What this category of data looks like
This category of data originates from customers’ historical business systems, CSV or Excel templates, database export files, and execution records of data import workflows. Daily associated documents include data import templates, migration implementation plans, field mapping comparison tables, and migration verification reports. Update frequency shifts irregularly for each individual project. Implementation participants include implementation consultants, data implementation engineers, and customer IT liaisons. Core data covers three types: business fields, association relationships, and historical operation records. No unified fixed field unit requirements apply. Configurations must match the field rules of the customer’s original system. This document is based on the form interaction configuration logic of FastGPT v4.17.0.
What constraints these characteristics impose on the "Forms and Interactions" link
Data sources are diverse and lack unified formats. This requires the formInput node to support collecting multiple types of data source files uploaded by users. Subsequent nodes can be configured with a visual interaction interface for field mapping. Update frequency adjusts per project. This requires an external configuration management module to support temporary saving and batch reuse of mapping configurations. Duplicate configuration of import rules for similar customers must be avoided. Daily documents include field mapping tables. This requires an external implementation interface to support import, export, and batch editing of mapping rules. Implementation participants include non-technical customer liaisons. This requires lowering the professional threshold for operating the formInput node. It also requires retaining configuration verification capabilities through the external implementation interface to proactively avoid issues such as field misalignment and data loss.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Form input node formInput | Test example: Select 3 fields from customer data import migration as required inputs. Actual fields are determined per task. | This node collects user input. Check interaction status when required fields are missing, to prevent subsequent nodes from receiving incomplete input. |
User selection node userSelect | Test example: Set 2 business options, check corresponding branches one by one. | This node handles user selection. Queries and filtering of records related to customer data import migration must be implemented by subsequent interfaces or external systems. |
| Field passing after submission | Test example: Prepare 10 input samples for customer data import migration, covering full completion, missing required fields, and canceled operations. | Compare input and node output to verify whether subsequent nodes receive corresponding fields. Result thresholds are determined per actual task. |
| External implementation item: Field mapping rule configuration | Must be implemented separately by external systems. Configure through the external implementation interface, support batch editing of mapping relationships. | Match daily used field mapping table documents to lower implementation barriers. |
| External implementation item: Field verification configuration | Must be implemented separately by external systems. Configure required field verification rules through external business systems or subsequent nodes. | Prevent empty core business fields after import. |
| External implementation item: Import failure retry configuration | Must be implemented separately by external systems. Configure retry rules in external workflows or subsequent nodes. Recommended retry count is 3 times, interval 60 seconds (test example value). | Address scenarios of temporary network fluctuations or temporary unavailability of data sources. |
Three common mistakes
- Phenomenon: A connection error prompt appears after submitting an import, and recovery fails even after enabling a proxy. Verification steps: Check the data source access whitelist configuration, verify whether the customer’s own database connection parameters are correctly passed to subsequent nodes.
- Phenomenon: Some business fields are empty after import, and the field mapping table shows that configuration has been completed. Verification steps: Verify whether the single-batch import size matches the single-read limit of the customer’s data source, check whether subsequent nodes fully load field data.
- Phenomenon: The migration verification report shows that the number of data entries differs from the source system, and no clear error is displayed. Verification steps: Check whether external business systems or subsequent nodes have configured dirty data filtering logic, verify the effective data entry statistics rules for imported data.
How to confirm that configurations are correctly set
- Upload a small test data sample to the
formInputnode, verify whether the fields identified by subsequent nodes match the preset field mapping table. - Simulate a single small-batch import, check whether subsequent node records include complete field format verification and data loading logs.
- Configure external retry rules, manually disconnect the data source connection, verify whether the preset retry logic is triggered.
- Save the current mapping configuration as a template through the external configuration management module, import another same-type data set, verify whether the mapping rules are fully reused.
The values provided here are common starting points, and should be evaluated 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.