What Data for This Category Looks Like
Data for this category comes primarily from cloud billing, monitoring systems, business forecasting reports, and stress test results. Daily produced documents include capacity planning reports, expansion application forms, resource utilization reports, and budget calculation sheets. Data updates occur mostly on a weekly or monthly basis. Fields include resource specifications such as CPU cores and storage capacity, utilization values, budget amounts, and time nodes. Common units are cores, GB, yuan, and hours.
Constraints Imposed on Vector Models and Indexes
Data update frequency is low. High-frequency incremental indexing is not required. Full-index periodic updates can be used. Data sources are scattered. Vector processing for multi-format documents must be supported. Associations between fields must be retained. Individual document sizes are large, such as stress test reports and budget calculation sheets. Chunking must adapt to long-text structures. Semantic associations of resource-related numeric fields must be accurately matched. Capacity judgment errors caused by vector deviation must be avoided. The weekly or monthly update feature allows a relaxed index construction time window. Millisecond-level response requirements are not necessary.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to long-text structures such as capacity planning reports and stress test reports. Prevents semantic breaks in single chunks |
| Overlap Length | 100–200 characters | Retains contextual associations across chunks. Prevents semantic separation of fields such as resource utilization and budget amounts |
| Similarity Threshold | 0.75–0.85 | Accurately matches core semantics such as resource specifications and bottleneck descriptions. Filters low-relevance historical report data |
| Single Index Limit | Top 20 entries | Adapts to the low-frequency update feature of weekly or monthly updates. Balances index construction efficiency and data integrity |
maxToken | 4096 token | Adapts to vector encoding requirements for long documents. Prevents information loss caused by long text truncation |
defaultToken | Calibrated based on actual measurements | Adapts to document formats from different sources. Compatible with field structures of cloud billing and monitoring data |
Three Common Misconfiguration Issues
- Phenomenon: Index construction process stops at the final set of files without completion. No progress updates appear in the interface. Cause: Chunk parameters for long documents are not adjusted. Single chunk content exceeds encoding limits. Implicit timeout is triggered.
- Phenomenon: New knowledge base gets stuck during the indexing step. Vectorization process cannot be completed. Cause: Document format support for the corresponding data source is not configured. Specific format fields of cloud billing or stress test reports cannot be recognized.
- Phenomenon: Indexing completes after switching embedding models, but search tests return errors. Cause: The similarity threshold is not updated to match the semantic matching range of the new model. Vector similarity calculation deviation exceeds the threshold range.
How to Confirm Proper Configuration
- View index construction logs in FastGPT v4.17.0. Confirm that the length of chunked text falls within the configured chunk length range.
- Test the vectorization process for a single capacity planning report. Verify that no implicit timeout or text truncation errors occur.
- After switching embedding models, recalibrate the adaptive range of the similarity threshold.
- Check the number of documents after indexing is complete. Ensure it matches the list of documents to be indexed.
The values provided here are common starting points. They should be evaluated 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.