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LMQL

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LMQL simplifies data analysis by enabling users to query large models using natural language.

About LMQL

LMQL is a programming language designed for interacting with large language models (LLMs). It enables users to construct robust and modular prompts using types, templates, constraints, and an optimizing runtime. LMQL supports features such as nested queries, typed variables, and direct integration with Python, allowing for procedural programming and prompt reusability. The tool is suitable for those looking to build advanced LLM workflows and can operate across multiple LLM backends, including OpenAI, llama.cpp, and Hugging Face Transformers. Pricing information is not provided on the site.

Best for: developers working with LLMs, AI researchers

Key features

  • Allows users to define prompts with constraints and types for LLMs
  • Supports nested queries for modular prompt construction
  • Integrates with Python for procedural prompt generation
  • Works with multiple LLM backends, including OpenAI and llama.cpp

Use cases

  • Enforcing output formats and constraints in LLM responses

Pros

  • Supports multiple LLM providers with easy backend switching
  • Enables modular and reusable prompt components

Screenshots

LMQL screenshot

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