What Data for This Category Looks Like
The data for this category originates from advertising platform backends, customer qualification documents, contract systems, and publicly available regulatory rules. Four core document types are processed daily: advertising review forms, qualification attachments, delivery records, and rectification notices. Unlike advertising material review scenarios, this use case focuses on retaining review and delivery evidence. Content filtering alone cannot meet the compliance requirements of this scenario. Data updates are completed per individual advertising campaign or monthly cycle. The most time-consuming steps include qualification archiving, delivery record retention, and rectification evidence organization. Data fields include advertising delivery periods, compliance review status, qualification validity periods, rectification completion deadlines, and other items. No unified fixed unit requirements apply; values vary based on the business attributes of each individual document.
Constraints Imposed by These Characteristics on Model Integration and Configuration
This document applies to FastGPT v4.17.0 model integration configuration. Dispersed data sources require model integration to adapt to interface specifications across multiple business systems. The required AI Proxy environment variables AIPROXY_API_ENDPOINT and AIPROXY_API_TOKEN must be configured in the App/Admin server. Document types include structured tables, attached images, and plain text records. Corresponding visual processing parameters must be configured for image-based qualification files. Data update cycles fluctuate per campaign or monthly. The maxTokens value for single calls must be limited to avoid exceeding interface quotas. Evidence requirements for compliance logging cannot be omitted. The model call context must cover all relevant documents to prevent missing key review nodes.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
AIPROXY_API_ENDPOINT | Enter the root address of the AI Proxy service, for example http://aiproxy:3000. Do not append /v1 or other interface paths, and do not use single-model service addresses | Required environment variable for AI Proxy, provides the AI proxy service access address for the App/Admin service |
AIPROXY_API_TOKEN | Enter the administrator token consistent with the AI Proxy server configuration, and the value cannot be empty | Required environment variable for AI Proxy, used for identity verification with the AI Proxy service |
maxTokens | 8000–12000 token | Adapts to the total length of all documents for a single month or campaign, avoiding exceeding interface call quotas |
temperature | 0.1–0.3 | Reduces output randomness, ensures accurate and consistent evidence descriptions for compliance logging, and avoids generating irrelevant content |
maxContext | Calibrated via actual testing | Covers all relevant review, delivery, and rectification documents, ensuring the model can associate the complete evidence chain |
Three Common Configuration Mistakes
- A 404 status code (no response body) is returned when clicking the model test button. The cause is incorrect configuration of the AI Proxy server environment variables
AIPROXY_API_ENDPOINT(failure to use the AI Proxy service root address, or appending extra paths such as /v1) orAIPROXY_API_TOKEN(token inconsistent with AI Proxy server configuration, or empty value). - Only reranking models are displayed in the channel model list after deploying the FastGPT commercial edition. The cause is failure to enable the general large language model access switch in system configuration, or failure to configure full model access permissions for the corresponding key.
- OneAPI-related configuration fails identity verification. The cause is failure to reset the username and password via the compliance logging-specific account management process, or failure to bind the key to the permissions of the corresponding business system.
How to Confirm Successful Configuration
- Manually call the configured
AIPROXY_API_ENDPOINTaddress (for example http://aiproxy:3000) to verify that the AI Proxy service responds normally. - Upload a single advertising review form and qualification attachment to test that the model can correctly identify and associate core document fields.
- Trigger a simulated compliance logging workflow to confirm that the model's output evidence description covers all relevant business nodes.
- Check the model list on the system configuration page to confirm that the target large language model is displayed normally in the selectable channel list.
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.