What this category of data looks like
Data for the construction engineering quality and safety supervision scenario covers daily business documents from housing and urban-rural development quality and safety supervision stations, construction units, supervision units, and project owners. This includes supervision plans, supervision inspection records, hidden danger rectification notices, quality problem handling forms, and completion acceptance supervision reports. Data sources include the project quality and safety supervision system, on-site construction real-name management platform, supervision logs, and test reports. The update frequency is once per week. Each individual document contains fields such as supervision scope, inspection nodes, rectification requirements, and acceptance conditions. Document formats and field arrangements vary across different sources, and classified calls must be made according to business scenarios.
What constraints do these characteristics impose on the "multi-turn dialogue and prompt words" link
The weekly data update rhythm requires that multi-turn dialogue context only retain business content from the last 7 days, to avoid referencing outdated supervision records. Differences in document formats and fields across multiple sources require that prompt words clearly specify call rules for different documents, ensuring returned content matches the field requirements of the corresponding business scenario. The high field complexity of daily documents requires limiting the total context length during multi-turn dialogue, to prevent exceeding the model's processing limits. Additionally, the consequences of errors in this scenario are severe, so prompt words must mandate that returned content be linked to specific document sources, to avoid unsupported policy interpretations.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 characters | Matches the total length of daily documents and the context requirements of weekly updated data |
messages context truncation rule | Retain the last 10 turns of dialogue | Avoids redundant historical content interfering with current policy queries |
variables binding fields | Bind supervision project ID, project type | Accurately links policy and document data for the corresponding project |
| Streaming output switch | Enabled | Enables real-time segmented return of policy basis |
| Streaming output rate | 1–2 seconds per segment, calibrated via actual testing | Adapts to the fluency requirements of front-end interaction |
chatId session binding rule | Bind the unique identifier of the current supervision project | Ensures context consistency across multi-turn dialogue |
Three common mistakes
- Symptom: When calling the dialogue API with streaming output enabled, document links in the returned content only overwrite the current page when clicked, and cannot jump to a new page. Cause: No front-end compliant jump identifier is embedded in the streaming returned content, causing the front-end rendering logic to fail to correctly identify and process link jump instructions.
- Symptom: In FastGPT v4.17.0, after initiating multiple dialogue requests for the same supervision project, the conversation log details page always displays the response content from the first dialogue. Cause:
chatIdis not bound to the unique identifier of the current supervision project, causing context from different sessions to be incorrectly overwritten, and the session ID associated with the log is inconsistent. - Symptom: The streaming output return interval is fixed at 4 seconds, and cannot be adjusted to the preset 1–2 seconds. Cause: The streaming output rate parameter is not configured, and the system default fixed return interval is used.
How to confirm the configuration is complete
- Initiate a dialogue containing multiple rounds of supervision policy queries, check whether the
messagesfield correctly retains the latest conversation history and does not include outdated supervision records. - Call the streaming output interface, verify that the segment interval of returned content conforms to the preset requirement of 1–2 seconds per segment, and there is no fixed 4-second interval issue.
- View the conversation log, confirm that the
chatIdmatches the unique identifier of the current supervision project, and the log content completely matches the actually returned response content. - Test policy basis queries, verify that returned content is linked to the document fields of the corresponding supervision project, and no policy interpretations without specific sources appear.
The values provided here 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.