What the data for this category looks like
This category uses four main data sources: the national land and spatial planning one-map system, project approval and supervision platform, current land use database, and ecological protection redline data. Updates occur on an irregular schedule. Updates are synced with project approval progress or land and spatial planning adjustments.
Daily business documents include land use preliminary review and site selection opinion, construction land planning permit, construction engineering planning permit, redline drawings, and planning conditions. Core fields cover project site selection coordinates, land use scale, planning control boundaries, pre-approval requirements, etc. There are no unified fixed units. Matching must be done according to the land and spatial planning standards of the project’s location.
What constraints these characteristics impose on the deployment and upgrade link
This deployment configuration follows the standard process of FastGPT v4.17.0. Multiple scattered data sources require permission verification rules for multi-source data access during deployment. Only authorized roles can access sensitive data such as the land and spatial planning one-map system. Irregular update frequency requires adapting dynamic data synchronization mechanisms during upgrades. This avoids Q&A result deviations caused by delayed data updates. Large differences in business document structures require dedicated parsing rules for different document types during deployment. This ensures unstructured documents such as redline drawings and planning conditions can be correctly extracted. Severe consequences of errors require retaining a rollback mechanism during the upgrade process. This prevents approval assistance functions from being interrupted due to deployment abnormalities.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 10–15 | Adapt to the concurrent access needs of multi-source business data, avoid data query timeouts caused by insufficient connection count |
REDIS_URL | redis://localhost:6379/0 | Used to cache frequently queried planning control rules and project approval status, reduce backend database pressure |
STORAGE_S3_ENDPOINT | Fill in according to the local object storage service address | Used to store uploaded business documents such as redline drawings and planning conditions, ensure file sharing in multi-node deployments |
FILE_TOKEN_KEY | 32-bit random string | Used to generate access tokens for business documents, ensure only authorized users can view sensitive planning data |
| Single search limit | Top 8 entries | Match the number of planning control items that need to be checked for a single project review in land use preliminary review business, ensure retrieval results cover core requirements |
| Maximum context | 8000 token | Adapt to the content length of combining party building learning Q&A and business documents, avoid exceeding the model’s processing limit |
Three common mistakes
- Symptom: SQL permission error occurs after restarting the Docker container, unable to query business data from the project approval and supervision platform. Cause: Database connection permission configuration was not persisted during deployment, permission configuration inside the container is lost after restart, and the access whitelist for the local database user was not bound.
- Symptom: The model only uses a single GPU, unable to call the second GPU resource. Cause: GPU allocation rules were not configured for parallel processing of multi-source business data, only GPU 0 is enabled by default.
- Symptom: Some historical project data cannot be retrieved normally after cross-version upgrade. Cause: The execution order of upgrade scripts was not adapted to the data update rhythm, and some migration steps for stock data were skipped.
How to confirm the configuration is complete
- Execute the database connection test command to verify that the connection count configured by
DB_MAX_LINKcan normally access the business database concurrently. - Upload a test redline drawing document to confirm that the storage service configured by
STORAGE_S3_ENDPOINTcan normally receive the document and return a file access link. - Restart the Docker container, check the database connection status to confirm that the permission configuration was not lost.
- Call the model interface, check the GPU resource usage to confirm that the multi-GPU allocation rules are effective.
The values listed above 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 2026-09-28.