Project Title

guidance — Efficient Programming Paradigm for Steering Large Language Models

Overview

Guidance is an innovative programming paradigm designed to control large language models effectively. It allows developers to structure output and achieve high-quality results tailored to specific use cases, all while reducing latency and cost compared to traditional prompting or fine-tuning methods. With Guidance, users can constrain generation using regex and context-free grammars, and seamlessly interleave control structures with generation.

Key Features

• Pythonic Interface for Language Models: Work with large language models using familiar Python idioms.
• Constrained Generation: Guarantee output syntax with powerful constrained generation capabilities.
• Custom Guidance Functions: Create custom functions that interact with language models using the @guidance decorator.

Use Cases

• Automated Customer Service: Use Guidance to create chatbots that can provide structured responses and handle a variety of customer inquiries.
• Content Generation: Employ Guidance for generating articles, reports, or other content with specific structural requirements.
• Educational Tools: Develop interactive educational applications that can provide tailored responses based on student input.

Advantages

• Reduced Latency and Cost: Guidance offers a more efficient way to interact with language models, cutting down on latency and cost.
• Seamless Integration of Control and Generation: Easily combine control structures like conditionals and loops with language model generation.
• Flexible and Powerful Constraint System: Ensure output conforms to any context-free grammar supported by the backend language model.

Limitations / Considerations

• Backend Compatibility: The effectiveness of Guidance's constraint system depends on the backend language model's support for Guidance.
• Complexity for Beginners: The powerful features of Guidance may have a steeper learning curve for developers new to this paradigm.

Similar / Related Projects

• Transformers: A library of state-of-the-art machine learning models for natural language processing, which Guidance can interface with.
• llama.cpp: A fast and lightweight library for deploying large language models, supported as a backend in Guidance.
• OpenAI: Offers large language models and APIs, which can be used as a backend for Guidance, providing access to cutting-edge models.

Basic Information

• GitHub: https://github.com/guidance-ai/guidance
• Stars: 20,699
• License: Unknown
• Last Commit: 2025-09-16

📊 Project Information

• Project Name: guidance
• GitHub URL: https://github.com/guidance-ai/guidance
• Programming Language: Jupyter Notebook
• ⭐ Stars: 20,699
• 🍴 Forks: 1,116
• 📅 Created: 2022-11-10
• 🔄 Last Updated: 2025-09-16

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