What the data for this category looks like
The core data for this category originates from package managers, code repositories, vulnerability databases, and license databases. Four standard document types are regularly generated: SBOM lists, dependency risk reports, license lists, and repair work orders. Most documents use a semi-structured format, with fixed fields including component name, version number, license type, CVE ID, and risk level. Updates occur once daily or per software version. The data structure is relatively standardized but has strong field correlations. The binding relationship between components and their associated risks and licenses must be preserved.
Constraints Imposed by These Characteristics on Vector Models and Indexing
The strong field correlations in this category’s data, plus the requirement to retain component-risk-license binding relationships, mean associated information for a single component cannot be overly split during chunking. The high update frequency requires indexes to support incremental updates, to avoid performance losses from full index reconstruction. Most documents consist of short text combinations, so vector models must adapt to the encoding accuracy of short fields such as component names and CVE IDs. Additionally, since the data is linked to high-severity vulnerabilities and compliance risks, the accuracy of index recall must strictly align with business requirements, to avoid mistakenly recalling low-risk dependencies or missing high-severity items.
Recommended Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the field density of SBOM and risk reports, avoids splitting associated information for a single component |
| Overlap Length | 50–100 characters | Retains component version and risk association information across chunks |
maxToken | 8192 | Adapts to the vector encoding limit for short texts such as open source component names and CVE IDs |
| Similarity Threshold | 0.75–0.85 | Distinguishes matching accuracy between high-severity vulnerabilities and low-risk dependencies |
| Single Recall Limit | Top 20 results | Balances vulnerability matching recall rate and query latency |
defaultToken | Calibrated via actual testing | Adapts to context requirements for local or privately deployed vector models |
Three Common Misconfigurations
- Symptom: Index fails to build when using a PostgreSQL database and Docker deployment, on an 8c16G CPU-only virtual machine with small file sizes. Cause: Chunk length and recall limit were not adjusted, causing vector computation memory usage to exceed allocated thresholds.
- Symptom: Persistent errors occur when connecting to the oneapi embedding model. Cause: The indexing model was not configured separately; the generic oneapi interface was reused directly, and no dedicated vector model endpoint was specified.
- Symptom: No valid index results are generated after importing Excel files and multi-dimensional documents from a Feishu folder. Cause: Parsing adaptation for the corresponding file formats was not enabled, and no field mapping rules were configured, so supply chain-related component information could not be extracted.
How to Verify Proper Configuration
- Upload a test SBOM list, check the vector index generation status in the FastGPT v4.17.0 admin backend, and confirm there are no field loss prompts
- Initiate a component vulnerability matching query, verify that the similarity values of the recalled results fall within the configured threshold range
- Check the index update logs to confirm that daily or per-version incremental update tasks are running normally
- Verify connection to a private vector model, check that the vector encoding return results have no format errors
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.