# Text Agent

The **Text Agent** is a generative AI agent that enables users to programmatically create text-based outputs using prompts and selected LLMs. It is ideal for applications requiring dynamic content generation, such as chatbots, content creation, automated reporting, and structured AI responses.

## Why Use the Text Agent?

- **AI-Powered Content Generation:** Automate text creation for various use cases.
- **Customizable AI Responses:** Define system and user prompts for precise output.
- **Flexible Model Selection:** Choose from different LLM providers based on your needs.
- **Seamless Integration:** Connect with flow for automated processing.

## Key Features

**Core Functionalities**

1. **Generative Model Selection** – Choose from multiple LLM providers and configure API credentials.
2. **Customizable Prompts** – Define user and system prompts for tailored AI responses.
3. **System Prompt Definition** – Guide AI behavior with context-aware instructions.
4. **Advanced Properties Management** – Fine-tune outputs with additional configuration options.

**Advantages**

1. **Flexibility** – Supports multiple LLMs, enabling diverse AI-powered applications.
2. **User-Friendly Interface** – Easily configure prompt settings for quick deployment.
3. **Enhanced Control** – Customize AI behavior through structured prompt templates.
4. **Scalability** – Reuse and adapt prompt templates for various flow.

## What Can I Build?

- **Automated Content Generation** – AI-powered writing for blogs, social media, and marketing.
- **Chatbots & Virtual Assistants** – Dynamic, context-aware conversational agents.
- **Automated Reports & Summaries** – AI-driven data analysis and business intelligence reporting.
- **Email & Message Drafting** – Smart communication tools for efficiency and personalization.

## How to Use the Text Agent?

### Creating a Text Agent via Flow Editor

1. **Add a Text Agent Node** – Select the **Text Agent** from the node list.
2. **Configure Prompts** – Define system-level and user prompts.
3. **Select an LLM Model** – Choose an AI model for text generation.
4. **Customize Output Settings** – Adjust properties for response formatting.
5. **Connect & Deploy** – Integrate the Text Agent into your workflow and execute.

### Creating a Text Agent via Agent Dashboard

1. **Go to the Agents Page** – Click **New Agent**.
2. **Choose Text Agent** – Select from available agent types.
3. **Configure Model & Prompts** – Set up LLM credentials and prompt templates.
4. **Deploy & Integrate** – Save and start using the agent in your application.

## Configuration Options

| **Parameter** | **Description** | **Example Value** |
| --- | --- | --- |
| **Prompts** | Define the prompts for system, user and assistant to be used for the LLM | `System Prompt, User Prompt` |
| **Models** | Selects the AI model for text generation. | `GPT-4 Turbo` |
| **Tools** | Tools which can be added to the agent for additional processing of the generated text. | `Sentiment Analysis` |
| **Messages** | System messages to guide the agent’s behavior. | `[{'user' : 'give me a write up for the topic : Claude vs GPT 4'}]` |
| **Memory** | Retains context across iterations. | `[{'sessionID' : '1234','context' : 'Claude vs GPT 4'}]` |

## Save Agent Configuration

You can save the configuration of any agent by clicking on the `Load Save Config` button and selecting `Save as New`. This will save the configuration of the agent and you can use it later by clicking on the `Load Configuration` button in other agents.

## 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.

## 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.
2. Verify API Key.