# LLM Node

The **LLM (Large Language Model) node** allows you to run prompts directly inside your Workflow using one of the available AI models.\
This makes it possible to **generate text, transform data, analyze inputs, or create structured outputs** automatically.

***

### 🛠️ How It Works

1. You **select a provider** (e.g., Zaia).
2. You **choose a model** (e.g., Claude, GPT, etc.).
3. You define the **output type** → text or JSON.
4. You set the **temperature** → controls balance between **precision** (deterministic answers) and **creativity** (diverse answers).
5. You write a **prompt** that the LLM will execute.

The result can then be passed to other nodes in the Workflow.

***

### ⚙️ Configuration Options

* **Provider** → The service powering the LLM (e.g., Zaia).
* **Model** → Which model to use (e.g., `claude-sonnet-4.5`).
* **Output type** →
  * **Text**: free-form answer.
  * **JSON**: structured response (ideal for automation).
* **Temperature** →
  * Low = deterministic (e.g., 0.1 → precise answers).
  * High = creative (e.g., 0.8 → more variation).
* **Prompt** → The instruction/query you want the LLM to process.

***

### 📌 Example Use Cases

* **Summarization**: Input long text, output a short summary.
* **Data transformation**: Convert unstructured text into JSON for APIs.
* **Creative generation**: Ask for product descriptions, social media posts, or marketing copies.
* **Decision support**: Evaluate conditions and suggest next steps.

***

### 🚀 Example

Prompt:

```
Extract the email and phone number from the following text and return in JSON:  

"Hi, my name is John. You can reach me at john@example.com or call me at +1 555 123 4567."  
```

Output (JSON):

```json
{
  "email": "john@example.com",
  "phone": "+1 555 123 4567"
}
```

***

⚡ **Tip:** Always be explicit in your prompts about the **format you expect** (e.g., JSON, bullet points, step-by-step instructions).


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# 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.zaia.app/workflows/workflow-nodes/llm-node.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.