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Query Large Models with Natural Language on Lmql

Programmatically interact with LLMs using LMQL. Craft modular prompts, execute complex tasks, and seamlessly switch between AI backends.

Programmatically interact with LLMs using LMQL. Craft modular prompts, execute complex tasks, and seamlessly switch between AI backends.

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Updated on April 19, 2025 (3 months ago)

AI Code Assistant: LMQL - Revolutionizing Interaction with Large Language Models

AI code assistants like LMQL are transforming the way we interact with AI in data analysis and natural language processing. This powerful programming language is specifically designed for Large Language Models (LLMs), enabling users to interact with these models in a more intuitive and efficient manner. LMQL empowers developers to construct complex prompts using types, templates, constraints, and an optimizing runtime, facilitating tasks ranging from simple queries to intricate procedural programming. Its modular approach encourages prompt reuse and simplifies the integration of Python control flow for enhanced flexibility. Moreover, LMQL's portability allows seamless switching between different LLM backends with a single line of code, making it a versatile tool for any AI enthusiast.

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