What This Category’s Data Looks Like
The core data for this category 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. Fields cover level ID, path node coordinates, prop placement positions, feedback severity levels, version numbers, and modification records. Data updates follow a weekly or single version iteration cycle. The size of single-submission level resource packages and test data fluctuates based on level complexity.
Constraints on Deployment and Upgrade
Data for this category is multi-source and updated frequently with version iterations. The deployment process must support access from multiple data sources such as level editors and art resource libraries. It must also support binding and associating version submission records with deployed versions. Fluctuations in the size of single-submission level resource packages and test data require deployment configurations to reserve sufficient storage and bandwidth margins. Frequent version update requirements demand upgrade processes that support rapid rollbacks and incremental deployments, to avoid interrupting level editing and online testing. Additionally, integration requirements with test feedback and defect systems require pre-configured connection parameters for external systems.
Configuration Settings
This page applies to FastGPT v4.17.0. The following configuration items are formulated based on the deployment specifications of this version.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 200–300 connections | Matches peak concurrent access demand from multi-source data for level content creation teams, adapts to concurrent pressure from weekly version updates |
MONGODB_URI | mongodb://username:password@host:port/database?authSource=admin | Stores unstructured data such as level design drafts and version submission records, supports flexible storage for multiple document types |
REDIS_URL | redis://:password@host:port/0 | Caches real-time level editing status and test feedback forms, reduces concurrent access pressure on the core database |
STORAGE_S3_ENDPOINT | Set based on actual testing | Adapts to storage paths for art resource libraries, matches upload and download bandwidth requirements for level resource packages |
FILE_TOKEN_KEY | 32-character random string | Secures access to level resource upload interfaces, prevents unauthorized resource submissions |
FE_DOMAIN | https://your-custom-domain.com | Binds the frontend access address for the level editor, unifies frontend resource loading and redirection paths |
Three Common Configuration Mistakes
- Symptom: An "offset out of range" error appears when uploading large level resource packages or test data PDFs near the end of the upload progress. Cause: Incorrectly configured file upload chunk parameters or storage session validity period, leading to mismatched chunk checksums or session timeouts during large file uploads.
- Symptom: Unable to pull specified images during local Docker deployment, with pull timeout or image not found errors. Cause: Incorrectly configured image repository access address, or no external network access permission enabled for the deployment environment.
- Symptom: The [Text Processing] module does not appear in the backend management interface after deployment, making it impossible to configure text cleaning or formatting rules for level content. Cause: Corresponding plugins were not loaded in startup parameters, or the backend was logged into with incorrect
ROOT_KEYpermissions, resulting in hidden functions.
How to Verify Successful Configuration
- Run an image pull test to verify that the configured image repository address can be accessed and required images can be pulled normally.
- Upload a small test file to confirm that the file upload process has no errors and resources can be properly stored in the configured storage path.
- Log into the backend using
ROOT_KEYpermissions to confirm that the [Text Processing] module is displayed in the function list. - Check real-time monitoring logs to confirm that database and cache service connection status is normal, with no abnormal disconnections.
The values provided here are common starting points, and should be evaluated against the user’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.