Avoid Asking Redundant Questions with Dynamically Generated Forms using OpenAI

Avoid Asking Redundant Questions with Dynamically Generated Forms using OpenAI Target Audience This workflow has been built for those who require a form to capture as much data as possible as well as the answers to predefined questions, whilst optimising the user experience by avoiding asking redundant questions. Use Case When creating a form to capture information, it can be useful to give the user an opportunity to input a long answer to a large, open-ended question. We then want to drill down to answer specific questions that we require the answer to. When doing this, we don't want to ask duplicate questions. This particular scenario imagines an AI consultancy capturing leads. What it Does This workflow requires users to input basic information and then answer an open ended question. The specific questions on the next page will only be those that weren't answered in the open-ended question. How it Works The open-ended question (and relevant basic information) is analysed by an LLM to determine which specific questions have not been answered. Chain-of-thought reasoning is utilised and the output structure is specified with the Structured Output Parser.

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