What This Category's Data Looks Like
Data for this category primarily originates from customer requirements, public data sources, collection tools, and in-house sample libraries. Update cycles follow single-project or weekly timelines. Daily output documents cover collection plans, sample specifications, authorization instructions, and task schedules. Typical document fields include sample scope, collection fields, compliance requirements, and schedule nodes. The data remains unprocessed, uncleaned, and unlabeled. It consists only of raw, pending collection requirement definitions and rule documents, with no pre-splitting or additional processing.
Constraints Imposed on Context and Token
Documents in this category are primarily structured rule definitions. Individual document lengths vary significantly. Some collection plans include multiple pages of compliance instructions and sample details. Data sources are scattered and updates are frequent, so context association must cover cross-document requirement logic and historical rules. Token consumption depends on the number of fields defined in the sample scope and the length of compliance text. Without limits on context and token quotas, single calls may exceed the model's supported limits. Configuration deviations may also occur if historical collection rules are not associated. Raw data has not been pre-split, so context processing must accurately match requirements to corresponding collection rules to prevent token overflow.
How to Set Configurations
The following configurations are based on FastGPT v4.17.0, and are adapted to the business characteristics of this category:
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Matches the total length of associated documents such as collection plans and sample specifications under a single project in this category, to avoid single calls exceeding model limits |
| Historical Reference Limit | Top 6 task configurations | Aligns with the project-based update rhythm of this category, to avoid context overload affecting call efficiency |
quoteMaxToken | 1500–2000 token | Adapts to the typical length of a single sample specification document in this category, to ensure core collection rules are fully included in the context |
| Context Refresh Trigger Condition | Execute per project node | Matches the update frequency of this category per project or week, to avoid using expired historical collection rules |
| Single Recalled Token Limit | 2000 token | Limits token consumption for a single collection rule, to prevent token overflow caused by unsplit documents |
Three Common Misconfigurations
- Phenomenon:
LLM model response emptyerror occurs during calls. Cause: No limit is set on themaxContextquota. Total context token exceeds the model's supported range, so the model cannot generate valid responses. - Phenomenon: The system prompts a single-round call token limit exceeded after setting
quoteMaxTokento 2000 token. Cause: The totalmaxContextquota is not adjusted synchronously. The combined token of single references exceeds the overall context limit. - Phenomenon: Historical collection task rules cannot be associated in continuous conversations, leading to configuration deviations. Cause: No context refresh logic triggered by project nodes is configured. Expired historical configurations are used.
How to Confirm Proper Configuration
- Check the total length of a single collection plan and its associated documents. Adjust the
maxContextvalue to cover the typical document scale of the current project. - Test call scenarios that include 3 historical task configurations. Confirm that the token for single references does not exceed the
quoteMaxTokenlimit. - Trigger a project node update. Confirm that the context configuration automatically refreshes to the latest task rules.
- Review system operation logs. Confirm that no error records of token limit exceeded or empty responses appear.
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.