Evaluation overview

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Summary: Learn about evaluating the correctness and completeness of assistant responses.

Original Documentation

Documentation Index#

Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt Use this file to discover all available pages before exploring further.

Learn about evaluating the correctness and completeness of assistant responses.

You can evaluate the correctness and completeness of a response from an assistant or RAG system.

Use cases#

Response evaluation is useful when performing tasks like the following:

  • Understanding how well the Pinecone Assistant captures the facts of the ground truth answer.
  • Comparing the Pinecone Assistant’s answers to those of another RAG system.
  • Comparing the answers of your own RAG system to those of the Pinecone Assistant or another RAG system.

SDK support#

You can evaluate responses directly or through the Pinecone Python SDK.

Request#

The request body requires the following fields:

FieldDescription
questionThe question asked to the RAG system.
answerThe answer provided by the assistant being evaluated.
ground_truth_answerThe expected answer.

For example:

{
  "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."
}

Response#

Metrics#

Calculated scores between 0 to 1 are returned for the following metrics:

MetricDescription
correctnessCorrectness of the RAG system’s answer compared to the ground truth answer.
completenessCompleteness of the RAG system’s answer compared to the ground truth answer.
alignmentA combined score of the correctness and completeness scores.
{
  "metrics": {
    "correctness": 0.5,
    "completeness": 0.333,
    "alignment": 0.398,
  }
},

...

Reasoning#

The response includes explanations for the reasoning behind each metric’s score. This includes a list of evaluated facts with their entailment status:

StatusDescription
entailedThe fact is supported by the ground truth answer.
contradictedThe fact contradicts the ground truth answer.
neutralThe fact is neither supported nor contradicted by the ground truth answer.
...

  "reasoning":{
    "evaluated_facts": [
      {
        "fact": {"content": "Paris is the capital of France"},
        "entailment": "entailed",
      },
      {
        "fact": {"content": "London is the capital of England"},
        "entailment": "neutral"
      },
      {
        "fact": {"content": "Madrid is the capital of Spain"},
        "entailment": "contradicted",
      }
    ]
  },

...

Usage#

The response includes the number of tokens used to calculate the metrics. This includes the number of tokens used for the prompt and completion.

...

  "usage": {
    "prompt_tokens": 22,
    "completion_tokens": 33,
    "total_tokens": 55
  }
}

Pricing#

Cost is calculated by token usage. See Pricing for up-to-date pricing information.

Response evaluation is only available for Standard and Enterprise plans.

Link last verified June 7, 2026. View original ↗
Source: Pinecone Docs
Link last verified: 2026-02-26