What the Data for This Category Looks Like
This category’s data originates from crowdsourcing platforms, annotation quality collection systems, training assessment records, and financial settlement systems. It supports test case design and defect analysis for crowdsourced annotation projects. Daily maintained documents include personnel access rules, annotation skill training materials, monthly performance reports, and settlement statements. Data update frequencies fall into two categories: daily and monthly. Daily update data includes same-day annotation quality and personnel online status. Monthly update data includes monthly performance metrics and settlement details. Data fields include unique personnel identifiers, training assessment results, task completion volume, settlement amounts, and similar items, with no additional custom units.
Constraints on Citation Sources and Traceability
These data characteristics create clear constraints during the citation sources and traceability workflow. Data sources are spread across multiple independent systems. Traceability must associate unique personnel identifiers across different data sources to prevent cross-system data confusion that would reduce test case accuracy. Differences in update frequencies require distinct call logic for real-time and historical data during traceability. Daily update data must match same-day annotation tasks for real-time defect troubleshooting. Monthly update data must be locked to the corresponding settlement cycle for monthly performance testing. Multiple document types exist with varying field weights. Citation matching rules must be configured specifically to avoid confusing training materials with performance and settlement documents, which would cause test case failure. Settlement data includes monetary fields. Additional verification of data access scope is required during traceability to prevent sensitive information leaks that would undermine the credibility of defect analysis.
Configuration Settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | Adapts to the content length of longer documents such as performance reports and settlement statements, avoiding truncation of key fields like unique personnel IDs and settlement amounts |
responseData | Return only associated data sources | Reduces redundant information and focuses on core traceability data for personnel access, performance, and settlement |
detail | Full field display | Retains necessary identifiers such as unique personnel IDs and task completion volume to facilitate cross-system cross-checking |
| Maximum number of recalled entries | Top 3–5 entries | Matches the number of data sources for this category, avoiding excessive irrelevant documents interfering with traceability results |
| Similarity threshold | 0.75–0.85 | Distinguishes semantic similarity across different document types, preventing accidental association between training materials and settlement statements |
Three Common Misconfigurations
- Phenomenon: Retrieved content references unassociated current data sources, or empty reference identifiers appear. Cause: No data source association rules are configured, causing the system to recall document data from non-target categories.
- Phenomenon: Mixed references of different document types appear during retrieval, such as training materials and settlement statements being displayed simultaneously. Cause: No filtering conditions based on document type are set, causing semantic similarity matching to cover data sources from unrelated categories.
- Phenomenon: Parameter verification errors occur after configuring citation variables, or returned results do not match the preset traceability scope. Cause: Unique identifiers of data sources are not correctly bound, or parameter naming methods that do not comply with platform specifications are used.
How to Confirm Successful Configuration
- Manually enter a query related to personnel performance, and check whether the returned citation content only includes target category documents such as performance reports and settlement statements.
- Check whether the fields of reference identifiers include category-specific fields such as unique personnel IDs and task volume, confirming that data sources match.
- Adjust the value range of configuration items to verify whether the length of citation content complies with the preset token limit.
- Enable traceability logs to check whether the system only calls configured data sources and does not recall data sources from cross categories.
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.