# Available Parameters

#### **Main Sampling Parameters:**

1. **`temperature`** (default: 1.0)
   * Controls randomness in token selection.
   * Higher values (>1.0) increase randomness.
   * Lower values (<1.0) make outputs more deterministic.
   * A value of 0 forces greedy decoding.
2. **`top_p` (Nucleus Sampling)** (default: 1.0)
   * Controls the probability mass of token selection.
   * Only considers tokens that sum up to `top_p` probability.
   * Lower values (for example, 0.9) limit token choices to more likely options.
   * Higher values (close to 1.0) allow a broader range of tokens.
3. **`top_k`** (default: `-1`, which means disabled)
   * Limits token selection to the top `k` most probable tokens.
   * Lower values (for example, `top_k=50`) make output more deterministic.
   * If `-1`, this setting is ignored.
   * Since `top_k` is not defined in OpenAI spec, it should be passed in `extra_body` field.
4. **`max_tokens`** (default: `None`)
   * Sets the maximum number of tokens to generate.
   * Helps prevent excessively long responses.
5. **`repetition_penalty`** (default: 1.0)
   * Penalizes repeated tokens to avoid looping responses.
   * Values >1.0 discourage repetition.
   * Common values: 1.1 - 1.2.
6. **`presence_penalty`** (default: 0.0)
   * Increases the likelihood of introducing new tokens.
   * Useful for making outputs more diverse.
7. **`frequency_penalty`** (default: 0.0)
   * Penalizes tokens that have appeared frequently.
   * Helps prevent excessive repetition of common words.
8. **`seed`** (default: `None`)
   * Sets a fixed seed for reproducible results.
   * Useful for debugging or deterministic sampling.

#### **How These Work Together:**

* Setting **`temperature=0`** forces deterministic output (greedy decoding).
* Using **`top_p`** and **`top_k`** together balances diversity and coherence.
* **`repetition_penalty`** and **`presence_penalty`** help avoid repetitive loops.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.parasail.io/parasail-docs/serverless-and-models/available-parameters.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.