What Data in This Category Looks Like
This category of data primarily comes from local public data open platforms, integrated big data platforms, departmental business databases, and electronic certificate repositories. Daily processed documents include public data resource catalogs, data open lists, data item descriptions, desensitization rules, interface documents, and update frequency notes. Data is updated on a monthly basis. Documents contain both structured fields and unstructured text. Structured fields cover data item codes, open scope, desensitization methods, interface addresses, and more. Unstructured text includes interface call instructions and update details. Field formats are adjusted based on departmental submission requirements, with no unified fixed unit.
Constraints Imposed on Vector Models and Indexes by These Characteristics
The monthly update requirement means indexes must support incremental updates and regular full refreshes. This prevents a disconnect between index data and actual published data. Documents from multiple sources and formats require adaptive embedding for both structured data items and unstructured interface documents. Unified preprocessing logic must be used to ensure vector consistency. Field requirements for desensitization rules and open scope must filter sensitive information during the embedding stage. This prevents data leakage risks. At the same time, index results must correspond one-to-one with catalog entries. This avoids situations where search results do not match actual published data.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the semantic integrity of data item descriptions and interface documents, avoid semantic breaks within chunks |
| Overlap Length | 100–150 characters | Retain cross-chunk context association, prevent semantic segmentation of data items and interface descriptions |
| Similarity Threshold | 0.72–0.80 | Filter non-compliant data items with low matching degrees, ensure consistency between search results and open catalogs |
defaultToken | 4096 token | Adapt to the embedding length of single-batch data item descriptions, balance computing resources and processing efficiency |
maxToken | 8192 token | Support complete embedding of long-text interface documents, avoid semantic loss caused by long-text truncation |
| Single Search Limit | Top 10 entries | Cover the number of catalog entries submitted by multiple departments, meet the full matching requirements of declaration review |
Three Common Misconfigurations
- Vector search results include non-desensitized sensitive fields. This happens when preprocessing does not remove desensitized sensitive data, and raw data is passed directly to the embedding process. This violates data security requirements.
- Search results return catalog entries that do not match real-time data on the public data open platform. This happens when no monthly full index update is configured, and only an initial one-time index is run. This leads to outdated index data.
- Embedding failures occur during batch import of data open lists. This happens when no reasonable chunk length is set, causing long text fragments to exceed the
maxTokenrange supported by the model. This triggers embedding errors.
How to Verify Correct Configuration
- Import a data item description document. Check the knowledge base storage statistics to confirm that the original file, split file chunks, and embedding vectors are all present. This aligns with FastGPT v4.17.0 storage logic.
- Trigger an incremental index task. Wait for the task to complete, then search for updated catalog entries. Verify that newly submitted departmental data items appear normally in search results.
- Enter a query containing desensitization rule keywords. Check that search results only return compliant open data items, and do not include non-desensitized sensitive information.
- Adjust the similarity threshold to 0.70 and 0.85 for separate tests. Observe changes in the number of search results to confirm that the threshold configuration takes effect.
The values listed here are common starting points, and 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 2026-09-28.