What the data for this use case looks like
The business data for information feed ad creative testing mainly comes from advertising platforms, material libraries, user interaction data, and conversion data. Update frequencies are mostly daily or weekly. Daily supporting documents include creative scripts, material test sheets, delivery data reports, and iteration checklists. Core fields include creative combinations (images/videos/copy), test batches, click-through rates, conversion costs, and violation flags. Core work for this use case revolves around creative variable design, material fatigue judgment, and test conclusion summarization. Both data and documents support effect verification and rapid iteration of creative combinations.
What constraints these characteristics impose on HTTP interfaces and external systems
The business characteristics of information feed ad creative testing impose multiple constraints on the HTTP interfaces and external systems link. Multi-source data docking requirements require interfaces to adapt to return formats of external systems such as advertising platforms and material libraries. Parameter passing must accurately match the field rules of different data sources. Daily or weekly update frequencies require interface synchronization to match the business rhythm. This prevents overly frequent requests from triggering rate limits, or too slow synchronization from causing test data lag. Creative testing document field requirements require interfaces to pass standardized creative variable parameters. This ensures consistency between test configurations and document content. Rapid iteration business requirements require interfaces to support interrupting model generation. Interfaces must also be compatible with access configurations for external large model APIs.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | A key string prefixed with Bearer | Complies with FastGPT API identity verification specifications, ensuring valid interface call permissions |
variables | Pass image IDs, copy content, test batch IDs for creative combinations | Matches fields in creative scripts and material test sheets, passing standardized test parameters |
responseData | Return only click-through rate, conversion cost, and violation flag fields | Filters redundant data, adapts to field requirements of delivery data reports, reduces data transmission volume |
| Interface timeout period | 600 seconds | Matches the daily data synchronization rhythm of creative testing, preventing valid test requests from being interrupted by short timeouts |
| Retry mechanism | Retry 2 times after failure, with a 30-second interval | Addresses temporary fluctuations in advertising platform interfaces, reducing the risk of test interruptions |
| Interrupt generation switch | Enabled | Supports rapid switching of test variables, adapting to rapid adjustment needs for creative iteration |
Three common configuration mistakes
- Phenomenon: When sending test requests consecutively, subsequent requests cannot interrupt the previous model generation process, and the returned results still contain content from the previous request. Cause: The FastGPT interrupt generation configuration is not enabled, or the correct session identification parameter is not included in the request.
- Phenomenon: The
responseDatafield returned by the interface is empty, and delivery effect data cannot be obtained. Cause: TheresponseDataparameter is not configured correctly, and the required core business fields are not specified, causing the interface to filter all returned content. - Phenomenon: Calling an external large model API returns an identity verification failure with a status code of 401. Cause: The
Authorizationparameter is not configured correctly, or the external large model access switch is not enabled in FastGPT v4.17.0.
How to confirm the configuration is correct
- Send a test request carrying the
variablesparameter, check whether the returned results contain the passed creative combination fields, confirming that parameter passing is correct. - View the interface response log, confirm that the
Authorizationparameter verification passes, and there are no 401-level identity errors, ensuring normal interface permissions. - Send two consecutive test requests, verify that the subsequent request can trigger the interruption of the previous generation process, confirming that the interrupt configuration is effective.
- After connecting to an external large model API, call the interface to confirm that the returned results conform to the response format of the corresponding model, verifying that the external access configuration is correct.
The values provided here 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.