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import json
import pandas as pd
from datasets import Dataset
from ragas import evaluate
from ragas.metrics import context_precision, faithfulness, answer_relevancy, context_recall
from dotenv import load_dotenv
import os
from langchain_openai import ChatOpenAI
# Load environment variables
load_dotenv()
# Get the OpenAI API key
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
if not OPENAI_API_KEY:
raise ValueError("OpenAI API key not found in environment variables.")
# Load the local JSON file
with open("testset_with_answers.json", "r") as f:
data = json.load(f)
# Convert the JSON data to a pandas DataFrame
df = pd.DataFrame(data)
# Convert the pandas DataFrame to a Hugging Face Dataset
ai_ans = Dataset.from_pandas(df)
# Create a ChatOpenAI instance with the API key
llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY)
# Now you can proceed with the evaluation
result = evaluate(
ai_ans,
metrics=[
context_precision,
faithfulness,
answer_relevancy,
context_recall,
],
llm=llm # Pass the LLM instance here
)
print(result) |