Tomaz Bratanic explores the potential of using a JSON-based agent with the Mixtral 8x7b language model to enhance interactions with the Neo4j graph database through a semantic layer. The approach leverages the LangChain framework to construct a system where language models can dynamically interact with tools via a predefined JSON structure, allowing for more sophisticated and context-aware responses. By integrating tools such as recommendation engines and smalltalk functions, Bratanic demonstrates how language models can access real-time data and perform tasks beyond mere information retrieval, like personalizing user experiences and affecting the environment, such as booking meetings. Despite challenges in prompting Mixtral to use tools only when necessary, a workaround using a dummy smalltalk tool is introduced to manage exceptions. While Mixtral may not match the refined capabilities of GPT-4, Bratanic remains optimistic about the potential for open-source language models to evolve into effective agents with further fine-tuning and development.