What this category's data looks like
Business data for search ad keyword management primarily comes from search ad backends, search term reports, bidding ranking data, and landing page data. Updates run on a daily or weekly schedule. Commonly used documents include structured keyword lists, negative keyword tables, bid records, and search term reports. Data fields include keyword text, match type, bid amount, negative keyword rules, search volume metrics, and more. Most files use table-based structured formats for daily keyword optimization and strategy adjustments.
Constraints on HTTP interfaces and external systems
The multi-source nature of category data requires HTTP interfaces to adapt to authentication and return formats of different ad backends. Unified docking logic must be implemented to reduce maintenance costs. The daily or weekly update schedule limits interface call frequency. High-frequency requests that trigger rate limits from external ad platforms must be avoided. The structured data format requires fields returned by interfaces to strictly align with category document fields, to facilitate subsequent data analysis and model processing. Failures directly cause business losses including invalid clicks and brand term takeover. Therefore, interface exception handling and retry mechanisms must have sufficient robustness.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer <application-specific API Key> | Complies with authentication standards for external ad APIs, and follows FastGPT application API call specifications |
variables | {"ad_platform": "baidu", "update_cycle": "daily"} | Passes category-specific business parameters to adapt to interface logic of different ad backends |
responseData | Extract keyword, match type, bid amount, and negative keyword status fields | Aligns with the structured document format of category data to facilitate subsequent model processing |
| HTTP request timeout setting | 30-60 seconds | Adapts to average response delays of ad backend interfaces, avoids frequent timeouts that trigger rate limits |
| Failed retry count | 2-3 times | Addresses temporary network fluctuations in ad backends, avoids business exceptions caused by repeated submissions |
Three common mistakes
- Symptom: External ad API call returns 401 Unauthorized error. Cause: The AI Proxy admin Token is mistakenly used as the authentication value for the
Authorizationparameter, instead of the application-specific API Key. - Symptom: Workflow API calls cannot continue context conversations. Cause: The
variablesparameter does not correctly configure the chatId passing rule, so session state cannot be persisted. - Symptom: Frequent external interface rate limits are triggered during bulk keyword data synchronization. Cause: No reasonable request interval and timeout time are set, and too many interface requests are initiated in a short period.
How to confirm the configuration is correct
- Check that the
AIPROXY_API_ENDPOINT(root address of the AI Proxy service) andAIPROXY_API_TOKEN(AI Proxy admin Token) environment variables on the FastGPT v4.17.0 server are correctly configured, with no/v1or other path suffixes attached. - Initiate a single test call to confirm whether the
responseDataaccurately extracts core fields required by the category, including keywords and match types. - Verify that the
Authorizationparameter uses the application-specific API Key, and no other types of authentication tokens are used. - Simulate bulk data synchronization requests to confirm that the interface does not trigger rate limit errors under reasonable intervals.
The values provided 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.