LMQL
AIQuery Language for Controlled Language Model Outputs
Overview
LMQL (Language Model Query Language) is an open-source query language built to simplify and control interactions with large language models (LLMs). It merges natural language prompts with structured constraints, allowing developers to define output formats, logical conditions, and token limits directly in queries. Ideal for tasks needing precise outputs like JSON or tables, LMQL cuts boilerplate code and boosts LLM result reliability. It integrates smoothly with popular LLMs such as GPT-4, Llama 2, and Mistral, supporting local and cloud deployments. With type checking, variable binding, and conditional logic, it helps build robust LLM apps faster, from chatbots to data extraction tools.
Key Features
- Structured constraints for precise LLM outputs
- Seamless integration with GPT-4, Llama 2, Mistral
- Open-source with local/cloud deployment support
- Variable binding and conditional logic in queries
Top Alternatives
Guidance
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Tool Info
Pros
- ⊕ Simplifies controlled LLM output with structured queries
- ⊕ Open-source and works with major LLMs
Cons
- ⊖ Steeper learning curve for complex constraints
- ⊖ Limited community support vs. larger frameworks like LangChain