What data looks like for this category
Core data for this category comes from the enterprise registration full-process electronic system, the national enterprise credit information publicity system, the electronic business license system, and the residence information database. The update frequency is daily. Daily processed documents include establishment registration applications, articles of association, shareholder resolutions, residence certificates, business licenses, food business license applications, and more. Data fields include entity name, shareholder information, residence address, license category, application material number, and others. All content uses government service standard formats, with no custom units.
What constraints these characteristics impose on the vector models and indexes link
Document formats from multiple system sources have differences, which create requirements for format compatibility during vector extraction. The daily update frequency requires indexes to support incremental synchronization, avoiding excessive time consumption caused by full reconstruction. Daily documents include multiple types of standardized texts with large length differences, requiring flexible chunking rules to adapt to the structure of different documents. At the same time, government verification requires accurate matching of key content such as names, residences, and shareholder information. This places clear requirements for vector recall accuracy, and the quality of recall results must be strictly controlled.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the paragraph length of daily government documents, avoid losing semantic association due to overly long single chunks |
| Overlap Length | 100–200 characters | Ensure semantic continuity between adjacent chunks, prevent key content such as residence addresses and shareholder information from being truncated |
| Similarity Threshold | 0.85–0.92 | Match the accuracy requirements of government verification, filter irrelevant materials with low matching degrees |
| Single Search Limit | Top 10 entries | Control the recall scope, avoid excessive redundant data interfering with the judgment of pre- and post-licensing conditions |
defaultToken | 8192 | Adapt to the vector extraction limit for long documents, cover complete establishment registration application documents |
| Maximum Context | Calibrated based on actual testing | Adapt to employee query needs in internal office scenarios, avoid response timeouts caused by overly long context |
Three common configuration mistakes
- The symptom is that index construction tasks remain stuck in the "running" state with no log updates. Restarting the service after commenting out the index model configuration does not restore normal operation. The cause is that the system retains uncleaned index process cache, or the network connection configuration for the external index service was not updated correctly.
- The symptom is that after creating an index model, the previously bound language model configuration fields are empty. The cause is that some interfaces in FastGPT v4.17.0 do not correctly retain the association binding relationship between multiple models, causing index model creation operations to overwrite language model configuration items.
- The symptom is that a "call limit exceeded" error is returned when using a free index model. The cause is that the call frequency limit for the free model was not configured, or the interface parameter format for the free model was not adapted correctly.
How to confirm the configuration is correct
- Upload a standard establishment registration application document, check whether the vector extraction progress completes normally with no error prompts.
- Initiate a residence address matching query, confirm that the similarity of recall results falls within the preset threshold range.
- View the system's index update logs, confirm that daily incremental synchronization tasks are triggered and completed normally.
- Check the model binding configuration page, confirm that the association relationship between the index model and the language model has been correctly saved.
The values provided 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.