ContextCompletenessScorer
Evaluates whether the provided context contains all necessary information to fully support the answer. Assesses if context is complete enough to answer the query comprehensively, helping evaluate retrieval system effectiveness.
Overview
Evaluates whether the provided context contains all necessary information to fully support the answer. Assesses if context is complete enough to answer the query comprehensively, helping evaluate retrieval system effectiveness.
Use Cases
- General AI evaluation and quality assessment
How It Works
This scorer uses LLM-as-Judge technology to evaluate responses. It prompts a large language model with specific evaluation criteria and the content to assess, then analyzes the LLM's judgment to produce a score and detailed reasoning.
Input Schema
| Parameter | Type | Required | Description |
|---|---|---|---|
| output_text | str | Yes | Generated answer |
| input_text | str | Yes | Original question |
| context | list[str] | str | Yes | Retrieved context to evaluate for completeness |
Output Schema
| Field | Type | Description |
|---|---|---|
| score | float | Completeness score (0-10) |
| passed | bool | True if context is complete |
| reasoning | str | Completeness analysis |
| metadata | dict | Missing information if any |
Score Interpretation
Default threshold: 7/10
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Frequently Asked Questions
When should I use this scorer?
Use ContextCompletenessScorer when you need to evaluate multi-context and completeness aspects of your AI outputs. It's particularly useful for general ai evaluation and quality assessment.
Why doesn't this scorer need expected output?
This scorer evaluates quality aspects that don't require comparison against a reference answer. It uses the system prompt and context as the implicit ground truth.
Can I customize the threshold?
Yes, the default threshold of 7 can be customized when configuring the scorer.
Quick Info
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