Reference only; verify against the target FastGPT release and deployment documentation.
What This Category of Data Entails
Data for this use case comes from the national unified construction project EIA declaration and approval system, ecological environment zoning control results, pollution discharge permit platform, and monitoring data. Update frequency is irregular. Commonly processed documents include environmental impact assessment reports or report forms, approval applications, public participation explanations, technical assessment opinions, and EIA approval documents. Document structure is divided by core fields such as project category, EIA level, pollution prevention measures, and public participation status. It must adapt to declaration materials of different scales, and there is no unified fixed single-document length.
What Constraints Do These Characteristics Impose on Workflow Orchestration
The need to integrate multi-source data requires that workflows be configured with cross-system data pull nodes to ensure linked verification of declaration materials, zoning control data, and monitoring data. Inconsistent document structures require workflows to support flexible chunking and field extraction rules to avoid node exceptions caused by differences in document length. Irregular update cycles mean workflows cannot rely on fixed scheduled pull logic, and data synchronization must be triggered on demand. At the same time, review errors can lead to serious consequences such as project suspension or revocation of approval documents. Workflows must add pre-check and failure rollback links to ensure the accuracy of the review process.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind project number, project category, declaration material ID | Accurately match exclusive data for corresponding EIA projects, avoid cross-project review confusion |
| Question Optimization | Enable and set to "Optimize questions according to EIA approval professional standards" | Adapt to EIA domain terminology, improve the review node's understanding accuracy of complex documents |
| Single Search Limit | Top 10 entries | Cover core reference data of EIA documents, avoid redundant information interfering with review judgments |
| Reranking | Enable, sort by relevance | Prioritize core review fields such as pollution prevention measures and public participation, improve review efficiency |
| Maximum Context | 8000–12000 token | Accommodate complete EIA report chapters and approval history data, value range calibrated based on actual testing |
| Node Timeout Setting | 600 seconds | Adapt to loading and review duration of long documents, avoid interrupting the complete review process due to timeout |
Three Common Misconfigurations
- An AI chat node in the workflow appends a fixed platform prompt at the end of its output. The symptom is test returns "FastGPT is a knowledge base question answering system based on large language models (LLM)". The cause is that a custom review prompt is not configured in the system prompt of the chat node, and the platform's built-in general prompt is loaded by default.
- The configuration effect of the AI chat node's temperature switch is confused. The symptom is that setting the temperature to 0 and disabling the temperature switch produce no obvious difference in output results. The cause is that the underlying logical differences between the two configurations are not clearly understood. Some nodes default to treating disabling the temperature switch as limiting randomness to the lowest level, which has a subtle difference from the logic of setting temperature to 0.
- The question classification node runs slowly. The symptom is node response timeout when processing EIA declaration materials in batches. The cause is that the input text length limit of the classification node is not set, and chunking processing logic is not enabled, resulting in an excessively large amount of document data loaded in a single run.
How to Verify Proper Configuration
- Navigate to the workflow test page, enter a simulated EIA project number, and check whether the project number, category and other fields bound to
variablesare loaded correctly. - Run the workflow, check whether the output of the AI chat node includes the core review fields required for EIA approval, and there are no redundant platform prompt messages.
- Adjust the single search limit to Top 5 and Top 15 entries, compare the relevance and redundancy of returned results, and confirm that they meet the needs of the current review scenario.
- Batch import 3 EIA declaration materials of different categories, verify that the response time of the question classification node corresponding to
nodeIdmeets expectations.
The configuration values listed above are common starting points, and should be adjusted based on 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.