Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Data sources for this category include the national unified construction project environmental impact assessment declaration and approval system, ecological environment zoning control results, pollution discharge permit platform, and monitoring data. The update frequency is irregular. Daily processed documents include environmental impact assessment reports or report forms, approval applications, public participation explanations, technical assessment opinions, and environmental impact assessment approvals. These documents contain both structured fields such as project name, industry category, and approval status, as well as lengthy technical argumentation and public participation text. There is no fixed uniform standard for single-document length.
What constraints these characteristics impose on model access and configuration
Multi-source data access requires configuration to adapt to data formats from different systems. Irregular updates require support for incremental synchronization and regular verification. Long-text environmental impact assessment documents consume large amounts of model context. Sufficient context capacity must be set to avoid truncation of key information. Ledger summary requires association of multiple documents of different types, which places requirements on the model's multi-document processing capabilities. Additionally, since the consequences of errors are severe, strict content verification and sensitive word filtering mechanisms must be configured to prevent incorrect information from entering the approval process.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the long-text content of environmental impact assessment reports, avoids truncation of key approval basis such as project category and pollution prevention measures |
temperature | 0.1–0.3 | Ensures the rigor of content related to environmental impact assessment approval, reduces conclusion deviation caused by subjective divergence |
toolChoice | auto | Automatically selects appropriate tools to complete multi-document association, ledger field extraction, and report generation tasks |
quoteMaxToken | 1500–2000 characters | Ensures that recalled environmental impact assessment document fragments fully cover the technical argumentation and compliance basis required for approval review |
AIPROXY_API_ENDPOINT | Fill in according to the deployment environment | Adapts to the API access address of self-built or cloud services, ensures normal model call link |
AIPROXY_API_TOKEN | Key generated according to permissions | Ensures the identity legitimacy of API calls, prevents unauthorized access |
Three common mistakes
- Call failure when calling a custom API channel. Cause:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare not configured correctly, or the call permission for the corresponding channel has not been enabled. - Unfiltered sensitive expressions appear in the generated ledger or report. Cause: The model's built-in sensitive word verification module is not enabled, or custom sensitive word rules suitable for the environmental impact assessment scenario are not configured.
- After importing multi-column Excel-format environmental impact assessment ledger data, the RAG chunking results are chaotic. Cause: The rule of using rows as the chunking unit is not configured, and the automatic chunking logic incorrectly splits structured ledger fields.
How to confirm the configuration is correct
- Upload a single environmental impact assessment approval application document, trigger the ledger generation process, and check whether the returned result contains complete preset project fields.
- Call the configured API interface, view the returned request log, and confirm that
AIPROXY_API_ENDPOINTand identity verification information are correct. - Upload multiple associated environmental impact assessment documents, and check whether the model can correctly associate project information from different documents and complete the summary.
- Import multi-column Excel-format environmental impact assessment ledger data, and check whether the chunking results are split by row, with complete and non-missing fields.
The values provided are common starting points and should be evaluated 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.