Dynamic Form with AI
Configured with Aggregate, Chain LLM, Filter, Form, and additional nodes. Review the connections and setup before adapting this template.
Node categories in this workflow
- AI & models
- Integration
- Trigger
- Transform
- Routing
Icons describe general node roles, inferred from node types. Inspect the parameters for the configured action.
Drag to pan; use + and − to zoom. Reconstructed from the exported node positions; nothing runs here. Dashed lines represent non-main connections. Full node names and notes appear below.
How it works
The exported workflow contains the following configured nodes. Their connections are shown above; inspect the JSON for the complete logic, expressions, and external actions.
| Node | Category | Type | Operation |
|---|---|---|---|
| OpenAI Chat Model | AI & models | OpenAI Chat Model | See node parameters |
| Clarification Questions | Integration | Form | See node parameters |
| Get Basic Information | Trigger | Form Trigger | See node parameters |
| Get Business Overview | Integration | Form | See node parameters |
| End Form | Integration | Form | completion |
| Structured Output Parser | Transform | Output Parser Structured | See node parameters |
| Remove Already Answered Questions | Routing | Filter | See node parameters |
| Analyse Response | AI & models | Chain LLM | See node parameters |
| Split Out Analysis | Transform | Split Out | See node parameters |
| Prepare For Form Generation | Transform | Edit Fields | See node parameters |
| Aggregate For Form Generation | Transform | Aggregate | See node parameters |
Setup
- Download the JSON and import it into an isolated n8n instance. Leave the workflow inactive.
- Connect your own credentials through n8n’s credential store. Replace
REPLACE_WITH_*values with your resource identifiers. - Inspect API destinations, Code nodes, database queries, file paths, and outbound actions.
- Run with synthetic data and harmless destinations. Enable triggers only after checking the actual outputs.
Requirements
An n8n instance with the listed node types and compatible versions. Service-connected workflows may require accounts, credentials, or paid APIs.
Credential types declared in the source
openAiApi
Workflow notes
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.
- 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 analyse the form response - those that are qualified should be given the opportunity to book an appointment
Setup
Setup
- Add your OpenAI credentials
- Go to the Get Basic Information node and click Test Step
- Complete the form to test the generic use case
- Modify the prompt in Analyse Response to fit your use case
Modification
Modification
Replace this sub-node to use a different language model
Modification
Modification
Modify the prompt to suit your use case
Dynamic Form with AI
Dynamic Form with AI
Purpose and structure
This folder contains the Dynamic Form with AI workflow. Its executable nodes use aggregate, chainLlm, filter, form, formTrigger, lmChatOpenAi, outputParserStructured, set, splitOut. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.
Setup
Import inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.
Entry points
Get Basic Information
Verification
Sanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.
Attribution
https://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Splitout/1784_Splitout_Filter_Automation_Triggered.json MIT; preserve source notices.
Canvas section labels
These name areas of the original canvas; they do not include explanatory instructions.
- 1. Initial Form Pages
- 2. Analyse Response
- 3. Clean Up Analysis
- 4. Generate Final Form Page & End Form