What Data for This Category Looks Like
Data for this category primarily originates from art asset libraries, project management systems, engine resources, and outsourced delivery packages. Daily maintained documents include art requirement sheets, asset specification tables, outsourced feedback forms, and acceptance records. Core fields cover asset ID, specification parameters, delivery time, acceptance status, and other relevant details. Data update frequency is mostly daily or weekly. It covers the full lifecycle management of art resources including characters, scenes, and special effects, and supports daily work for art PMs, original artists, 3D artists, and outsourced project managers.
What Constraints These Characteristics Impose on Deployment and Upgrade
Because data sources are scattered and include large-volume outsourced delivery packages and engine resources, deployment requires configuring permissions for multiple data source connections and adapting to large-capacity storage. Frequently updated asset data requires ensuring stability of incremental synchronization during upgrades to avoid interrupting business processes. Different types of art documents need matching dedicated parsing rules; otherwise, field extraction will fail. Errors from mismatched resources or missing version materials directly impact research and development progress. Therefore, the deployment and upgrade link must reserve configuration space for resource verification and version rollback, and must not interfere with the engine resource import process. During upgrades, follow the official update workflow: first back up core data and storage files, then perform code pulling and configuration updates to ensure team edition functions and the ticket system operate normally.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | Art asset data has high read/write frequency; avoid exhausting database connections to prevent business disruption |
MONGODB_URI | Dedicated connection string within a private network | Stores core business data such as asset metadata and acceptance records; ensures access security |
PG_URL | Configure private connection string as needed | Alternative to MongoDB; adapts to database migration requirements for private deployments |
STORAGE_S3_ENDPOINT | Corresponding cloud storage service provider node address; set single file maximum size to 1000 MB | Stores large-volume files such as outsourced delivery packages and engine exported resources; meets art asset storage requirements |
FE_DOMAIN | Enterprise internal operations portal domain name | Allows art-related personnel to access internal ticket and asset management interfaces; unifies business entry points |
ROOT_KEY | Configure team management permission key as needed | Enables locally deployed team edition functions for art teams to share assets and tickets |
FILE_TOKEN_KEY | 32-byte key, calibrated via actual testing | Verifies access permissions for art asset files; prevents unauthorized access to outsourced delivery resources |
Three Common Misconfigurations
- Symptom: Core fields appear empty after art assets are imported. Cause: No dedicated parsing rules are configured for art requirement sheets and asset specification documents, leading to failure to extract standardized fields.
- Symptom: MongoDB connection timeout errors occur after an upgrade. Cause: The
DB_MAX_LINKparameter was not adjusted to match the high-frequency read/write demands of art assets, and the default connection count is insufficient after the upgrade. - Symptom: Outsourced delivery packages cannot be synchronized to the art asset library. Cause: No storage access permissions corresponding to
STORAGE_S3_ENDPOINTwere configured, resulting in failed large file uploads.
How to Confirm Configurations Are Properly Set
- Log in to the FastGPT v4.17.0 backend, check the connection status of
MONGODB_URIorPG_URL, and confirm there are no abnormal error logs. - Upload a standard art asset specification document to verify that the completeness of core fields after parsing meets preset requirements.
- Trigger an incremental synchronization task to confirm that outsourced delivery packages can be normally synchronized to the specified storage path.
- Check the version tag of the locally deployed FastGPT code to confirm it matches the target version, such as via the git tag or git log command.
The values listed above 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.