diff --git a/.github/workflows/build_and_test.yml b/.github/workflows/build_and_test.yml index 23379878a..d92136cd0 100644 --- a/.github/workflows/build_and_test.yml +++ b/.github/workflows/build_and_test.yml @@ -17,7 +17,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [ "3.9","3.10", "3.11" ] + python-version: ["3.12", "3.13"] steps: - name: Free up disk space at start @@ -25,7 +25,6 @@ jobs: sudo apt clean sudo rm -rf /usr/share/dotnet /usr/local/lib/android /opt/ghc sudo rm -rf "/usr/local/share/boost" - sudo rm -rf "$AGENT_TOOLSDIRECTORY" df -h - uses: actions/checkout@v3 @@ -53,7 +52,7 @@ jobs: if: steps.cached-poetry-dependencies.outputs.cache-hit != 'true' run: | poetry cache clear pypi --all -n > /dev/null - poetry install --with dev --all-extras --no-cache --quiet --no-interaction + poetry install --with dev --all-extras --no-cache --no-interaction source ./.venv/bin/activate && pip uninstall -y pyspark && rm -rf ./.venv/lib/python${{ matrix.python-version }}/site-packages/pyspark*/ pip install pyspark==3.5.6 diff --git a/.github/workflows/llm_tests_build.yml b/.github/workflows/llm_tests_build.yml index bf29c7fd8..09b5f8f0c 100644 --- a/.github/workflows/llm_tests_build.yml +++ b/.github/workflows/llm_tests_build.yml @@ -10,7 +10,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [ "3.8", "3.9", "3.10" ] + python-version: [ "3.12", "3.13" ] steps: - uses: actions/checkout@v3 diff --git a/.github/workflows/release.yaml b/.github/workflows/release.yaml index 0f050f3d1..559666e98 100644 --- a/.github/workflows/release.yaml +++ b/.github/workflows/release.yaml @@ -9,7 +9,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [3.9] + python-version: [3.12] poetry-version: [2.1.3] os: [ubuntu-latest] runs-on: ${{ matrix.os }} diff --git a/langtest/datahandler/datasource.py b/langtest/datahandler/datasource.py index 59ec3320b..94f3c7604 100644 --- a/langtest/datahandler/datasource.py +++ b/langtest/datahandler/datasource.py @@ -808,7 +808,7 @@ def load_raw_data(self, standardize_columns: bool = False) -> List[Dict]: parsed CSV file into list of dicts """ - if type(self._file_path) == dict: + if isinstance(self._file_path, dict): df = pd.read_csv(self._file_path["data_source"]) if self.task == "text-classification": diff --git a/langtest/langtest.py b/langtest/langtest.py index 910fc8c19..a21961fcb 100644 --- a/langtest/langtest.py +++ b/langtest/langtest.py @@ -286,7 +286,7 @@ def configure(self, config: Union[HarnessConfig, dict, str]) -> HarnessConfig: Returns: dict: Loaded configuration. """ - if type(config) == dict: + if isinstance(config, dict): self._config = config else: with open(config, "r", encoding="utf-8") as yml: diff --git a/langtest/metrics/llm_eval.py b/langtest/metrics/llm_eval.py index b8a16878e..ab510115b 100644 --- a/langtest/metrics/llm_eval.py +++ b/langtest/metrics/llm_eval.py @@ -66,25 +66,22 @@ def build_prompt( f"""\n\nScore the student answer based on the following criteria:\n{eval_criteria}""" ) - prompt += dedent( - f""" - Example Format: - QUESTION: question here - STUDENT ANSWER: student's answer here - TRUE ANSWER: true answer here - GRADE: {grade_list} here - - { - ("Grade the student answers based ONLY on their factual accuracy. Ignore differences" - " in punctuation and phrasing between the student answer and true answer. It is OK " - "if the student answer contains more or relevant information than the true answer, as" - " long as it does not contain any conflicting statements. Begin!") - } - - QUESTION: {{query}} - STUDENT ANSWER: {{result}} - TRUE ANSWER: {{answer}} - GRADE:""" + prompt += ( + "Example Format:\n" + "QUESTION: question here\n" + "STUDENT ANSWER: student's answer here\n" + "TRUE ANSWER: true answer here\n" + f"GRADE: {grade_list} here" + "\n\n" + "Grade the student answers based ONLY on their factual accuracy. Ignore differences" + " in punctuation and phrasing between the student answer and true answer. It is OK " + "if the student answer contains more or relevant information than the true answer, as" + " long as it does not contain any conflicting statements. Begin!" + "\n\n" + "QUESTION: {{query}}\n" + "STUDENT ANSWER: {{result}}\n" + "TRUE ANSWER: {{answer}}\n" + "GRADE:\n" ) return prompt diff --git a/langtest/modelhandler/__init__.py b/langtest/modelhandler/__init__.py index fb579ca58..c0d9da261 100644 --- a/langtest/modelhandler/__init__.py +++ b/langtest/modelhandler/__init__.py @@ -33,7 +33,7 @@ if "langchain" in INSTALLED_HUBS: - import langchain + from langtest.modelhandler.utils import MODEL_CLASSES LANGCHAIN_HUBS = { ( @@ -41,7 +41,7 @@ if hub.lower() in RENAME_HUBS else hub.lower() ): hub - for hub in langchain.llms.__all__ + for hub in list(MODEL_CLASSES.keys()) } LANGCHAIN_HUBS["openrouter"] = "openrouter" diff --git a/langtest/modelhandler/llm_modelhandler.py b/langtest/modelhandler/llm_modelhandler.py index c469727ec..f73f7fb44 100644 --- a/langtest/modelhandler/llm_modelhandler.py +++ b/langtest/modelhandler/llm_modelhandler.py @@ -3,9 +3,9 @@ import os from typing import Any, List, Type, Union, TypeVar -import langchain.llms as lc +import langchain_classic.llms as lc import langchain.chat_models as chat_models -from langchain.chains.llm import LLMChain +from langchain_classic.chains.llm import LLMChain from langchain_core.prompts import PromptTemplate from langchain_core.language_models.base import BaseLanguageModel from langchain_core.exceptions import OutputParserException diff --git a/langtest/modelhandler/modelhandler.py b/langtest/modelhandler/modelhandler.py index f597a7c09..13c98b40a 100644 --- a/langtest/modelhandler/modelhandler.py +++ b/langtest/modelhandler/modelhandler.py @@ -14,8 +14,8 @@ } if try_import_lib("langchain"): - import langchain - import langchain.llms + + from langtest.modelhandler.utils import MODEL_CLASSES LANGCHAIN_HUBS = { ( @@ -23,7 +23,7 @@ if hub.lower() in RENAME_HUBS else hub.lower() ): hub - for hub in langchain.llms.__all__ + for hub in list(MODEL_CLASSES.keys()) } LANGCHAIN_HUBS["openrouter"] = "openrouter" else: diff --git a/langtest/modelhandler/transformers_modelhandler.py b/langtest/modelhandler/transformers_modelhandler.py index c8020ad4c..57779cdd5 100644 --- a/langtest/modelhandler/transformers_modelhandler.py +++ b/langtest/modelhandler/transformers_modelhandler.py @@ -441,7 +441,7 @@ def load_model(cls, path: str, *args, **kwargs) -> "Pipeline": tgt_lang = config.get("target_language") or kwargs.get("target_language") if "t5" in path: - return cls(pipeline(f"translation_en_to_{tgt_lang}", model=path)) + return cls(pipeline("text-generation", model=path)) else: return cls(pipeline(model=path, src_lang="en", tgt_lang=tgt_lang)) @@ -746,7 +746,6 @@ def load_model(cls, path: str, **kwargs): task = filtered_kwargs.pop("task", None) tasks = [ "text-generation", - "text2text-generation", "summarization", ] # Add more tasks if needed diff --git a/langtest/modelhandler/utils.py b/langtest/modelhandler/utils.py index f6656e5f9..2f649d193 100644 --- a/langtest/modelhandler/utils.py +++ b/langtest/modelhandler/utils.py @@ -75,7 +75,6 @@ class Info(TypedDict): "gigachat": "GigaChat", "google_palm": "ChatGooglePalm", "gpt_router": "GPTRouter", - "huggingface": "ChatHuggingFace", "human": "HumanInputChatModel", "hunyuan": "ChatHunyuan", "javelin_ai_gateway": "ChatJavelinAIGateway", diff --git a/langtest/prompts.py b/langtest/prompts.py index dd0b84cd0..e15041c18 100644 --- a/langtest/prompts.py +++ b/langtest/prompts.py @@ -1,11 +1,11 @@ from collections import defaultdict -from typing import Dict, List, Union +from typing import Any, Dict, List, Optional, Union, ClassVar -from pydantic.v1 import BaseModel, validator, Extra, ConfigDict +from pydantic import BaseModel, ConfigDict, model_validator class MessageType(BaseModel): - __field_order: List[str] = [ + __field_order: ClassVar[List[str]] = [ "content", "context", "question", @@ -15,14 +15,15 @@ class MessageType(BaseModel): "answer", ] - model_config = ConfigDict(extra=Extra.allow) + model_config = ConfigDict(extra="allow") - @validator("*", pre=True, allow_reuse=True) - def add_field(cls, v, values, field, **kwargs): - if "fields" not in values: - values["fields"] = [] - values["fields"].append(field) - return v + @model_validator(mode="before") + def add_field(cls, data: Any): + if isinstance(data, dict): + data = dict(data) + data.setdefault("fields", []) + data["fields"] = [k for k in data.keys() if k != "fields"] + return data @property def get_template(self): @@ -70,14 +71,16 @@ class Conversion(BaseModel): user: MessageType ai: MessageType - model_config = ConfigDict(extra=Extra.allow) + model_config = ConfigDict(extra="allow") - @validator("*", pre=True, allow_reuse=True) - def add_field(cls, v, values, field, **kwargs): - if "fields" not in values: - values["fields"] = [] - values["fields"].append(field) - return v + @model_validator(mode="before") + @classmethod + def add_field(cls, data: Any): + if isinstance(data, dict): + data = dict(data) + data.setdefault("fields", []) + data["fields"] = [k for k in data.keys() if k != "fields"] + return data @property def get_examples(self): @@ -93,7 +96,7 @@ def get_suffix_user(self): class PromptConfig(BaseModel): instructions: str prompt_type: str - examples: Union[Conversion, List[Conversion]] = None + examples: Optional[Union[Conversion, List[Conversion]]] = None @property def get_examples(self) -> List[dict]: @@ -126,7 +129,7 @@ def get_input_variables(self): def prompt_style(self): """Generate a prompt based on the prompt type.""" if self.prompt_type in ["chat", "instruct"]: - from langchain.prompts import ( + from langchain_core.prompts import ( ChatPromptTemplate, FewShotChatMessagePromptTemplate, ) @@ -149,7 +152,7 @@ def prompt_style(self): return final_prompt elif self.prompt_type == "completion": - from langchain.prompts import FewShotPromptTemplate, PromptTemplate + from langchain_core.prompts import FewShotPromptTemplate, PromptTemplate template = "".join(v for _, v in self.get_template) template = f"{template.replace('Answer:', '')}" @@ -208,9 +211,9 @@ def lm_studio_prompt(self): class PromptManager: - _instance = None + _instance: "PromptManager" = None prompt_configs: Dict[str, PromptConfig] = defaultdict(PromptConfig) - _default_state = None + _default_state: str = None def __new__(cls, *args, **kwargs): if cls._instance is None: diff --git a/langtest/transform/accuracy.py b/langtest/transform/accuracy.py index 0893c4b64..ed913f4a8 100644 --- a/langtest/transform/accuracy.py +++ b/langtest/transform/accuracy.py @@ -276,7 +276,8 @@ class BaseAccuracy(ABC): TestConfig = TypedDict( "TestConfig", - min_score=Union[Dict[str, float], float], + # min_score=Union[Dict[str, float], float], + {"min_score": Union[Dict[str, float], float]}, ) @classmethod @@ -1029,9 +1030,15 @@ class LLMEval(BaseAccuracy): TestConfig = TypedDict( "TestConfig", - model=str, - hub=str, - min_score=float, + # model=str, + # hub=str, + # min_score=float, + { + "model": str, + "hub": str, + "model_parameters": dict, + "min_score": float, + }, ) @classmethod diff --git a/langtest/transform/base.py b/langtest/transform/base.py index b4109a307..88e98d2a6 100644 --- a/langtest/transform/base.py +++ b/langtest/transform/base.py @@ -201,7 +201,7 @@ async def async_run( category_output = all_categories[each].run( values, model_handler, progress_bar=tests, **kwargs ) - if type(category_output) == list: + if isinstance(category_output, list): all_results.extend(category_output) else: all_results.append(category_output) @@ -264,7 +264,7 @@ def run( if len(test_name.split("-")) > 1: test_name = "multiple_perturbations" test_output = supported_tests[test_name].async_run(samples, model, **kwargs) - if type(test_output) == list: + if isinstance(test_output, list): tasks.extend(test_output) else: tasks.append(test_output) diff --git a/langtest/transform/bias.py b/langtest/transform/bias.py index 0406a3691..c7b62e48b 100644 --- a/langtest/transform/bias.py +++ b/langtest/transform/bias.py @@ -267,7 +267,7 @@ class BaseBias(ABC): ] # Config Hint for the bias tests - TestConfig = TypedDict("TestConfig", min_pass_rate=float) + TestConfig = TypedDict("TestConfig", {"min_pass_rate": float}) @abstractmethod def transform(self, sample_list: List[Sample], *args, **kwargs) -> List[Sample]: diff --git a/langtest/transform/clinical.py b/langtest/transform/clinical.py index bd2929f43..d18fbad54 100644 --- a/langtest/transform/clinical.py +++ b/langtest/transform/clinical.py @@ -119,7 +119,8 @@ class BaseClinical(ABC): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + {"min_pass_rate": float}, ) @staticmethod diff --git a/langtest/transform/disinformation.py b/langtest/transform/disinformation.py index cd59d4fff..509f8cc2e 100644 --- a/langtest/transform/disinformation.py +++ b/langtest/transform/disinformation.py @@ -17,7 +17,8 @@ class DisinformationTestFactory(ITests): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + {"min_pass_rate": float}, ) def __init__(self, data_handler: List[Sample], tests: Dict = None, **kwargs) -> None: diff --git a/langtest/transform/factuality.py b/langtest/transform/factuality.py index 9d60c7a3f..066924d6e 100644 --- a/langtest/transform/factuality.py +++ b/langtest/transform/factuality.py @@ -14,7 +14,8 @@ class FactualityTestFactory(ITests): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + {"min_pass_rate": float}, ) def __init__(self, data_handler: List[Sample], tests: Dict = None, **kwargs) -> None: diff --git a/langtest/transform/fairness.py b/langtest/transform/fairness.py index cfc93b963..bd5240b4f 100644 --- a/langtest/transform/fairness.py +++ b/langtest/transform/fairness.py @@ -21,6 +21,12 @@ from langtest.transform.base import ITests +class GenderedConfig(TypedDict): + male: float + female: float + unknown: float + + class FairnessTestFactory(ITests): """ A class for performing fairness tests on a given dataset. @@ -292,8 +298,12 @@ class BaseFairness(ABC): TestConfig = TypedDict( "TestConfig", - min_score=Union[float, Dict[str, float]], - max_score=Union[float, Dict[str, float]], + # min_score=Union[float, Dict[str, float]], + # max_score=Union[float, Dict[str, float]], + { + "min_score": Union[float, Dict[str, float]], + "max_score": Union[float, Dict[str, float]], + }, ) @staticmethod @@ -361,16 +371,12 @@ class MinGenderF1Score(BaseFairness): alias_name = ["min_gender_f1_score"] - min_score = TypedDict( - "min_score", - male=float, - female=float, - unknown=float, - ) - TestConfig = TypedDict( "TestConfig", - min_score=Union[min_score, float], + # min_score=Union[min_score, float], + { + "min_score": Union[GenderedConfig, float], + }, ) @classmethod @@ -476,16 +482,12 @@ class MaxGenderF1Score(BaseFairness): alias_name = ["max_gender_f1_score"] - max_score = TypedDict( - "max_score", - male=float, - female=float, - unknown=float, - ) - TestConfig = TypedDict( "TestConfig", - max_score=Union[max_score, float], + # max_score=Union[max_score, float], + { + "max_score": Union[GenderedConfig, float], + }, ) @classmethod @@ -599,16 +601,12 @@ class MinGenderRougeScore(BaseFairness): ] supported_tasks = ["question-answering", "summarization"] - min_score = TypedDict( - "min_score", - male=float, - female=float, - unknown=float, - ) - TestConfig = TypedDict( "TestConfig", - min_score=Union[min_score, float], + # min_score=Union[min_score, float], + { + "min_score": Union[GenderedConfig, float], + }, ) @classmethod @@ -720,16 +718,12 @@ class MaxGenderRougeScore(BaseFairness): ] supported_tasks = ["question-answering", "summarization"] - max_score = TypedDict( - "max_score", - male=float, - female=float, - unknown=float, - ) - TestConfig = TypedDict( "TestConfig", - max_score=Union[max_score, float], + # max_score=Union[max_score, float], + { + "max_score": Union[GenderedConfig, float], + }, ) @classmethod @@ -835,16 +829,9 @@ class MinGenderLLMEval(BaseFairness): supported_tasks = ["question-answering"] eval_model = None - min_score = TypedDict( - "min_score", - male=float, - female=float, - unknown=float, - ) - TestConfig = TypedDict( "TestConfig", - min_score=Union[min_score, float], + {"min_score": Union[GenderedConfig, float]}, ) @classmethod @@ -983,16 +970,9 @@ class MaxGenderLLMEval(BaseFairness): supported_tasks = ["question-answering"] eval_model = None - max_score = TypedDict( - "max_score", - male=float, - female=float, - unknown=float, - ) - TestConfig = TypedDict( "TestConfig", - max_score=Union[max_score, float], + {"max_score": Union[GenderedConfig, float]}, ) @classmethod diff --git a/langtest/transform/grammar.py b/langtest/transform/grammar.py index d4902e9c0..6be3b9d9b 100644 --- a/langtest/transform/grammar.py +++ b/langtest/transform/grammar.py @@ -130,7 +130,10 @@ class BaseGrammar(ABC): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + { + "min_pass_rate": float, + }, ) @staticmethod @@ -177,7 +180,7 @@ def transform( from transformers import pipeline pipe = pipeline( - "text2text-generation", model="humarin/chatgpt_paraphraser_on_T5_base" + "text-generation", model="humarin/chatgpt_paraphraser_on_T5_base" ) for idx, sample in enumerate(sample_list): if isinstance(sample, str): diff --git a/langtest/transform/legal.py b/langtest/transform/legal.py index ce717f6d1..15656a62a 100644 --- a/langtest/transform/legal.py +++ b/langtest/transform/legal.py @@ -14,7 +14,10 @@ class LegalTestFactory(ITests): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + { + "min_pass_rate": float, + }, ) def __init__(self, data_handler: List[Sample], tests: Dict = None, **kwargs) -> None: diff --git a/langtest/transform/performance.py b/langtest/transform/performance.py index 6f0906bc7..47ab4e009 100644 --- a/langtest/transform/performance.py +++ b/langtest/transform/performance.py @@ -99,7 +99,10 @@ class BasePerformance(ABC): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + { + "min_pass_rate": float, + }, ) @staticmethod diff --git a/langtest/transform/representation.py b/langtest/transform/representation.py index d05f9cf3a..7da40f24b 100644 --- a/langtest/transform/representation.py +++ b/langtest/transform/representation.py @@ -110,8 +110,12 @@ class BaseRepresentation(ABC): # Config Hint for the representation tests TestConfig = TypedDict( "TestConfig", - min_count=Union[int, Dict[str, int]], - min_proportion=Union[float, Dict[str, float]], + # min_count=Union[int, Dict[str, int]], + # min_proportion=Union[float, Dict[str, float]], + { + "min_count": Union[int, Dict[str, int]], + "min_proportion": Union[float, Dict[str, float]], + }, ) @classmethod @@ -180,14 +184,20 @@ class GenderRepresentation(BaseRepresentation): "min_gender_representation_proportion", ] - min_count = TypedDict("min_count", male=int, female=int, unknown=int) - min_proportion = TypedDict("min_proportion", male=float, female=float, unknown=float) + min_count = TypedDict("min_count", {"male": int, "female": int, "unknown": int}) + min_proportion = TypedDict( + "min_proportion", {"male": float, "female": float, "unknown": float} + ) # Config Hint for the representation tests TestConfig = TypedDict( "TestConfig", - min_count=Union[min_count, int], - min_proportion=Union[min_proportion, float], + # min_count=Union[min_count, int], + # min_proportion=Union[min_proportion, float], + { + "min_count": Union[min_count, int], + "min_proportion": Union[min_proportion, float], + }, ) @classmethod @@ -356,28 +366,48 @@ class EthnicityRepresentation(BaseRepresentation): min_count = TypedDict( "min_count", - black=int, - asian=int, - white=int, - native_american=int, - hispanic=int, - inter_racial=int, + # black=int, + # asian=int, + # white=int, + # native_american=int, + # hispanic=int, + # inter_racial=int, + { + "black": int, + "asian": int, + "white": int, + "native_american": int, + "hispanic": int, + "inter_racial": int, + }, ) min_proportion = TypedDict( "min_proportion", - black=float, - asian=float, - white=float, - native_american=float, - hispanic=float, - inter_racial=float, + # black=float, + # asian=float, + # white=float, + # native_american=float, + # hispanic=float, + # inter_racial=float, + { + "black": float, + "asian": float, + "white": float, + "native_american": float, + "hispanic": float, + "inter_racial": float, + }, ) TestConfig = TypedDict( "TestConfig", - min_count=Union[min_count, int], - min_proportion=Union[min_proportion, float], + # min_count=Union[min_count, int], + # min_proportion=Union[min_proportion, float], + { + "min_count": Union[min_count, int], + "min_proportion": Union[min_proportion, float], + }, ) @classmethod @@ -717,30 +747,52 @@ class ReligionRepresentation(BaseRepresentation): min_count = TypedDict( "min_count", - muslim=int, - hindu=int, - sikh=int, - christian=int, - jain=int, - buddhist=int, - parsi=int, + # muslim=int, + # hindu=int, + # sikh=int, + # christian=int, + # jain=int, + # buddhist=int, + # parsi=int, + { + "muslim": int, + "hindu": int, + "sikh": int, + "christian": int, + "jain": int, + "buddhist": int, + "parsi": int, + }, ) min_proportion = TypedDict( "min_proportion", - muslim=float, - hindu=float, - sikh=float, - christian=float, - jain=float, - buddhist=float, - parsi=float, + # muslim=float, + # hindu=float, + # sikh=float, + # christian=float, + # jain=float, + # buddhist=float, + # parsi=float, + { + "muslim": float, + "hindu": float, + "sikh": float, + "christian": float, + "jain": float, + "buddhist": float, + "parsi": float, + }, ) TestConfig = TypedDict( "TestConfig", - min_count=Union[min_count, int], - min_proportion=Union[min_proportion, float], + # min_count=Union[min_count, int], + # min_proportion=Union[min_proportion, float], + { + "min_count": Union[min_count, int], + "min_proportion": Union[min_proportion, float], + }, ) @classmethod @@ -953,24 +1005,40 @@ class CountryEconomicRepresentation(BaseRepresentation): min_count = TypedDict( "min_count", - high_income=int, - low_income=int, - lower_middle_income=int, - upper_middle_income=int, + # high_income=int, + # low_income=int, + # lower_middle_income=int, + # upper_middle_income=int, + { + "high_income": int, + "low_income": int, + "lower_middle_income": int, + "upper_middle_income": int, + }, ) min_proportion = TypedDict( "min_proportion", - high_income=float, - low_income=float, - lower_middle_income=float, - upper_middle_income=float, + # high_income=float, + # low_income=float, + # lower_middle_income=float, + # upper_middle_income=float, + { + "high_income": float, + "low_income": float, + "lower_middle_income": float, + "upper_middle_income": float, + }, ) TestConfig = TypedDict( "TestConfig", - min_count=Union[min_count, int], - min_proportion=Union[min_proportion, float], + # min_count=Union[min_count, int], + # min_proportion=Union[min_proportion, float], + { + "min_count": Union[min_count, int], + "min_proportion": Union[min_proportion, float], + }, ) @classmethod diff --git a/langtest/transform/robustness.py b/langtest/transform/robustness.py index 758293707..62c0b69b9 100644 --- a/langtest/transform/robustness.py +++ b/langtest/transform/robustness.py @@ -305,7 +305,14 @@ class BaseRobustness(ABC): "translation", ] - TestConfig = TypedDict("TestConfig", min_pass_rate=float, prob=float) + TestConfig = TypedDict( + "TestConfig", + # min_pass_rate=float, prob=float + { + "min_pass_rate": float, + "prob": float, + }, + ) @staticmethod @abstractmethod @@ -515,9 +522,16 @@ class AddPunctuation(BaseRobustness): """A class for adding punctuation to text samples.""" alias_name = "add_punctuation" - parameters = TypedDict("parameters", whitelist=List[str]) + parameters = TypedDict("parameters", {"whitelist": List[str]}) TestConfig = TypedDict( - "TestConfig", min_pass_rate=float, prob=float, parameters=parameters, count=int + "TestConfig", + # min_pass_rate=float, prob=float, parameters=parameters, count=int + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + "count": int, + }, ) @staticmethod @@ -589,12 +603,17 @@ class StripPunctuation(BaseRobustness): """A class for stripping punctuation to text samples.""" alias_name = "strip_punctuation" - parameters = TypedDict("parameters", whitelist=List[str]) + parameters = TypedDict("parameters", {"whitelist": List[str]}) TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, - prob=float, - parameters=parameters, + # min_pass_rate=float, + # prob=float, + # parameters=parameters, + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + }, ) @staticmethod @@ -659,7 +678,15 @@ class AddTypo(BaseRobustness): alias_name = "add_typo" # TestConfig - TestConfig = TypedDict("TestConfig", min_pass_rate=float, prob=float, count=int) + TestConfig = TypedDict( + "TestConfig", + # min_pass_rate=float, prob=float, count=int + { + "min_pass_rate": float, + "prob": float, + "count": int, + }, + ) @staticmethod def transform( @@ -735,11 +762,17 @@ class SwapEntities(BaseRobustness): supported_tasks = ["ner"] # parameters - parameters = TypedDict("parameters", labels=List[List[str]], count=int) + parameters = TypedDict("parameters", {"labels": List[List[str]], "count": int}) # TestConfig TestConfig = TypedDict( - "TestConfig", min_pass_rate=float, prob=float, parameters=parameters + "TestConfig", + # min_pass_rate=float, prob=float, parameters=parameters + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + }, ) @staticmethod @@ -923,15 +956,27 @@ class AddContext(BaseRobustness): # additional parameters parameters = TypedDict( "parameters", - starting_context=List[str], - ending_context=List[str], - strategy=str, - count=int, + # starting_context=List[str], + # ending_context=List[str], + # strategy=str, + # count=int, + { + "starting_context": List[str], + "ending_context": List[str], + "strategy": str, + "count": int, + }, ) # TestConfig TestConfig = TypedDict( - "TestConfig", min_pass_rate=float, prob=float, parameters=parameters + "TestConfig", + # min_pass_rate=float, prob=float, parameters=parameters + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + }, ) @staticmethod @@ -1378,11 +1423,17 @@ class AddSpeechToTextTypo(BaseRobustness): alias_name = "add_speech_to_text_typo" # additional parameters - parameters = TypedDict("parameters", count=int) + parameters = TypedDict("parameters", {"count": int}) # TestConfig TestConfig = TypedDict( - "TestConfig", min_pass_rate=float, prob=float, parameters=parameters + "TestConfig", + # min_pass_rate=float, prob=float, parameters=parameters + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + }, ) @staticmethod @@ -1802,11 +1853,17 @@ class StripAllPunctuation(BaseRobustness): alias_name = "strip_all_punctuation" # additional parameters - parameters = TypedDict("parameters", whitelist=List[str]) + parameters = TypedDict("parameters", {"whitelist": List[str]}) # TestConfig TestConfig = TypedDict( - "TestConfig", min_pass_rate=float, prob=float, parameters=parameters + "TestConfig", + # min_pass_rate=float, prob=float, parameters=parameters + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + }, ) @staticmethod @@ -1935,11 +1992,17 @@ class RandomAge(BaseRobustness): alias_name = "randomize_age" # additional parameters - parameters = TypedDict("parameters", random_amount=int, count=int) + parameters = TypedDict("parameters", {"random_amount": int, "count": int}) # TestConfig TestConfig = TypedDict( - "TestConfig", min_pass_rate=float, prob=float, parameters=parameters + "TestConfig", + # min_pass_rate=float, prob=float, parameters=parameters + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + }, ) @staticmethod @@ -2027,11 +2090,17 @@ class AddNewLines(BaseRobustness): supported_tasks = ["text-classification", "question-answering", "summarization"] # additional parameters - parameters = TypedDict("parameters", max_lines=int, count=int) + parameters = TypedDict("parameters", {"max_lines": int, "count": int}) # TestConfig TestConfig = TypedDict( - "TestConfig", min_pass_rate=float, prob=float, parameters=parameters + "TestConfig", + # min_pass_rate=float, prob=float, parameters=parameters + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + }, ) @staticmethod @@ -2139,11 +2208,17 @@ class AddTabs(BaseRobustness): supported_tasks = ["text-classification", "question-answering", "summarization"] # additional parameters - parameters = TypedDict("parameters", count=int, max_tabs=int) + parameters = TypedDict("parameters", {"count": int, "max_tabs": int}) # TestConfig TestConfig = TypedDict( - "TestConfig", min_pass_rate=float, prob=float, parameters=parameters + "TestConfig", + # min_pass_rate=float, prob=float, parameters=parameters + { + "min_pass_rate": float, + "prob": float, + "parameters": parameters, + }, ) @staticmethod diff --git a/langtest/transform/safety.py b/langtest/transform/safety.py index 0f16ef209..9429e08b1 100644 --- a/langtest/transform/safety.py +++ b/langtest/transform/safety.py @@ -69,7 +69,10 @@ class BaseSafetyTest(ABC): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + { + "min_pass_rate": float, + }, ) def __init__(self, data_handler: List[Sample], **kwargs) -> None: diff --git a/langtest/transform/security.py b/langtest/transform/security.py index a07431ce4..7ce613e42 100644 --- a/langtest/transform/security.py +++ b/langtest/transform/security.py @@ -66,7 +66,10 @@ class BaseSecurity(ABC): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + { + "min_pass_rate": float, + }, ) @staticmethod diff --git a/langtest/transform/sensitivity.py b/langtest/transform/sensitivity.py index 847db683c..d24a81c15 100644 --- a/langtest/transform/sensitivity.py +++ b/langtest/transform/sensitivity.py @@ -141,7 +141,10 @@ class BaseSensitivity(ABC): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + { + "min_pass_rate": float, + }, ) @staticmethod diff --git a/langtest/transform/stereoset.py b/langtest/transform/stereoset.py index 74d8dc8f2..51d0f68e4 100644 --- a/langtest/transform/stereoset.py +++ b/langtest/transform/stereoset.py @@ -17,8 +17,12 @@ class StereoSetTestFactory(ITests): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, - diff_threshold=float, + # min_pass_rate=float, + # diff_threshold=float, + { + "min_pass_rate": float, + "diff_threshold": float, + }, ) def __init__(self, data_handler: List[Sample], tests: Dict = None, **kwargs) -> None: diff --git a/langtest/transform/stereotype.py b/langtest/transform/stereotype.py index cbb70b93d..f7d71e090 100644 --- a/langtest/transform/stereotype.py +++ b/langtest/transform/stereotype.py @@ -19,9 +19,14 @@ class StereoTypeTestFactory(ITests): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, - diff_threshold=float, - filter_threshold=float, + # min_pass_rate=float, + # diff_threshold=float, + # filter_threshold=float, + { + "min_pass_rate": float, + "diff_threshold": float, + "filter_threshold": float, + }, ) def __init__(self, data_handler: List[Sample], tests: Dict = None, **kwargs) -> None: diff --git a/langtest/transform/sycophancy.py b/langtest/transform/sycophancy.py index 3c4e85bc1..06b1ff6f5 100644 --- a/langtest/transform/sycophancy.py +++ b/langtest/transform/sycophancy.py @@ -127,7 +127,10 @@ class BaseSycophancy(ABC): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + { + "min_pass_rate": float, + }, ) @staticmethod diff --git a/langtest/transform/toxicity.py b/langtest/transform/toxicity.py index fdf9bc4f2..36d65c95b 100644 --- a/langtest/transform/toxicity.py +++ b/langtest/transform/toxicity.py @@ -86,7 +86,10 @@ class BaseToxicity(ABC): # TestConfig TestConfig = TypedDict( "TestConfig", - min_pass_rate=float, + # min_pass_rate=float, + { + "min_pass_rate": float, + }, ) @staticmethod diff --git a/langtest/utils/hf_utils.py b/langtest/utils/hf_utils.py index b7e051ffc..1217a6810 100644 --- a/langtest/utils/hf_utils.py +++ b/langtest/utils/hf_utils.py @@ -201,12 +201,17 @@ def _initialize_pipeline( AutoModelForCausalLM, AutoModelForSeq2SeqLM, AutoTokenizer, + AutoConfig, ) from transformers import pipeline as hf_pipeline except ImportError: raise ValueError(Errors.E085()) tokenizer = AutoTokenizer.from_pretrained(model_id) + config = AutoConfig.from_pretrained(model_id) + + # find the model type + config.architectures # remove the unnecessary kwargs kwargs.pop("model_type", None) @@ -215,10 +220,29 @@ def _initialize_pipeline( tokenizer.pad_token_id = tokenizer.eos_token_id try: - if task == "text-generation": - model = AutoModelForCausalLM.from_pretrained(model_id) - elif task in ("text2text-generation", "summarization"): + if task in ("text2text-generation", "summarization") or ( + config.architectures + and any( + any( + arch_name in arch.lower() + for arch_name in [ + "t5", + "bart", + "led", + "mbart", + "pegasus", + "blenderbot", + "blenderbotsmall", + "marian", + "mt5", + ] + ) + for arch in config.architectures + ) + ): model = AutoModelForSeq2SeqLM.from_pretrained(model_id) + elif task == "text-generation": + model = AutoModelForCausalLM.from_pretrained(model_id) else: raise ValueError(Errors.E086(task=task)) except ImportError as e: diff --git a/poetry.lock b/poetry.lock index f4cc4c011..dd72bef41 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,34 +1,34 @@ -# This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.2 and should not be changed by hand. 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"extra == \"transformers\"" files = [ - {file = "accelerate-1.10.0-py3-none-any.whl", hash = "sha256:260a72b560e100e839b517a331ec85ed495b3889d12886e79d1913071993c5a3"}, - {file = "accelerate-1.10.0.tar.gz", hash = "sha256:8270568fda9036b5cccdc09703fef47872abccd56eb5f6d53b54ea5fb7581496"}, + {file = "accelerate-1.13.0-py3-none-any.whl", hash = "sha256:cf1a3efb96c18f7b152eb0fa7490f3710b19c3f395699358f08decca2b8b62e0"}, + {file = "accelerate-1.13.0.tar.gz", hash = "sha256:d631b4e0f5b3de4aff2d7e9e6857d164810dfc3237d54d017f075122d057b236"}, ] [package.dependencies] huggingface_hub = ">=0.21.0" -numpy = ">=1.17,<3.0.0" +numpy = ">=1.17" packaging = ">=20.0" psutil = "*" pyyaml = "*" @@ -37,15 +37,15 @@ torch = ">=2.0.0" [package.extras] deepspeed = ["deepspeed"] -dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "diffusers", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-order", "pytest-subtests", "pytest-xdist", "rich", "ruff 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["langchain", "langchain-community", "ollama"] openai = ["langchain", "langchain-community", "langchain-openai", "openai"] spacy = ["spacy"] transformers = ["accelerate", "datasets", "torch", "transformers"] [metadata] lock-version = "2.1" -python-versions = ">=3.9,<4.0" -content-hash = "d28505f9ceb132b5a43dfcf8afcf1f3dc8232f160b380cffb3cacbcc448f9f2f" +python-versions = ">=3.12,<3.15" +content-hash = "c88bae49afd61a5a73514d58fa262b20424f71f3be3fbe5f2584fec17c0959c7" diff --git a/pyproject.toml b/pyproject.toml index bf24f5dca..59be9b5c2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,16 +55,16 @@ extend-exclude = "langtest/transform/constants.py" exclude = 'langtest/errors.py' [tool.poetry.dependencies] -python = ">=3.9,<4.0" +python = ">=3.12,<3.15" pydantic = ">=2.10.0" johnsnowlabs = {version = "^6.0.4", optional = true} rouge-score = { version = "^0.1.2", optional = true } evaluate = { version = "^0.4.0", optional = true } -transformers = "^4.52.4" +transformers = {version 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check-docstrings = "pydocstyle langtest/ --add-select=D417 --add-ignore=D100,D104,D105,D400,D415 --convention=google" diff --git a/tests/test_nlp_tasks.py b/tests/test_nlp_tasks.py index ef80b14b9..3f91b5533 100644 --- a/tests/test_nlp_tasks.py +++ b/tests/test_nlp_tasks.py @@ -22,7 +22,7 @@ "config": { "model_parameters": { "max_tokens": 20, - "task": "text2text-generation", + "task": "text-generation", }, "evaluation": { "metric": "embedding_distance", @@ -45,7 +45,7 @@ "config": { "model_parameters": { "max_tokens": 20, - "task": "text2text-generation", + "task": "text-generation", }, "evaluation": { "metric": "string_distance", @@ -68,7 +68,7 @@ "config": { "model_parameters": { "max_tokens": 20, - "task": "text2text-generation", + "task": "text-generation", }, "tests": { "defaults": {"min_pass_rate": 0.65}, @@ -84,7 +84,7 @@ "model": {"model": "t5-base", "hub": "huggingface"}, "data": {"data_source": "XSum", "split": "test-tiny"}, "config": { - "model_parameters": {"max_tokens": 128, "task": "text2text-generation"}, + "model_parameters": {"max_tokens": 128, "task": "text-generation"}, "tests": { "defaults": {"min_pass_rate": 0.65}, "robustness": { @@ -140,7 +140,7 @@ "config": { "model_parameters": { "max_tokens": 20, - "task": "text2text-generation", + "task": "text-generation", }, "tests": { "defaults": { @@ -194,7 +194,7 @@ "config": { "model_parameters": { "max_tokens": 20, - "task": "text2text-generation", + "task": "text-generation", }, "tests": { "defaults": { @@ -211,7 +211,7 @@ "config": { "model_parameters": { "max_tokens": 20, - "task": "text2text-generation", + "task": "text-generation", }, "tests": { "defaults": { @@ -260,7 +260,7 @@ def test_nlp_task(task_parameters): "config": { "model_parameters": { "max_tokens": 20, - "task": "text2text-generation", + "task": "text-generation", }, "tests": { "defaults": {