Patent drafting is a complex and high-stakes process for securing intellectual property rights. During the patent prosecution phase, maintaining confidentiality is crucial, making cloud-based third-party services inadequate for patent drafting assistance due to data security concerns. This study proposes AWACopilot, a secure, on-premise solution comprising a web service that leverages open-source large language models (LLMs) to assist patent attorneys in the intricate patent application drafting process. AWACopilot generates key patent sections such as background, abstract, detailed description, etc., from human-crafted claims, addressing the data security risks posed by cloud-based AI services. Its modular architecture enables customization and adaptability to different patent tasks. Although challenges remain-including reliance on LLM capabilities and the need for rigorous content verification-this study demonstrates the potential for secure, AI-driven solutions to enhance patent drafting workflows.