Prompting - Miscellaneous
Arbitrary properties
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
Arbitrary properties
Overview
When you need to extract undefined attributes, use a list of key-value pairs.
Example
<?php
require 'examples/boot.php';
use Cognesy\Instructor\Instructor;
use Cognesy\Polyglot\LLM\Enums\Mode;
class Property
{
public string $key;
public string $value;
}
class UserDetail
{
public int $age;
public string $name;
/** @var Property[] Extract any other properties that might be relevant */
public array $properties;
}
?>
Now we can use this data model to extract arbitrary properties from a text message in a form that is easier for future processing.
<?php
$text = <<<TEXT
Jason is 25 years old. He is a programmer. He has a car. He lives
in a small house in Alamo. He likes to play guitar.
TEXT;
$user = (new Instructor)->respond(
messages: [['role' => 'user', 'content' => $text]],
responseModel: UserDetail::class,
mode: Mode::Json,
);
dump($user);
assert($user->age === 25);
assert($user->name === "Jason");
assert(!empty($user->properties));
?>