What Data for This Category Looks Like
The daily operation and maintenance documents for this category include four types: terminal fault tickets, installation inventory lists, software installation records, and remote assistance records. Data mainly comes from terminal management platforms, asset systems, user complaint channels, and software repositories. Data is updated either daily or with each processing request. Document fields typically include terminal ID, user workstation information, fault phenomenon description, associated software version, troubleshooting step records, and processing status identifiers. There are no fixed mandatory units, and field content adjusts dynamically based on specific terminal operation and maintenance scenarios.
What Constraints Do These Characteristics Impose on Forms and Interactions
Data sources rely on terminal management platforms and asset systems, requiring forms to support receiving existing data such as terminal lists and software versions passed in by external business systems to reduce repetitive manual entry operations. Data update frequency is daily or real-time per request, requiring form nodes to receive the latest terminal and asset information passed in by external business systems as options. The field structure of daily documents is flexible, requiring external systems to implement custom field extensions to adapt to different fault scenarios. The FastGPT form node is responsible for receiving relevant field data. Fault reproduction and troubleshooting take up a high proportion of total time, requiring support for calling remote assistance entrances from external business systems and passing troubleshooting records to external systems for storage. Missing required fields can lead to work order backlogs or employee downtime, requiring forms to enforce integrity checks for core information.
How to Configure
This document applies to FastGPT v4.17.0, and the following configuration items are based on the interaction logic of this version.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Form input node formInput | Test example: Select 3 fields from desktop terminal support fields as required inputs; actual fields are determined by the task | This node collects user input; missing required items require checking interaction status to avoid subsequent nodes failing to receive complete input |
User selection node userSelect | Test example: Set 2 business options, check corresponding branches one by one | This node handles user selection; querying and filtering records related to desktop terminal support must be implemented by subsequent interfaces or external systems |
| Post-submission field passing | Test example: Prepare 10 desktop terminal support input samples, covering fully filled forms, missing required items, and canceled operations | Compare input and node output to verify whether subsequent nodes receive corresponding fields; result thresholds are determined by actual tasks |
| External implementation item: Form submission timeout | Must be implemented separately by the external system; test example value is 300 seconds | Adapt to fault troubleshooting scenarios, avoid interrupting the submission process midway |
| External implementation item: Third-party endpoint verification | Must be implemented separately by the external system; configured to have the external system or subsequent nodes perform synchronization verification of baseURL and model list after selecting a third-party endpoint | Avoid issues where configured endpoints do not match displayed models |
| External implementation item: Prompt binding | Must be implemented separately by the external system; associated with the pre-session interaction link | Ensure custom prompts take effect before AI invocation |
Three Common Misconfigurations
- After adding a custom plugin in a workflow, no input or output parameters are displayed, and no error logs are generated. The cause is that the output mapping of the corresponding interaction node was not correctly bound in the plugin configuration, causing the front end to fail to recognize the parameter structure.
- After configuring loop execution, array elements cannot be traversed correctly. The cause is that the input parameter of the loop body was not set to receive externally passed array-type data, causing abnormal traversal trigger logic.
- Custom prompts do not take effect in Ollama model sessions. The cause is that prompt configuration was only set in the global system settings and not associated with the pre-session interaction link of the current session.
How to Confirm Configuration Is Complete
- When submitting a blank form, trigger required field verification prompts to confirm that the required configuration of
formInputtakes effect. - After selecting a third-party endpoint, have the external system or subsequent nodes verify the consistency between the model list and baseURL to confirm that the endpoint verification configuration takes effect.
- After configuring loop execution related parameters, pass a test array, have the external system or subsequent nodes execute the array traversal logic, check whether the workflow triggers sessions as expected, and confirm that the loop logic is working correctly.
- After entering a custom prompt and initiating a session, check whether the AI reply matches the prompt requirements to confirm that the prompt binding configuration takes effect.
The values given are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.