What this category of data looks like
Typical documents include full campaign plans, targeted audience tag lists, budget scheduling tables, and conversion tracking configuration fields. Data sources include advertising platform APIs, user profile datasets, internal budget sheets, and attribution tool logs. Update frequency follows daily synchronization, or full updates when a single campaign starts. Most fields are enumerated targeting tags, numeric budget values, and boolean conversion switches. Individual document lengths vary widely, with no unified fixed format specification.
Constraints for Model Integration and Configuration
Compliance review data for campaign setup comes from multiple dispersed sources. Model integration must support unified parsing and integration of multi-source data. Document lengths vary widely. Dynamic context length configuration is required to avoid truncation of key compliance items. Update schedules are flexible. Real-time or scheduled data source synchronization configuration must be supported to ensure review data timeliness. Compliance review must match the compliance verification logic of advertising platforms. Tool call rules must be configured to link with compliance verification APIs, ensuring review results meet platform requirements.
How to Set Configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to varying campaign document lengths, avoiding compliance item omissions due to context truncation |
maxTokens | 2000–3000 token | Controls the output length of compliance review results, matching return limits of advertising platform APIs |
quoteMaxToken | 1500 token | Limits the length of referenced original document fragments, ensuring compliance review basis is clear and traceable |
toolChoice | auto | Automatically triggers compliance verification tool calls, adapting to verification needs for multiple types of compliance items in campaign plans |
temperature | 0.1–0.3 | Reduces output randomness, ensuring compliance review results align with fixed rules of advertising platforms |
AIPROXY_API_TOKEN | Must match and be non-empty with the administrator token configured for the AI Proxy server | Environment variable deployed for the App/Admin server, used for identity verification between the server and AI Proxy service. Must not be entered on the model configuration page |
Three Common Configuration Mistakes
- Symptom: Compliance review does not trigger reranking models, and returned results are not sorted by compliance priority. Cause: The
quoteMaxTokenormaxContextparameter is not configured, causing context to be too long and truncated, so the reranking model is not called. - Symptom: The default called model does not match the configured one, and compliance review results are not as expected. Cause: Default model parameters are not set consistently in global configuration and application configuration.
- Symptom: The model outputs compliance thinking content but does not return a formal review conclusion. Cause: The
maxTokensparameter is set too low, causing output to be truncated early.
How to Verify Successful Configuration
- Log in to the FastGPT v4.17.0 backend, enter the model configuration page of the corresponding application, and check that set parameters such as
maxContextandmaxTokensmatch the recommended values in the configuration table. - Upload a complete campaign plan document including targeting settings and budget scheduling, trigger compliance review, and verify that no context truncation prompt appears in the returned results.
- Simulate an API call request, check the returned log information, and confirm that the
toolChoiceparameter triggers a call to the compliance verification tool. - Modify the
temperatureparameter to 0.5, compare the differences between the two review results, and confirm that output randomness meets business requirements.
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.