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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 2024 walledai + + 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/README.md b/README.md index 5f21e077..9c19d370 100644 --- a/README.md +++ b/README.md @@ -6,6 +6,7 @@ [![PyPI Latest Release](https://img.shields.io/pypi/v/walledeval.svg)](https://pypi.org/project/walledeval/) [![PyPI Downloads](https://static.pepy.tech/badge/walledeval)](https://pepy.tech/project/walledeval) +[![GitHub Page Views Count](https://badges.toozhao.com/badges/01J0NWXGZ7XGDPFYWHZ9EX1F46/blue.svg)](https://github.com/walledai/walledeval) **WalledEval** is a simple library to test LLM safety by identifying if text generated by the LLM is indeed safe. We purposefully test benchmarks with negative information and toxic prompts to see if it is able to flag prompts of malice. diff --git a/poetry.lock b/poetry.lock index dd8ce3aa..9d57f4d2 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,5 +1,36 @@ # This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +[[package]] +name = "accelerate" +version = "0.31.0" +description = "Accelerate" +optional = false +python-versions = ">=3.8.0" +files = [ + {file = "accelerate-0.31.0-py3-none-any.whl", hash = "sha256:0fc608dc49584f64d04711a39711d73cb0ad4ef3d21cddee7ef2216e29471144"}, + {file = "accelerate-0.31.0.tar.gz", hash = "sha256:b5199865b26106ccf9205acacbe8e4b3b428ad585e7c472d6a46f6fb75b6c176"}, +] + +[package.dependencies] +huggingface-hub = "*" +numpy = ">=1.17" +packaging = ">=20.0" +psutil = "*" +pyyaml = "*" +safetensors = ">=0.3.1" +torch = ">=1.10.0" + +[package.extras] +deepspeed = ["deepspeed (<=0.14.0)"] +dev = ["bitsandbytes", "black 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platform_machine != \"aarch64\""} +scipy = "*" + +[package.extras] +dask = ["dask", "distributed", "pandas"] +datatable = ["datatable"] +pandas = ["pandas"] +plotting = ["graphviz", "matplotlib"] +pyspark = ["cloudpickle", "pyspark", "scikit-learn"] +scikit-learn = ["scikit-learn"] + [[package]] name = "xxhash" version = "3.4.1" @@ -4894,4 +5076,4 @@ multidict = ">=4.0" [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "981683452220aaabb6538fd8b08ff2ed2b49f2d455bebad4a38ff45b0d17fef5" +content-hash = "6cd39e626f05835504325c3ded6127acd89241c6c3132912de5a4404cfd4eedf" diff --git a/pyproject.toml b/pyproject.toml index 83048007..a9292de5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -28,6 +28,10 @@ transformers = "^4.40.1" datasets = "^2.19.0" pydantic = "^2.7.1" python-dotenv = "^1.0.1" +accelerate = "^0.31.0" +xgboost = "^2.1.0" +scikit-learn = "^1.5.0" +ollama = "^0.2.1" [tool.poetry.group.dev.dependencies] pytest = "^7.4" diff --git a/tutorials/judges/LionGuard Tutorial.ipynb b/tutorials/judges/LionGuard Tutorial.ipynb new file mode 100644 index 00000000..6152ff87 --- /dev/null +++ b/tutorials/judges/LionGuard Tutorial.ipynb @@ -0,0 +1,211 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "36906df5-9345-4150-b977-d52b9beda6c4", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "66f9fb11-d63e-4b7d-b58e-00bc4f9c1f6e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/usr/bin/python\n" + ] + } + ], + "source": [ + "!which python" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "3ad0a0c1-fe1d-47d5-b1a6-7b87aa8db304", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.\n", + "Token is valid (permission: write).\n", + "Your token has been saved to /root/.cache/huggingface/token\n", + "Login successful\n" + ] + } + ], + "source": [ + "from dotenv import load_dotenv\n", + "import os\n", + "load_dotenv(\"../.env\")\n", + "\n", + "from huggingface_hub import login\n", + "from datasets import Dataset, load_dataset, DatasetDict\n", + "login(os.getenv(\"HF_TOKEN\"))\n", + "\n", + "import sys\n", + "sys.path.append(\"..\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "f99f6d5f-51f5-4429-b107-db2d1231c6d1", + "metadata": {}, + "outputs": [], + "source": [ + "from walledeval.judge import LionGuardJudge" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "6c4ef989-f529-4f82-bea4-00056700e262", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "binary = LionGuardJudge.from_preset(\"binary\")\n", + "binary" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "e7f131af-66c1-431c-98e8-40286280b30f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.0343454 , 0.03316101, 0.02191255, ..., -0.00717639,\n", + " -0.00188533, 0.01511723]], dtype=float32)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "binary.embed(\"Hello World\")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "76823a20-0b69-447b-95c8-859bec7332a8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.07944314947105535" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "binary.check(\"Hello World\")" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "1e449ced-b954-4e76-8e8a-a2d202c28e59", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9448972910301721" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "binary.check(\"bloody fuck you bloody\")" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "6bd9a8dc-4c6b-4de4-ba62-7cb771ca407a", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0.6833139548316369" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "binary.check(\"knn\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0a3a393a-b3ac-415b-9dae-c02393d4f6f9", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/walledeval/judge/__init__.py b/walledeval/judge/__init__.py index 164f3fb3..feefaf26 100644 --- a/walledeval/judge/__init__.py +++ b/walledeval/judge/__init__.py @@ -1,9 +1,10 @@ # walledeval/judge/__init__.py from walledeval.judge.core import Judge +from walledeval.judge.lionguard import LionGuardJudge from walledeval.judge.mcq import MCQJudge from walledeval.judge.llm import ( - LLMasaJudge, + LLMasaJudge, QuestionLLMasaJudge, SystemLLMasaJudge, MultiClassToxicityJudge, LlamaGuardJudge, LlamaGuardOutput @@ -19,5 +20,5 @@ "QuestionLLMasaJudge", "SystemLLMasaJudge", "MultiClassToxicityJudge", "LlamaGuardJudge", "LlamaGuardOutput", - "ToxicityModelJudge" + "ToxicityModelJudge", "LionGuardJudge" ] diff --git a/walledeval/judge/classifiers/__init__.py b/walledeval/judge/classifiers/__init__.py new file mode 100644 index 00000000..201d1c09 --- /dev/null +++ b/walledeval/judge/classifiers/__init__.py @@ -0,0 +1,57 @@ +# walledeval/judge/classifiers.py + +import json +import numpy as np + +from sklearn.linear_model import RidgeClassifier +from xgboost import XGBClassifier + +import numpy.typing as npt + +__all__ = [ + "Ridge", "XGBoost" +] + + +class Ridge(RidgeClassifier): + @classmethod + def from_config(cls, config_path: str, **kwargs): + with open(config_path, 'r') as config_file: + config = json.load(config_file) + + # assert "attributes" in config, "Key 'attributes' missing in config" + + attributes = config.pop("attributes", {}) + + classifier = cls(**kwargs) + classifier.set_params(**config) + + if "coef_" in attributes: + classifier.coef_ = np.array(attributes["coef_"]) + if "intercept_" in attributes: + classifier.intercept_ = np.array(attributes["intercept_"]) + if "n_features_in_" in attributes: + classifier.n_features_in_ = np.array(attributes["n_features_in_"]) + + return classifier + + def predict(self, input: npt.ArrayLike) -> list[float]: + decision = self.decision_function(input) + + decision = np.c_[-decision, decision] + probs = np.exp(decision) / np.sum(np.exp(decision)) + preds = probs[:, 1] + return preds.tolist() + + +class XGBoost(XGBClassifier): + @classmethod + def from_config(cls, config_path: str, **kwargs): + classifier = cls(**kwargs) + classifier.load_model(config_path) + + def predict(self, input: npt.ArrayLike) -> list[float]: + preds = self.predict_proba(input)[:, 1] + return preds.tolist() + + \ No newline at end of file diff --git a/walledeval/judge/lionguard/__init__.py b/walledeval/judge/lionguard/__init__.py new file mode 100644 index 00000000..47de447c --- /dev/null +++ b/walledeval/judge/lionguard/__init__.py @@ -0,0 +1,89 @@ +# walledeval/judge/lionguard.py + +import yaml +import torch +import numpy as np +from pathlib import Path + +from transformers import ( + AutoTokenizer, AutoModel, + AutoModelForSequenceClassification +) +from huggingface_hub import hf_hub_download + +from walledeval.judge.core import Judge +from walledeval.judge.classifiers import Ridge, XGBoost + +__all__ = [ + "LionGuardJudge" +] + + +class LionGuardJudge(Judge[None, float]): + def __init__(self, name: str, type: str, + config_file: str, + tokenizer: str, embedding_model: str, + max_length: int = 512, batch_size: int = 32): + super().__init__(name) + + self.type = type + + self.tokenizer = AutoTokenizer.from_pretrained(tokenizer) + self.embedding_model = AutoModel.from_pretrained(embedding_model) + self.max_length = max_length + self.batch_size = batch_size + + self.model_path = hf_hub_download(repo_id=name, filename=config_file) + + if self.type == "xgboost": + self.classifier = XGBoost.from_config(self.model_path) + elif self.type == "ridge": + self.classifier = Ridge.from_config(self.model_path) + else: + raise NotImplementedError(f"Model type '{self.type}' not implement yet.") + + @classmethod + def from_preset(cls, name: str = "beta"): + yaml_fp = Path(__file__).resolve().parent / f"presets/{name}.yaml" + yaml_text = yaml_fp.read_text(encoding="utf-8") + config = yaml.safe_load(yaml_text) + + return cls( + name = config.get("model_id", ""), + type = config.get("model_type", "ridge"), + config_file = config.get("config_file", "config.json"), + tokenizer = config.get("tokenizer", "BAAI/bge-large-en-v1.5"), + embedding_model = config.get("embedding_model", "BAAI/bge-large-en-v1.5"), + max_length = int(config.get("max_length", 512)), + batch_size = int(config.get("batch_size", 32)) + ) + + def embed(self, prompt: str): + # TODO: Implement Batching + # num_batches = int(np.ceil(len(data) / self.batch_size)) + # output = [] + + # for i in range(num_batches): + # sentences + encoded_input = self.tokenizer( + [prompt], + max_length=self.max_length, + padding=True, + truncation=True, + return_tensors='pt' + ) + + with torch.no_grad(): + model_output = self.embedding_model(**encoded_input) + embeddings = model_output[0][:, 0] + + embeddings = torch.nn.functional.normalize(embeddings, p=2, dim=1) + output = np.array(embeddings.cpu().numpy()) + # returns (1, embed_dim) + return output + + + def check(self, response: str, answer: None = None) -> float: + embeddings = self.embed(response) + preds = self.classifier.predict(embeddings) + return preds[0] diff --git a/walledeval/judge/lionguard/presets/beta.yaml b/walledeval/judge/lionguard/presets/beta.yaml new file mode 100644 index 00000000..f859103b --- /dev/null +++ b/walledeval/judge/lionguard/presets/beta.yaml @@ -0,0 +1,7 @@ +model_id: jfooyh/lionguard_beta +model_type: xgboost +config_file: lionguard_binary.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/lionguard/presets/binary.yaml b/walledeval/judge/lionguard/presets/binary.yaml new file mode 100644 index 00000000..1b37806e --- /dev/null +++ b/walledeval/judge/lionguard/presets/binary.yaml @@ -0,0 +1,7 @@ +model_id: dsaidgovsg/lionguard-binary-v1.0 +model_type: ridge +config_file: lionguard_binary.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/lionguard/presets/harassment.yaml b/walledeval/judge/lionguard/presets/harassment.yaml new file mode 100644 index 00000000..a966e175 --- /dev/null +++ b/walledeval/judge/lionguard/presets/harassment.yaml @@ -0,0 +1,7 @@ +model_id: dsaidgovsg/lionguard-harassment-v1.0 +model_type: ridge +config_file: lionguard_harassment.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/lionguard/presets/hateful.yaml b/walledeval/judge/lionguard/presets/hateful.yaml new file mode 100644 index 00000000..d6c8a2e5 --- /dev/null +++ b/walledeval/judge/lionguard/presets/hateful.yaml @@ -0,0 +1,7 @@ +model_id: dsaidgovsg/lionguard-hateful-v1.0 +model_type: ridge +config_file: lionguard_hateful.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/lionguard/presets/public_harm.yaml b/walledeval/judge/lionguard/presets/public_harm.yaml new file mode 100644 index 00000000..699f2a3e --- /dev/null +++ b/walledeval/judge/lionguard/presets/public_harm.yaml @@ -0,0 +1,7 @@ +model_id: dsaidgovsg/lionguard-public_harm-v1.0 +model_type: ridge +config_file: lionguard_public_harm.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/lionguard/presets/self_harm.yaml b/walledeval/judge/lionguard/presets/self_harm.yaml new file mode 100644 index 00000000..202ab66e --- /dev/null +++ b/walledeval/judge/lionguard/presets/self_harm.yaml @@ -0,0 +1,7 @@ +model_id: dsaidgovsg/lionguard-self_harm-v1.0 +model_type: ridge +config_file: lionguard_self_harm.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/lionguard/presets/sexual.yaml b/walledeval/judge/lionguard/presets/sexual.yaml new file mode 100644 index 00000000..26f01fcc --- /dev/null +++ b/walledeval/judge/lionguard/presets/sexual.yaml @@ -0,0 +1,7 @@ +model_id: dsaidgovsg/lionguard-sexual-v1.0 +model_type: ridge +config_file: lionguard_sexual.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/lionguard/presets/toxic.yaml b/walledeval/judge/lionguard/presets/toxic.yaml new file mode 100644 index 00000000..4c5e4d73 --- /dev/null +++ b/walledeval/judge/lionguard/presets/toxic.yaml @@ -0,0 +1,7 @@ +model_id: dsaidgovsg/lionguard-toxic-v1.0 +model_type: ridge +config_file: lionguard_toxic.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/lionguard/presets/violent.yaml b/walledeval/judge/lionguard/presets/violent.yaml new file mode 100644 index 00000000..649bf1b3 --- /dev/null +++ b/walledeval/judge/lionguard/presets/violent.yaml @@ -0,0 +1,7 @@ +model_id: dsaidgovsg/lionguard-violent-v1.0 +model_type: ridge +config_file: lionguard_violent.json +tokenizer: BAAI/bge-large-en-v1.5 +embedding_model: BAAI/bge-large-en-v1.5 +max_length: 512 +batch_size: 32 \ No newline at end of file diff --git a/walledeval/judge/llm/llamaguard.py b/walledeval/judge/llm/llamaguard.py index 536c8743..ee403191 100644 --- a/walledeval/judge/llm/llamaguard.py +++ b/walledeval/judge/llm/llamaguard.py @@ -1,6 +1,7 @@ # walledeval/judge/llm/llamaguard.py from enum import Enum +import torch from walledeval.llm import HF_LLM from walledeval.types import LLMType @@ -23,26 +24,36 @@ class LlamaGuardJudge(LLMasaJudge[LlamaGuardOutput]): "meta-llama/Meta-Llama-Guard-2-8B" ] - def __init__(self, version: int): + def __init__(self, version: int, + model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto", **kwargs): if version < 0 or version > len(self._VERSIONS): raise ValueError(f"Invalid Version {version}") self.version = version - self.model_id = self._VERSIONS[version % 2] + self.model_id = self._VERSIONS[(version+1) % 2] llm = HF_LLM( self.model_id, - type=LLMType.INSTRUCT + type=LLMType.INSTRUCT, + model_kwargs=model_kwargs, + device_map=device_map, + **kwargs ) super().__init__(self.model_id, llm) def generate(self, response: str) -> str: return self._llm.generate( - [{ - "role": "assistant", - "content": response - }] + [ + { + "role": "user", + "content": "" + }, { + "role": "assistant", + "content": response + } + ], + temperature=0.1 ) def process_llm_output(self, response: str) -> LlamaGuardOutput: diff --git a/walledeval/judge/llm/question.py b/walledeval/judge/llm/question.py index 534adfc6..a65efc3f 100644 --- a/walledeval/judge/llm/question.py +++ b/walledeval/judge/llm/question.py @@ -22,7 +22,7 @@ Answer in one word Yes or No:""" -class QuestionLLMasaJudge(LLMasaJudge[O], Generic[O], ABC): +class QuestionLLMasaJudge(LLMasaJudge[O], ABC, Generic[O]): def __init__(self, name: str, llm: LLM, template: str): super().__init__(name, llm) self.template = template diff --git a/walledeval/judge/llm/system.py b/walledeval/judge/llm/system.py index 2ef0ad80..18eb7e70 100644 --- a/walledeval/judge/llm/system.py +++ b/walledeval/judge/llm/system.py @@ -11,7 +11,7 @@ O = TypeVar("O") # Output Field -class SystemLLMasaJudge(LLMasaJudge[O], Generic[O], ABC): +class SystemLLMasaJudge(LLMasaJudge[O], ABC, Generic[O]): def generate(self, response: str, system: str) -> str: return self._llm.generate([ { diff --git a/walledeval/llm/ollama_llm.py b/walledeval/llm/ollama_llm.py new file mode 100644 index 00000000..cae66b97 --- /dev/null +++ b/walledeval/llm/ollama_llm.py @@ -0,0 +1,20 @@ +# walledeval/llm/ollama.py + +import ollama + +from typing import Optional, Union + +from walledeval.types import Message, Messages, LLMType +from walledeval.llm.core import LLM + + +class OllamaLLM(LLM): + def __init__(self, + id: str, + system_prompt: str = "", + type: Optional[Union[LLMType, int]] = LLMType.NEITHER): + super().__init__( + id, + system_prompt, + type + ) \ No newline at end of file