> ## Documentation Index
> Fetch the complete documentation index at: https://docs.uptrain.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

> Quickest way to perform evaluations on your data

UpTrain provides a simple and easy way to perform evaluations on your data. You can pass any of these Evals to the `evaluate` function in `EvalLLM` class and it will automatically perform the evaluation.

These evals require a combination of the following columns to be present in your data:

* `question`: The question you want to ask
* `context`: The context relevant to the question
* `response`: The response to the question

Some evals may require additional parameters to be passed to them. These are called parametric evals. Any eval below that has a `Parameters` section is a parametric eval.

You can choose evals as per your needs. We have divided them into a few categories for your convenience:

<AccordionGroup>
  <Accordion title="Ground Truth Comparison Evals">
    | Eval                                                                                   | Description                                                              |
    | -------------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
    | [Response Matching](/predefined-evaluations/ground-truth-comparison/response-matching) | Grades how relevant the generated context was to the question specified. |
  </Accordion>

  <Accordion title="Response Quality Evals">
    | Eval                                                                                   | Description                                                                                                             |
    | -------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------- |
    | [Reponse Completeness](/predefined-evaluations/response-quality/response-completeness) | Grades whether the response has answered all the aspects of the question specified.                                     |
    | [Reponse Conciseness](/predefined-evaluations/response-quality/response-conciseness)   | Grades how concise the generated response is or if it has any additional irrelevant information for the question asked. |
    | [Reponse Relevance](/predefined-evaluations/response-quality/response-relevance)       | Grades how relevant the generated context was to the question specified.                                                |
    | [Reponse Validity](/predefined-evaluations/response-quality/response-validity)         | Grades if the response generated is valid or not. A response is considered to be valid if it contains any information.  |
    | [Reponse Consistency](/predefined-evaluations/response-quality/response-consistency)   | Grades how consistent the response is with the question asked as well as with the context provided.                     |
  </Accordion>

  <Accordion title="Context Awareness Evals">
    | Eval                                                                                 | Description                                                                                                              |
    | ------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------ |
    | [Context Relevance](/predefined-evaluations/context-awareness/context-relevance)     | Grades how relevant the context was to the question specified.                                                           |
    | [Context Utilization](/predefined-evaluations/context-awareness/context-utilization) | Grades how complete the generated response was for the question specified given the information provided in the context. |
    | [Factual Accuracy](/predefined-evaluations/context-awareness/factual-accuracy)       | Grades whether the response generated is factually correct and grounded by the provided context.                         |
    | [Context Conciseness](/predefined-evaluations/context-awareness/context-conciseness) | Evaluates the concise context cited from an original context for irrelevant information.                                 |
    | [Context Reranking](/predefined-evaluations/context-awareness/context-reranking)     | Evaluates how efficient the reranked context is compared to the original context.                                        |
  </Accordion>

  <Accordion title="Security Evals">
    | Eval                                                                      | Description                                                                                               |
    | ------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
    | [Prompt Injection](/predefined-evaluations/safeguarding/prompt-injection) | Grades whether the generated response is leaking any system prompt.                                       |
    | [Jailbreak Detection](/predefined-evaluations/safeguarding/jailbreak)     | Grades whether the user's prompt is an attempt to jailbreak (i.e. generate illegal or harmful responses). |
  </Accordion>

  <Accordion title="Language Quality Evals">
    | Eval                                                                                | Description                                                                         |
    | ----------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------- |
    | [Language Features](/predefined-evaluations/language-quality/fluency-and-coherence) | Grades whether the response has answered all the aspects of the question specified. |
    | [Tonality](/predefined-evaluations/language-quality/tonality)                       | Grades whether the generated response matches the required persona's tone           |
  </Accordion>

  <Accordion title="Query Clarity Evals">
    | Eval                                                                                   | Description                                                                                             |
    | -------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------- |
    | [Sub-query Completeness](/predefined-evaluations/query-quality/sub-query-completeness) | Evaluate if the list of generated sub-questions comprehensively cover all aspects of the main question. |
    | [Multi-query Accuracy](/predefined-evaluations/query-quality/multi-query-accuracy)     | Evaluates how accurately the variations of the query represent the same question.                       |
  </Accordion>

  <Accordion title="Code Related Evals">
    | Eval                                                                        | Description                                                                          |
    | --------------------------------------------------------------------------- | ------------------------------------------------------------------------------------ |
    | [Code Hallucination](/predefined-evaluations/code-evals/code-hallucination) | Grade whether the code present in the generated response is grounded by the context. |
  </Accordion>

  <Accordion title="Conversation Evals">
    | Eval                                                                              | Description                                                        |
    | --------------------------------------------------------------------------------- | ------------------------------------------------------------------ |
    | [User Satisfaction](/predefined-evaluations/conversation-evals/user-satisfaction) | Grade the conversations between the user and the LLM/AI assistant. |
  </Accordion>

  <Accordion title="Creating Custom Evals">
    | Eval                                                                      | Description                                                                     |
    | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------- |
    | [Custom Guideline](/predefined-evaluations/custom-evals/custom-guideline) | Grades how well the LLM adheres to a provided guideline when giving a response. |
    | [Custom Prompts](/predefined-evaluations/custom-evals/custom-prompt-eval) | Allows you to create your own set of evaluations.                               |
  </Accordion>
</AccordionGroup>