What this category of data looks like
This category of data primarily 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 subject name, residence address, shareholder information, license type, application material number, and others. Most single pieces of data are a mix of structured forms and unstructured documents, with no unified fixed long-text structure.
What constraints these characteristics impose on the vector models and indexes link
Daily updated data requires indexes to support incremental synchronization, avoiding resource consumption caused by full reconstruction. The mixed data characteristics of structured forms and unstructured documents require flexible chunking rules, while ensuring consistent vector mapping for structured fields. Data from multiple sources needs unified field mapping to prevent field misalignment in the index. For core fields related to business access, the vector matching threshold must strictly correspond to business rules, avoiding licensing determination errors caused by matching deviations.
How to configure the settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the mixed form and document text length of this category, avoiding losing context from overly small chunks or reduced vector accuracy from overly long chunks |
| Overlap Length | 100–150 characters | Ensures context continuity between adjacent chunks, covering key business fields such as residence address and shareholder information that span chunks |
| Similarity Threshold | 0.75–0.85 | Matches rule texts related to business access, avoiding overly low values that cause false matches and overly high values that lead to insufficient recall |
defaultToken | 4096 | Adapts to the input limits of common embedding models, covering the total text length of materials processed in a single batch for this category |
maxToken | 8192 | Supports full-text indexing of long texts, processing application materials including complete articles of association |
| Single Search Limit | Top 8 entries | Balances recall efficiency and the material coverage required for business judgment, avoiding excessive redundant results that disrupt process guidance |
Three common misconfigurations
- Phenomenon: The exported dataset.csv from the knowledge base only contains the index field and no content field. Cause: The text extraction rule after chunking is not configured correctly, only index metadata is stored without associating the text content of the original business documents.
- Phenomenon: Integration of the index model fails after Docker deployment, returning a connection timeout error. Cause: The port mapping for the index model is not opened in the docker-compose configuration, or the API key is not correctly bound to the FastGPT vector model configuration item.
- Phenomenon: The vector matching results in the name verification step have large deviations, with frequent false judgments. Cause: The similarity threshold is set in violation of business rules, incorrectly matching unrelated residence information or shareholder materials as target business texts.
How to confirm the configuration is correct
- On the knowledge base settings page of FastGPT v4.17.0, manually upload a standard establishment registration application, view the chunk preview content, and confirm that each chunk contains complete business text with no missing content.
- View the vector model call logs, confirm that the
defaultTokenandmaxTokenconfigurations are correctly loaded, with no input length truncation errors. - Simulate submitting a test application including a residence certificate, view the recall results of the process guidance, and confirm that the corresponding pre-licensing rule text is included.
- Check the running status of the incremental synchronization task, confirm that daily updated multi-source data can be normally synchronized to the index database.
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 2026-09-28.