# Tips & Tricks

### Too many nodes?

When you work with many nodes, loops, or branches, nodes are always registered in the workflow as a flat list. Having too many nodes can make it difficult to visually follow the execution flow and focus on a certain part of the workflow for changes or new development.

Instead of a flat 20-node array, break it into logical sections:

```php
 class MyWorkflow extends Workflow
 {
     ... 
    protected function nodes(): array
    {
        return [
            ...$this->classificationProcess(),
            ...$this->analysis(),
            ...$this->postProcessing(),
        ];
    }
    
    /**
     * Initial classification process
     */
    protected function classificationProcess(): array
    {
        return [
            // Nodes here...
        ];
    }
}
```

The spread operator (...) keeps the runtime behavior identical. It's still a flat array. But now the
\
`nodes()` method reads like a table of contents, and each group is self-documenting.

## Example Projects

### AIForm - Conversational Data Collection

AIForm is a component for collecting structured data through multi-turn natural language conversations. It uses an AI agent to progressively gather information defined by a structured output class, validating each piece of data along the way.

The form maintains conversation history, tracks collected fields, missing fields, and validation errors across multiple turns.

<a href="https://github.com/neuron-core/ai-form" class="button secondary" data-icon="github">Check out the GitHub repository</a>

### Deep Research Agent

This project is inspired by Open Deep Research, which uses LangGraph for implementation. Other implementations exist also for llamaindex, and others. Our version leverages Neuron to create a powerful, modular workflow for research and analysis.

Neuron Open Deep Research provides a structured approach to generating comprehensive research reports on any topic using large language models, with a focus on modularity, extensibility, and real-time results.

#### Architecture

**DeepResearchAgent**: Orchestrates the overall report generation process

* **Planning**: Creates the structure of the report
* **GenerateSectionContent**: Generates content for each section using search results
* **Format**: Compiles the final report

**SearchWorkflow**: Handles search operations as a nested workflow

* **GenerateQueries**: Creates search queries based on section topics
* **SearchTheWeb**: Executes parallel searches and processes results

<a href="https://github.com/neuron-core/deep-research-agent" class="button secondary" data-icon="github">Check out the GitHub repository</a>

### Travel Planner Agent

This project demonstrates how to create a tour planner using Neuron PHP framework for agentic applications.

Stack Used:

* Neuron Workflow for multi-agent orchestration.
* [SerpAPI](https://serpapi.com/) for finding hotels, flights and places to visit comprehensive research reports on any topic using large language models, with a focus on modularity, extensibility, and real-time results.

#### Architecture

**TravelPlannerAgent**: Orchestrates the overall itinerary generation process

#### Nodes

* **Receptionist**: Collect all the information from the user
* **Delegator**: Generates single reports for flights, hotels, and places to visit
  * *Flights*
  * *Hotels*
  * *Places*
* **GenerateItinerary**: Generates the final report

<a href="https://github.com/neuron-core/travel-planner-agent" class="button secondary" data-icon="github">Check out the GitHub Repository</a>

### Laravel Travel Agent

This project demonstrates how to integrate multi-agent workflows in a Laravel application using Neuron PHP AI framework.&#x20;

Stack Used:

* [Laravel](https://laravel.com/) and [Livewire](https://livewire.laravel.com/) for the application.
* [Neuron Workflow](https://docs.neuron-ai.dev/workflow/getting-started) for multi-agent orchestration.
* [SerpAPI](https://serpapi.com/) for finding hotels, flights and places to visit comprehensive research reports on any topic using large language models, with a focus on modularity, extensibility, and real-time results.

<figure><img src="https://content.gitbook.com/content/GHx4l2LknIex7vFIUg1R/blobs/EKh727BovIG1YXS5MQWw/laravel-travel-planner-ai-agent.png" alt=""><figcaption></figcaption></figure>

#### How to use this project

Download the project on your machine and open your terminal in the project directory. First, install the composer dependencies:

```bash
composer install

npm run build

php artisan migrate
```

Create a `.env` file in your project root (see `.env.example` for a template), and provides the API keys based on the service you want to connect with.

```
# At least one required
ANTHROPIC_API_KEY=
GEMINI_API_KEY=
OPENAI_API_KEY=

#Required
SERPAPI_KEY=

# Optional
INSPECTOR_INGESTION_KEY=
INSPECTOR_TRANSPORT=sync
```

Open the project in your browser, register an account, and start planning your trip.