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

# Use constrained outputs

> Set clear boundaries and rules for the model's responses to improve accuracy, consistency, and utility

## What are constrained outputs

Constrained outputs involve instructing the LLM to generate responses that adhere to specific limitations or formats. This could mean setting a word limit, specifying a response type (like "yes" or "no"), or requiring the output to match a particular pattern or structure.

## How to implement constrained outputs

1. **Set clear instructions**: Be explicit about the constraints you want the model to follow.
2. **Specify the format**: Define the exact format or pattern you expect.
3. **Limit the length**: Set boundaries on the response length, such as word or character counts.
4. **Use controlled vocabularies**: Restrict the model to use only certain words or phrases.
5. **Provide templates**: Offer a template that the model should fill in.

## Example

<AccordionGroup>
  <Accordion title="Example 1: Binary Classification.">
    Limiting the response to 'Approved' or 'Denied' ensures consistency and simplifies automated processing.

    **Prompt:**

    ```
    Review the following application and respond with 'Approved' or 'Denied' only.

    Application Details: [Applicant's information and criteria]

    Decision:
    ```
  </Accordion>

  <Accordion title="Example 2: Short Answer Generation.">
    By specifying that the answer should be in one sentence, you prevent the model from providing overly long or off-topic responses.  **Prompt:**

    **Prompt:**

    ```
    Based on the text below, answer the question in one sentence.

    Text: 'The Great Barrier Reef is the world's largest coral reef system located in Australia.'

    Question: 'Where is the Great Barrier Reef located?'

    Answer:
    ```
  </Accordion>

  <Accordion title="Example 3: Technical writing.">
    Setting an exact word limit challenges the model to be concise and focus on the most important information.

    **Prompt:**

    ```
    Summarize the following article in exactly 50 words.

    [Insert article text]

    Summary (50 words):
    ```
  </Accordion>
</AccordionGroup>

## Why use constrained outputs

* **Increase precision**: Helps the model provide exactly what you need without unnecessary information.
* **Enhance consistency**: Ensures uniformity across multiple outputs, which is crucial for tasks like data entry or form filling.
* **Simplify parsing**: Makes it easier to programmatically process the responses.
* **Reduce errors**: Minimizes the chance of irrelevant or incorrect information creeping into the output.

***

<Accordion title="Need more help?">
  Additional questions or feedback? Reach out to
  [help@helicone.ai](mailto:help@helicone.ai) or [schedule a
  call](https://cal.com/team/helicone/helicone-discovery) with us.
</Accordion>