Evaluate an answer
For guidance and examples, see Evaluate answers.
# To use the Python SDK, install the plugin:
# pip install --upgrade pinecone pinecone-plugin-assistant
# pip install requests
import requests
from pinecone_plugins.assistant.models.chat import Message
qa_data = {
"question": "What are the capital cities of France, England and Spain?",
"ground_truth_answer": "Paris is the capital city of France, London of England and Madrid of Spain"
}
for qa in qa_data:
chat_context = [Message(role="user", content=qa["question"])]
response = assistant.chat(messages=chat_context)
answer = response.message.content # The answer from the Assistant - see https://docs.pinecone.io/guides/assistant/chat-with-assistant
eval_data = {
"question": qa["question"],
"answer": answer,
"ground_truth_answer": qa["ground_truth_answer"]
}
response = requests.post(
"https://prod-1-data.ke.pinecone.io/assistant/evaluation/metrics/alignment",
headers={
"Api-Key": os.environ["PINECONE_API_KEY"],
"Content-Type": "application/json"
},
json=eval_data
)
print(response.text)PINECONE_API_KEY="YOUR_API_KEY"
curl https://prod-1-data.ke.pinecone.io/assistant/evaluation/metrics/alignment \
-H "Api-Key: $PINECONE_API_KEY" \
-H "Content-Type: application/json" \
-H "X-Pinecone-Api-Version: 2025-04" \
-d '{
"question": "What are the capital cities of France, England and Spain?",
"answer": "Paris is the capital city of France and Barcelona of Spain",
"ground_truth_answer": "Paris is the capital city of France, London of England and Madrid of Spain"
}'POST /evaluation/metrics/alignment
Request body
Section titled “Request body”question(body, string, required) — The question for which the answer was generated.answer(body, string, required) — The generated answer.ground_truth_answer(body, string, required) — The ground truth answer to the question.
Responses
Section titled “Responses”200— The evaluation metrics and reasoning for the generated answer.422— Validation error.500— Internal server error.