What the data for this category looks like
Data sources for this category include the territorial spatial basic information platform, natural resource survey and monitoring data, population and economic statistics, and remote sensing images. The update frequency is annual. Daily processing covers documents including territorial spatial overall plans, detailed plans, special plans, planning implementation evaluation reports, and public opinion summaries. These cover spatial vector layers, attribute statistical fields, and unstructured feedback content, involving core information such as regional spatial layout, control indicators, and public appeals.
What constraints these characteristics impose on the "model access and configuration" link
The annual update data feature requires the knowledge base synchronization cycle to align with the annual data update rhythm, to avoid using outdated planning content. The multi-source heterogeneous data structure requires model configuration to support parsing and association of mixed format content such as spatial layers, statistical reports, and public opinions. Long-format planning documents require configuring a sufficient context window to carry complete business data segments and avoid loss of key information. At the same time, the consequences of errors caused by planning approval delays require configuring a stable model call retry mechanism and error capture logic to ensure the accuracy and timeliness of responses.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Territorial spatial planning documents have a long length, and need to carry complete planning text, associated data, and public opinion segments |
maxTokens | 4000–6000 token | Control the single-round output length of service inquiry responses, and adapt to the output limits of general model interfaces |
quoteMaxToken | 2000–3000 token | Ensure that sufficient compliant basis segments can be extracted from planning reports and implementation evaluation materials to support responses |
temperature | 0.2–0.4 | Planning responses need to maintain rigor, and avoid generating arbitrary content inconsistent with policies |
AIPROXY_API_ENDPOINT | Compliant domestic model proxy endpoints | Adapt to the data security and compliance requirements of natural resource departments, and avoid cross-border data transmission risks |
toolChoice | auto | Automatically call necessary tools to handle complex tasks such as spatial data parsing and multi-source data association |
Three common mistakes
- Phenomenon: The text extraction component returns empty results, or fails to extract planning document content from knowledge base references. Cause: No reasonable value is set for the
quoteMaxTokenparameter, resulting in insufficient length of extracted basis segments, or the document parsing permission of the corresponding tool is not enabled. - Phenomenon: A prompt indicating no available model permissions appears when calling the model. Cause: The
AIPROXY_API_TOKENparameter is not configured correctly, or the permission for the proxy endpoint is not activated, resulting in failure to call the model interface normally. - Phenomenon: Model call times out or returns truncated results. Cause: The
maxContextormaxTokensparameters are not adjusted based on the actual length of planning documents, exceeding the carrying limit of the model interface.
How to confirm the configuration is complete
A typical territorial spatial overall plan document is uploaded. Content referenced from the knowledge base is extracted for testing, and the returned result is checked to confirm whether it contains document segments. After configuration is complete, a test question related to planning consultation is initiated. The model is checked to confirm whether it can normally return a response without error prompts. The configuration content of AIPROXY_API_ENDPOINT and AIPROXY_API_TOKEN is verified to ensure they match the information of the model service in use. The temperature parameter is adjusted, and a test is initiated. The rigor of the response content is checked to confirm whether it meets expectations, and the parameter value is confirmed to be adapted to business requirements.
The values provided are common starting points and should be measured against sample data relevant to the specific deployment context.
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.