A Framework for Enterprise Large Language Model Applications

f-case is a modular framework for deploying enterprise-grade large language model (LLM) applications, built around a function-calling architecture in which the LLM acts as a reasoning engine that selects and invokes specialised tools rather than executing tasks directly. Separating reasoning from execution lets the system integrate with knowledge bases, APIs, and existing enterprise systems while preserving security boundaries and a clean separation of concerns. The framework uses exclusively open-source models, enabling complete local deployment and addressing enterprise constraints around data privacy, cost, and offline operation. It comprises a React frontend, a Python orchestration backend, a function-calling system for tool invocation, and specialised integration modules — knowledge-base retrieval, code-repository analysis, web search, and enterprise-system connectors — with context-management strategies that sustain coherent conversations across extended sessions and multiple data sources. Evaluation shows the system runs effectively on consumer-grade hardware (tested on an NVIDIA RTX 2060, 6 GB VRAM) and improves response relevance, coherence, factual accuracy, and helpfulness over a baseline direct-LLM implementation, with the strongest results in knowledge-base integration and code-repository analysis.