Introduction
Structured data processing in PHP, powered by LLMs. Designed for simplicity, transparency, and control.
What is Instructor?
Instructor is a library that allows you to get structured, validated data from multiple types of inputs: text, chat messages, or images. It is powered by Large Language Models (LLMs).
The library is inspired by the Instructor for Python created by Jason Liu.
Learn More…
Get Started
Check how to set up Instructor in your project and start processing data with LLMs
Concepts
Read more about basic concepts behind Instructor
Essentials
Learn Instructor features and capabilities
Cookbooks
Browse examples to see Instructor in action and find out how to use it in your projects
Internals
Deep dive into Instructor internals and low level mechanisms
Feature Highlights
Instructor is designed to make it easy to process data with LLMs in PHP. Here are some of the key features of the library:
Core features
- Get structured responses from LLM inference
- Validation of returned data
- Automated retries in case of errors when LLM responds with invalid data
Flexible inputs
- Process various types of input data: text, series of chat messages or images
- ’Structured-to-structured’ processing - provide object or array as an input and get object with the results of inference back
- Demonstrate examples to improve the quality of inference
Customizable outputs
- Define response data model the way to need: type-hinted classes, JSON Schema arrays, or dynamically define your data shapes with Structures
- Customize prompts and retry prompts
- Use attributes or PHP DocBlocks to provide additional instructions for LLM
- Customize response model processing by providing your own implementation of schema, deserialization, validation and transformation interfaces
Sync and streaming support
- Receive synchronous or streaming responses
- Get partial updates & stream completed sequence items
Observability
- Get detailed insight into internal processing via events
Support for multiple LLMs / API providers
- Use multiple LLM API providers (incl. OpenAI, Anthropic, Cohere, Azure, Groq, Mistral, Fireworks AI, Ollama, OpenRouter, Together AI)
- Use local models with Ollama
Documentation and examples
- Learn more from growing documentation and 50+ cookbooks
Instructor in Other Languages
Instructor has been implemented in various technology stacks. Check out implementations in other languages below:
- Python (original)
- Javascript (port)
- Elixir (port)
- Ruby (port)
- Go (port)
If you want to port Instructor to another language, please reach out to us on Twitter we’d love to help you get started!