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

# Advanced Parameters

> Detailed reference for all LLM API parameters including sampling, penalties, streaming, and response formatting.

## Chat Completions Parameters

These parameters are available on the [Chat Completions](/llm-api/chat-completions) endpoint (OpenAI-compatible).

### Core Parameters

| Parameter    | Type    | Required | Default | Description                                                                    |
| ------------ | ------- | -------- | ------- | ------------------------------------------------------------------------------ |
| `model`      | string  | Yes      | —       | Model ID to use. See [List Models](/llm-api/list-models) for available models. |
| `messages`   | array   | Yes      | —       | Array of message objects with `role` and `content`.                            |
| `max_tokens` | integer | No       | 1000    | Maximum tokens to generate. Range: 1 to model's max context.                   |
| `stream`     | boolean | No       | `false` | Enable Server-Sent Events streaming.                                           |

### Sampling Parameters

| Parameter     | Type    | Range | Default | Description                                                                                                                                                                           |
| ------------- | ------- | ----- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `temperature` | float   | 0–2   | 1.0     | Controls randomness. Lower values (0.1–0.3) produce focused, deterministic output. Higher values (0.8–1.5) increase creativity and variety. Set to 0 for greedy decoding.             |
| `top_p`       | float   | 0–1   | 1.0     | Nucleus sampling — only consider tokens with cumulative probability above this threshold. Lower values (0.1) make output more focused. Use either `temperature` or `top_p`, not both. |
| `top_k`       | integer | 1+    | —       | Only sample from the top K most likely tokens. Lower values constrain output. Not all models support this.                                                                            |

<Warning>
  Avoid setting both `temperature` and `top_p` at the same time. Use one or the other for best results.
</Warning>

### Penalty Parameters

| Parameter            | Type  | Range   | Default | Description                                                                                                          |
| -------------------- | ----- | ------- | ------- | -------------------------------------------------------------------------------------------------------------------- |
| `presence_penalty`   | float | -2 to 2 | 0       | Penalizes tokens that have appeared in the text so far. Positive values encourage the model to explore new topics.   |
| `frequency_penalty`  | float | -2 to 2 | 0       | Penalizes tokens based on how often they've appeared. Positive values reduce repetition proportionally to frequency. |
| `repetition_penalty` | float | 0.1–2   | 1.0     | Multiplicative penalty on repeated tokens. Values > 1 discourage repetition, \< 1 encourage it.                      |

### Stop Sequences

| Parameter | Type            | Default | Description                                                                                            |
| --------- | --------------- | ------- | ------------------------------------------------------------------------------------------------------ |
| `stop`    | string or array | `null`  | Up to 4 sequences where the API will stop generating. The stop sequence is not included in the output. |

````json theme={null}
{
  "stop": ["\n\n", "END", "```"]
}
````

### Response Format

| Parameter         | Type    | Default | Description                                                                      |
| ----------------- | ------- | ------- | -------------------------------------------------------------------------------- |
| `response_format` | object  | —       | Force the model to output in a specific format.                                  |
| `seed`            | integer | —       | Attempt deterministic output. Same seed + same input should produce same output. |
| `n`               | integer | 1       | Number of completions to generate.                                               |

**JSON mode:**

```json theme={null}
{
  "response_format": {"type": "json_object"}
}
```

<Info>
  When using JSON mode, you must also instruct the model to output JSON in your system or user message, e.g. "Respond in JSON format."
</Info>

### Function Calling

| Parameter             | Type             | Default  | Description                                                                                    |
| --------------------- | ---------------- | -------- | ---------------------------------------------------------------------------------------------- |
| `tools`               | array            | —        | List of tools/functions the model can call. See [Function Calling](/llm-api/function-calling). |
| `tool_choice`         | string or object | `"auto"` | Controls tool usage: `"auto"`, `"none"`, `"required"`, or a specific tool.                     |
| `parallel_tool_calls` | boolean          | `true`   | Whether the model can call multiple tools in one turn.                                         |

***

## Messages Parameters

These parameters are available on the [Messages](/llm-api/messages) endpoint (Anthropic-compatible).

### Core Parameters

| Parameter    | Type    | Required | Default | Description                                                                         |
| ------------ | ------- | -------- | ------- | ----------------------------------------------------------------------------------- |
| `model`      | string  | Yes      | —       | Model ID to use.                                                                    |
| `messages`   | array   | Yes      | —       | Input messages. Roles: `user` and `assistant` only (system goes in `system` param). |
| `max_tokens` | integer | Yes      | —       | Maximum tokens to generate. Required for Anthropic format.                          |
| `system`     | string  | No       | —       | System prompt. Passed separately, not as a message.                                 |
| `stream`     | boolean | No       | `false` | Enable streaming via Server-Sent Events.                                            |

### Sampling Parameters

| Parameter     | Type    | Range | Default | Description                                                       |
| ------------- | ------- | ----- | ------- | ----------------------------------------------------------------- |
| `temperature` | float   | 0–1   | 1.0     | Controls randomness. Note: Anthropic format caps at 1.0, not 2.0. |
| `top_p`       | float   | 0–1   | —       | Nucleus sampling threshold.                                       |
| `top_k`       | integer | 1+    | —       | Only sample from the top K tokens.                                |

### Stop Sequences

| Parameter        | Type  | Default | Description            |
| ---------------- | ----- | ------- | ---------------------- |
| `stop_sequences` | array | —       | Custom stop sequences. |

### Tool Use

| Parameter     | Type   | Default            | Description                                                                                                              |
| ------------- | ------ | ------------------ | ------------------------------------------------------------------------------------------------------------------------ |
| `tools`       | array  | —                  | Tools the model can use. Uses `input_schema` instead of `parameters`. See [Function Calling](/llm-api/function-calling). |
| `tool_choice` | object | `{"type": "auto"}` | Controls tool usage: `{"type": "auto"}`, `{"type": "any"}`, or `{"type": "tool", "name": "..."}`.                        |

***

## Common Patterns

### Deterministic Output

For reproducible results, use low temperature with a seed:

```json theme={null}
{
  "temperature": 0,
  "seed": 42
}
```

### Creative Writing

For creative, varied output:

```json theme={null}
{
  "temperature": 1.2,
  "presence_penalty": 0.6,
  "frequency_penalty": 0.3
}
```

### Structured Extraction

For extracting structured data:

```json theme={null}
{
  "temperature": 0,
  "response_format": {"type": "json_object"},
  "max_tokens": 2000
}
```

### Code Generation

For code generation tasks:

````json theme={null}
{
  "temperature": 0.2,
  "top_p": 0.95,
  "stop": ["\n\n\n", "```"]
}
````

### Conversational

For natural, engaging conversations:

```json theme={null}
{
  "temperature": 0.8,
  "presence_penalty": 0.5,
  "max_tokens": 500
}
```