Grounded Evals

from athina.evals import AnswerSimilarity
from athina.evals.grounded.similarity import CosineSimilarity

# Checks the similarity between the response and the reference answer
response = "The capital of France is Paris."
expected_response = "Paris is the capital of France."
AnswerSimilarity(comparator=CosineSimilarity()).run(response=response, expected_response=expected_response).to_df()

from athina.loaders import Loader
raw_data = [
    {
        "response": "Thomas Edison invented the light bulb.",
        "expected_response": "The light bulb was invented by Thomas Edison."
    },
    {
        "response":  "The capital of France is Paris.",
        "expected_response": "Paris is the capital of France."
    }
]
# Load the data from JSON, Athina or Dictionary
dataset = Loader().load_dict(raw_data)

from athina.evals import AnswerSimilarity
from athina.evals.grounded.similarity import CosineSimilarity

# Evaluates the similarity of the response to the expected response
AnswerSimilarity(comparator=CosineSimilarity()).run_batch(data=dataset).to_df()

from athina.evals import AnswerSimilarity
from athina.evals.grounded.similarity import CosineSimilarity

AnswerSimilarity(comparator=CosineSimilarity(), failure_threshold=0.75).run_batch(data=dataset).to_df()

from athina.evals import ContextSimilarity
from athina.evals.grounded.similarity import CosineSimilarity

ContextSimilarity(comparator=CosineSimilarity(), failure_threshold=0.75).run_batch(data=dataset).to_df()