What data this category includes
Data for this category comes from the national land spatial planning unified map, project approval and supervision platform, land use status database, and ecological protection redline data, with irregular update frequency. Daily processed documents include land pre-examination and site selection opinions, construction land planning permits, construction engineering planning permits, redline diagrams, and planning conditions. Most documents contain structured fields such as project site selection scope, land use scale, and planning control requirements, alongside supporting vector graphic files. The data is linked to the full project approval cycle, with no fixed batch update cycle.
What constraints these characteristics impose on deployment and upgrade
Data sources for this category are scattered and connected to multiple business systems. Deployment must support unified access to multi-source heterogeneous data and permission isolation. Documents include vector graphics and structured text, so deployment requires configuring storage and indexing rules tailored to vector files. Since data updates have no fixed cycle, deployment must support incremental synchronization configuration to prevent excessive system resource usage from full re-imports. Business link errors carry severe consequences, so deployment must reserve performance tuning space and a fast rollback mechanism to ensure stable approval processes.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | Dedicated business database connection string, set maximum connection pool size to 100 | This category's data links to multiple business systems, requiring isolation of business data from general data to avoid connection resource competition |
STORAGE_S3_ENDPOINT | Endpoint address of the internal vector file storage service | This category includes vector files such as redline diagrams, requiring a dedicated storage service to ensure efficient file reading |
REDIS_URL | Configure cache connection with a 600-second timeout | Irregularly updated data needs cached query results to reduce repeated request pressure on the business database |
DB_MAX_LINK | 80–120 | This category's documents include structured and vector content, requiring a balance between concurrent parsing and storage connection usage |
FE_DOMAIN | Official domain name of the internal approval platform | Ensure generated document links point to the internal compliant system |
FILE_TOKEN_KEY | Unified secret key prefix for internal systems | Ensure uploaded project documents can only be accessed by authorized processes |
Three common configuration errors
- A slow operation timeout error appears in logs when parsing knowledge base files after deploying Docker containers. This happens because the storage endpoint tailored for vector files is not configured, causing request timeouts during parsing of large redline diagrams.
- No available channels display on the OneAPI page after deployment. This occurs because the
ROOT_KEYpermission is not configured correctly, or internal service link connectivity checks are not completed. - Deployment cycles are extended because offline deployment resources are not prepared in advance. This happens because the matching version of Docker images and dependent resources are not pulled, and adaptation to the internal network isolation environment is not finished.
How to confirm configuration is complete
- Log in to the FastGPT backend, view storage configuration items, confirm
STORAGE_S3_ENDPOINTpoints to the internal vector storage service, and that test redline diagram files can be uploaded normally. - Navigate to the knowledge base management page, initiate an incremental synchronization test, confirm data synchronization has no timeout errors, and that it aligns with the timeout requirements set in the
REDIS_URLconfiguration. - Check the OneAPI page, confirm corresponding channel permissions are configured, and that test document drafting interface call links can be generated normally.
- View MongoDB connection logs, confirm connection pool connection counts do not exceed the threshold set by
DB_MAX_LINK, and that there are no abnormal connection accumulations.
The values provided are common starting points and should be measured against the operator’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 2026-09-28.