Prompting - Miscellaneous
Handling errors
Cookbook
Instructor - Basics
- Basic use
- Basic use via mixin
- Handling errors with `Maybe` helper class
- Modes
- Making some fields optional
- Private vs public object field
- Automatic correction based on validation results
- Using attributes
- Using LLM API connections from config file
- Validation
- Custom validation using Symfony Validator
- Validation across multiple fields
- Validation with LLM
Instructor - Advanced
- Context caching (structured output)
- Customize parameters of LLM driver
- Custom prompts
- Using structured data as an input
- Extracting arguments of function or method
- Streaming partial updates during inference
- Providing example inputs and outputs
- Extracting scalar values
- Extracting sequences of objects
- Streaming
- Structures
Instructor - Troubleshooting
Instructor - LLM API Support
Instructor - Extras
- Extraction of complex objects
- Extraction of complex objects (Anthropic)
- Extraction of complex objects (Cohere)
- Extraction of complex objects (Gemini)
- Image processing - car damage detection
- Image to data (OpenAI)
- Image to data (Anthropic)
- Image to data (Gemini)
- Generating JSON Schema from PHP classes
- Generating JSON Schema dynamically
- Create tasks from meeting transcription
- Translating UI text fields
- Web page to PHP objects
Polyglot - LLM Basics
Polyglot - LLM Advanced
Polyglot - LLM Troubleshooting
Polyglot - LLM API Support
Polyglot - LLM Extras
Prompting - Zero-Shot Prompting
Prompting - Few-Shot Prompting
Prompting - Thought Generation
Prompting - Miscellaneous
- Arbitrary properties
- Consistent values of arbitrary properties
- Chain of Summaries
- Chain of Thought
- Single label classification
- Multiclass classification
- Entity relationship extraction
- Handling errors
- Limiting the length of lists
- Reflection Prompting
- Restating instructions
- Ask LLM to rewrite instructions
- Expanding search queries
- Summary with Keywords
- Reusing components
- Using CoT to improve interpretation of component data
Prompting - Miscellaneous
Handling errors
Overview
You can create a wrapper class to hold either the result of an operation or an error message. This allows you to remain within a function call even if an error occurs, facilitating better error handling without breaking the code flow.
NOTE: Instructor offers a built-in Maybe wrapper class that you can use to handle errors. See the example in Basics section for more details.
Example
<?php
require 'examples/boot.php';
use Cognesy\Instructor\Instructor;
class UserDetail
{
public string $name;
public int $age;
}
class MaybeUser
{
public ?UserDetail $user = null;
public bool $noUserData = false;
/** If no user data, provide reason */
public ?string $errorMessage = '';
public function get(): ?UserDetail
{
return $this->noUserData ? null : $this->user;
}
}
$user = (new Instructor)->respond(
messages: [['role' => 'user', 'content' => 'We don\'t know anything about this guy.']],
responseModel: MaybeUser::class
);
dump($user);
assert($user->noUserData);
assert(!empty($user->errorMessage));
assert($user->get() === null);
?>