What the data for this category looks like
Data sources include the national land and spatial planning one-map, project approval and supervision platform, current land use database, and ecological protection red line data. Update frequency is irregular. Core daily documents include land pre-examination and site selection approval documents, construction land planning permits, construction engineering planning permits, red line drawings, and planning conditions. Data fields cover project name, site selection coordinates, land scale, permit number, pre-approval node status, and other items. Units include square meters, hectares, project numbers, and other items. Each single data entry is associated with multiple types of pre-approval documents and spatial control data.
What constraints do these characteristics impose on HTTP interfaces and external systems
Multiple heterogeneous data sources require interfaces to support compatible return formats. Irregular data updates require interfaces to support on-demand triggering. Daily documents include two types of data: spatial coordinate data and text approval data. Interfaces must adapt to parsing logic for both field types to avoid mixing spatial data and text fields. Each single data entry is associated with multiple pre-approval files. Interface calls must carry a project unique identifier as a parameter to ensure pulled data is accurately bound to the corresponding project. Data errors can block project initiation. Interfaces must return clear status identifiers and error messages to facilitate subsequent troubleshooting.
How to configure
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Read dynamic tokens from variables | Adapt to interface access permissions for different projects, avoid security risks caused by hardcoding tokens |
variables | Store project ID, interface address, data type parameters | Facilitate quick parameter adjustment for multi-project calls without modifying interface configurations |
responseData | Extract specified fields and convert to structured tables | Adapt to batch data organization needs for ledger summary, facilitate subsequent report generation |
| Timeout setting | 30-60 seconds | Account for time spent pulling spatial data, avoid incomplete data due to request timeout |
| Retry strategy | Retry 2 times after failure | Address temporary network fluctuations or temporary interface unavailability scenarios |
| Response data cache duration | 24 hours | Avoid repeatedly pulling the same non-real-time data |
| Single request data volume limit | 500 entries | Avoid slow interface responses caused by overly large single request data volume |
| Field mapping rule | Match according to business document fields | Ensure extracted data corresponds one-to-one with ledger fields, facilitate report generation |
Three common mistakes
- Interface requests automatically add extra Bearer tokens, causing identity verification failure. Cause: FastGPT's built-in automatic token supplement logic is not disabled, resulting in duplicate identity verification fields in the request header.
- Ledger data fields are empty or do not match actual business documents. Cause: Field mapping rules are not configured according to business documents, resulting in extracted fields not matching ledger requirements.
- Interface calls time out or return incomplete data. Cause: Timeout setting is too short, not adapting to time requirements for pulling spatial data.
How to confirm configuration is complete
- Call the test interface, check if the value of
Authorizationin the request header matches the configuration, with no extra automatically added tokens. - Pass a test project ID, verify that the interface returned fields include project name, land scale and other fields required by business documents.
- Simulate network fluctuation scenarios, confirm that the interface executes the preset retry strategy after failure.
- View the structured data after response parsing, confirm that mapping has been completed according to business document fields, and it can be directly used for ledger summary.
The values given 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 2026-09-28.