What the data for this category looks like
This category's data primarily comes from cloud bills, monitoring systems, business forecast reports, and stress test results. Daily produced documents include capacity planning reports, expansion application forms, resource utilization reports, and budget calculation sheets. Data updates follow a weekly or monthly cadence. Fields cover resource usage, peak thresholds, applied configuration quotas, and budget calculation quotas. Units include CPU cores, memory in GB, storage in TB, and the like. Some documents include historical peak comparisons and forecast trends.
What constraints these characteristics impose on the citation sources and traceability link
Because this category's data sources are scattered and update cycles are long, the citation traceability link must bind the collection time and source identifier of original data. This ensures the timeliness and traceability of cited content. Daily document structures are fixed. Citations must strictly match the fields and units within documents. Avoid cross-category field mismatch issues. Errors in peak forecasting and resource bottleneck positioning can trigger peak failures or resource waste. Therefore, traceability must link test case execution logs and defect records. This facilitates locating problem root causes. Additionally, data updates proceed slowly. The validity period of citations must match the data update cycle. Avoid citing expired forecasts or report content.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
quoteMaxToken | 1000–1500 token | Adapts to the length of single-segment core data in capacity planning reports. Prevents truncation of critical thresholds and values, and aligns with the citation configuration logic of FastGPT v4.17.0 |
responseData | Enable source binding | Associates the collection time and source identifier of original data, matching the weekly/monthly data update cadence |
detail | Show full traceability path | Includes storage nodes of original data such as cloud bills and monitoring systems, facilitating resource bottleneck troubleshooting |
| Number of citations displayed per single request | Top 2–4 entries | Matches core data entries in daily reports, avoiding information overload that disrupts operational analysis |
| Citation validity period rule | Set according to the data update cycle | Aligns with the weekly/monthly data update cadence, avoiding citing expired forecasts or report content |
Three common mistakes
- Symptom: Cited content displays "No permission to operate this conversation record", and traceability information cannot be displayed normally. Cause: The traceability data view permission for the corresponding role is not enabled, or the original data storage node bound to the citation does not have access permissions enabled.
- Symptom: After importing an expansion workflow from another environment, the associated capacity planning data citations fail. Cause: The traceability identifier of the original data was not included during export, and local data source configurations cannot be matched after cross-environment import.
- Symptom: The cited peak forecast data range is insufficient, failing to cover complete capacity analysis requirements. Cause: The single citation count limit is set too low, not matching the core data entries in stress test reports.
How to confirm the configuration is complete
- Initiate a test conversation related to capacity planning. Check whether cited content includes the source identifier and collection time of original data.
- Export the current citation rule configuration. Verify that the values of configuration items align with the update cadence and document structure of business data.
- Import an expansion workflow from the test environment. Verify that associated capacity planning data citations load normally.
- View the conversation execution log. Confirm that the token length of cited content has not been truncated, and core thresholds and values are fully displayed.
The values provided 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 2026-10-19.