What Data Looks Like for This Category
Data for this category comes from the national land spatial planning unified map, project approval and supervision platform, land use status database, and ecological protection redline data. Update frequency is irregular. Daily processed documents include land pre-examination and site selection opinions, construction land planning permits, construction engineering planning permits, redline drawings, and planning conditions. These documents have fixed fields such as project site selection scope, land use scale, control requirements, and approval nodes. Some documents are in visual formats, including coordinate markings, boundary lines, and other content.
Constraints Imposed by These Characteristics on Model Access and Configuration
Irregularly updated multi-source data requires configuration to adapt to variable-length context content, to avoid missing key approval basis in documents due to incomplete data loading. Fixed-field document structures require the model to accurately match field requirements, to prevent generated content from deviating from approval specifications. Visual documents such as redline drawings and planning conditions require configuration to support visual parsing capabilities, to extract key information such as coordinates and boundaries from drawings. Cross-departmental pre-coordination data must be included in the context, requiring configuration to have sufficient context capacity to ensure all associated information is fully utilized.
How to Set the Configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to multi-source historical data such as land spatial planning and project approval, to avoid context overflow |
maxTokens | 3000–4000 token | Meets the complete output length requirements of land pre-examination and planning permit documents, covering content such as approval opinions and redline explanations |
vision | Enabled | Supports parsing visual documents such as redline drawings and attached planning condition drawings, to extract key information such as coordinates and control boundaries |
temperature | 0.1–0.3 | Reduces generation randomness, ensuring consistency in the output of core fields such as land use scale and control requirements |
AIPROXY_API_ENDPOINT | Fill in the exclusive address provided by the FastGPT v4.17.0 platform | Connects to compliant model services, adapting to document processing needs in the natural resources sector |
toolChoice | auto | Automatically calls associated tools to check land conflicts, without manually specifying call logic |
Three Common Misconfigurations
- Generated results only include thought processes, with no formal document content. The cause is that the prompt fails to clearly distinguish between thought and output stages, or the
temperaturesetting deviates from the reasonable range. - Visual documents such as redline drawings cannot be parsed, and generated content lacks key information extracted from drawings. The cause is that the
visionconfiguration is not enabled, or a model that supports visual capabilities is not selected. - Generated documents are truncated, and key approval requirements are not fully presented. The cause is that
maxTokensis set too small to support complete document output.
How to Confirm the Configuration Is Correct
- Upload a single redline drawing and planning condition document to verify whether the model can extract core fields such as land boundaries and control indicators.
- Submit a test case containing multi-source data to check whether the generated document covers all associated approval requirements.
- View the model call log to confirm that configuration items such as
maxContextandvisionare correctly loaded. - Verify the field integrity of the generated content to confirm that no key information such as project site selection scope and land use scale is missing.
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.