LMQL screenshot

LMQL

OtherPricing unavailable

LMQL: A Programming Language for Large Language Models

Last updated Dec 1, 2025

Claim Tool

What is LMQL?

LMQL is a programming language tailored for large language models (LLMs). It offers robust and modular LLM prompting through the use of types, templates, constraints, and an optimizing runtime. It simplifies the creation of complex prompts by allowing procedural programming techniques in a query-like syntax. Created by the SRI Lab at ETH Zurich, LMQL supports features such as nested queries, scripted prompting, and custom constraints. It also provides a Playground IDE for ease of use.

LMQL's Top Features

Key capabilities that make LMQL stand out.

Nested Queries

Scripted Prompting

Custom Constraints

Optimizing Runtime

Playground IDE

Local Model Support

Tool Augmentation

High-level Constraint Management

Sequential Query Execution

Integration with Popular Libraries

Use Cases

Who benefits most from this tool.

Developers

Creating complex and modular prompt structures for LLMs.

Researchers

Implementing advanced prompting techniques and optimization strategies.

Data Scientists

Utilizing structured prompting for data analysis and interpretation.

AI Practitioners

Building intelligent chatbots and interactive systems.

Educators

Teaching and demonstrating advanced prompting and LLM capabilities.

Hobbyists

Experimenting with LLMs and custom prompt designs.

Enterprises

Optimizing internal and customer-facing interactions through advanced LLM prompting.

AI Enthusiasts

Exploring the potential of procedural programming in LLM prompting.

Tech Startups

Innovating new applications and solutions using optimized LLM prompts.

Community Members

Participating in the development and documentation of LMQL features.

Explore Top AI Use Cases

Tags

programming languagelarge language modelstypestemplatesconstraintsoptimizing runtimequeriesSRI LabETH Zurichnested queriesscripted promptingcustom constraintsPlayground IDE

Top LMQL Alternatives

User Reviews

Share your thoughts

If you've used this product, share your thoughts with other builders

Recent reviews

Frequently Asked Questions

What is LMQL?
LMQL is a programming language designed for large language models, enabling robust and modular prompting through types, templates, and constraints.
Who developed LMQL?
LMQL was developed by the SRI Lab at ETH Zurich along with various contributors.
Can LMQL handle nested queries?
Yes, LMQL supports nested queries, which allow for modularized local instructions and the re-use of prompt components.
What is scripted prompting in LMQL?
Scripted prompting in LMQL allows for control flow and branching behavior in prompt construction, enabling more sophisticated prompt designs.
What constraints can be applied in LMQL?
LMQL allows for high-level constraints such as length restrictions and logical conditions to be applied to prompt outputs.
Is there an IDE available for LMQL?
Yes, LMQL provides a Playground IDE which can be used for writing and testing queries.
Can I use local models with LMQL?
Yes, LMQL supports self-hosted models via frameworks like 🤗 Transformers and llama.cpp.
What are some use cases of LMQL?
LMQL can be used for complex prompt generation, chatbots, interactive systems, and any scenario requiring structured prompting and constrained generation.
Does LMQL support integration with other tools?
Yes, LMQL supports tool augmentation and has integrations with LangChain, LlamaIndex, and Pandas among others.
How does LMQL optimize LLM queries?
LMQL uses an optimizing runtime to efficiently handle constraints and improve the performance of large language model queries.