What data looks like for this category
This category of data primarily comes from level editors, art resource libraries, player test data, and defect systems. Daily produced documents include level design drafts, resource requirement sheets, test feedback forms, and version submission records. Common fields include level number, resource path, test node identifier, defect severity, and submission version number. Data update frequency follows weekly or per-version submission cycles. Content focuses on specific map layouts, task workflows, and resource configurations.
What constraints these characteristics impose on model integration and configuration
The weekly or version-level update rhythm requires model context length to adapt to incremental content within a single cycle. This prevents frequent truncation of core design information. Mixed input requirements for multiple document types require configuration to support materials with different field structures, such as level design drafts and test feedback forms. The specific attributes of individual maps and task implementations require model output to link to specific level nodes, avoiding generic descriptions. Content errors can cause launch delays, so configure stable retry and error capture mechanisms. This configuration applies to FastGPT v4.17.0.
How to set the configuration
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the cumulative content volume of weekly-updated level design drafts and test feedback forms, avoiding context truncation |
maxTokens | 2000–3000 token | Meets the output length requirement for compliance review results, ensuring complete presentation of key judgment conclusions |
temperature | 0.1–0.3 | Ensures stability of compliance judgments, reducing the impact of randomized output on review results |
vision | Enabled | Supports parsing image-based art resource layouts and scene details in level design drafts |
AIPROXY_API_ENDPOINT | Enter the root address of the AI Proxy service, for example http://aiproxy:3000. Do not append /v1 or individual model service address paths | Required environment variable for FastGPT App/Admin server, used to route AI Proxy requests |
AIPROXY_API_TOKEN | Enter the administrator token matching the AI Proxy server configuration, and the value cannot be empty | Required environment variable for FastGPT App/Admin server, used for AI Proxy call identity verification |
Three common configuration errors
- No return results when calling the review function. Troubleshooting step: Check if
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare configured correctly. These variables are required environment variables for the FastGPT App/Admin server. Missing configuration triggers service startup verification failure or large model call link exceptions. - Request error occurs when uploading PDF level design draft files. Cause: The
visionconfiguration item is not enabled, so embedded art resource layout images in the PDF cannot be parsed. - Abnormal node ID error appears during review in the chat interface. Cause: The value of
maxContextis too small, causing context overflow and triggering internal node errors.
How to confirm the configuration is complete
- After confirming that the FastGPT App/Admin server has correctly configured the
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENenvironment variables, initiate a test call to check if preliminary compliance review results can be returned. - Upload a screenshot of a level design draft to verify that the
visionconfiguration works normally, and whether resource layout information in the image can be parsed. - Adjust
temperatureto the preset low value range, call the same review task multiple times, and check if the output results remain consistent. - Submit a collection of weekly updated level documents to verify that
maxContextcan fully load all content without truncation prompts.
The values provided here are common starting points, and 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.