What this category of data looks like
Data for this category comes primarily from ad platform APIs, internal user profile libraries, budget scheduling tables, and attribution tools. Core daily deliverables include campaign plans, targeting setting rules, budget scheduling tables, and conversion tracking configuration items. Data updates occur daily, or when a single campaign is launched. Core fields include target audience dimensions, daily budget amount, conversion event code, and delivery time slot parameters. Common units are yuan, impressions, hours, and similar.
What constraints do these characteristics impose on forms and interactions
Scattered data sources require cross-tool synchronization. Forms must support field linkage validation across multiple data sources. This prevents format errors from manual data entry. Flexible update rhythms require forms to support switching between temporary editing and batch saving. This fits update needs for single campaigns or daily syncs. Core fields include three strongly linked sets: target audience, budget amount, and conversion event. Any abnormal field will prevent campaign launch. So interactions must include dependency validation rules between fields. Document structures are layered. Forms must match the document hierarchy. This avoids confusing field levels and reduces filling efficiency.
How to configure settings
The following configurations apply to the campaign setup scenario. Some functions must be implemented by external business systems or downstream nodes.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Form input node formInput | Test example: Select 3 fields from campaign setup as required inputs. Actual fields are determined by the task. | This node collects user input. When required fields are missing, check interaction status. This prevents downstream nodes from receiving incomplete input. |
User selection node userSelect | Test example: Set 2 business options. Verify corresponding branches one by one. | This node handles user selection. Querying and filtering records related to campaign setup must be implemented by downstream interfaces or external systems. |
| Field passing after submission | Test example: Prepare 10 campaign setup input samples. Cover full completion, missing required fields, and cancel operations. | Compare input and node output. Verify if downstream nodes receive the correct fields. Result thresholds are determined by the actual task. |
| External implementation item: Auto-save interval | Must be implemented separately by external systems. External business systems or downstream nodes implement auto-save logic. Recommended approach: 300 seconds. Test external auto-save logic after setup. | This fits daily sync or campaign launch update rhythms. It prevents loss of edited content. |
| External implementation item: Field validation rules | Must be implemented separately by external systems. External business systems or downstream nodes implement field linkage validation. Recommended approach: Validate the relationship between budget and targeting. Test validation logic after setup. | Abnormal strongly linked fields will prevent campaign launch. Validation intercepts errors early. |
| External implementation item: Batch edit entry | Must be implemented separately by external systems. External business systems or downstream nodes configure the batch edit entry location. Recommended approach: Place at a fixed position at the top of the page. Test external batch edit logic after setup. | This matches the batch adjustment needs of budget scheduling tables. It improves operational efficiency. |
Three common configuration mistakes
- External business systems or downstream nodes configure file format and size limits for FastGPT's
formInputnode. Uploading non-table files causes parsing failure, with a file format mismatch prompt. The root cause is that supporting documents for campaign plans are mostly budget tables and targeting rule files. Unrestricted formats allow invalid files to consume resources. - External business systems or downstream nodes configure tag validation logic for FastGPT's
userSelectnode. Manually entered target audience dimensions do not comply with ad platform specifications. This causes campaign launch failure after submission. The root cause is failure to match the ad platform's preset tag library, leading to abnormal field formats. - After adding a custom plugin node in a FastGPT workflow, external business systems or downstream nodes do not configure input and output parameters. During campaign setup testing, the plugin cannot be called to complete conversion event validation. The interface shows no parameters and no error logs.
How to verify correct configuration
- Upload a test budget scheduling table. After FastGPT's
formInputnode collects the file, external business systems or downstream nodes check if file content is correctly identified and passed to corresponding downstream nodes. - Select preset targeting tags. After FastGPT's
userSelectnode receives the selection, external business systems or downstream nodes verify if the budget amount validation rule is updated accordingly. - Edit the form and wait 300 seconds. External business systems or downstream nodes check if edited content is saved per the configured auto-save logic.
- Add a custom plugin node in a FastGPT workflow. External business systems or downstream nodes configure input and output parameters. Confirm that parameters are correctly displayed in the configuration interface.
The values provided here are common starting points. They 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.