Work in progress

Instructor for PHP

Structured data processing in PHP, powered by LLMs. Designed for simplicity, transparency, and control.

Introduction

Start processing your data with LLMs in under 5 minutes

Quickstart

Set up Instructor in your project and start processing data with LLMs

Setup

Why use Instructor?

Managing and rendering prompts in Instructor

Prompt Templates

Response model defines the structure of results returned by LLM.

Response Models

Configure your environment for Instructor

Environment

How to set up location of Instructor configuration directory for your project

Configuration Path

Instructor supports a number of LLM API providers.

LLM API Providers

Running and viewing cookbooks with Instructor Hub tool

Instructor Cookbooks

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

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

Debugging

Receive specific internal event with onEvent()

Tracking token usage via events

Receive all internal events with wiretap()

Anthropic

Azure OpenAI

Cerebras

Cohere

DeepSeek

Fireworks.ai

Google Gemini

Groq

Minimaxi

Mistral AI

MoonshotAI

Local / Ollama

OpenAI

OpenRouter

SambaNova

Together.ai

xAI / Grok

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

Assign a Role

Auto-Refine The Prompt

Clarify Ambiguous Information

Define Style

Emotional Stimuli

Generate Follow-Up Questions

Ask Model to Repeat the Query

Simulate a Perspective

Generate In-Context Examples

Analogical Prompting

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

Polyglot is a PHP library that provides a unified API to access various LLM API providers.

Embeddings are a way to represent data (text, images, audio) in a continuous vector space.

Polyglot Guide

​Work in progress

Work in progress