OpenAI’s GPT has emerged as the foremost AI tool globally and is proficient at addressing queries based on its training data. However, it can not answer questions about unknown topics:

Recent events after Sep 2021
Your non-public documents
Information from past conversations

This task gets even more complicated when you deal with real-time data that frequently changes. Moreover, you cannot feed extensive content to GPT, nor can it retain your data over extended periods. In this case, you need to build a custom LLM (Language Learning Model) app efficiently to give context to the answer process. This piece will walk you through the steps to develop such an application utilizing the open-source LLM App library in Python. The source code is on GitHub (linked below in the section “Build a ChatGPT Python API for Sales”).

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