What This Category of Data Looks Like
Reference only; verify against the target FastGPT release and deployment documentation.
Constraints on Vector Models and Indexing
The daily update feature of the data requires indexes to support incremental construction, avoiding resource consumption and time delays caused by full reconstruction. Document types cover structured application form fields, semi-structured approval notices, and unstructured service guides, so the vector model must support semantic alignment for multiple text types. Administrative licensing items have clear boundaries, so indexing must group by item dimension to prevent invalid cross-item matching. The requirement to associate binary format electronic certificates means the vector generation link needs to support conversion of a small amount of non-text data. The fixed field feature does not require adaptation logic for dynamically added fields.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the semantic integrity of long texts such as service guides and approval decision documents, avoid chunk breaks affecting matching accuracy |
| Overlap Length | 100–150 characters | Cover key approval condition statements across chunks, reduce semantic fragmentation |
| Similarity Threshold | 0.75–0.85 | Meet strict matching requirements for administrative licensing items, avoid misjudging low-correlation application materials |
| Max Context | 8192 token | Support full loading of handling conditions and associated approval documents for a single item, meet full-process context requirements for internal office work |
defaultToken | 4096 token | Adapt to the standard length of vector calculation for single approval materials, unify the vector generation benchmark for different documents |
maxToken | 16384 token | Cover vector requirements for batch processing of multiple electronic certificate documents retrieved across departments |
Three Common Misconfigurations
- Phenomenon: A 200 status code is returned after calling the file upload interface, but usable vectors are not generated after waiting more than 10 minutes, or index construction failure is displayed on the interface. Cause: The automatic trigger rule for daily incremental indexing is not configured, or the data synchronization task is not executed at the set update frequency, leading to backlogged indexing tasks.
- Phenomenon: After entering keywords for the handling conditions of an approval item, search results return documents unrelated to the current item, and the similarity score falls within the set threshold range. Cause: The chunk length is set too small, causing the semantics of key handling conditions to be split, losing core correlation information during vector matching.
- Phenomenon: Abnormally high or low token usage values appear when counting application token usage. Cause:
defaultTokenis not uniformly used as the benchmark length for vector generation, or duplicate header and footer information in approval documents is not filtered during chunking, leading to repeated calculation of invalid tokens.
How to Verify Proper Configuration
- A standard administrative licensing service guide document can be uploaded, the vector generation progress checked, and the notification for completed index construction verified for normal triggering.
- Keywords for the handling conditions of an administrative licensing item can be entered, and the associated documents in the search results verified to belong to the corresponding item. The similarity threshold can be adjusted to meet business matching requirements.
- A standardized application form document can be imported, the generated vector token count checked to fall within the set range of
maxToken, and abnormal truncation or overflow confirmed to be absent. - Index update logs can be viewed, and daily incremental update tasks confirmed to be automatically executed at the set frequency with no failed records.
The values provided are common starting points and should be evaluated against local 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.