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What Data Looks Like for This Category
Typical users of this category include on-site outsourced engineers, service managers, and customer IT departments. Teams process daily documents including on-site daily reports, helpdesk tickets, inspection reports, and SLA monthly reports. Data sources cover customer ITSM systems, monitoring platforms, asset inventories, and on-duty records. Update frequency is daily or monthly. Data format mixes structured entries and unstructured text. Fields typically include ticket numbers, inspection items, service response records, and similar content.
Constraints Imposed on Context and Token Handling
Data sources for this category are scattered. Content mixes structured and unstructured formats. Splicing context often creates redundant information. Strictly limit total token volume to avoid exceeding model processing limits. Daily updated tickets and inspection data have strong timeliness. Prioritize recent entries for context recall, while controlling token consumption per context round. Long documents such as SLA monthly reports may use excessive token quotas for a single recalled knowledge base chunk. Adjust context allocation rules as needed. On-site services involve internal customer assets and service details. Accurately match context token statistics to actual document lengths to prevent leakage of unrelated sensitive information.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to context requirements for splicing multiple on-site service documents, avoids exceeding context processing limits of mainstream large models |
quoteMaxToken | 1500 token | Matches average token length of single documents such as inspection reports and service tickets, prevents single citations from occupying excessive context space |
| Number of recall entries per single round | Top 6 | Balances information completeness and token consumption, adapts to recall requirements for multi-source on-site service data |
| Recalled data time range | Past 30 days | Matches daily/monthly updated data cycles, prioritizes timely on-site related data |
| Knowledge base chunk size | Calibrated via actual testing | Adapts to structural characteristics of on-site documents, avoids token overflow after recall caused by overly large chunks |
Three Common Misconfigurations
- In some scenarios, response content suddenly becomes shorter, and the displayed response token count in the interface is 200. Context splicing occupies too much total token quota, triggering the model's single-round response token limit.
- When deploying via cloud space, individual token configuration fields cannot be found. Cloud version token configuration is integrated in the application key binding process, and no separate configuration entry is exposed.
- An abnormal recall occurs even when the knowledge base chunk size is set to 5000 token and the citation limit is 1500 token. Actual token statistics after chunking deviate from preset values, and the total context token limit was not adjusted synchronously.
How to Verify Proper Configuration
- View the application's context statistics panel, confirm that the
maxContextconfiguration value matches the actual displayed context token limit. - Submit a test request containing multiple on-site documents, check that the cited token count in returned content does not exceed the
quoteMaxTokensetting. - Test document recall across different time ranges, confirm that only on-site related data from the past 30 days is recalled.
- View token statistics fields in system logs, confirm that actual consumed tokens match configured values.
These values serve as common starting points, and should be validated against actual samples from the target use case.
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.