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Evaluate RAG system answers with Pinecone Assistant using correctness, completeness, and alignment metrics against a ground truth answer.
metrics_alignment operation.
You can evaluate a response from an assistant, as in the following example. The question is what you asked, the answer is the response to evaluate, and ground_truth_answer (groundTruth in Node.js) is the response you expect.
from pinecone import Pinecone
pc = Pinecone(api_key="YOUR_API_KEY")
result = pc.assistants.evaluate_alignment(
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.",
)
print(result)
import { Pinecone } from '@pinecone-database/pinecone';
const pc = new Pinecone({ apiKey: 'YOUR_API_KEY' });
const result = await pc.assistants.evaluate({
question: 'What are the capital cities of France, England and Spain?',
answer: 'Paris is the capital city of France and Barcelona of Spain',
groundTruth: 'Paris is the capital city of France, London of England and Madrid of Spain.',
});
console.log(result);
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" \
-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"
}'
{
"metrics": {
"correctness": 0.5,
"completeness": 0.3333,
"alignment": 0.4
},
"reasoning": {
"evaluated_facts": [
{
"fact": {
"content": "Paris is the capital city of France."
},
"entailment": "entailed"
},
{
"fact": {
"content": "London is the capital city of England."
},
"entailment": "neutral"
},
{
"fact": {
"content": "Madrid is the capital city of Spain."
},
"entailment": "contradicted"
}
]
},
"usage": {
"prompt_tokens": 1223,
"completion_tokens": 51,
"total_tokens": 1274
}
}
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