What data for this category looks like
This category’s main data comes from game operation logs, real-time online player count monitoring, business databases, and player feedback tickets. Daily documents include server architecture descriptions, server expansion plans, server merging data verification processes, and online fault troubleshooting reports. Most data updates happen daily. Updates follow the event cycle during large-scale version events. Document structures include deployment parameters, resource usage thresholds, and fault troubleshooting steps. Some data has clear units: online player count uses "players" as the unit, and log timestamps are precise to the millisecond.
What constraints do these characteristics impose on the citation sources and traceability link
This category’s data has high update frequency and strong ties to online business. Citation and traceability workflows must link latest real-time data and historical documents. Using expired configurations may cause server startup exceptions. Fields like deployment parameters and resource thresholds in daily documents have clear units. Retain original field names and units when citing, otherwise capacity estimation deviations may occur. In fault troubleshooting scenarios, link logs, tickets, and architecture documents simultaneously. The traceability link must clearly mark data source types to facilitate subsequent reproduction of online issues.
How to set configurations
The following configurations are adjusted based on FastGPT v4.17.0:
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
quoteMaxToken | 1000–1500 token | Matches the core content length of single fault reports and server merging verification processes in documents of this category, ensuring complete citation of key parameters |
responseData | Includes source type identifiers | Makes it easy to distinguish whether data comes from game logs, business databases, or player tickets in outputs, meeting traceability requirements |
detail | Recall the top 4 sources | Balances information density and troubleshooting efficiency, avoiding excessive redundant log entries that interfere with server status analysis |
| Maximum context length | 8000–10000 characters | Adapts to multi-document splicing needs, covering associative analysis of server expansion plans, architecture descriptions, and fault logs |
Three common errors
- Phenomenon: No citation source entries appear after calling an external API to generate a response. Cause: The
responseDataconfiguration item is not enabled, or the configured parameter value exceeds the recall range of the current knowledge base. - Phenomenon: The large model response does not cite any recalled content after increasing
quoteMaxToken. Cause: The parameter value is too high, causing recalled content to be truncated and unable to match the semantic matching logic of the response context. - Phenomenon: Citation works normally in local tests, but the interface cannot be called via external release channels. Cause: Authentication parameters for the external API are not configured correctly, or interface access permissions for the release channel are not enabled.
How to confirm configurations are set correctly
- Enter the knowledge base management page, check whether the
quoteMaxTokenconfiguration value matches the average length of business documents. - Initiate a test query, check whether the response includes source type and data source identification information.
- Call the external API interface, verify whether the returned results include the source details corresponding to the
detailfield. - Adjust the
responseDataconfiguration item, compare the differences between pre- and post-adjustment return results to confirm that the configuration takes effect.
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.