What the data for this category looks like
This segment’s data is sourced from the national unified construction project EIA declaration and approval system, ecological environment zoning control results, pollution discharge permit platform, and monitoring data, with irregular updates. Commonly processed documents include environmental impact assessment reports or report forms, approval applications, public participation explanations, technical assessment opinions, and EIA approval documents. Each document includes core fields such as project category, EIA grade, pollution prevention measures, and public participation status. There is no fixed unified unit, so industry specifications must be matched based on actual project details.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering by These Characteristics
Data sources are scattered, and updates follow no fixed cycle. This requires multi-turn dialogue to dynamically call fields from different systems, avoiding reliance on static knowledge bases. Core document fields have no unified unit, so prompt engineering must adapt to industry classification rules for different projects, with no preset fixed formats. The most time-consuming verification step requires multi-turn dialogue to gradually break down verification points such as project category, EIA grade, and pollution prevention measures. It must retain previous verification results via context to avoid repeated questions. The consequences of errors are severe, so compliance verification nodes must be added to the dialogue process. This ensures every round of output meets the legal requirements for EIA approval.
How to Set the Configuration
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
messages | Retain the first 10–15 dialogue history entries | EIA approval requires retrospective access to early project declaration information; sufficient historical context avoids repeated inquiries about basic project information |
variables | Bind fixed business fields such as project code and industry category | Static business data can be injected into prompt engineering in advance, reducing repeated input content |
chatId | Bind sessions using the unique identifier of the approval project | Ensure that multi-turn review sessions for the same approval project do not mix up historical information, avoiding cross-project context interference |
| Maximum single-dialogue tokens | 8000 tokens, calibrated through actual testing | EIA documents have relatively long content, requiring space to accommodate complete technical assessment opinions or report summaries |
| Prompt engineering update rules | Append current verification results after each round of dialogue | Ensure that the next round of review can directly use previous conclusions as input basis |
| Branch trigger conditions | Execute node jumps based on verification results | Enable process branching after compliance verification, adapting to review correction or termination requirements |
Three Common Errors
- Only a small amount of context is displayed in the dialogue details, making it impossible to associate historical verification results. The cause is incorrect configuration of the number of retained
messagesentries, or an overly small context window setting, resulting in early project information being truncated. - Unable to use the verification conclusion from the previous round as input for the next round of prompt engineering. The cause is failure to bind previous output fields through
variables, and failure to inject dialogue results into subsequent prompt engineering templates. - Loop process execution is abnormal, unable to terminate or restart based on verification results. The cause is incorrect configuration of branch trigger rules, and failure to bind verification results to node jump logic.
How to Confirm the Configuration Is Complete
Reference only; verify against the target FastGPT release and deployment documentation.
- Initiate a test dialogue, enter basic project information, then inquire about historical content. Verify that the dialogue details fully display previous interaction records.
- Trigger one round of verification, then check whether the current verification result is stored in
variables. Confirm that this field can be called in subsequent dialogues. - After configuring the loop branch, enter an invalid verification result and check whether the regeneration node is triggered. Enter a valid verification result and confirm that the process terminates.
- Check whether
chatIdremains consistent within the same session. Confirm that sessions for different approval projects do not experience context mixing.
The values provided here 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.