What This Category of Data Looks Like
Daily documents for this category include Land Use Preliminary Examination and Site Selection Opinions, Construction Land Planning Permits, Construction Engineering Planning Permits, red line drawings, and planning conditions. Data sources include the national integrated land and space planning map, project approval and supervision platform, current land use database, and ecological protection red line data. Update frequency is irregular. Each document contains fields such as project number, site selection scope, land use scale, and control requirements. Most fields involve spatial coordinates, area values, and approval status identifiers. There is no fixed word count for a single document.
Constraints Imposed on Deployment and Upgrade
Data sources for this category are scattered, and updates have no fixed cycle. During deployment, support dynamic access and incremental synchronization configuration for multiple data sources to avoid excessive resource usage from full pull operations. Documents contain structured and unstructured content including spatial coordinates and area values. During deployment, match storage and parsing configurations that support corresponding formats. Since data updates have no fixed rhythm, upgrades must be compatible with field changes in historical data to avoid ledger summary failures caused by field mismatches. Because error consequences directly affect project approval and construction, configure reliable database connections and exception alert rules during deployment to ensure data processing stability.
Configuration Guidelines
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:27017/fastgpt?authSource=admin | Stores historical approval document and ledger data; requires a connection address with permission verification |
PG_URL | postgresql://username:password@host:5432/fastgpt | Stores structured project field data such as land use scale and approval status; must support relational queries |
REDIS_URL | redis://:your_password@host:6379/0 | Caches spatial coordinate data and approval status from frequent queries to reduce delays from multi-data-source pulls |
DB_MAX_LINK | 20–30 | Adapts to concurrent query demands for multi-project ledgers; avoids database blocking from excessive connections |
STORAGE_S3_ENDPOINT | Fill in according to the local storage or cloud service provider's object storage address | Stores unstructured documents such as red line drawings and planning conditions; must match the actual path of data storage |
FILE_TOKEN_KEY | A randomly generated 32-character string | Encrypts stored document access tokens to ensure access security for unstructured documents |
Three Common Misconfigurations
- Phenomenon: The generated ledger report includes content from unconfigured data sources, and it still appears even when the reference switch is disabled. Cause: Data source permission filtering rules are not configured correctly, leading to unauthorized land and space planning data being included in the summary scope.
- Phenomenon: Database connection timeout errors occur after deployment, with a status code of 503. Cause: The
DB_MAX_LINKconfiguration value is too low to support concurrent query requests for multi-project ledgers. - Phenomenon: Model access deployed outside Docker cannot trigger tool calls. Cause:
REDIS_URLis not configured correctly for caching tool call context, preventing normal reading of tool call status.
How to Verify Successful Configuration
- Log in to the FastGPT backend data source management page, check the connection status of
MONGODB_URIandPG_URL, and confirm the status shows normal. - Upload a red line drawing document to verify that the
STORAGE_S3_ENDPOINTstorage configuration works correctly, and that the document can be previewed and downloaded normally. - Initiate a ledger summary request, confirm that the returned results only include content from authorized data sources, with no unconfigured external data included.
- Adjust the
DB_MAX_LINKconfiguration value, observe database load during concurrent queries, and confirm that the connection count configuration matches actual business requirements.
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 2026-09-28.