guidance-ai/guidance

Health v2 · maintenance only

Adoption not part of the score

21714 stars · 1201 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Guidance is a Python library providing an efficient programming paradigm for steering large language models, letting you interleave control flow (conditionals, loops, tool use) with generation. It supports constrained generation via regex and context-free grammars to guarantee output syntax, working with backends like Transformers, llama.cpp, and OpenAI.

Use cases

• force an LLM to output valid JSON or structured data
• constrain model generation with a regex or grammar
• build prompt programs with control flow interleaved with generation
• capture and reuse specific parts of model output
• reduce latency and cost versus conventional prompting
• prototype LLM apps in Jupyter notebooks

When to choose

• you need guaranteed output syntax like JSON, regex, or CFG-constrained formats
• you want deterministic structure from LLMs without fine-tuning
• you want a Pythonic interface across multiple model backends
• you're prototyping LLM workflows interactively in notebooks

When to avoid

• you need a full agent framework with built-in memory and tool orchestration
• your backend model isn't supported by one of Guidance's adapters
• you only need simple one-off prompting without structured output

Facets

library · maturity active

llm-inference prompt-engineering nlp sdk large-language-models artificial-intelligence developer-tools python cross-platform constrained-generation structured-output llm-programming grammar-constrained-decoding jupyter natural-language-processing

Member repositories

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markdown · JSON · MCP: product_card(name="guidance-ai/guidance")