "有", + "我", + "他", + "这", + "个", + "们", + "中", + "来", + "上", + "大", + "为", + "和", + "国", + "地", + "到", + "以", + "说", + "时", + "要", + "就", + "出", + "会", + "可", + "也", + "你", + "对", + "生", + "能", + "而", + "子", + "那", + "得", + "于", + "着", + "下", + "自", + "之", + "年", + "过", + "发", + "后", + "作", + "里", + "用", + "道", + "行", + "所", + "然", + "家", + "种", + "事", + "成", + "方", + "多", + "经", + "么", + "去", + "法", + "学", + "如", + "都", + "同", + "现", + "当", + "没", + "动", + "面", + "起", + "看", + "定", + "天", + "分", + "还", + "进", + "好", + "小", + "部", + "其", + "些", + "主", + "样", + "理", + "心", + "她", + "本", + "前", + "开", + "但", + "因", + "只", + "从", + "想", + "实", + ], + "Ukrainian": [ + "о", + "а", + "н", + "і", + "и", + "р", + "в", + "т", + "е", + "с", + "к", + "л", + "у", + "д", + "м", + "п", + "з", + "я", + "ь", + "б", + "г", + "й", + "ч", + "х", + "ц", + "ї", + ], + "Norwegian": [ + "e", + "r", + "n", + "t", + "a", + "s", + "i", + "o", + "l", + "d", + "g", + "k", + "m", + "v", + "f", + "p", + "u", + "b", + "h", + "å", + "y", + "j", + "ø", + "c", + "æ", + "w", + ], + "Finnish": [ + "a", + "i", + "n", + "t", + "e", + "s", + "l", + "o", + "u", + "k", + "ä", + "m", + "r", + "v", + "j", + "h", + "p", + "y", + "d", + "ö", + "g", + "c", + "b", + "f", + "w", + "z", + ], + "Vietnamese": [ + "n", + "h", + "t", + "i", + "c", + "g", + "a", + "o", + "u", + "m", + "l", + "r", + "à", + "đ", + "s", + "e", + "v", + "p", + "b", + "y", + "ư", + "d", + "á", + "k", + "ộ", + "ế", + ], + "Czech": [ + "o", + "e", + "a", + "n", + "t", + "s", + "i", + "l", + "v", + "r", + "k", + "d", + "u", + "m", + "p", + "í", + "c", + "h", + "z", + "á", + "y", + "j", + "b", + "ě", + "é", + "ř", + ], + "Hungarian": [ + "e", + "a", + "t", + "l", + "s", + "n", + "k", + "r", + "i", + "o", + "z", + "á", + "é", + "g", + "m", + "b", + "y", + "v", + "d", + "h", + "u", + "p", + "j", + "ö", + "f", + "c", + ], + "Korean": [ + "이", + "다", + "에", + "의", + "는", + "로", + "하", + "을", + "가", + "고", + "지", + "서", + "한", + "은", + "기", + "으", + "년", + "대", + "사", + "시", + "를", + "리", + "도", + "인", + "스", + "일", + ], + "Indonesian": [ + "a", + "n", + "e", + "i", + "r", + "t", + "u", + "s", + "d", + "k", + "m", + "l", + "g", + "p", + "b", + "o", + "h", + "y", + "j", + "c", + "w", + "f", + "v", + "z", + "x", + "q", + ], + "Turkish": [ + "a", + "e", + "i", + "n", + "r", + "l", + "ı", + "k", + "d", + "t", + "s", + "m", + "y", + "u", + "o", + "b", + "ü", + "ş", + "v", + "g", + "z", + "h", + "c", + "p", + "ç", + "ğ", + ], + "Romanian": [ + "e", + "i", + "a", + "r", + "n", + "t", + "u", + "l", + "o", + "c", + "s", + "d", + "p", + "m", + "ă", + "f", + "v", + "î", + "g", + "b", + "ș", + "ț", + "z", + "h", + "â", + "j", + ], + "Farsi": [ + "ا", + "ی", + "ر", + "د", + "ن", + "ه", + "و", + "م", + "ت", + "ب", + "س", + "ل", + "ک", + "ش", + "ز", + "ف", + "گ", + "ع", + "خ", + "ق", + "ج", + "آ", + "پ", + "ح", + "ط", + "ص", + ], + "Arabic": [ + "ا", + "ل", + "ي", + "م", + "و", + "ن", + "ر", + "ت", + "ب", + "ة", + "ع", + "د", + "س", + "ف", + "ه", + "ك", + "ق", + "أ", + "ح", + "ج", + "ش", + "ط", + "ص", + "ى", + "خ", + "إ", + ], + "Danish": [ + "e", + "r", + "n", + "t", + "a", + "i", + "s", + "d", + "l", + "o", + "g", + "m", + "k", + "f", + "v", + "u", + "b", + "h", + "p", + "å", + "y", + "ø", + "æ", + "c", + "j", + "w", + ], + "Serbian": [ + "а", + "и", + "о", + "е", + "н", + "р", + "с", + "у", + "т", + "к", + "ј", + "в", + "д", + "м", + "п", + "л", + "г", + "з", + "б", + "a", + "i", + "e", + "o", + "n", + "ц", + "ш", + ], + "Lithuanian": [ + "i", + "a", + "s", + "o", + "r", + "e", + "t", + "n", + "u", + "k", + "m", + "l", + "p", + "v", + "d", + "j", + "g", + "ė", + "b", + "y", + "ų", + "š", + "ž", + "c", + "ą", + "į", + ], + "Slovene": [ + "e", + "a", + "i", + "o", + "n", + "r", + "s", + "l", + "t", + "j", + "v", + "k", + "d", + "p", + "m", + "u", + "z", + "b", + "g", + "h", + "č", + "c", + "š", + "ž", + "f", + "y", + ], + "Slovak": [ + "o", + "a", + "e", + "n", + "i", + "r", + "v", + "t", + "s", + "l", + "k", + "d", + "m", + "p", + "u", + "c", + "h", + "j", + "b", + "z", + "á", + "y", + "ý", + "í", + "č", + "é", + ], + "Hebrew": [ + "י", + "ו", + "ה", + "ל", + "ר", + "ב", + "ת", + "מ", + "א", + "ש", + "נ", + "ע", + "ם", + "ד", + "ק", + "ח", + "פ", + "ס", + "כ", + "ג", + "ט", + "צ", + "ן", + "ז", + "ך", + ], + "Bulgarian": [ + "а", + "и", + "о", + "е", + "н", + "т", + "р", + "с", + "в", + "л", + "к", + "д", + "п", + "м", + "з", + "г", + "я", + "ъ", + "у", + "б", + "ч", + "ц", + "й", + "ж", + "щ", + "х", + ], + "Croatian": [ + "a", + "i", + "o", + "e", + "n", + "r", + "j", + "s", + "t", + "u", + "k", + "l", + "v", + "d", + "m", + "p", + "g", + "z", + "b", + "c", + "č", + "h", + "š", + "ž", + "ć", + "f", + ], + "Hindi": [ + "क", + "र", + "स", + "न", + "त", + "म", + "ह", + "प", + "य", + "ल", + "व", + "ज", + "द", + "ग", + "ब", + "श", + "ट", + "अ", + "ए", + "थ", + "भ", + "ड", + "च", + "ध", + "ष", + "इ", + ], + "Estonian": [ + "a", + "i", + "e", + "s", + "t", + "l", + "u", + "n", + "o", + "k", + "r", + "d", + "m", + "v", + "g", + "p", + "j", + "h", + "ä", + "b", + "õ", + "ü", + "f", + "c", + "ö", + "y", + ], + "Thai": [ + "า", + "น", + "ร", + "อ", + "ก", + "เ", + "ง", + "ม", + "ย", + "ล", + "ว", + "ด", + "ท", + "ส", + "ต", + "ะ", + "ป", + "บ", + "ค", + "ห", + "แ", + "จ", + "พ", + "ช", + "ข", + "ใ", + ], + "Greek": [ + "α", + "τ", + "ο", + "ι", + "ε", + "ν", + "ρ", + "σ", + "κ", + "η", + "π", + "ς", + "υ", + "μ", + "λ", + "ί", + "ό", + "ά", + "γ", + "έ", + "δ", + "ή", + "ω", + "χ", + "θ", + "ύ", + ], + "Tamil": [ + "க", + "த", + "ப", + "ட", + "ர", + "ம", + "ல", + "ன", + "வ", + "ற", + "ய", + "ள", + "ச", + "ந", + "இ", + "ண", + "அ", + "ஆ", + "ழ", + "ங", + "எ", + "உ", + "ஒ", + "ஸ", + ], + "Kazakh": [ + "а", + "ы", + "е", + "н", + "т", + "р", + "л", + "і", + "д", + "с", + "м", + "қ", + "к", + "о", + "б", + "и", + "у", + "ғ", + "ж", + "ң", + "з", + "ш", + "й", + "п", + "г", + "ө", + ], +} + +LANGUAGE_SUPPORTED_COUNT: int = len(FREQUENCIES) diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/legacy.py b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/legacy.py new file mode 100644 index 0000000000000000000000000000000000000000..43aad21a9dd1c08c8d31e38908485d46b14efbd2 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/legacy.py @@ -0,0 +1,54 @@ +from typing import Any, Dict, Optional, Union +from warnings import warn + +from .api import from_bytes +from .constant import CHARDET_CORRESPONDENCE + + +def detect( + byte_str: bytes, should_rename_legacy: bool = False, **kwargs: Any +) -> Dict[str, Optional[Union[str, float]]]: + """ + chardet legacy method + Detect the encoding of the given byte string. It should be mostly backward-compatible. + Encoding name will match Chardet own writing whenever possible. (Not on encoding name unsupported by it) + This function is deprecated and should be used to migrate your project easily, consult the documentation for + further information. Not planned for removal. + + :param byte_str: The byte sequence to examine. + :param should_rename_legacy: Should we rename legacy encodings + to their more modern equivalents? + """ + if len(kwargs): + warn( + f"charset-normalizer disregard arguments '{','.join(list(kwargs.keys()))}' in legacy function detect()" + ) + + if not isinstance(byte_str, (bytearray, bytes)): + raise TypeError( # pragma: nocover + "Expected object of type bytes or bytearray, got: " + "{0}".format(type(byte_str)) + ) + + if isinstance(byte_str, bytearray): + byte_str = bytes(byte_str) + + r = from_bytes(byte_str).best() + + encoding = r.encoding if r is not None else None + language = r.language if r is not None and r.language != "Unknown" else "" + confidence = 1.0 - r.chaos if r is not None else None + + # Note: CharsetNormalizer does not return 'UTF-8-SIG' as the sig get stripped in the detection/normalization process + # but chardet does return 'utf-8-sig' and it is a valid codec name. + if r is not None and encoding == "utf_8" and r.bom: + encoding += "_sig" + + if should_rename_legacy is False and encoding in CHARDET_CORRESPONDENCE: + encoding = CHARDET_CORRESPONDENCE[encoding] + + return { + "encoding": encoding, + "language": language, + "confidence": confidence, + } diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/md.py b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/md.py new file mode 100644 index 0000000000000000000000000000000000000000..77897aae4f44d084d6a59d7f7f1665035ff0047d --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/md.py @@ -0,0 +1,615 @@ +from functools import lru_cache +from logging import getLogger +from typing import List, Optional + +from .constant import ( + COMMON_SAFE_ASCII_CHARACTERS, + TRACE, + UNICODE_SECONDARY_RANGE_KEYWORD, +) +from .utils import ( + is_accentuated, + is_arabic, + is_arabic_isolated_form, + is_case_variable, + is_cjk, + is_emoticon, + is_hangul, + is_hiragana, + is_katakana, + is_latin, + is_punctuation, + is_separator, + is_symbol, + is_thai, + is_unprintable, + remove_accent, + unicode_range, +) + + +class MessDetectorPlugin: + """ + Base abstract class used for mess detection plugins. + All detectors MUST extend and implement given methods. + """ + + def eligible(self, character: str) -> bool: + """ + Determine if given character should be fed in. + """ + raise NotImplementedError # pragma: nocover + + def feed(self, character: str) -> None: + """ + The main routine to be executed upon character. + Insert the logic in witch the text would be considered chaotic. + """ + raise NotImplementedError # pragma: nocover + + def reset(self) -> None: # pragma: no cover + """ + Permit to reset the plugin to the initial state. + """ + raise NotImplementedError + + @property + def ratio(self) -> float: + """ + Compute the chaos ratio based on what your feed() has seen. + Must NOT be lower than 0.; No restriction gt 0. + """ + raise NotImplementedError # pragma: nocover + + +class TooManySymbolOrPunctuationPlugin(MessDetectorPlugin): + def __init__(self) -> None: + self._punctuation_count: int = 0 + self._symbol_count: int = 0 + self._character_count: int = 0 + + self._last_printable_char: Optional[str] = None + self._frenzy_symbol_in_word: bool = False + + def eligible(self, character: str) -> bool: + return character.isprintable() + + def feed(self, character: str) -> None: + self._character_count += 1 + + if ( + character != self._last_printable_char + and character not in COMMON_SAFE_ASCII_CHARACTERS + ): + if is_punctuation(character): + self._punctuation_count += 1 + elif ( + character.isdigit() is False + and is_symbol(character) + and is_emoticon(character) is False + ): + self._symbol_count += 2 + + self._last_printable_char = character + + def reset(self) -> None: # pragma: no cover + self._punctuation_count = 0 + self._character_count = 0 + self._symbol_count = 0 + + @property + def ratio(self) -> float: + if self._character_count == 0: + return 0.0 + + ratio_of_punctuation: float = ( + self._punctuation_count + self._symbol_count + ) / self._character_count + + return ratio_of_punctuation if ratio_of_punctuation >= 0.3 else 0.0 + + +class TooManyAccentuatedPlugin(MessDetectorPlugin): + def __init__(self) -> None: + self._character_count: int = 0 + self._accentuated_count: int = 0 + + def eligible(self, character: str) -> bool: + return character.isalpha() + + def feed(self, character: str) -> None: + self._character_count += 1 + + if is_accentuated(character): + self._accentuated_count += 1 + + def reset(self) -> None: # pragma: no cover + self._character_count = 0 + self._accentuated_count = 0 + + @property + def ratio(self) -> float: + if self._character_count < 8: + return 0.0 + + ratio_of_accentuation: float = self._accentuated_count / self._character_count + return ratio_of_accentuation if ratio_of_accentuation >= 0.35 else 0.0 + + +class UnprintablePlugin(MessDetectorPlugin): + def __init__(self) -> None: + self._unprintable_count: int = 0 + self._character_count: int = 0 + + def eligible(self, character: str) -> bool: + return True + + def feed(self, character: str) -> None: + if is_unprintable(character): + self._unprintable_count += 1 + self._character_count += 1 + + def reset(self) -> None: # pragma: no cover + self._unprintable_count = 0 + + @property + def ratio(self) -> float: + if self._character_count == 0: + return 0.0 + + return (self._unprintable_count * 8) / self._character_count + + +class SuspiciousDuplicateAccentPlugin(MessDetectorPlugin): + def __init__(self) -> None: + self._successive_count: int = 0 + self._character_count: int = 0 + + self._last_latin_character: Optional[str] = None + + def eligible(self, character: str) -> bool: + return character.isalpha() and is_latin(character) + + def feed(self, character: str) -> None: + self._character_count += 1 + if ( + self._last_latin_character is not None + and is_accentuated(character) + and is_accentuated(self._last_latin_character) + ): + if character.isupper() and self._last_latin_character.isupper(): + self._successive_count += 1 + # Worse if its the same char duplicated with different accent. + if remove_accent(character) == remove_accent(self._last_latin_character): + self._successive_count += 1 + self._last_latin_character = character + + def reset(self) -> None: # pragma: no cover + self._successive_count = 0 + self._character_count = 0 + self._last_latin_character = None + + @property + def ratio(self) -> float: + if self._character_count == 0: + return 0.0 + + return (self._successive_count * 2) / self._character_count + + +class SuspiciousRange(MessDetectorPlugin): + def __init__(self) -> None: + self._suspicious_successive_range_count: int = 0 + self._character_count: int = 0 + self._last_printable_seen: Optional[str] = None + + def eligible(self, character: str) -> bool: + return character.isprintable() + + def feed(self, character: str) -> None: + self._character_count += 1 + + if ( + character.isspace() + or is_punctuation(character) + or character in COMMON_SAFE_ASCII_CHARACTERS + ): + self._last_printable_seen = None + return + + if self._last_printable_seen is None: + self._last_printable_seen = character + return + + unicode_range_a: Optional[str] = unicode_range(self._last_printable_seen) + unicode_range_b: Optional[str] = unicode_range(character) + + if is_suspiciously_successive_range(unicode_range_a, unicode_range_b): + self._suspicious_successive_range_count += 1 + + self._last_printable_seen = character + + def reset(self) -> None: # pragma: no cover + self._character_count = 0 + self._suspicious_successive_range_count = 0 + self._last_printable_seen = None + + @property + def ratio(self) -> float: + if self._character_count <= 24: + return 0.0 + + ratio_of_suspicious_range_usage: float = ( + self._suspicious_successive_range_count * 2 + ) / self._character_count + + return ratio_of_suspicious_range_usage + + +class SuperWeirdWordPlugin(MessDetectorPlugin): + def __init__(self) -> None: + self._word_count: int = 0 + self._bad_word_count: int = 0 + self._foreign_long_count: int = 0 + + self._is_current_word_bad: bool = False + self._foreign_long_watch: bool = False + + self._character_count: int = 0 + self._bad_character_count: int = 0 + + self._buffer: str = "" + self._buffer_accent_count: int = 0 + + def eligible(self, character: str) -> bool: + return True + + def feed(self, character: str) -> None: + if character.isalpha(): + self._buffer += character + if is_accentuated(character): + self._buffer_accent_count += 1 + if ( + self._foreign_long_watch is False + and (is_latin(character) is False or is_accentuated(character)) + and is_cjk(character) is False + and is_hangul(character) is False + and is_katakana(character) is False + and is_hiragana(character) is False + and is_thai(character) is False + ): + self._foreign_long_watch = True + return + if not self._buffer: + return + if ( + character.isspace() or is_punctuation(character) or is_separator(character) + ) and self._buffer: + self._word_count += 1 + buffer_length: int = len(self._buffer) + + self._character_count += buffer_length + + if buffer_length >= 4: + if self._buffer_accent_count / buffer_length > 0.34: + self._is_current_word_bad = True + # Word/Buffer ending with an upper case accentuated letter are so rare, + # that we will consider them all as suspicious. Same weight as foreign_long suspicious. + if ( + is_accentuated(self._buffer[-1]) + and self._buffer[-1].isupper() + and all(_.isupper() for _ in self._buffer) is False + ): + self._foreign_long_count += 1 + self._is_current_word_bad = True + if buffer_length >= 24 and self._foreign_long_watch: + camel_case_dst = [ + i + for c, i in zip(self._buffer, range(0, buffer_length)) + if c.isupper() + ] + probable_camel_cased: bool = False + + if camel_case_dst and (len(camel_case_dst) / buffer_length <= 0.3): + probable_camel_cased = True + + if not probable_camel_cased: + self._foreign_long_count += 1 + self._is_current_word_bad = True + + if self._is_current_word_bad: + self._bad_word_count += 1 + self._bad_character_count += len(self._buffer) + self._is_current_word_bad = False + + self._foreign_long_watch = False + self._buffer = "" + self._buffer_accent_count = 0 + elif ( + character not in {"<", ">", "-", "=", "~", "|", "_"} + and character.isdigit() is False + and is_symbol(character) + ): + self._is_current_word_bad = True + self._buffer += character + + def reset(self) -> None: # pragma: no cover + self._buffer = "" + self._is_current_word_bad = False + self._foreign_long_watch = False + self._bad_word_count = 0 + self._word_count = 0 + self._character_count = 0 + self._bad_character_count = 0 + self._foreign_long_count = 0 + + @property + def ratio(self) -> float: + if self._word_count <= 10 and self._foreign_long_count == 0: + return 0.0 + + return self._bad_character_count / self._character_count + + +class CjkInvalidStopPlugin(MessDetectorPlugin): + """ + GB(Chinese) based encoding often render the stop incorrectly when the content does not fit and + can be easily detected. Searching for the overuse of '丅' and '丄'. + """ + + def __init__(self) -> None: + self._wrong_stop_count: int = 0 + self._cjk_character_count: int = 0 + + def eligible(self, character: str) -> bool: + return True + + def feed(self, character: str) -> None: + if character in {"丅", "丄"}: + self._wrong_stop_count += 1 + return + if is_cjk(character): + self._cjk_character_count += 1 + + def reset(self) -> None: # pragma: no cover + self._wrong_stop_count = 0 + self._cjk_character_count = 0 + + @property + def ratio(self) -> float: + if self._cjk_character_count < 16: + return 0.0 + return self._wrong_stop_count / self._cjk_character_count + + +class ArchaicUpperLowerPlugin(MessDetectorPlugin): + def __init__(self) -> None: + self._buf: bool = False + + self._character_count_since_last_sep: int = 0 + + self._successive_upper_lower_count: int = 0 + self._successive_upper_lower_count_final: int = 0 + + self._character_count: int = 0 + + self._last_alpha_seen: Optional[str] = None + self._current_ascii_only: bool = True + + def eligible(self, character: str) -> bool: + return True + + def feed(self, character: str) -> None: + is_concerned = character.isalpha() and is_case_variable(character) + chunk_sep = is_concerned is False + + if chunk_sep and self._character_count_since_last_sep > 0: + if ( + self._character_count_since_last_sep <= 64 + and character.isdigit() is False + and self._current_ascii_only is False + ): + self._successive_upper_lower_count_final += ( + self._successive_upper_lower_count + ) + + self._successive_upper_lower_count = 0 + self._character_count_since_last_sep = 0 + self._last_alpha_seen = None + self._buf = False + self._character_count += 1 + self._current_ascii_only = True + + return + + if self._current_ascii_only is True and character.isascii() is False: + self._current_ascii_only = False + + if self._last_alpha_seen is not None: + if (character.isupper() and self._last_alpha_seen.islower()) or ( + character.islower() and self._last_alpha_seen.isupper() + ): + if self._buf is True: + self._successive_upper_lower_count += 2 + self._buf = False + else: + self._buf = True + else: + self._buf = False + + self._character_count += 1 + self._character_count_since_last_sep += 1 + self._last_alpha_seen = character + + def reset(self) -> None: # pragma: no cover + self._character_count = 0 + self._character_count_since_last_sep = 0 + self._successive_upper_lower_count = 0 + self._successive_upper_lower_count_final = 0 + self._last_alpha_seen = None + self._buf = False + self._current_ascii_only = True + + @property + def ratio(self) -> float: + if self._character_count == 0: + return 0.0 + + return self._successive_upper_lower_count_final / self._character_count + + +class ArabicIsolatedFormPlugin(MessDetectorPlugin): + def __init__(self) -> None: + self._character_count: int = 0 + self._isolated_form_count: int = 0 + + def reset(self) -> None: # pragma: no cover + self._character_count = 0 + self._isolated_form_count = 0 + + def eligible(self, character: str) -> bool: + return is_arabic(character) + + def feed(self, character: str) -> None: + self._character_count += 1 + + if is_arabic_isolated_form(character): + self._isolated_form_count += 1 + + @property + def ratio(self) -> float: + if self._character_count < 8: + return 0.0 + + isolated_form_usage: float = self._isolated_form_count / self._character_count + + return isolated_form_usage + + +@lru_cache(maxsize=1024) +def is_suspiciously_successive_range( + unicode_range_a: Optional[str], unicode_range_b: Optional[str] +) -> bool: + """ + Determine if two Unicode range seen next to each other can be considered as suspicious. + """ + if unicode_range_a is None or unicode_range_b is None: + return True + + if unicode_range_a == unicode_range_b: + return False + + if "Latin" in unicode_range_a and "Latin" in unicode_range_b: + return False + + if "Emoticons" in unicode_range_a or "Emoticons" in unicode_range_b: + return False + + # Latin characters can be accompanied with a combining diacritical mark + # eg. Vietnamese. + if ("Latin" in unicode_range_a or "Latin" in unicode_range_b) and ( + "Combining" in unicode_range_a or "Combining" in unicode_range_b + ): + return False + + keywords_range_a, keywords_range_b = unicode_range_a.split( + " " + ), unicode_range_b.split(" ") + + for el in keywords_range_a: + if el in UNICODE_SECONDARY_RANGE_KEYWORD: + continue + if el in keywords_range_b: + return False + + # Japanese Exception + range_a_jp_chars, range_b_jp_chars = ( + unicode_range_a + in ( + "Hiragana", + "Katakana", + ), + unicode_range_b in ("Hiragana", "Katakana"), + ) + if (range_a_jp_chars or range_b_jp_chars) and ( + "CJK" in unicode_range_a or "CJK" in unicode_range_b + ): + return False + if range_a_jp_chars and range_b_jp_chars: + return False + + if "Hangul" in unicode_range_a or "Hangul" in unicode_range_b: + if "CJK" in unicode_range_a or "CJK" in unicode_range_b: + return False + if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin": + return False + + # Chinese/Japanese use dedicated range for punctuation and/or separators. + if ("CJK" in unicode_range_a or "CJK" in unicode_range_b) or ( + unicode_range_a in ["Katakana", "Hiragana"] + and unicode_range_b in ["Katakana", "Hiragana"] + ): + if "Punctuation" in unicode_range_a or "Punctuation" in unicode_range_b: + return False + if "Forms" in unicode_range_a or "Forms" in unicode_range_b: + return False + if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin": + return False + + return True + + +@lru_cache(maxsize=2048) +def mess_ratio( + decoded_sequence: str, maximum_threshold: float = 0.2, debug: bool = False +) -> float: + """ + Compute a mess ratio given a decoded bytes sequence. The maximum threshold does stop the computation earlier. + """ + + detectors: List[MessDetectorPlugin] = [ + md_class() for md_class in MessDetectorPlugin.__subclasses__() + ] + + length: int = len(decoded_sequence) + 1 + + mean_mess_ratio: float = 0.0 + + if length < 512: + intermediary_mean_mess_ratio_calc: int = 32 + elif length <= 1024: + intermediary_mean_mess_ratio_calc = 64 + else: + intermediary_mean_mess_ratio_calc = 128 + + for character, index in zip(decoded_sequence + "\n", range(length)): + for detector in detectors: + if detector.eligible(character): + detector.feed(character) + + if ( + index > 0 and index % intermediary_mean_mess_ratio_calc == 0 + ) or index == length - 1: + mean_mess_ratio = sum(dt.ratio for dt in detectors) + + if mean_mess_ratio >= maximum_threshold: + break + + if debug: + logger = getLogger("charset_normalizer") + + logger.log( + TRACE, + "Mess-detector extended-analysis start. " + f"intermediary_mean_mess_ratio_calc={intermediary_mean_mess_ratio_calc} mean_mess_ratio={mean_mess_ratio} " + f"maximum_threshold={maximum_threshold}", + ) + + if len(decoded_sequence) > 16: + logger.log(TRACE, f"Starting with: {decoded_sequence[:16]}") + logger.log(TRACE, f"Ending with: {decoded_sequence[-16::]}") + + for dt in detectors: # pragma: nocover + logger.log(TRACE, f"{dt.__class__}: {dt.ratio}") + + return round(mean_mess_ratio, 3) diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/md__mypyc.cpython-310-x86_64-linux-gnu.so b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/md__mypyc.cpython-310-x86_64-linux-gnu.so new file mode 100644 index 0000000000000000000000000000000000000000..7ebead5dcde902718372fb8aa618afd1d973956b Binary files /dev/null and b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/md__mypyc.cpython-310-x86_64-linux-gnu.so differ diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/py.typed b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/utils.py b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..e5cbbf4c0ddfa5c1b5898d8a4405e27292100d41 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/utils.py @@ -0,0 +1,421 @@ +import importlib +import logging +import unicodedata +from codecs import IncrementalDecoder +from encodings.aliases import aliases +from functools import lru_cache +from re import findall +from typing import Generator, List, Optional, Set, Tuple, Union + +from _multibytecodec import MultibyteIncrementalDecoder + +from .constant import ( + ENCODING_MARKS, + IANA_SUPPORTED_SIMILAR, + RE_POSSIBLE_ENCODING_INDICATION, + UNICODE_RANGES_COMBINED, + UNICODE_SECONDARY_RANGE_KEYWORD, + UTF8_MAXIMAL_ALLOCATION, +) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_accentuated(character: str) -> bool: + try: + description: str = unicodedata.name(character) + except ValueError: + return False + return ( + "WITH GRAVE" in description + or "WITH ACUTE" in description + or "WITH CEDILLA" in description + or "WITH DIAERESIS" in description + or "WITH CIRCUMFLEX" in description + or "WITH TILDE" in description + or "WITH MACRON" in description + or "WITH RING ABOVE" in description + ) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def remove_accent(character: str) -> str: + decomposed: str = unicodedata.decomposition(character) + if not decomposed: + return character + + codes: List[str] = decomposed.split(" ") + + return chr(int(codes[0], 16)) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def unicode_range(character: str) -> Optional[str]: + """ + Retrieve the Unicode range official name from a single character. + """ + character_ord: int = ord(character) + + for range_name, ord_range in UNICODE_RANGES_COMBINED.items(): + if character_ord in ord_range: + return range_name + + return None + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_latin(character: str) -> bool: + try: + description: str = unicodedata.name(character) + except ValueError: + return False + return "LATIN" in description + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_punctuation(character: str) -> bool: + character_category: str = unicodedata.category(character) + + if "P" in character_category: + return True + + character_range: Optional[str] = unicode_range(character) + + if character_range is None: + return False + + return "Punctuation" in character_range + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_symbol(character: str) -> bool: + character_category: str = unicodedata.category(character) + + if "S" in character_category or "N" in character_category: + return True + + character_range: Optional[str] = unicode_range(character) + + if character_range is None: + return False + + return "Forms" in character_range and character_category != "Lo" + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_emoticon(character: str) -> bool: + character_range: Optional[str] = unicode_range(character) + + if character_range is None: + return False + + return "Emoticons" in character_range or "Pictographs" in character_range + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_separator(character: str) -> bool: + if character.isspace() or character in {"｜", "+", "<", ">"}: + return True + + character_category: str = unicodedata.category(character) + + return "Z" in character_category or character_category in {"Po", "Pd", "Pc"} + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_case_variable(character: str) -> bool: + return character.islower() != character.isupper() + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_cjk(character: str) -> bool: + try: + character_name = unicodedata.name(character) + except ValueError: + return False + + return "CJK" in character_name + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_hiragana(character: str) -> bool: + try: + character_name = unicodedata.name(character) + except ValueError: + return False + + return "HIRAGANA" in character_name + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_katakana(character: str) -> bool: + try: + character_name = unicodedata.name(character) + except ValueError: + return False + + return "KATAKANA" in character_name + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_hangul(character: str) -> bool: + try: + character_name = unicodedata.name(character) + except ValueError: + return False + + return "HANGUL" in character_name + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_thai(character: str) -> bool: + try: + character_name = unicodedata.name(character) + except ValueError: + return False + + return "THAI" in character_name + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_arabic(character: str) -> bool: + try: + character_name = unicodedata.name(character) + except ValueError: + return False + + return "ARABIC" in character_name + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_arabic_isolated_form(character: str) -> bool: + try: + character_name = unicodedata.name(character) + except ValueError: + return False + + return "ARABIC" in character_name and "ISOLATED FORM" in character_name + + +@lru_cache(maxsize=len(UNICODE_RANGES_COMBINED)) +def is_unicode_range_secondary(range_name: str) -> bool: + return any(keyword in range_name for keyword in UNICODE_SECONDARY_RANGE_KEYWORD) + + +@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION) +def is_unprintable(character: str) -> bool: + return ( + character.isspace() is False # includes \n \t \r \v + and character.isprintable() is False + and character != "\x1A" # Why? Its the ASCII substitute character. + and character != "\ufeff" # bug discovered in Python, + # Zero Width No-Break Space located in Arabic Presentation Forms-B, Unicode 1.1 not acknowledged as space. + ) + + +def any_specified_encoding(sequence: bytes, search_zone: int = 8192) -> Optional[str]: + """ + Extract using ASCII-only decoder any specified encoding in the first n-bytes. + """ + if not isinstance(sequence, bytes): + raise TypeError + + seq_len: int = len(sequence) + + results: List[str] = findall( + RE_POSSIBLE_ENCODING_INDICATION, + sequence[: min(seq_len, search_zone)].decode("ascii", errors="ignore"), + ) + + if len(results) == 0: + return None + + for specified_encoding in results: + specified_encoding = specified_encoding.lower().replace("-", "_") + + encoding_alias: str + encoding_iana: str + + for encoding_alias, encoding_iana in aliases.items(): + if encoding_alias == specified_encoding: + return encoding_iana + if encoding_iana == specified_encoding: + return encoding_iana + + return None + + +@lru_cache(maxsize=128) +def is_multi_byte_encoding(name: str) -> bool: + """ + Verify is a specific encoding is a multi byte one based on it IANA name + """ + return name in { + "utf_8", + "utf_8_sig", + "utf_16", + "utf_16_be", + "utf_16_le", + "utf_32", + "utf_32_le", + "utf_32_be", + "utf_7", + } or issubclass( + importlib.import_module("encodings.{}".format(name)).IncrementalDecoder, + MultibyteIncrementalDecoder, + ) + + +def identify_sig_or_bom(sequence: bytes) -> Tuple[Optional[str], bytes]: + """ + Identify and extract SIG/BOM in given sequence. + """ + + for iana_encoding in ENCODING_MARKS: + marks: Union[bytes, List[bytes]] = ENCODING_MARKS[iana_encoding] + + if isinstance(marks, bytes): + marks = [marks] + + for mark in marks: + if sequence.startswith(mark): + return iana_encoding, mark + + return None, b"" + + +def should_strip_sig_or_bom(iana_encoding: str) -> bool: + return iana_encoding not in {"utf_16", "utf_32"} + + +def iana_name(cp_name: str, strict: bool = True) -> str: + cp_name = cp_name.lower().replace("-", "_") + + encoding_alias: str + encoding_iana: str + + for encoding_alias, encoding_iana in aliases.items(): + if cp_name in [encoding_alias, encoding_iana]: + return encoding_iana + + if strict: + raise ValueError("Unable to retrieve IANA for '{}'".format(cp_name)) + + return cp_name + + +def range_scan(decoded_sequence: str) -> List[str]: + ranges: Set[str] = set() + + for character in decoded_sequence: + character_range: Optional[str] = unicode_range(character) + + if character_range is None: + continue + + ranges.add(character_range) + + return list(ranges) + + +def cp_similarity(iana_name_a: str, iana_name_b: str) -> float: + if is_multi_byte_encoding(iana_name_a) or is_multi_byte_encoding(iana_name_b): + return 0.0 + + decoder_a = importlib.import_module( + "encodings.{}".format(iana_name_a) + ).IncrementalDecoder + decoder_b = importlib.import_module( + "encodings.{}".format(iana_name_b) + ).IncrementalDecoder + + id_a: IncrementalDecoder = decoder_a(errors="ignore") + id_b: IncrementalDecoder = decoder_b(errors="ignore") + + character_match_count: int = 0 + + for i in range(255): + to_be_decoded: bytes = bytes([i]) + if id_a.decode(to_be_decoded) == id_b.decode(to_be_decoded): + character_match_count += 1 + + return character_match_count / 254 + + +def is_cp_similar(iana_name_a: str, iana_name_b: str) -> bool: + """ + Determine if two code page are at least 80% similar. IANA_SUPPORTED_SIMILAR dict was generated using + the function cp_similarity. + """ + return ( + iana_name_a in IANA_SUPPORTED_SIMILAR + and iana_name_b in IANA_SUPPORTED_SIMILAR[iana_name_a] + ) + + +def set_logging_handler( + name: str = "charset_normalizer", + level: int = logging.INFO, + format_string: str = "%(asctime)s | %(levelname)s | %(message)s", +) -> None: + logger = logging.getLogger(name) + logger.setLevel(level) + + handler = logging.StreamHandler() + handler.setFormatter(logging.Formatter(format_string)) + logger.addHandler(handler) + + +def cut_sequence_chunks( + sequences: bytes, + encoding_iana: str, + offsets: range, + chunk_size: int, + bom_or_sig_available: bool, + strip_sig_or_bom: bool, + sig_payload: bytes, + is_multi_byte_decoder: bool, + decoded_payload: Optional[str] = None, +) -> Generator[str, None, None]: + if decoded_payload and is_multi_byte_decoder is False: + for i in offsets: + chunk = decoded_payload[i : i + chunk_size] + if not chunk: + break + yield chunk + else: + for i in offsets: + chunk_end = i + chunk_size + if chunk_end > len(sequences) + 8: + continue + + cut_sequence = sequences[i : i + chunk_size] + + if bom_or_sig_available and strip_sig_or_bom is False: + cut_sequence = sig_payload + cut_sequence + + chunk = cut_sequence.decode( + encoding_iana, + errors="ignore" if is_multi_byte_decoder else "strict", + ) + + # multi-byte bad cutting detector and adjustment + # not the cleanest way to perform that fix but clever enough for now. + if is_multi_byte_decoder and i > 0: + chunk_partial_size_chk: int = min(chunk_size, 16) + + if ( + decoded_payload + and chunk[:chunk_partial_size_chk] not in decoded_payload + ): + for j in range(i, i - 4, -1): + cut_sequence = sequences[j:chunk_end] + + if bom_or_sig_available and strip_sig_or_bom is False: + cut_sequence = sig_payload + cut_sequence + + chunk = cut_sequence.decode(encoding_iana, errors="ignore") + + if chunk[:chunk_partial_size_chk] in decoded_payload: + break + + yield chunk diff --git a/env-llmeval/lib/python3.10/site-packages/charset_normalizer/version.py b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/version.py new file mode 100644 index 0000000000000000000000000000000000000000..5a4da4ff49bc80ef49e8aa7e01cc8555518bd1b1 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/charset_normalizer/version.py @@ -0,0 +1,6 @@ +""" +Expose version +""" + +__version__ = "3.3.2" +VERSION = __version__.split(".") diff --git a/env-llmeval/lib/python3.10/site-packages/examples/__init__.py b/env-llmeval/lib/python3.10/site-packages/examples/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/env-llmeval/lib/python3.10/site-packages/examples/__pycache__/__init__.cpython-310.pyc b/env-llmeval/lib/python3.10/site-packages/examples/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..afa54107894e8b04d74a71b6c6c8cfd9c5431abd Binary files /dev/null and b/env-llmeval/lib/python3.10/site-packages/examples/__pycache__/__init__.cpython-310.pyc differ diff --git a/env-llmeval/lib/python3.10/site-packages/examples/__pycache__/basic_example.cpython-310.pyc b/env-llmeval/lib/python3.10/site-packages/examples/__pycache__/basic_example.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..d9707eead13423071ecd9d4715ce129d88d25a14 Binary files /dev/null and b/env-llmeval/lib/python3.10/site-packages/examples/__pycache__/basic_example.cpython-310.pyc differ diff --git a/env-llmeval/lib/python3.10/site-packages/examples/basic_example.py b/env-llmeval/lib/python3.10/site-packages/examples/basic_example.py new file mode 100644 index 0000000000000000000000000000000000000000..7d6402f67c25ac28f5d0132398e3982d030c86f9 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/examples/basic_example.py @@ -0,0 +1,60 @@ +from time import sleep +import multiprocessing + +import logging +from tqdm_multiprocess.logger import setup_logger_tqdm +logger = logging.getLogger(__name__) + +from tqdm_multiprocess import TqdmMultiProcessPool + +def some_other_function(tqdm_func): + iterations1 = 100 + iterations2 = 5 + iterations3 = 2 + + total_iterations = iterations1 * iterations2 * iterations3 + with tqdm_func(total=total_iterations, dynamic_ncols=True) as progress3: + progress3.set_description("outer") + for i in range(iterations3): + logger.info("outer") + total_iterations = iterations1 * iterations2 + with tqdm_func(total=total_iterations, dynamic_ncols=True) as progress2: + progress2.set_description("middle") + for j in range(iterations2): + logger.info("middle") + #for k in tqdm_func(range(iterations1), dynamic_ncols=True, desc="inner"): + with tqdm_func(total=iterations1, dynamic_ncols=True) as progress1: + for j in range(iterations1): + # logger.info("inner") # Spam slows down tqdm too much + progress1.set_description("innert") + sleep(0.01) + progress1.update() + progress2.update() + progress3.update() + + logger.warning(f"Warning test message. {multiprocessing.current_process().name}") + logger.error(f"Error test message. {multiprocessing.current_process().name}") + + +# Multiprocessed +def example_multiprocessing_function(some_input, tqdm_func): + logger.debug(f"Debug test message - I won't show up in console. {multiprocessing.current_process().name}") + logger.info(f"Info test message. {multiprocessing.current_process().name}") + some_other_function(tqdm_func) + return True + +def error_callback(): + print("Error!") + +def example(): + pool = TqdmMultiProcessPool() + process_count = 4 + task_count = 10 + initial_tasks = [(example_multiprocessing_function, (i,)) for i in range(task_count)] + results = pool.map(process_count, initial_tasks, error_callback) + print(results) + +if __name__ == '__main__': + logfile_path = "tqdm_multiprocessing_example.log" + setup_logger_tqdm(logfile_path) # Logger will write messages using tqdm.write + example() \ No newline at end of file diff --git a/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/INSTALLER b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/INSTALLER @@ -0,0 +1 @@ +pip diff --git a/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/LICENSE b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..7082a2d5b9047bfc09589f387053e24ea490bc54 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/LICENSE @@ -0,0 +1,201 @@ +Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2013-2019 Nikolay Kim and Andrew Svetlov + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/METADATA b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..60603d5a5a4db0e2896acef9d10496d89aed677e --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/METADATA @@ -0,0 +1,420 @@ +Metadata-Version: 2.1 +Name: frozenlist +Version: 1.4.1 +Summary: A list-like structure which implements collections.abc.MutableSequence +Home-page: https://github.com/aio-libs/frozenlist +Maintainer: aiohttp team +Maintainer-email: team@aiohttp.org +License: Apache 2 +Project-URL: Chat: Matrix, https://matrix.to/#/#aio-libs:matrix.org +Project-URL: Chat: Matrix Space, https://matrix.to/#/#aio-libs-space:matrix.org +Project-URL: CI: Github Actions, https://github.com/aio-libs/frozenlist/actions +Project-URL: Code of Conduct, https://github.com/aio-libs/.github/blob/master/CODE_OF_CONDUCT.md +Project-URL: Coverage: codecov, https://codecov.io/github/aio-libs/frozenlist +Project-URL: Docs: Changelog, https://github.com/aio-libs/frozenlist/blob/master/CHANGES.rst#changelog +Project-URL: Docs: RTD, https://frozenlist.aio-libs.org +Project-URL: GitHub: issues, https://github.com/aio-libs/frozenlist/issues +Project-URL: GitHub: repo, https://github.com/aio-libs/frozenlist +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: Apache Software License +Classifier: Operating System :: POSIX +Classifier: Operating System :: MacOS :: MacOS X +Classifier: Operating System :: Microsoft :: Windows +Classifier: Programming Language :: Cython +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Programming Language :: Python :: Implementation :: CPython +Classifier: Programming Language :: Python :: Implementation :: PyPy +Requires-Python: >=3.8 +Description-Content-Type: text/x-rst +License-File: LICENSE + +frozenlist +========== + +.. image:: https://github.com/aio-libs/frozenlist/workflows/CI/badge.svg + :target: https://github.com/aio-libs/frozenlist/actions + :alt: GitHub status for master branch + +.. image:: https://codecov.io/gh/aio-libs/frozenlist/branch/master/graph/badge.svg + :target: https://codecov.io/gh/aio-libs/frozenlist + :alt: codecov.io status for master branch + +.. image:: https://img.shields.io/pypi/v/frozenlist.svg?logo=Python&logoColor=white + :target: https://pypi.org/project/frozenlist + :alt: frozenlist @ PyPI + +.. image:: https://readthedocs.org/projects/frozenlist/badge/?version=latest + :target: https://frozenlist.aio-libs.org + :alt: Read The Docs build status badge + +.. image:: https://img.shields.io/matrix/aio-libs:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat + :target: https://matrix.to/#/%23aio-libs:matrix.org + :alt: Matrix Room — #aio-libs:matrix.org + +.. image:: https://img.shields.io/matrix/aio-libs-space:matrix.org?label=Discuss%20on%20Matrix%20at%20%23aio-libs-space%3Amatrix.org&logo=matrix&server_fqdn=matrix.org&style=flat + :target: https://matrix.to/#/%23aio-libs-space:matrix.org + :alt: Matrix Space — #aio-libs-space:matrix.org + +Introduction +------------ + +``frozenlist.FrozenList`` is a list-like structure which implements +``collections.abc.MutableSequence``. The list is *mutable* until ``FrozenList.freeze`` +is called, after which list modifications raise ``RuntimeError``: + + +>>> from frozenlist import FrozenList +>>> fl = FrozenList([17, 42]) +>>> fl.append('spam') +>>> fl.append('Vikings') +>>> fl + +>>> fl.freeze() +>>> fl + +>>> fl.frozen +True +>>> fl.append("Monty") +Traceback (most recent call last): + File "", line 1, in + File "frozenlist/_frozenlist.pyx", line 97, in frozenlist._frozenlist.FrozenList.append + self._check_frozen() + File "frozenlist/_frozenlist.pyx", line 19, in frozenlist._frozenlist.FrozenList._check_frozen + raise RuntimeError("Cannot modify frozen list.") +RuntimeError: Cannot modify frozen list. + + +FrozenList is also hashable, but only when frozen. Otherwise it also throws a RuntimeError: + + +>>> fl = FrozenList([17, 42, 'spam']) +>>> hash(fl) +Traceback (most recent call last): + File "", line 1, in + File "frozenlist/_frozenlist.pyx", line 111, in frozenlist._frozenlist.FrozenList.__hash__ + raise RuntimeError("Cannot hash unfrozen list.") +RuntimeError: Cannot hash unfrozen list. +>>> fl.freeze() +>>> hash(fl) +3713081631934410656 +>>> dictionary = {fl: 'Vikings'} # frozen fl can be a dict key +>>> dictionary +{: 'Vikings'} + + +Installation +------------ + +:: + + $ pip install frozenlist + +The library requires Python 3.8 or newer. + + +Documentation +------------- + +https://frozenlist.aio-libs.org + +Communication channels +---------------------- + +We have a *Matrix Space* `#aio-libs-space:matrix.org +`_ which is +also accessible via Gitter. + +Requirements +------------ + +- Python >= 3.8 + +License +------- + +``frozenlist`` is offered under the Apache 2 license. + +Source code +----------- + +The project is hosted on GitHub_ + +Please file an issue in the `bug tracker +`_ if you have found a bug +or have some suggestions to improve the library. + +.. _GitHub: https://github.com/aio-libs/frozenlist + +========= +Changelog +========= + +.. + You should *NOT* be adding new change log entries to this file, this + file is managed by towncrier. You *may* edit previous change logs to + fix problems like typo corrections or such. + To add a new change log entry, please see + https://pip.pypa.io/en/latest/development/contributing/#news-entries + we named the news folder "changes". + + WARNING: Don't drop the next directive! + +.. towncrier release notes start + +1.4.1 (2023-12-15) +================== + +Packaging updates and notes for downstreams +------------------------------------------- + +- Declared Python 3.12 and PyPy 3.8-3.10 supported officially + in the distribution package metadata. + + + *Related issues and pull requests on GitHub:* + `#553 `__. + +- Replaced the packaging is replaced from an old-fashioned ``setup.py`` to an + in-tree `PEP 517 `__ build backend -- by `@webknjaz `__. + + Whenever the end-users or downstream packagers need to build ``frozenlist`` + from source (a Git checkout or an sdist), they may pass a ``config_settings`` + flag ``pure-python``. If this flag is not set, a C-extension will be built + and included into the distribution. + + Here is how this can be done with ``pip``: + + .. code-block:: console + + $ python3 -m pip install . --config-settings=pure-python= + + This will also work with ``-e | --editable``. + + The same can be achieved via ``pypa/build``: + + .. code-block:: console + + $ python3 -m build --config-setting=pure-python= + + Adding ``-w | --wheel`` can force ``pypa/build`` produce a wheel from source + directly, as opposed to building an ``sdist`` and then building from it. + + + *Related issues and pull requests on GitHub:* + `#560 `__. + + +Contributor-facing changes +-------------------------- + +- It is now possible to request line tracing in Cython builds using the + ``with-cython-tracing`` `PEP 517 `__ config setting + -- `@webknjaz `__. + + This can be used in CI and development environment to measure coverage + on Cython modules, but is not normally useful to the end-users or + downstream packagers. + + Here's a usage example: + + .. code-block:: console + + $ python3 -Im pip install . --config-settings=with-cython-tracing=true + + For editable installs, this setting is on by default. Otherwise, it's + off unless requested explicitly. + + The following produces C-files required for the Cython coverage + plugin to map the measurements back to the PYX-files: + + .. code-block:: console + + $ python -Im pip install -e . + + Alternatively, the ``FROZENLIST_CYTHON_TRACING=1`` environment variable + can be set to do the same as the `PEP 517 `__ config setting. + + + *Related issues and pull requests on GitHub:* + `#560 `__. + +- Coverage collection has been implemented for the Cython modules + -- by `@webknjaz `__. + + It will also be reported to Codecov from any non-release CI jobs. + + + *Related issues and pull requests on GitHub:* + `#561 `__. + +- A step-by-step ``Release Guide`` guide has + been added, describing how to release *frozenlist* -- by `@webknjaz `__. + + This is primarily targeting the maintainers. + + + *Related issues and pull requests on GitHub:* + `#563 `__. + +- Detailed ``Contributing Guidelines`` on + authoring the changelog fragments have been published in the + documentation -- by `@webknjaz `__. + + + *Related issues and pull requests on GitHub:* + `#564 `__. + + +---- + + +1.4.0 (2023-07-12) +================== + +The published source distribution package became buildable +under Python 3.12. + + +---- + + +Bugfixes +-------- + +- Removed an unused ``typing.Tuple`` import + `#411 `_ + + +Deprecations and Removals +------------------------- + +- Dropped Python 3.7 support. + `#413 `_ + + +Misc +---- + +- `#410 `_, `#433 `_ + + +---- + + +1.3.3 (2022-11-08) +================== + +- Fixed CI runs when creating a new release, where new towncrier versions + fail when the current version section is already present. + + +---- + + +1.3.2 (2022-11-08) +================== + +Misc +---- + +- Updated the CI runs to better check for test results and to avoid deprecated syntax. `#327 `_ + + +---- + + +1.3.1 (2022-08-02) +================== + +The published source distribution package became buildable +under Python 3.11. + + +---- + + +1.3.0 (2022-01-18) +================== + +Bugfixes +-------- + +- Do not install C sources with binary distributions. + `#250 `_ + + +Deprecations and Removals +------------------------- + +- Dropped Python 3.6 support + `#274 `_ + + +---- + + +1.2.0 (2021-10-16) +================== + +Features +-------- + +- ``FrozenList`` now supports being used as a generic type as per PEP 585, e.g. ``frozen_int_list: FrozenList[int]`` (requires Python 3.9 or newer). + `#172 `_ +- Added support for Python 3.10. + `#227 `_ +- Started shipping platform-specific wheels with the ``musl`` tag targeting typical Alpine Linux runtimes. + `#227 `_ +- Started shipping platform-specific arm64 wheels for Apple Silicon. + `#227 `_ + + +---- + + +1.1.1 (2020-11-14) +================== + +Bugfixes +-------- + +- Provide x86 Windows wheels. + `#169 `_ + + +---- + + +1.1.0 (2020-10-13) +================== + +Features +-------- + +- Add support for hashing of a frozen list. + `#136 `_ + +- Support Python 3.8 and 3.9. + +- Provide wheels for ``aarch64``, ``i686``, ``ppc64le``, ``s390x`` architectures on + Linux as well as ``x86_64``. + + +---- + + +1.0.0 (2019-11-09) +================== + +Deprecations and Removals +------------------------- + +- Dropped support for Python 3.5; only 3.6, 3.7 and 3.8 are supported going forward. + `#24 `_ diff --git a/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/RECORD b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..b55212cbb06d5523203c55e2ff396b55dc900b59 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/RECORD @@ -0,0 +1,12 @@ +frozenlist-1.4.1.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4 +frozenlist-1.4.1.dist-info/LICENSE,sha256=b9UkPpLdf5jsacesN3co50kFcJ_1J6W_mNbQJjwE9bY,11332 +frozenlist-1.4.1.dist-info/METADATA,sha256=i-BTxwxpJrHm-I8DMpFRvXVXJiqXwUcsPiUR47NY6eg,12136 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b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/WHEEL @@ -0,0 +1,8 @@ +Wheel-Version: 1.0 +Generator: bdist_wheel (0.42.0) +Root-Is-Purelib: false +Tag: cp310-cp310-manylinux_2_5_x86_64 +Tag: cp310-cp310-manylinux1_x86_64 +Tag: cp310-cp310-manylinux_2_17_x86_64 +Tag: cp310-cp310-manylinux2014_x86_64 + diff --git a/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/top_level.txt b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..52f13fc459edf8f3def6f792c432f0b64f313176 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/frozenlist-1.4.1.dist-info/top_level.txt @@ -0,0 +1 @@ +frozenlist diff --git a/env-llmeval/lib/python3.10/site-packages/idna/__init__.py b/env-llmeval/lib/python3.10/site-packages/idna/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..a40eeafcc914108ca79c5d83d6e81da1b29c6e80 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/idna/__init__.py @@ -0,0 +1,44 @@ +from .package_data import __version__ +from .core import ( + IDNABidiError, + IDNAError, + InvalidCodepoint, + InvalidCodepointContext, + alabel, + check_bidi, + check_hyphen_ok, + check_initial_combiner, + check_label, + check_nfc, + decode, + encode, + ulabel, + uts46_remap, + valid_contextj, + valid_contexto, + valid_label_length, + valid_string_length, +) +from .intranges import intranges_contain + +__all__ = [ + "IDNABidiError", + "IDNAError", + "InvalidCodepoint", + "InvalidCodepointContext", + "alabel", + "check_bidi", + "check_hyphen_ok", + "check_initial_combiner", + "check_label", + "check_nfc", + "decode", + "encode", + "intranges_contain", + "ulabel", + "uts46_remap", + "valid_contextj", + "valid_contexto", + "valid_label_length", + "valid_string_length", +] diff --git a/env-llmeval/lib/python3.10/site-packages/idna/__pycache__/__init__.cpython-310.pyc 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b/env-llmeval/lib/python3.10/site-packages/idna/__pycache__/uts46data.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..1ae0d133f3c4107aca2b290be008fd21abb10ed5 Binary files /dev/null and b/env-llmeval/lib/python3.10/site-packages/idna/__pycache__/uts46data.cpython-310.pyc differ diff --git a/env-llmeval/lib/python3.10/site-packages/idna/codec.py b/env-llmeval/lib/python3.10/site-packages/idna/codec.py new file mode 100644 index 0000000000000000000000000000000000000000..c855a4de6d781815acf2334306f41b7a036c45d4 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/idna/codec.py @@ -0,0 +1,118 @@ +from .core import encode, decode, alabel, ulabel, IDNAError +import codecs +import re +from typing import Any, Tuple, Optional + +_unicode_dots_re = re.compile('[\u002e\u3002\uff0e\uff61]') + +class Codec(codecs.Codec): + + def encode(self, data: str, errors: str = 'strict') -> Tuple[bytes, int]: + if errors != 'strict': + raise IDNAError('Unsupported error handling \"{}\"'.format(errors)) + + if not data: + return b"", 0 + + return encode(data), len(data) + + def decode(self, data: bytes, errors: str = 'strict') -> Tuple[str, int]: + if errors != 'strict': + raise IDNAError('Unsupported error handling \"{}\"'.format(errors)) + + if not data: + return '', 0 + + return decode(data), len(data) + +class IncrementalEncoder(codecs.BufferedIncrementalEncoder): + def _buffer_encode(self, data: str, errors: str, final: bool) -> Tuple[bytes, int]: + if errors != 'strict': + raise IDNAError('Unsupported error handling \"{}\"'.format(errors)) + + if not data: + return b'', 0 + + labels = _unicode_dots_re.split(data) + trailing_dot = b'' + if labels: + if not labels[-1]: + trailing_dot = b'.' + del labels[-1] + elif not final: + # Keep potentially unfinished label until the next call + del labels[-1] + if labels: + trailing_dot = b'.' + + result = [] + size = 0 + for label in labels: + result.append(alabel(label)) + if size: + size += 1 + size += len(label) + + # Join with U+002E + result_bytes = b'.'.join(result) + trailing_dot + size += len(trailing_dot) + return result_bytes, size + +class IncrementalDecoder(codecs.BufferedIncrementalDecoder): + def _buffer_decode(self, data: Any, errors: str, final: bool) -> Tuple[str, int]: + if errors != 'strict': + raise IDNAError('Unsupported error handling \"{}\"'.format(errors)) + + if not data: + return ('', 0) + + if not isinstance(data, str): + data = str(data, 'ascii') + + labels = _unicode_dots_re.split(data) + trailing_dot = '' + if labels: + if not labels[-1]: + trailing_dot = '.' + del labels[-1] + elif not final: + # Keep potentially unfinished label until the next call + del labels[-1] + if labels: + trailing_dot = '.' + + result = [] + size = 0 + for label in labels: + result.append(ulabel(label)) + if size: + size += 1 + size += len(label) + + result_str = '.'.join(result) + trailing_dot + size += len(trailing_dot) + return (result_str, size) + + +class StreamWriter(Codec, codecs.StreamWriter): + pass + + +class StreamReader(Codec, codecs.StreamReader): + pass + + +def search_function(name: str) -> Optional[codecs.CodecInfo]: + if name != 'idna2008': + return None + return codecs.CodecInfo( + name=name, + encode=Codec().encode, + decode=Codec().decode, + incrementalencoder=IncrementalEncoder, + incrementaldecoder=IncrementalDecoder, + streamwriter=StreamWriter, + streamreader=StreamReader, + ) + +codecs.register(search_function) diff --git a/env-llmeval/lib/python3.10/site-packages/idna/compat.py b/env-llmeval/lib/python3.10/site-packages/idna/compat.py new file mode 100644 index 0000000000000000000000000000000000000000..786e6bda63699b72d588ba91dd73df017570aee5 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/idna/compat.py @@ -0,0 +1,13 @@ +from .core import * +from .codec import * +from typing import Any, Union + +def ToASCII(label: str) -> bytes: + return encode(label) + +def ToUnicode(label: Union[bytes, bytearray]) -> str: + return decode(label) + +def nameprep(s: Any) -> None: + raise NotImplementedError('IDNA 2008 does not utilise nameprep protocol') + diff --git a/env-llmeval/lib/python3.10/site-packages/idna/core.py b/env-llmeval/lib/python3.10/site-packages/idna/core.py new file mode 100644 index 0000000000000000000000000000000000000000..0dae61acdbccad9a08f1a82cf14839037873dc56 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/idna/core.py @@ -0,0 +1,395 @@ +from . import idnadata +import bisect +import unicodedata +import re +from typing import Union, Optional +from .intranges import intranges_contain + +_virama_combining_class = 9 +_alabel_prefix = b'xn--' +_unicode_dots_re = re.compile('[\u002e\u3002\uff0e\uff61]') + +class IDNAError(UnicodeError): + """ Base exception for all IDNA-encoding related problems """ + pass + + +class IDNABidiError(IDNAError): + """ Exception when bidirectional requirements are not satisfied """ + pass + + +class InvalidCodepoint(IDNAError): + """ Exception when a disallowed or unallocated codepoint is used """ + pass + + +class InvalidCodepointContext(IDNAError): + """ Exception when the codepoint is not valid in the context it is used """ + pass + + +def _combining_class(cp: int) -> int: + v = unicodedata.combining(chr(cp)) + if v == 0: + if not unicodedata.name(chr(cp)): + raise ValueError('Unknown character in unicodedata') + return v + +def _is_script(cp: str, script: str) -> bool: + return intranges_contain(ord(cp), idnadata.scripts[script]) + +def _punycode(s: str) -> bytes: + return s.encode('punycode') + +def _unot(s: int) -> str: + return 'U+{:04X}'.format(s) + + +def valid_label_length(label: Union[bytes, str]) -> bool: + if len(label) > 63: + return False + return True + + +def valid_string_length(label: Union[bytes, str], trailing_dot: bool) -> bool: + if len(label) > (254 if trailing_dot else 253): + return False + return True + + +def check_bidi(label: str, check_ltr: bool = False) -> bool: + # Bidi rules should only be applied if string contains RTL characters + bidi_label = False + for (idx, cp) in enumerate(label, 1): + direction = unicodedata.bidirectional(cp) + if direction == '': + # String likely comes from a newer version of Unicode + raise IDNABidiError('Unknown directionality in label {} at position {}'.format(repr(label), idx)) + if direction in ['R', 'AL', 'AN']: + bidi_label = True + if not bidi_label and not check_ltr: + return True + + # Bidi rule 1 + direction = unicodedata.bidirectional(label[0]) + if direction in ['R', 'AL']: + rtl = True + elif direction == 'L': + rtl = False + else: + raise IDNABidiError('First codepoint in label {} must be directionality L, R or AL'.format(repr(label))) + + valid_ending = False + number_type = None # type: Optional[str] + for (idx, cp) in enumerate(label, 1): + direction = unicodedata.bidirectional(cp) + + if rtl: + # Bidi rule 2 + if not direction in ['R', 'AL', 'AN', 'EN', 'ES', 'CS', 'ET', 'ON', 'BN', 'NSM']: + raise IDNABidiError('Invalid direction for codepoint at position {} in a right-to-left label'.format(idx)) + # Bidi rule 3 + if direction in ['R', 'AL', 'EN', 'AN']: + valid_ending = True + elif direction != 'NSM': + valid_ending = False + # Bidi rule 4 + if direction in ['AN', 'EN']: + if not number_type: + number_type = direction + else: + if number_type != direction: + raise IDNABidiError('Can not mix numeral types in a right-to-left label') + else: + # Bidi rule 5 + if not direction in ['L', 'EN', 'ES', 'CS', 'ET', 'ON', 'BN', 'NSM']: + raise IDNABidiError('Invalid direction for codepoint at position {} in a left-to-right label'.format(idx)) + # Bidi rule 6 + if direction in ['L', 'EN']: + valid_ending = True + elif direction != 'NSM': + valid_ending = False + + if not valid_ending: + raise IDNABidiError('Label ends with illegal codepoint directionality') + + return True + + +def check_initial_combiner(label: str) -> bool: + if unicodedata.category(label[0])[0] == 'M': + raise IDNAError('Label begins with an illegal combining character') + return True + + +def check_hyphen_ok(label: str) -> bool: + if label[2:4] == '--': + raise IDNAError('Label has disallowed hyphens in 3rd and 4th position') + if label[0] == '-' or label[-1] == '-': + raise IDNAError('Label must not start or end with a hyphen') + return True + + +def check_nfc(label: str) -> None: + if unicodedata.normalize('NFC', label) != label: + raise IDNAError('Label must be in Normalization Form C') + + +def valid_contextj(label: str, pos: int) -> bool: + cp_value = ord(label[pos]) + + if cp_value == 0x200c: + + if pos > 0: + if _combining_class(ord(label[pos - 1])) == _virama_combining_class: + return True + + ok = False + for i in range(pos-1, -1, -1): + joining_type = idnadata.joining_types.get(ord(label[i])) + if joining_type == ord('T'): + continue + elif joining_type in [ord('L'), ord('D')]: + ok = True + break + else: + break + + if not ok: + return False + + ok = False + for i in range(pos+1, len(label)): + joining_type = idnadata.joining_types.get(ord(label[i])) + if joining_type == ord('T'): + continue + elif joining_type in [ord('R'), ord('D')]: + ok = True + break + else: + break + return ok + + if cp_value == 0x200d: + + if pos > 0: + if _combining_class(ord(label[pos - 1])) == _virama_combining_class: + return True + return False + + else: + + return False + + +def valid_contexto(label: str, pos: int, exception: bool = False) -> bool: + cp_value = ord(label[pos]) + + if cp_value == 0x00b7: + if 0 < pos < len(label)-1: + if ord(label[pos - 1]) == 0x006c and ord(label[pos + 1]) == 0x006c: + return True + return False + + elif cp_value == 0x0375: + if pos < len(label)-1 and len(label) > 1: + return _is_script(label[pos + 1], 'Greek') + return False + + elif cp_value == 0x05f3 or cp_value == 0x05f4: + if pos > 0: + return _is_script(label[pos - 1], 'Hebrew') + return False + + elif cp_value == 0x30fb: + for cp in label: + if cp == '\u30fb': + continue + if _is_script(cp, 'Hiragana') or _is_script(cp, 'Katakana') or _is_script(cp, 'Han'): + return True + return False + + elif 0x660 <= cp_value <= 0x669: + for cp in label: + if 0x6f0 <= ord(cp) <= 0x06f9: + return False + return True + + elif 0x6f0 <= cp_value <= 0x6f9: + for cp in label: + if 0x660 <= ord(cp) <= 0x0669: + return False + return True + + return False + + +def check_label(label: Union[str, bytes, bytearray]) -> None: + if isinstance(label, (bytes, bytearray)): + label = label.decode('utf-8') + if len(label) == 0: + raise IDNAError('Empty Label') + + check_nfc(label) + check_hyphen_ok(label) + check_initial_combiner(label) + + for (pos, cp) in enumerate(label): + cp_value = ord(cp) + if intranges_contain(cp_value, idnadata.codepoint_classes['PVALID']): + continue + elif intranges_contain(cp_value, idnadata.codepoint_classes['CONTEXTJ']): + if not valid_contextj(label, pos): + raise InvalidCodepointContext('Joiner {} not allowed at position {} in {}'.format( + _unot(cp_value), pos+1, repr(label))) + elif intranges_contain(cp_value, idnadata.codepoint_classes['CONTEXTO']): + if not valid_contexto(label, pos): + raise InvalidCodepointContext('Codepoint {} not allowed at position {} in {}'.format(_unot(cp_value), pos+1, repr(label))) + else: + raise InvalidCodepoint('Codepoint {} at position {} of {} not allowed'.format(_unot(cp_value), pos+1, repr(label))) + + check_bidi(label) + + +def alabel(label: str) -> bytes: + try: + label_bytes = label.encode('ascii') + ulabel(label_bytes) + if not valid_label_length(label_bytes): + raise IDNAError('Label too long') + return label_bytes + except UnicodeEncodeError: + pass + + check_label(label) + label_bytes = _alabel_prefix + _punycode(label) + + if not valid_label_length(label_bytes): + raise IDNAError('Label too long') + + return label_bytes + + +def ulabel(label: Union[str, bytes, bytearray]) -> str: + if not isinstance(label, (bytes, bytearray)): + try: + label_bytes = label.encode('ascii') + except UnicodeEncodeError: + check_label(label) + return label + else: + label_bytes = label + + label_bytes = label_bytes.lower() + if label_bytes.startswith(_alabel_prefix): + label_bytes = label_bytes[len(_alabel_prefix):] + if not label_bytes: + raise IDNAError('Malformed A-label, no Punycode eligible content found') + if label_bytes.decode('ascii')[-1] == '-': + raise IDNAError('A-label must not end with a hyphen') + else: + check_label(label_bytes) + return label_bytes.decode('ascii') + + try: + label = label_bytes.decode('punycode') + except UnicodeError: + raise IDNAError('Invalid A-label') + check_label(label) + return label + + +def uts46_remap(domain: str, std3_rules: bool = True, transitional: bool = False) -> str: + """Re-map the characters in the string according to UTS46 processing.""" + from .uts46data import uts46data + output = '' + + for pos, char in enumerate(domain): + code_point = ord(char) + try: + uts46row = uts46data[code_point if code_point < 256 else + bisect.bisect_left(uts46data, (code_point, 'Z')) - 1] + status = uts46row[1] + replacement = None # type: Optional[str] + if len(uts46row) == 3: + replacement = uts46row[2] + if (status == 'V' or + (status == 'D' and not transitional) or + (status == '3' and not std3_rules and replacement is None)): + output += char + elif replacement is not None and (status == 'M' or + (status == '3' and not std3_rules) or + (status == 'D' and transitional)): + output += replacement + elif status != 'I': + raise IndexError() + except IndexError: + raise InvalidCodepoint( + 'Codepoint {} not allowed at position {} in {}'.format( + _unot(code_point), pos + 1, repr(domain))) + + return unicodedata.normalize('NFC', output) + + +def encode(s: Union[str, bytes, bytearray], strict: bool = False, uts46: bool = False, std3_rules: bool = False, transitional: bool = False) -> bytes: + if not isinstance(s, str): + try: + s = str(s, 'ascii') + except UnicodeDecodeError: + raise IDNAError('should pass a unicode string to the function rather than a byte string.') + if uts46: + s = uts46_remap(s, std3_rules, transitional) + trailing_dot = False + result = [] + if strict: + labels = s.split('.') + else: + labels = _unicode_dots_re.split(s) + if not labels or labels == ['']: + raise IDNAError('Empty domain') + if labels[-1] == '': + del labels[-1] + trailing_dot = True + for label in labels: + s = alabel(label) + if s: + result.append(s) + else: + raise IDNAError('Empty label') + if trailing_dot: + result.append(b'') + s = b'.'.join(result) + if not valid_string_length(s, trailing_dot): + raise IDNAError('Domain too long') + return s + + +def decode(s: Union[str, bytes, bytearray], strict: bool = False, uts46: bool = False, std3_rules: bool = False) -> str: + try: + if not isinstance(s, str): + s = str(s, 'ascii') + except UnicodeDecodeError: + raise IDNAError('Invalid ASCII in A-label') + if uts46: + s = uts46_remap(s, std3_rules, False) + trailing_dot = False + result = [] + if not strict: + labels = _unicode_dots_re.split(s) + else: + labels = s.split('.') + if not labels or labels == ['']: + raise IDNAError('Empty domain') + if not labels[-1]: + del labels[-1] + trailing_dot = True + for label in labels: + s = ulabel(label) + if s: + result.append(s) + else: + raise IDNAError('Empty label') + if trailing_dot: + result.append('') + return '.'.join(result) diff --git a/env-llmeval/lib/python3.10/site-packages/idna/idnadata.py b/env-llmeval/lib/python3.10/site-packages/idna/idnadata.py new file mode 100644 index 0000000000000000000000000000000000000000..c61dcf977e57ec0d139e828a7c5a9cd86e55b43a --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/idna/idnadata.py @@ -0,0 +1,4245 @@ +# This file is automatically generated by tools/idna-data + +__version__ = '15.1.0' +scripts = { + 'Greek': ( + 0x37000000374, + 0x37500000378, + 0x37a0000037e, + 0x37f00000380, + 0x38400000385, + 0x38600000387, + 0x3880000038b, + 0x38c0000038d, + 0x38e000003a2, + 0x3a3000003e2, + 0x3f000000400, + 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up of (hopefully) a small number of long runs +of consecutive integers, compute a representation of the form +((start1, end1), (start2, end2) ...). Then answer the question "was x present +in the original list?" in time O(log(# runs)). +""" + +import bisect +from typing import List, Tuple + +def intranges_from_list(list_: List[int]) -> Tuple[int, ...]: + """Represent a list of integers as a sequence of ranges: + ((start_0, end_0), (start_1, end_1), ...), such that the original + integers are exactly those x such that start_i <= x < end_i for some i. + + Ranges are encoded as single integers (start << 32 | end), not as tuples. + """ + + sorted_list = sorted(list_) + ranges = [] + last_write = -1 + for i in range(len(sorted_list)): + if i+1 < len(sorted_list): + if sorted_list[i] == sorted_list[i+1]-1: + continue + current_range = sorted_list[last_write+1:i+1] + ranges.append(_encode_range(current_range[0], current_range[-1] + 1)) + last_write = i + + return tuple(ranges) + +def _encode_range(start: int, end: int) -> int: + return (start << 32) | end + +def _decode_range(r: int) -> Tuple[int, int]: + return (r >> 32), (r & ((1 << 32) - 1)) + + +def intranges_contain(int_: int, ranges: Tuple[int, ...]) -> bool: + """Determine if `int_` falls into one of the ranges in `ranges`.""" + tuple_ = _encode_range(int_, 0) + pos = bisect.bisect_left(ranges, tuple_) + # we could be immediately ahead of a tuple (start, end) + # with start < int_ <= end + if pos > 0: + left, right = _decode_range(ranges[pos-1]) + if left <= int_ < right: + return True + # or we could be immediately behind a tuple (int_, end) + if pos < len(ranges): + left, _ = _decode_range(ranges[pos]) + if left == int_: + return True + return False diff --git a/env-llmeval/lib/python3.10/site-packages/idna/package_data.py b/env-llmeval/lib/python3.10/site-packages/idna/package_data.py new file mode 100644 index 0000000000000000000000000000000000000000..ed8111336331554058dfb0a8d5dcbc0defc62dfe --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/idna/package_data.py @@ -0,0 +1,2 @@ +__version__ = '3.7' + diff --git 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+ + _seg_55() + + _seg_56() + + _seg_57() + + _seg_58() + + _seg_59() + + _seg_60() + + _seg_61() + + _seg_62() + + _seg_63() + + _seg_64() + + _seg_65() + + _seg_66() + + _seg_67() + + _seg_68() + + _seg_69() + + _seg_70() + + _seg_71() + + _seg_72() + + _seg_73() + + _seg_74() + + _seg_75() + + _seg_76() + + _seg_77() + + _seg_78() + + _seg_79() + + _seg_80() + + _seg_81() +) # type: Tuple[Union[Tuple[int, str], Tuple[int, str, str]], ...] diff --git a/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/INSTALLER b/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/INSTALLER @@ -0,0 +1 @@ +pip diff --git a/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/LICENSE.md b/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/LICENSE.md new file mode 100644 index 0000000000000000000000000000000000000000..12e6063183935e876e232db276568baf4954b492 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/LICENSE.md @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2020 EleutherAI + +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. diff --git a/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/METADATA b/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..099b22d41332a805b8a2ad11a66212cbb5c61ef0 --- /dev/null +++ b/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/METADATA @@ -0,0 +1,542 @@ +Metadata-Version: 2.1 +Name: lm_eval +Version: 0.4.2 +Summary: A framework for evaluating language models +Author-email: EleutherAI +License: MIT +Project-URL: Homepage, https://github.com/EleutherAI/lm-evaluation-harness +Project-URL: Repository, https://github.com/EleutherAI/lm-evaluation-harness +Classifier: Development Status :: 3 - Alpha +Classifier: Programming Language :: Python :: 3 +Classifier: License :: OSI Approved :: MIT License +Classifier: Operating System :: OS Independent +Requires-Python: >=3.8 +Description-Content-Type: text/markdown +License-File: LICENSE.md +Requires-Dist: accelerate >=0.21.0 +Requires-Dist: evaluate +Requires-Dist: datasets >=2.16.0 +Requires-Dist: evaluate >=0.4.0 +Requires-Dist: jsonlines +Requires-Dist: numexpr +Requires-Dist: peft >=0.2.0 +Requires-Dist: pybind11 >=2.6.2 +Requires-Dist: pytablewriter +Requires-Dist: rouge-score >=0.0.4 +Requires-Dist: sacrebleu >=1.5.0 +Requires-Dist: scikit-learn >=0.24.1 +Requires-Dist: sqlitedict +Requires-Dist: torch >=1.8 +Requires-Dist: tqdm-multiprocess +Requires-Dist: transformers >=4.1 +Requires-Dist: zstandard +Requires-Dist: dill +Requires-Dist: word2number +Requires-Dist: more-itertools +Provides-Extra: all +Requires-Dist: lm-eval[anthropic] ; extra == 'all' +Requires-Dist: lm-eval[dev] ; extra == 'all' +Requires-Dist: lm-eval[gptq] ; extra == 'all' +Requires-Dist: lm-eval[hf_transfer] ; extra == 'all' +Requires-Dist: lm-eval[ifeval] ; extra == 'all' +Requires-Dist: lm-eval[mamba] ; extra == 'all' +Requires-Dist: lm-eval[math] ; extra == 'all' +Requires-Dist: lm-eval[multilingual] ; extra == 'all' +Requires-Dist: lm-eval[openai] ; extra == 'all' +Requires-Dist: lm-eval[promptsource] ; extra == 'all' +Requires-Dist: lm-eval[sentencepiece] ; extra == 'all' +Requires-Dist: lm-eval[testing] ; extra == 'all' +Requires-Dist: lm-eval[vllm] ; extra == 'all' +Requires-Dist: lm-eval[zeno] ; extra == 'all' +Requires-Dist: lm-eval[wandb] ; extra == 'all' +Provides-Extra: anthropic +Requires-Dist: anthropic ; extra == 'anthropic' +Provides-Extra: dev +Requires-Dist: pytest ; extra == 'dev' +Requires-Dist: pytest-cov ; extra == 'dev' +Requires-Dist: pytest-xdist ; extra == 'dev' +Requires-Dist: pre-commit ; extra == 'dev' +Requires-Dist: mypy ; extra == 'dev' +Provides-Extra: gptq +Requires-Dist: auto-gptq[triton] >=0.6.0 ; extra == 'gptq' +Provides-Extra: hf_transfer +Requires-Dist: hf-transfer ; extra == 'hf_transfer' +Provides-Extra: ifeval +Requires-Dist: langdetect ; extra == 'ifeval' +Requires-Dist: immutabledict ; extra == 'ifeval' +Provides-Extra: mamba +Requires-Dist: mamba-ssm ; extra == 'mamba' +Requires-Dist: causal-conv1d ==1.0.2 ; extra == 'mamba' +Provides-Extra: math +Requires-Dist: sympy >=1.12 ; extra == 'math' +Requires-Dist: antlr4-python3-runtime ==4.11 ; extra == 'math' +Provides-Extra: multilingual +Requires-Dist: nagisa >=0.2.7 ; extra == 'multilingual' +Requires-Dist: jieba >=0.42.1 ; extra == 'multilingual' +Requires-Dist: pycountry ; extra == 'multilingual' +Provides-Extra: neuronx +Requires-Dist: optimum[neuronx] ; extra == 'neuronx' +Provides-Extra: openai +Requires-Dist: openai ==1.3.9 ; extra == 'openai' +Requires-Dist: tiktoken ; extra == 'openai' +Provides-Extra: optimum +Requires-Dist: optimum[openvino] ; extra == 'optimum' +Provides-Extra: promptsource +Requires-Dist: promptsource >=0.2.3 ; extra == 'promptsource' +Provides-Extra: sentencepiece +Requires-Dist: sentencepiece >=0.1.98 ; extra == 'sentencepiece' +Requires-Dist: protobuf >=4.22.1 ; extra == 'sentencepiece' +Provides-Extra: testing +Requires-Dist: pytest ; extra == 'testing' +Requires-Dist: pytest-cov ; extra == 'testing' +Requires-Dist: pytest-xdist ; extra == 'testing' +Provides-Extra: vllm +Requires-Dist: vllm ==0.3.2 ; extra == 'vllm' +Provides-Extra: wandb +Requires-Dist: wandb >=0.16.3 ; extra == 'wandb' +Requires-Dist: pandas ; extra == 'wandb' +Requires-Dist: numpy ; extra == 'wandb' +Provides-Extra: zeno +Requires-Dist: pandas ; extra == 'zeno' +Requires-Dist: zeno-client ; extra == 'zeno' + +# Language Model Evaluation Harness + +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10256836.svg)](https://doi.org/10.5281/zenodo.10256836) + +## Announcement +**A new v0.4.0 release of lm-evaluation-harness is available** ! + +New updates and features include: + +- Internal refactoring +- Config-based task creation and configuration +- Easier import and sharing of externally-defined task config YAMLs +- Support for Jinja2 prompt design, easy modification of prompts + prompt imports from Promptsource +- More advanced configuration options, including output post-processing, answer extraction, and multiple LM generations per document, configurable fewshot settings, and more +- Speedups and new modeling libraries supported, including: faster data-parallel HF model usage, vLLM support, MPS support with HuggingFace, and more +- Logging and usability changes +- New tasks including CoT BIG-Bench-Hard, Belebele, user-defined task groupings, and more + +Please see our updated documentation pages in `docs/` for more details. + +Development will be continuing on the `main` branch, and we encourage you to give us feedback on what features are desired and how to improve the library further, or ask questions, either in issues or PRs on GitHub, or in the [EleutherAI discord](https://discord.gg/eleutherai)! + +## Overview + +This project provides a unified framework to test generative language models on a large number of different evaluation tasks. + +**Features:** +- Over 60 standard academic benchmarks for LLMs, with hundreds of subtasks and variants implemented. +- Support for models loaded via [transformers](https://github.com/huggingface/transformers/) (including quantization via [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ)), [GPT-NeoX](https://github.com/EleutherAI/gpt-neox), and [Megatron-DeepSpeed](https://github.com/microsoft/Megatron-DeepSpeed/), with a flexible tokenization-agnostic interface. +- Support for fast and memory-efficient inference with [vLLM](https://github.com/vllm-project/vllm). +- Support for commercial APIs including [OpenAI](https://openai.com), and [TextSynth](https://textsynth.com/). +- Support for evaluation on adapters (e.g. LoRA) supported in [HuggingFace's PEFT library](https://github.com/huggingface/peft). +- Support for local models and benchmarks. +- Evaluation with publicly available prompts ensures reproducibility and comparability between papers. +- Easy support for custom prompts and evaluation metrics. + +The Language Model Evaluation Harness is the backend for 🤗 Hugging Face's popular [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard), has been used in [hundreds of papers](https://scholar.google.com/scholar?oi=bibs&hl=en&authuser=2&cites=15052937328817631261,4097184744846514103,1520777361382155671,17476825572045927382,18443729326628441434,14801318227356878622,7890865700763267262,12854182577605049984,15641002901115500560,5104500764547628290), and is used internally by dozens of organizations including NVIDIA, Cohere, BigScience, BigCode, Nous Research, and Mosaic ML. + +## Install + +To install the `lm-eval` package from the github repository, run: + +```bash +git clone https://github.com/EleutherAI/lm-evaluation-harness +cd lm-evaluation-harness +pip install -e . +``` + +We also provide a number of optional dependencies for extended functionality. A detailed table is available at the end of this document. + +## Basic Usage + +### Hugging Face `transformers` + +To evaluate a model hosted on the [HuggingFace Hub](https://huggingface.co/models) (e.g. GPT-J-6B) on `hellaswag` you can use the following command (this assumes you are using a CUDA-compatible GPU): + +```bash +lm_eval --model hf \ + --model_args pretrained=EleutherAI/gpt-j-6B \ + --tasks hellaswag \ + --device cuda:0 \ + --batch_size 8 +``` + +Additional arguments can be provided to the model constructor using the `--model_args` flag. Most notably, this supports the common practice of using the `revisions` feature on the Hub to store partially trained checkpoints, or to specify the datatype for running a model: + +```bash +lm_eval --model hf \ + --model_args pretrained=EleutherAI/pythia-160m,revision=step100000,dtype="float" \ + --tasks lambada_openai,hellaswag \ + --device cuda:0 \ + --batch_size 8 +``` + +Models that are loaded via both `transformers.AutoModelForCausalLM` (autoregressive, decoder-only GPT style models) and `transformers.AutoModelForSeq2SeqLM` (such as encoder-decoder models like T5) in Huggingface are supported. + +Batch size selection can be automated by setting the ```--batch_size``` flag to ```auto```. This will perform automatic detection of the largest batch size that will fit on your device. On tasks where there is a large difference between the longest and shortest example, it can be helpful to periodically recompute the largest batch size, to gain a further speedup. To do this, append ```:N``` to above flag to automatically recompute the largest batch size ```N``` times. For example, to recompute the batch size 4 times, the command would be: + +```bash +lm_eval --model hf \ + --model_args pretrained=EleutherAI/pythia-160m,revision=step100000,dtype="float" \ + --tasks lambada_openai,hellaswag \ + --device cuda:0 \ + --batch_size auto:4 +``` + +The full list of supported arguments are provided [here](./docs/interface.md), and on the terminal by calling `lm_eval -h`. Alternatively, you can use `lm-eval` instead of `lm_eval`. + +> [!Note] +> Just like you can provide a local path to `transformers.AutoModel`, you can also provide a local path to `lm_eval` via `--model_args pretrained=/path/to/model` + +#### Multi-GPU Evaluation with Hugging Face `accelerate` + +We support two main ways of using Hugging Face's [accelerate 🚀](https://github.com/huggingface/accelerate) library for multi-GPU evaluation. + +To perform *data-parallel evaluation* (where each GPU loads a **separate full copy** of the model), we leverage the `accelerate` launcher as follows: + +``` +accelerate launch -m lm_eval --model hf \ + --tasks lambada_openai,arc_easy \ + --batch_size 16 +``` +(or via `accelerate launch --no-python lm_eval`). + +For cases where your model can fit on a single GPU, this allows you to evaluate on K GPUs K times faster than on one. + +**WARNING**: This setup does not work with FSDP model sharding, so in `accelerate config` FSDP must be disabled, or the NO_SHARD FSDP option must be used. + +The second way of using `accelerate` for multi-GPU evaluation is when your model is *too large to fit on a single GPU.* + +In this setting, run the library *outside of the `accelerate` launcher*, but passing `parallelize=True` to `--model_args` as follows: + +``` +lm_eval --model hf \ + --tasks lambada_openai,arc_easy \ + --model_args parallelize=True \ + --batch_size 16 +``` + +This means that your model's weights will be split across all available GPUs. + +For more advanced users or even larger models, we allow for the following arguments when `parallelize=True` as well: +- `device_map_option`: How to split model weights across available GPUs. defaults to "auto". +- `max_memory_per_gpu`: the max GPU memory to use per GPU in loading the model. +- `max_cpu_memory`: the max amount of CPU memory to use when offloading the model weights to RAM. +- `offload_folder`: a folder where model weights will be offloaded to disk if needed. + +These two options (`accelerate launch` and `parallelize=True`) are mutually exclusive. + +**Note: we do not currently support multi-node evaluations natively, and advise using either an externally hosted server to run inference requests against, or creating a custom integration with your distributed framework [as is done for the GPT-NeoX library](https://github.com/EleutherAI/gpt-neox/blob/main/eval_tasks/eval_adapter.py).** + +### NVIDIA `nemo` models + +[NVIDIA NeMo Framework](https://github.com/NVIDIA/NeMo) is a generative AI framework built for researchers and pytorch developers working on language models. + +To evaluate a `nemo` model, start by installing NeMo following [the documentation](https://github.com/NVIDIA/NeMo?tab=readme-ov-file#installation). We highly recommended to use the NVIDIA PyTorch or NeMo container, especially if having issues installing Apex or any other dependencies (see [latest released containers](https://github.com/NVIDIA/NeMo/releases)). Please also install the lm evaluation harness library following the instructions in [the Install section](https://github.com/EleutherAI/lm-evaluation-harness/tree/main?tab=readme-ov-file#install). + +NeMo models can be obtained through [NVIDIA NGC Catalog](https://catalog.ngc.nvidia.com/models) or in [NVIDIA's Hugging Face page](https://huggingface.co/nvidia). In [NVIDIA NeMo Framework](https://github.com/NVIDIA/NeMo/tree/main/scripts/nlp_language_modeling) there are conversion scripts to convert the `hf` checkpoints of popular models like llama, falcon, mixtral or mpt to `nemo`. + +Run a `nemo` model on one GPU: +```bash +lm_eval --model nemo_lm \ + --model_args path= \ + --tasks hellaswag \ + --batch_size 32 +``` + +It is recommended to unpack the `nemo` model to avoid the unpacking inside the docker container - it may overflow disk space. For that you can run: + +``` +mkdir MY_MODEL +tar -xvf MY_MODEL.nemo -c MY_MODEL +``` + +#### Multi-GPU evaluation with NVIDIA `nemo` models + +By default, only one GPU is used. But we do support either data replication or tensor/pipeline parallelism during evaluation, on one node. + +1) To enable data replication, set the `model_args` of `devices` to the number of data replicas to run. For example, the command to run 8 data replicas over 8 GPUs is: +```bash +torchrun --nproc-per-node=8 --no-python lm_eval \ + --model nemo_lm \ + --model_args path=,devices=8 \ + --tasks hellaswag \ + --batch_size 32 +``` + +2) To enable tensor and/or pipeline parallelism, set the `model_args` of `tensor_model_parallel_size` and/or `pipeline_model_parallel_size`. In addition, you also have to set up `devices` to be equal to the product of `tensor_model_parallel_size` and/or `pipeline_model_parallel_size`. For example, the command to use one node of 4 GPUs with tensor parallelism of 2 and pipeline parallelism of 2 is: +```bash +torchrun --nproc-per-node=4 --no-python lm_eval \ + --model nemo_lm \ + --model_args path=,devices=4,tensor_model_parallel_size=2,pipeline_model_parallel_size=2 \ + --tasks hellaswag \ + --batch_size 32 +``` +Note that it is recommended to substitute the `python` command by `torchrun --nproc-per-node= --no-python` to facilitate loading the model into the GPUs. This is especially important for large checkpoints loaded into multiple GPUs. + +Not supported yet: multi-node evaluation and combinations of data replication with tensor or pipeline parallelism. + +### Tensor + Data Parallel and Optimized Inference with `vLLM` + +We also support vLLM for faster inference on [supported model types](https://docs.vllm.ai/en/latest/models/supported_models.html), especially faster when splitting a model across multiple GPUs. For single-GPU or multi-GPU — tensor parallel, data parallel, or a combination of both — inference, for example: + +```bash +lm_eval --model vllm \ + --model_args pretrained={model_name},tensor_parallel_size={GPUs_per_model},dtype=auto,gpu_memory_utilization=0.8,data_parallel_size={model_replicas} \ + --tasks lambada_openai \ + --batch_size auto +``` +To use vllm, do `pip install lm_eval[vllm]`. For a full list of supported vLLM configurations, please reference our [vLLM integration](https://github.com/EleutherAI/lm-evaluation-harness/blob/e74ec966556253fbe3d8ecba9de675c77c075bce/lm_eval/models/vllm_causallms.py) and the vLLM documentation. + +vLLM occasionally differs in output from Huggingface. We treat Huggingface as the reference implementation, and provide a [script](./scripts/model_comparator.py) for checking the validity of vllm results against HF. + +> [!Tip] +> For fastest performance, we recommend using `--batch_size auto` for vLLM whenever possible, to leverage its continuous batching functionality! + +> [!Tip] +> Passing `max_model_len=4096` or some other reasonable default to vLLM through model args may cause speedups or prevent out-of-memory errors when trying to use auto batch size, such as for Mistral-7B-v0.1 which defaults to a maximum length of 32k. + +### Model APIs and Inference Servers + +Our library also supports the evaluation of models served via several commercial APIs, and we hope to implement support for the most commonly used performant local/self-hosted inference servers. + +To call a hosted model, use: + +```bash +export OPENAI_API_KEY=YOUR_KEY_HERE +lm_eval --model openai-completions \ + --model_args model=davinci \ + --tasks lambada_openai,hellaswag +``` + +We also support using your own local inference server with servers that mirror the OpenAI Completions and ChatCompletions APIs. + +```bash +lm_eval --model local-chat-completions --tasks gsm8k --model_args model=facebook/opt-125m,base_url=http://{yourip}:8000/v1 +``` +Note that for externally hosted models, configs such as `--device` and `--batch_size` should not be used and do not function. Just like you can use `--model_args` to pass arbitrary arguments to the model constructor for local models, you can use it to pass arbitrary arguments to the model API for hosted models. See the documentation of the hosting service for information on what arguments they support. + +| API or Inference Server | Implemented? | `--model ` name | Models supported: | Request Types: | +|---------------------------------------------------------------------------------------------------------------------------|---------------------------------|---------------------------------------------------------------------|-----------------------------------------------------------------------------------------------|------------------------------------------------------------| +| OpenAI Completions | :heavy_check_mark: | `openai-completions`, `local-completions` | All OpenAI Completions API models | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | +| OpenAI ChatCompletions | :heavy_check_mark: | `openai-chat-completions`, `local-chat-completions` | [All ChatCompletions API models](https://platform.openai.com/docs/guides/gpt) | `generate_until` (no logprobs) | +| Anthropic | :heavy_check_mark: | `anthropic` | [Supported Anthropic Engines](https://docs.anthropic.com/claude/reference/selecting-a-model) | `generate_until` (no logprobs) | +| Anthropic Chat | :heavy_check_mark: | `anthropic-chat`, `anthropic-chat-completions` | [Supported Anthropic Engines](https://docs.anthropic.com/claude/docs/models-overview) | `generate_until` (no logprobs) | +| Textsynth | :heavy_check_mark: | `textsynth` | [All supported engines](https://textsynth.com/documentation.html#engines) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | +| Cohere | [:hourglass: - blocked on Cohere API bug](https://github.com/EleutherAI/lm-evaluation-harness/pull/395) | N/A | [All `cohere.generate()` engines](https://docs.cohere.com/docs/models) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | +| [Llama.cpp](https://github.com/ggerganov/llama.cpp) (via [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)) | :heavy_check_mark: | `gguf`, `ggml` | [All models supported by llama.cpp](https://github.com/ggerganov/llama.cpp) | `generate_until`, `loglikelihood`, (perplexity evaluation not yet implemented) | +| vLLM | :heavy_check_mark: | `vllm` | [Most HF Causal Language Models](https://docs.vllm.ai/en/latest/models/supported_models.html) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | +| Mamba | :heavy_check_mark: | `mamba_ssm` | [Mamba architecture Language Models via the `mamba_ssm` package](https://huggingface.co/state-spaces) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | +| Huggingface Optimum (Causal LMs) | ✔️ | `openvino` | Any decoder-only AutoModelForCausalLM converted with Huggingface Optimum into OpenVINO™ Intermediate Representation (IR) format | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | +| Neuron via AWS Inf2 (Causal LMs) | ✔️ | `neuronx` | Any decoder-only AutoModelForCausalLM supported to run on [huggingface-ami image for inferentia2](https://aws.amazon.com/marketplace/pp/prodview-gr3e6yiscria2) | `generate_until`, `loglikelihood`, `loglikelihood_rolling` | ... | +| Your local inference server! | :heavy_check_mark: | `local-completions` or `local-chat-completions` (using `openai-chat-completions` model type) | Any server address that accepts GET requests using HF models and mirror's OpenAI's Completions or ChatCompletions interface | `generate_until` | | ... | + +Models which do not supply logits or logprobs can be used with tasks of type `generate_until` only, while local models, or APIs that supply logprobs/logits of their prompts, can be run on all task types: `generate_until`, `loglikelihood`, `loglikelihood_rolling`, and `multiple_choice`. + +For more information on the different task `output_types` and model request types, see [our documentation](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/model_guide.md#interface). + +> [!Note] +> For best performance with closed chat model APIs such as Anthropic Claude 3 and GPT-4, we recommend carefully looking at a few sample outputs using `--limit 10` first to confirm answer extraction and scoring on generative tasks is performing as expected. providing `system=""` within `--model_args` for anthropic-chat-completions, to instruct the model what format to respond in, may be useful. + + +### Other Frameworks + +A number of other libraries contain scripts for calling the eval harness through their library. These include [GPT-NeoX](https://github.com/EleutherAI/gpt-neox/blob/main/eval_tasks/eval_adapter.py), [Megatron-DeepSpeed](https://github.com/microsoft/Megatron-DeepSpeed/blob/main/examples/MoE/readme_evalharness.md), and [mesh-transformer-jax](https://github.com/kingoflolz/mesh-transformer-jax/blob/master/eval_harness.py). + +To create your own custom integration you can follow instructions from [this tutorial](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/interface.md#external-library-usage). + +### Additional Features +> [!Note] +> For tasks unsuitable for direct evaluation — either due risks associated with executing untrusted code or complexities in the evaluation process — the `--predict_only` flag is available to obtain decoded generations for post-hoc evaluation. + +If you have a Metal compatible Mac, you can run the eval harness using the MPS back-end by replacing `--device cuda:0` with `--device mps` (requires PyTorch version 2.1 or higher). + +> [!Note] +> You can inspect what the LM inputs look like by running the following command: +> ```bash +> python write_out.py \ +> --tasks \ +> --num_fewshot 5 \ +> --num_examples 10 \ +> --output_base_path /path/to/output/folder +> ``` +> This will write out one text file for each task. + +To verify the data integrity of the tasks you're performing in addition to running the tasks themselves, you can use the `--check_integrity` flag: + +```bash +lm_eval --model openai \ + --model_args engine=davinci \ + --tasks lambada_openai,hellaswag \ + --check_integrity +``` + +## Advanced Usage Tips + +For models loaded with the HuggingFace `transformers` library, any arguments provided via `--model_args` get passed to the relevant constructor directly. This means that anything you can do with `AutoModel` can be done with our library. For example, you can pass a local path via `pretrained=` or use models finetuned with [PEFT](https://github.com/huggingface/peft) by taking the call you would run to evaluate the base model and add `,peft=PATH` to the `model_args` argument: +```bash +lm_eval --model hf \ + --model_args pretrained=EleutherAI/gpt-j-6b,parallelize=True,load_in_4bit=True,peft=nomic-ai/gpt4all-j-lora \ + --tasks openbookqa,arc_easy,winogrande,hellaswag,arc_challenge,piqa,boolq \ + --device cuda:0 +``` + +[GPTQ](https://github.com/PanQiWei/AutoGPTQ) quantized models can be loaded by specifying their file names in `,autogptq=NAME` (or `,autogptq=True` for default names) in the `model_args` argument: + +```bash +lm_eval --model hf \ + --model_args pretrained=model-name-or-path,autogptq=model.safetensors,gptq_use_triton=True \ + --tasks hellaswag +``` + +We support wildcards in task names, for example you can run all of the machine-translated lambada tasks via `--task lambada_openai_mt_*`. + +To save evaluation results provide an `--output_path`. We also support logging model responses with the `--log_samples` flag for post-hoc analysis. + +Additionally, one can provide a directory with `--use_cache` to cache the results of prior runs. This allows you to avoid repeated execution of the same (model, task) pairs for re-scoring. + +For a full list of supported arguments, check out the [interface](https://github.com/EleutherAI/lm-evaluation-harness/blob/main/docs/interface.md) guide in our documentation! + +## Visualizing Results + +You can seamlessly visualize and analyze the results of your evaluation harness runs using both Weights & Biases (W&B) and Zeno. + +### Zeno + +You can use [Zeno](https://zenoml.com) to visualize the results of your eval harness runs. + +First, head to [hub.zenoml.com](https://hub.zenoml.com) to create an account and get an API key [on your account page](https://hub.zenoml.com/account). +Add this key as an environment variable: + +```bash +export ZENO_API_KEY=[your api key] +``` + +You'll also need to install the `lm_eval[zeno]` package extra. + +To visualize the results, run the eval harness with the `log_samples` and `output_path` flags. +We expect `output_path` to contain multiple folders that represent individual model names. +You can thus run your evaluation on any number of tasks and models and upload all of the results as projects on Zeno. + +```bash +lm_eval \ + --model hf \ + --model_args pretrained=EleutherAI/gpt-j-6B \ + --tasks hellaswag \ + --device cuda:0 \ + --batch_size 8 \ + --log_samples \ + --output_path output/gpt-j-6B +``` + +Then, you can upload the resulting data using the `zeno_visualize` script: + +```bash +python scripts/zeno_visualize.py \ + --data_path output \ + --project_name "Eleuther Project" +``` + +This will use all subfolders in `data_path` as different models and upload all tasks within these model folders to Zeno. +If you run the eval harness on multiple tasks, the `project_name` will be used as a prefix and one project will be created per task. + +You can find an example of this workflow in [examples/visualize-zeno.ipynb](examples/visualize-zeno.ipynb). + +### Weights and Biases + +With the [Weights and Biases](https://wandb.ai/site) integration, you can now spend more time extracting deeper insights into your evaluation results. The integration is designed to streamline the process of logging and visualizing experiment results using the Weights & Biases (W&B) platform. + +The integration provide functionalities + +- to automatically log the evaluation results, +- log the samples as W&B Tables for easy visualization, +- log the `results.json` file as an artifact for version control, +- log the `_eval_samples.json` file if the samples are logged, +- generate a comprehensive report for analysis and visualization with all the important metric, +- log task and cli specific configs, +- and more out of the box like the command used to run the evaluation, GPU/CPU counts, timestamp, etc. + +First you'll need to install the lm_eval[wandb] package extra. Do `pip install lm_eval[wandb]`. + +Authenticate your machine with an your unique W&B token. Visit https://wandb.ai/authorize to get one. Do `wandb login` in your command line terminal. + +Run eval harness as usual with a `wandb_args` flag. Use this flag to provide arguments for initializing a wandb run ([wandb.init](https://docs.wandb.ai/ref/python/init)) as comma separated string arguments. + +```bash +lm_eval \ + --model hf \ + --model_args pretrained=microsoft/phi-2,trust_remote_code=True \ + --tasks hellaswag,mmlu_abstract_algebra \ + --device cuda:0 \ + --batch_size 8 \ + --output_path output/phi-2 \ + --limit 10 \ + --wandb_args project=lm-eval-harness-integration \ + --log_samples +``` + +In the stdout, you will find the link to the W&B run page as well as link to the generated report. You can find an example of this workflow in [examples/visualize-wandb.ipynb](examples/visualize-wandb.ipynb), and an example of how to integrate it beyond the CLI. + +## How to Contribute or Learn More? + +For more information on the library and how everything fits together, check out all of our [documentation pages](https://github.com/EleutherAI/lm-evaluation-harness/tree/main/docs)! We plan to post a larger roadmap of desired + planned library improvements soon, with more information on how contributors can help. + +### Implementing new tasks + +To implement a new task in the eval harness, see [this guide](./docs/new_task_guide.md). + +In general, we follow this priority list for addressing concerns about prompting and other eval details: +1. If there is widespread agreement among people who train LLMs, use the agreed upon procedure. +2. If there is a clear and unambiguous official implementation, use that procedure. +3. If there is widespread agreement among people who evaluate LLMs, use the agreed upon procedure. +4. If there are multiple common implementations but not universal or widespread agreement, use our preferred option among the common implementations. As before, prioritize choosing from among the implementations found in LLM training papers. + +These are guidelines and not rules, and can be overruled in special circumstances. + +We try to prioritize agreement with the procedures used by other groups to decrease the harm when people inevitably compare runs across different papers despite our discouragement of the practice. Historically, we also prioritized the implementation from [Language Models are Few Shot Learners](https://arxiv.org/abs/2005.14165) as our original goal was specifically to compare results with that paper. + +### Support + +The best way to get support is to open an issue on this repo or join the [EleutherAI Discord server](https://discord.gg/eleutherai). The `#lm-thunderdome` channel is dedicated to developing this project and the `#release-discussion` channel is for receiving support for our releases. If you've used the library and have had a positive (or negative) experience, we'd love to hear from you! + +## Optional Extras +Extras dependencies can be installed via `pip install -e ".[NAME]"` + +| Name | Use | +|---------------|---------------------------------------| +| anthropic | For using Anthropic's models | +| dev | For linting PRs and contributions | +| gptq | For loading models with GPTQ | +| hf_transfer | For speeding up HF Hub file downloads | +| ifeval | For running the IFEval task | +| neuronx | For running on AWS inf2 instances | +| mamba | For loading Mamba SSM models | +| math | For running math task answer checking | +| multilingual | For multilingual tokenizers | +| openai | For using OpenAI's models | +| optimum | For running Intel OpenVINO models | +| promptsource | For using PromptSource prompts | +| sentencepiece | For using the sentencepiece tokenizer | +| testing | For running library test suite | +| vllm | For loading models with vLLM | +| zeno | For visualizing results with Zeno | +|---------------|---------------------------------------| +| all | Loads all extras (not recommended) | + +## Cite as + +``` +@misc{eval-harness, + author = {Gao, Leo and Tow, Jonathan and Abbasi, Baber and Biderman, Stella and Black, Sid and DiPofi, Anthony and Foster, Charles and Golding, Laurence and Hsu, Jeffrey and Le Noac'h, Alain and Li, Haonan and McDonell, Kyle and Muennighoff, Niklas and Ociepa, Chris and Phang, Jason and Reynolds, Laria and Schoelkopf, Hailey and Skowron, Aviya and Sutawika, Lintang and Tang, Eric and Thite, Anish and Wang, Ben and Wang, Kevin and Zou, Andy}, + title = {A framework for few-shot language model evaluation}, + month = 12, + year = 2023, + publisher = {Zenodo}, + version = {v0.4.0}, + doi = {10.5281/zenodo.10256836}, + url = {https://zenodo.org/records/10256836} +} +``` diff --git a/env-llmeval/lib/python3.10/site-packages/lm_eval-0.4.2.dist-info/RECORD 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