2025¶

Announcing unified provider interface

We are pleased to introduce a significant enhancement to Instructor: the from_provider() function. While Instructor has always focused on providing robust structured outputs, we've observed that many users work with multiple LLM providers. This often involves repetitive setup for each client.

The from_provider() function aims to simplify this process, making it easier to initialize clients and experiment across different models.

This new feature offers a streamlined, string-based method to initialize an Instructor-enhanced client for a variety of popular LLM providers.

Using Anthropic's Web Search with Instructor for Real-Time Data

Anthropic's new web search tool, when combined with Instructor, provides a powerful way to get real-time, structured data from the web. This allows you to build applications that can answer questions and provide information that is up-to-date, going beyond the knowledge cut-off of large language models.

In this post, we'll explore how to use the web_search tool with Instructor to fetch the latest information and structure it into a Pydantic model. Even a simple structure can be very effective for clarity and further processing.

What is MCP

With OpenAI joining Anthropic in supporting the Model Context Protocol (MCP), we're witnessing a unified standard for language models to interact with external systems. This creates exciting opportunities for multi-LLM architectures where specialized AI applications work in parallel-discovering tools, handing off tasks, and accessing powerful capabilities through standardized interfaces.

Instructor Adopts llms.txt: Making Documentation AI-Friendly

We're excited to announce that Instructor now implements the llms.txt specification! You can now find our llms.txt file at python.useinstructor.com/llms.txt. This adoption marks an important step in making our documentation more accessible to AI language models.

Instructor Adopting Cursor Rules

AI-assisted coding is changing how we use version control. Many developers now use what I call "vibe coding" - coding with AI help. This creates new challenges with Git. Today I'll share how we're using Cursor rules in Instructor to solve these problems.