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Non-English Testset Generation

Synthetic test generation from non-english corpus

In this notebook, you'll learn how to adapt synthetic test data generation to non-english corpus settings. For the sake of this tutorial, I am generating queries in Spanish from Spanish wikipedia articles.

Download and Load corpus

! git clone https://huggingface.co/datasets/explodinggradients/Sample_non_english_corpus

Cloning into 'Sample_non_english_corpus'...
remote: Enumerating objects: 12, done.
remote: Counting objects: 100% (8/8), done.
remote: Compressing objects: 100% (8/8), done.
remote: Total 12 (delta 0), reused 0 (delta 0), pack-reused 4 (from 1)
Unpacking objects: 100% (12/12), 11.43 KiB | 780.00 KiB/s, done.

from langchain_community.document_loaders import DirectoryLoader, TextLoader


path = "Sample_non_english_corpus/"
loader = DirectoryLoader(path, glob="**/*.txt")
docs = loader.load()

/opt/homebrew/Caskroom/miniforge/base/envs/ragas/lib/python3.9/site-packages/requests/__init__.py:102: RequestsDependencyWarning: urllib3 (1.26.20) or chardet (5.2.0)/charset_normalizer (None) doesn't match a supported version!
  warnings.warn("urllib3 ({}) or chardet ({})/charset_normalizer ({}) doesn't match a supported "

len(docs)

6

Initialize required models

from ragas.llms import LangchainLLMWrapper
from ragas.embeddings import LangchainEmbeddingsWrapper
from langchain_openai import ChatOpenAI
from langchain_openai import OpenAIEmbeddings

generator_llm = LangchainLLMWrapper(ChatOpenAI(model="gpt-4o-mini"))
generator_embeddings = LangchainEmbeddingsWrapper(OpenAIEmbeddings())

/opt/homebrew/Caskroom/miniforge/base/envs/ragas/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
  from .autonotebook import tqdm as notebook_tqdm

Setup Persona and transforms

you may automatically create personas using this notebook. For the sake of simplicity, I am using a pre-defined person, two basic tranforms and simple specic query distribution.

from ragas.testset.persona import Persona

personas = [
    Persona(
        name="curious student",
        role_description="A student who is curious about the world and wants to learn more about different cultures and languages",
    ),
]

from ragas.testset.transforms.extractors.llm_based import NERExtractor
from ragas.testset.transforms.splitters import HeadlineSplitter

transforms = [HeadlineSplitter(), NERExtractor()]

Initialize test generator

from ragas.testset import TestsetGenerator

generator = TestsetGenerator(
    llm=generator_llm, embedding_model=generator_embeddings, persona_list=personas
)

Load and Adapt Queries

Here we load the required query types and adapt them to the target language. 

from ragas.testset.synthesizers.single_hop.specific import (
    SingleHopSpecificQuerySynthesizer,
)

distribution = [
    (SingleHopSpecificQuerySynthesizer(llm=generator_llm), 1.0),
]

for query, _ in distribution:
    prompts = await query.adapt_prompts("spanish", llm=generator_llm)
    query.set_prompts(**prompts)

Generate

dataset = generator.generate_with_langchain_docs(
    docs[:],
    testset_size=5,
    transforms=transforms,
    query_distribution=distribution,
)

Applying HeadlineSplitter:   0%|          | 0/6 [00:00<?, ?it/s]unable to apply transformation: 'headlines' property not found in this node
unable to apply transformation: 'headlines' property not found in this node
unable to apply transformation: 'headlines' property not found in this node
unable to apply transformation: 'headlines' property not found in this node
unable to apply transformation: 'headlines' property not found in this node
unable to apply transformation: 'headlines' property not found in this node
Generating Scenarios: 100%|██████████| 1/1 [00:07<00:00,  7.75s/it] 
Generating Samples: 100%|██████████| 5/5 [00:03<00:00,  1.65it/s]

eval_dataset = dataset.to_evaluation_dataset()

print("Query:", eval_dataset[0].user_input)
print("Reference:", eval_dataset[0].reference)

Query: Quelles sont les caractéristiques du Bronx en tant que borough de New York?
Reference: Le Bronx est l'un des cinq arrondissements de New York, qui est la plus grande ville des États-Unis. Bien que le contexte ne fournisse pas de détails spécifiques sur le Bronx, il mentionne que New York est une ville cosmopolite avec de nombreux quartiers ethniques, ce qui pourrait inclure des caractéristiques culturelles variées présentes dans le Bronx.

That's it. You can customize the test generation process as per your requirements.