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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: For example:

Response

Metrics

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

Reasoning

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

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.

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.