Avoid Asking Redundant Questions with Dynamically Generated Forms using OpenAITarget 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 optimizing the user experience by avoiding 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 analyzed by an LLM to determine which specific questions have not been answered. Chain-of-thought reasoning is utilized and the output structure is specified with the Structured Output Parser.

Those questions that have already been answered are filtered out nodes. The remaining items are then used to generate the last page of the form. Once the user has filled in the final page of the form, they are shown a form completion page.

Next Steps
– Add additional nodes to send an email to the form owner.
– Add a subsequent LLM call to analyze the form response – those that are qualified should be given the opportunity to book an appointment.