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A guidance language for controlling large language models with precision and efficiency.

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Tracked since2026
0 reviews tracked

The Bottom Line

Entry price

Free, no paid tier

Biggest pro

Provides fine-grained control over LLM output

Biggest con

Requires programming knowledge (Python)

TL;DR - Guidance

  • Controls large language models with a Pythonic interface.
  • Constrains LLM output using regex and context-free grammars.
  • Reduces latency and cost compared to conventional prompting.
Pricing: Free forever
Best for: Individuals & startups

What is Guidance?

Editorial review
Guidance is an efficient programming paradigm designed to steer and control large language models (LLMs). It provides a Pythonic interface that allows developers to interact with LLMs using familiar Python idioms, enabling seamless interleaving of control flow (conditionals, loops, tool use) and text generation. This approach helps users structure LLM output, achieve high-quality results, and potentially reduce latency and cost compared to traditional prompting or fine-tuning methods. The tool is particularly useful for developers and researchers working with LLMs who need fine-grained control over the generation process. It supports constraining output using regular expressions and context-free grammars, ensuring that the generated text adheres to specific formats or choices. Guidance also facilitates the creation of custom functions that encapsulate complex interactions with language models, making it easier to build sophisticated AI applications.

Available on: Web

Pros & Cons

Pros

  • Provides fine-grained control over LLM output
  • Ensures high-quality and structured output
  • Potentially reduces latency and cost
  • Integrates with common Python idioms
  • Supports multiple LLM backends

Cons

  • Requires programming knowledge (Python)
  • Full CFG support depends on the backend LLM

Preview

Key Features

Pythonic interface for interacting with LLMsConstrained generation using regular expressionsConstrained generation using context-free grammars (CFGs)Interleave control (conditionals, loops, tool use) and generationCapture generated text programmaticallySupport for various LLM backends (Transformers, llama.cpp, OpenAI)Custom Guidance functions using decoratorsJupyter notebook widget for richer user experience

Pricing Plans

Pricing checked Jul 11, 2026

Open Source

Free

  • Full source code access
  • MIT License license
  • Community support
  • Self-hosted

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Guidance FAQ

How does Guidance help developers create AI Assistants?

Guidance assists in creating AI Assistants by providing a programming paradigm to steer and control large language models. It allows developers to interleave control flow like conditionals and loops with text generation, which is crucial for building sophisticated and responsive assistants. This enables the creation of custom functions that encapsulate complex interactions with language models.

Which teams would benefit most from using Guidance?

Guidance is best suited for developers and researchers who work with large language models and require fine-grained control over the generation process. Teams building AI applications that need structured, high-quality LLM output and efficient interaction with models will find it particularly useful.

How does Guidance compare to the OpenAI API for controlling LLMs?

Guidance offers a distinct approach to controlling LLMs compared to the OpenAI API by providing a Pythonic interface that deeply integrates control flow with text generation. While the OpenAI API provides access to powerful models, Guidance focuses on giving developers fine-grained control over output structure and generation logic, potentially leading to more efficient and precise results.

What kind of programming knowledge is necessary to use Guidance effectively?

To use Guidance effectively, programming knowledge in Python is required. The tool provides a Pythonic interface, allowing developers to interact with large language models using familiar Python idioms and integrate control flow seamlessly.

Can Guidance ensure that generated text adheres to specific formats?

Yes, Guidance can ensure generated text adheres to specific formats by supporting output constraints using regular expressions and context-free grammars. This capability helps in achieving high-quality and structured output from large language models, aligning with predefined requirements.

Does Guidance include a free tier?

Guidance is free to use, meaning no paid plan is required to access its features. This allows developers and researchers to leverage its capabilities for controlling large language models without any associated cost.

Why might a developer choose Guidance over traditional prompting methods?

A developer might choose Guidance over traditional prompting methods because it offers fine-grained control over LLM output and enables seamless interleaving of control flow with text generation. This approach can lead to more structured and high-quality results, potentially reducing latency and cost compared to simpler prompting techniques.

Source: github.com

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