From Tool Calling to Symbolic Thinking: LLMs in a Persistent Lisp Metaprogramming Loop

Fuente: arXiv
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Main Author: de la Torre, Jordi
Format: Preprint
Published: 2025
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author de la Torre, Jordi
author_facet de la Torre, Jordi
contents We propose a novel architecture for integrating large language models (LLMs) with a persistent, interactive Lisp environment. This setup enables LLMs to define, invoke, and evolve their own tools through programmatic interaction with a live REPL. By embedding Lisp expressions within generation and intercepting them via a middleware layer, the system allows for stateful external memory, reflective programming, and dynamic tool creation. We present a design framework and architectural principles to guide future implementations of interactive AI systems that integrate symbolic programming with neural language generation.
format Preprint
id arxiv_https___arxiv_org_abs_2506_10021
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle From Tool Calling to Symbolic Thinking: LLMs in a Persistent Lisp Metaprogramming Loop
de la Torre, Jordi
Programming Languages
Artificial Intelligence
We propose a novel architecture for integrating large language models (LLMs) with a persistent, interactive Lisp environment. This setup enables LLMs to define, invoke, and evolve their own tools through programmatic interaction with a live REPL. By embedding Lisp expressions within generation and intercepting them via a middleware layer, the system allows for stateful external memory, reflective programming, and dynamic tool creation. We present a design framework and architectural principles to guide future implementations of interactive AI systems that integrate symbolic programming with neural language generation.
title From Tool Calling to Symbolic Thinking: LLMs in a Persistent Lisp Metaprogramming Loop
topic Programming Languages
Artificial Intelligence
url https://arxiv.org/abs/2506.10021