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Nuanced: Giving LLMs Precise Call Graph Context for AI Coding Assistants

2025-03-12

Nuanced is an open-source Python library that provides LLMs with precise call graph context by analyzing function relationships and generating a structured representation of code dependencies. It addresses the limitations of current AI coding assistants, which lack understanding of code structure and rely on limited context windows and embeddings. Nuanced leverages static analysis to build a traversable graph of function relationships, offering `init` (to generate the call graph) and `enrich` (to query specific functions) commands. This allows AI tools to access the same structured program understanding developers rely on, improving code comprehension and efficiency. Future development will include function purity analysis, code complexity metrics, and more.

AI Coding Assistants Need More Context: Experiments and Insights

2025-02-10

Traditional AI coding assistants, while proficient in code generation, often lack crucial context about the broader system environment. This leads developers to spend extra time bridging the gap between code and various information sources. This article details experiments integrating operational context (call graphs, metrics, exception reports) into AI assistants to improve debugging accuracy. Results show structured performance data and error reports enhance AI analysis, but efficiently representing vast amounts of context remains a challenge. The future lies in a knowledge graph encompassing production behavior, system metrics, and more, enabling AI assistants to understand system behavior holistically.