> For the complete documentation index, see [llms.txt](https://lamatic.ai/llms.txt).

# Generate Text Node

<NodeOverview slug="generate-text-node" type="ai" />

## Overview

The Generate Text node allows users to programmatically generate text outputs by submitting prompts to selected LLMs. These text outputs can be further processed within each flow. This node is particularly useful for applications requiring dynamic text creation, such as chatbots, content creation, and automated report generation.

![text-gen.png](../img/text-gen/text-llm.webp)

<NodeTypeInfo 
  batchTrigger={false}
  eventTrigger={false}
  action={true}
  description="This node is an Action node that processes input data and generates text output based on the provided prompt and selected LLM model."
/>

## Features

<details>
<summary>**Key Functionalities**</summary>
1. **Generative Model Selection**: Allows users to select credentials for their preferred generative model, ensuring flexibility and compatibility with various LLMs.

2. **Customizable Prompts**: Features a field for creating prompt templates, enabling tailored input for specific use cases.

3. **System Prompt Definition**: Includes an option to define a system-level prompt to guide the AI's behavior, ensuring context-aware and role-specific responses.

4. **Additional Properties Management**: Offers expandable sections for configuring advanced properties to fine-tune AI-generated outputs.
</details> 

<details>
<summary>**Benefits**</summary>

5. **Flexibility**: Supports integration with multiple LLMs, allowing users to utilize different models based on their specific needs and use cases.

6. **User-Centric Design**: Provides intuitive interfaces for prompt customization and system prompt definition, making it accessible to both beginners and advanced users.

7. **Enhanced Control**: Enables precise control over the AI's behavior and output quality through customizable prompts and system configurations.

8. **Scalability**: Facilitates the creation of reusable prompt templates for diverse flow, ensuring consistency across projects.
</details>

## What Can I Build?

1. Automated content creation flow for blogs and social media posts.
1. Intelligent chatbots capable of generating dynamic and personalized responses.
1. Automated report generation systems for business intelligence and data analysis.
1. Customizable email and message drafting tools for improved communication efficiency.

## Prompt Examples

### Summarize

Condenses a long piece of text into a short, clear summary.

**System Prompt**
```
You are a summarization assistant.
Summarize the given text in 3-5 sentences.
Be concise and keep only the most important points.
Do not add any information that is not in the original text.
```

**User Prompt**
```
Summarize the following text:
{{triggerNode_1.content}}
```

> Note: To make the summary shorter or longer, update the sentence count in the System Prompt.

---

### Score Generator

Evaluates an input and returns a score with a short reason.

**System Prompt**
```
You are a scoring assistant.
Read the input and give it a score from 1 to 10 based on quality and relevance.
Return the score followed by a one-line reason.
Format: Score: X/10 — Reason: <your reason>
```

**User Prompt**
```
Score the following response:
{{triggerNode_1.response}}
```

> Update the scoring criteria in the System Prompt to match your use case (e.g. clarity, tone, accuracy).

## Setup

### Select the Text LLM Node

1. Fill in the required parameters.
1. Build the desired flow
1. Deploy the Project
1. Click Setup on the workflow editor to get the automatically generated instruction and add it in your application.

## Configuration Reference

| **Parameter**             | **Description**                                                                                                | **Example Value**            |
| ------------------------- | -------------------------------------------------------------------------------------------------------------- | ---------------------------- |
| **Generative Model Name** | Select the model to generate text based on the prompt.                                                         | Gemini Model                 |
| **User Prompt**           | Define the instructions for generating the text output.Define the instructions for generating the text output. | Tell me something about Bali |
| **System Prompt**         | System prompt to guide the LLM                                                                                 | You are Travel Planner       |

## Low-Code Example

```yaml
nodes:
  - nodeId: LLMNode_565
    nodeType: LLMNode
    nodeName: Text Generate
    values:
      promptTemplate: Tell me something about Bali
      systemPrompt: You are an AI Assistant
      messages: "[]"
      generativeModelName:
        provider_name: openai
        type: generator/text
        credential_name: Test OpenAI
        credentialId: aeeb2922-a7d3-431a-a376-77e01e725c51
        model_name: gpt-4-turbo
    needs:
      - triggerNode_1
```

## Output

### `_meta`

- A nested object containing metadata about the processing of the text generation request.

  - **`prompt_tokens`**: Number of tokens in the input prompt.
  - **`completion_tokens`**: Number of tokens in the generated output.
  - **`total_tokens`**: Sum of `prompt_tokens` and `completion_tokens`.

  - **`prompt_tokens_details`**: Breakdown of token usage in the prompt.

    - **`cached_tokens`**: Tokens reused from cache.
    - **`audio_tokens`**: Tokens from audio input (if applicable).

  - **`completion_tokens_details`**: Breakdown of token usage in the generated output.

    - **`reasoning_tokens`**: Tokens used for reasoning.
    - **`audio_tokens`**: Tokens from audio output (if applicable).
    - **`accepted_prediction_tokens`**: Tokens from accepted predictions.
    - **`rejected_prediction_tokens`**: Tokens from rejected predictions.

  - **`model_name`**: Name of the AI model used for text generation.
  - **`model_provider`**: The provider or organization supplying the model.

### `generatedResponse`

- A string containing the text output generated by the model based on the input prompt.

### Example Output

```json
{
  "_meta": {
    "prompt_tokens": 19,
    "completion_tokens": 212,
    "total_tokens": 231,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    },
    "model_name": "gpt-4-turbo",
    "model_provider": "openai"
  },
  "generatedResponse": "Response"
}
```

## Troubleshooting

### Common Issues

| **Problem**                    | **Solution**                                                 |
| ------------------------------ | ------------------------------------------------------------ |
| **Invalid API Key**            | Ensure the API key is correct and has not expired.           |
| **Dynamic Content Not Loaded** | Increase the `Wait for Page Load` time in the configuration. |

### Debugging

1. Check Lamatic Flow logs for error details.
1. Verify API Key.