Reference only; verify against the target FastGPT release and deployment documentation.
What data for this category looks like
This category’s core data originates from the national spatial planning unified map, project approval and supervision platform, current land use database, and ecological protection red line data. Updates occur irregularly. Daily accessed documents include land pre-examination and site selection opinions, construction land planning permits, construction engineering planning permits, red line drawings, and planning conditions. Document fields cover project site selection scope, land use scale, planning control requirements, prior approval conditions, and more. No unified fixed unit format exists. Corresponding fields and values are matched to specific approval documents as needed. This covers approval basis and control rules for the full project process from pre-examination to permit issuance.
What constraints do these characteristics impose on model access and configuration
Scattered data sources and irregular updates require model access configuration to support real-time retrieval or regular synchronization of latest planning and approval data. This avoids use of expired information. Document types include vector drawings and text files. Parameters for multimodal input must be configured to process drawing data such as red line drawings. Fields have no unified fixed format. The model must accurately identify and match field content from different documents. Randomness of generated content must be limited to ensure responses meet strict natural resource control requirements. Errors directly affect project approval and construction. Reference of basis and accuracy verification for responses must be strengthened.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Documents related to land pre-examination and planning permits are lengthy. This ensures complete context coverage across multiple approval documents and planning control data |
maxTokens | 4000–6000 token | Consultation responses require detailed compliance explanations and basis. This avoids truncation of key approval rules and project requirements |
quoteMaxToken | 2000–3000 token | Core document fragments such as planning red lines and approval opinions must be fully cited to ensure traceable basis for responses |
temperature | 0.1–0.3 | Consultation responses require strict accuracy. This avoids generating vague content that does not comply with natural resource control specifications |
toolChoice | auto | Supports the model to independently call knowledge base retrieval for planning data and approval records, improving response accuracy |
AIPROXY_API_ENDPOINT | Fill in the address provided by the model service provider | Completes access endpoint configuration for private or cloud platform large models, ensuring normal communication |
AIPROXY_API_TOKEN | Fill in the key allocated by the platform | Completes identity verification for model access, ensuring valid access permissions |
Three common configuration errors
- A 404 error occurs during model testing. The cause is incorrect configuration of
AIPROXY_API_ENDPOINTorAIPROXY_API_TOKEN, which are not aligned with verified model service configurations. - The model output contains no thought process. The cause is that
toolChoiceis set to restricted mode, or the model's native thought output switch is not enabled, resulting in only conclusive content being returned. - Model inference delay exceeds expectations. The cause is that
maxContextexceeds the context window supported by the model, or insufficient resource allocation leads to increased inference time.
How to Confirm Successful Configuration
- A consultation question including project site selection scope and planning control requirements is submitted. The returned result is checked for accurate cited fragments of corresponding documents.
- Different model access configurations are switched. The model’s ability to normally return responses compliant with land pre-examination and planning permit specifications is confirmed.
- The configuration of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENis checked to ensure alignment with verification information provided by the model service provider. - The
temperatureparameter is adjusted. The rigor of responses against consultation work requirements is verified.
The values provided are common starting points and should be measured against samples relevant to the 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.