What this category of data looks like
This category of data draws from four main sources: the national land spatial planning unified map, project approval and supervision platform, current land use database, and ecological protection redline data. Updates occur on an irregular basis. Daily processed documents include land pre-examination and site selection opinions, construction land planning permits, construction project planning permits, redline drawings, and planning conditions. Structured documents contain fields such as project subject information, site selection scope, land use scale, and planning control requirements. Vector graphic documents include spatial coordinate and boundary information.
What constraints these characteristics impose on model access and configuration
The multi-source, heterogeneous nature of this category of data requires model access links to support parsing of both structured documents and vector spatial data. Irregularly updated data sources require configuration that supports dynamic adjustment of data synchronization ranges. Land pre-examination and planning permit business data requires dual verification of spatial coordinates and control indicators. The model must link spatial information with text rules. Errors here can affect project approval and construction, so the configuration link must strictly control output accuracy. Cross-departmental coordination prerequisites in business processes require model access to connect to project approval and supervision platform interfaces. The setup must adapt to permission and format requirements of different data sources.
How to set up configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | This category requires associating multiple pre-approval documents and spatial data, so sufficient context must be accommodated to complete association verification |
maxTokens | 4000–6000 token | Business verification requires generating complete compliance analysis to avoid core information loss caused by output truncation |
quoteMaxToken | 2000 token | Core document fragments such as redline drawings and planning conditions need to be referenced, and the length of referenced content must be controlled to ensure readability |
temperature | 0.1–0.3 | The business must strictly comply with planning control rules, so output randomness should be reduced to ensure verification accuracy |
toolChoice | auto | Need to automatically select text verification or spatial analysis tools based on input to adapt to multi-source data processing needs |
AIPROXY_API_TOKEN | Bind a dedicated team key | Meet model isolation requirements, and facilitate subsequent calculation of model call costs by team or user |
Three common configuration errors
- Symptom: Model calls take over 10 seconds, with noticeable single-dialogue response delays. Cause: The system does not adapt to this category’s multi-source spatial data parsing logic, or the
maxContextvalue is set too large, leading to excessive context loading time. - Symptom: Testing fails when connecting multimodal Embedding models. The system returns an error message containing
Invalid. Cause: The system does not correctly configure multimodal data parsing rules, or does not match the document formats and input parameters supported by the target model. - Symptom: The team cannot distinguish and calculate model call costs across different users or departments. Cause: The system does not bind model calls to a dedicated team key, or does not correctly configure access parameters related to model isolation.
How to confirm successful configuration
- Send a test request that includes the project site selection scope and planning control requirements. Check if the model output links core information from the corresponding data sources.
- Simulate mixed input of multi-source data. Verify that the model automatically adapts to documents and spatial data in different formats to complete verification logic.
- Review model call logs. Confirm that each request’s response duration meets business expectations, with no abnormal timeouts.
- Bind keys for different teams or users. Verify that permissions and cost statistics for model calls can be independently tracked.
The values provided 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.