What the Data for This Category Looks Like
Data sources for this category include advertising platform backends, customer qualification systems, contract systems, and publicly available regulatory rules. Update frequency is once per campaign or monthly. Daily documents fall into four categories: advertising review forms, qualification attachments, delivery records, and rectification notices. Core fields include compliance subject information, delivery cycle, qualification number, and rectification status.
Advertising platform compliance teams, agency legal teams, and brand marketing teams maintain data daily. The most time-consuming steps are qualification archiving and delivery record organization. Missing or incomplete data leads to consequences including insufficient evidence during regulatory inspections, customer liability claims, and account penalties. The core difference from the advertising material review category is a focus on evidence preservation across the entire review and delivery workflow.
How These Characteristics Impose Constraints on Forms and Interactions
Multiple data sources require configuring read-only fields linked to different systems via external business systems or subsequent workflow nodes. This avoids duplicate entry and data inconsistency.
Fixed update frequencies require configuring trigger-based or scheduled data synchronization mechanisms via external systems or subsequent workflow nodes. This ensures timeliness of compliance evidence.
Multiple document types require configuring field groups sorted by document category via external business systems or subsequent workflow nodes. This adapts to entry rules for different fields.
Strict compliance consequences require pairing external verification logic and subsequent nodes to implement required field verification and operation record-keeping. This prevents missing core evidence.
The difference from material review requires forms to focus on delivery-related evidence fields. Forms do not need to cover material creative content.
The professional attributes of job users require configuring concise interaction processes via external business systems or subsequent workflow nodes. This reduces unnecessary configuration steps.
How to Set Configurations
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Form input node formInput | Test example: Select 3 required input fields from advertising compliance record-keeping fields; actual fields are determined per task | This node collects user input. Check interaction status if required fields are missing, 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. Query and filtering of advertising compliance record-keeping related records must be implemented via subsequent interfaces or external systems |
| Post-submission field passing | Test example: Prepare 10 advertising compliance record-keeping 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 per actual task |
| External implementation item: Data source association configuration | Must be implemented separately by external systems. Associate read-only data sources from advertising platform backends and customer qualification systems, with no more than 5 fields per single association | Match the data source scope of this category, avoid excessive associations leading to slow loading |
| External implementation item: Field verification rules | Must be implemented separately by external systems. Use external storage systems or subsequent nodes to handle size verification for qualification attachment fields, with a recommended limit under 1000 MB | Comply with storage specification examples for compliance document attachments in this test, avoid over-limit storage |
| External implementation item: Submission record-keeping configuration | Must be implemented separately by external systems. Use subsequent workflow nodes or external business systems to record operator, operation time, and modified version number | Meet audit requirements for compliance record-keeping, enable traceability of data changes |
Three Common Misconfigurations
- When using the user selection node
userSelect, select configured options one by one to verify whether the workflow enters the corresponding branch. For advertising compliance record-keeping record filtering, additionally verify the input, permissions, and return values of the external interface. - Phenomenon: An
Invalid array lengtherror occurs when configuring aformInputnode with multiple data source associations. Cause: The data format of the qualification attachment field does not meet the requirements of subsequent nodes. Passing an empty array when the field has no data triggers verification failure. - Phenomenon: After setting a session-level selection process, the selection status resets every time the page is refreshed. Cause: External session storage or workflow status recording is not configured, leading to selection results not being retained within the session cycle.
How to Verify a Successful Configuration
- Open the form editing page, check whether the required fields of the
formInputnode include core compliance elements such as delivery date and qualification number. - Test whether the options of the
userSelectnode match the advertising compliance subject types, and whether selections can be saved normally to the form configuration. - Trigger the externally configured data source synchronization operation, check whether the latest delivery record data can be pulled from the advertising platform backend, with no error prompts.
- Simulate form submission, check whether operation record-keeping records are generated, and whether the data format complies with the storage requirements of compliance documents.
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.