ZenPipe

ZenPipe is a simple and flexible PHP pipeline library that allows you to chain operations together to process, transform, or act on input.

$calculator = zenpipe()
   ->pipe(fn($price, $next) => $next($price * 0.8)) // 20% discount  
   ->pipe(fn($price, $next) => $next($price * 1.1)); // add 10% tax

$calculator(100); // $88 (100 -> 80 -> 88)

You can also run the pipeline on demand:

zenpipe(100)
   ->pipe(fn($price, $next) => $next($price * 0.8)) // 20% discount  
   ->pipe(fn($price, $next) => $next($price * 1.1)) // add 10% tax
   ->process(); // 88

Sections

1. ZenPipe
2. Requirements
3. Installation
4. Usage
   • Pipeline Operations
   • Class Methods as Operations
   • More Examples
5. API Reference
6. Contributing
7. License
8. Roadmap

Requirements

• PHP 8.2 or higher

Installation

composer require dynamik-dev/zenpipe-php

Usage

Pipeline Operations

Pipeline operations are functions that take an input and return a processed value. Each operation can receive up to three parameters:

• $input: The value being processed
• $next: A callback to pass the value to the next operation
• $return: (Optional) A callback to exit the pipeline early with a value

Basic Operation Example

Let's build an input sanitization pipeline:

// String sanitization pipeline
$sanitizer = zenpipe()
    ->pipe(fn($input, $next) => $next(trim($input)))
    ->pipe(fn($input, $next) => $next(preg_replace('/\s+/', ' ', $input)))
    ->pipe(fn($input, $next) => $next(strip_tags($input)))
    ->pipe(fn($input, $next) => $next(htmlspecialchars($input)))
    ->pipe(fn($input, $next) => $next(mb_convert_encoding(
        $input, 'UTF-8', mb_detect_encoding($input)
    )));

// Usage examples:
$dirtyInput = "  <script>alert('xss')</script>  Hello   World! ¥€$ ";
$cleanInput = $sanitizer($dirtyInput);
// Output: "Hello World! ¥€$"

// Can also be run on demand:
$result = zenpipe($dirtyInput)
    ->pipe(fn($input, $next) => $next(trim($input)))
    ->pipe(fn($input, $next) => $next(strip_tags($input)))
    ->process();

Operation with Early Return

Below is a practical example of a content moderation pipeline with early returns:

// Content moderation pipeline with early returns
$moderationPipeline = zenpipe()
    ->pipe(function($content, $next, $return) {
        // Skip moderation for trusted authors
        if (Auth::user()->isTrusted()) {
            return $return([
                'status' => 'approved',
                'content' => $content,
                'skipped' => true
            ]);
        }
        return $next($content);
    })
    ->pipe(function($content, $next, $return) {
        // Quick check for banned words
        if (containsBannedWords($content)) {
            return $return([
                'status' => 'rejected',
                'reason' => 'prohibited_content'
            ]);
        }
        return $next($content);
    })
    ->pipe(function($content, $next) {
        // Send to AI moderation for nuanced analysis
        return $next(
            AI::moderate($content)
        );
    });

// Usage:
$result = $moderationPipeline("Hello, world!"); 
// Trusted user: Immediately returns approved
// Regular user: Goes through full moderation

Class Methods as Operations

You can also use class methods as operations, with the same parameter options:

class MyClass
{
    public function validate($input, $next, $return)
    {
        if (empty($input)) {
            return $return('Input cannot be empty');
        }
        return $next(strtoupper($input));
    }
}

$pipeline = zenpipe()
   ->pipe([MyClass::class, 'validate']);

You can also pass an array of operations:

$pipeline = zenpipe()
   ->pipe([
        fn($input, $next) => $next(strtoupper($input)),
        [MyClass::class, 'validate']
    ]);

More Examples

RAG Processes

This pipeline can be used for RAG processes, where the output of one model is used as input for another.

$ragPipeline = zenpipe()
    ->pipe(fn($query, $next) => $next([
        'query' => $query,
        'embeddings' => OpenAI::embeddings()->create([
            'model' => 'text-embedding-3-small',
            'input' => $query
        ])->embeddings[0]->embedding
    ]))
    ->pipe(fn($data, $next) => $next([
        ...$data,
        'context' => Qdrant::collection('knowledge-base')
            ->search($data['embeddings'], limit: 3)
            ->map(fn($doc) => $doc->content)
            ->join("\n")
    ]))
    ->pipe(fn($data, $next) => $next(
        OpenAI::chat()->create([
            'model' => 'gpt-4-turbo-preview',
            'messages' => [
                [
                    'role' => 'system',
                    'content' => 'Answer using the provided context only.'
                ],
                [
                    'role' => 'user',
                    'content' => "Context: {$data['context']}\n\nQuery: {$data['query']}"
                ]
            ]
        ])->choices[0]->message->content
    ));

$answer = $ragPipeline("What's our refund policy?");

Email Validation with Early Return

This pipeline demonstrates early returns for email validation:

$emailValidationPipeline = zenpipe()
    ->pipe(function($input, $next, $return) {
        if (!is_string($input)) {
            return $return('Input must be a string');
        }
        return $next(filter_var($input, FILTER_VALIDATE_EMAIL));
    })
    ->pipe(function($email, $next, $return) {
        if (!$email) {
            return $return('Invalid email format');
        }
        
        $domain = substr(strrchr($email, "@"), 1);
        $mxhosts = [];
        
        if (!getmxrr($domain, $mxhosts)) {
            return $return('Domain has no valid mail servers');
        }
        
        return $next(true);
    });

$result = $emailValidationPipeline('example@example.com');
// Returns: 'Domain has no valid mail servers'

$result = $emailValidationPipeline('invalid-email');
// Returns: 'Invalid email format'

API Reference

See API Reference for details.

Contributing

See CONTRIBUTING.md for details.

License

The MIT License (MIT). See LICENSE for details.

Roadmap

• Add support for PSR-15 middleware