Background
In November 2022, OpenAI unveiled chatGPT, which greatly transformed the way people perceive AI. Almost a year has passed since its release, and the AI industry’s development in the realm of large language models has been primarily driven by two aspects. On one hand, there are continuous model updates and advancements by commercial companies like OpenAI, resulting in more intelligent conversational models with increasing parameters and longer supported context lengths. Google’s BARD has followed suit. Leading the open-source initiatives is Facebook Meta’s LLAMA series. On the other hand, there is a focus on rapidly developing applications based on the foundational capabilities of large language models, such as the emergence of open-source application development frameworks led by Langchain.
Motivation for Comparing Three Mainstream Frameworks:
Recently, due to our company’s needs, we have planned to embark on a secondary development using these open-source development frameworks. Considering development costs, we aim to avoid starting from scratch. Therefore, we conducted research into the current leading frameworks for large model application development, including Langchain, Autochain, and the recently introduced Semantic Kernel by Microsoft.
