What This Category of Data Looks Like
This category of data originates from social insurance handling systems, tax social insurance premium collection systems, market entity registration information, and shared public security and civil affairs data. Daily processed documents include social insurance registration forms, payment base declaration forms, personnel change forms, social insurance premium verification notices, and personal benefit records. Each individual document contains structured and semi-structured fields such as personnel identification markers, payment bases, and personnel change lists. Data is updated daily, and core fields must be aligned in real time across multiple systems to ensure consistency between registration and payment information.
Constraints on Vector Models and Indexes
Multi-source data access requires indexes to support mixed parsing of structured and semi-structured documents to avoid field misalignment. The daily update feature requires an incremental indexing mechanism to prevent excessive resource consumption from full index reconstruction. Each individual document contains sensitive and precise fields such as personnel identification and payment base. Vector chunking must retain field relevance to prevent loss of identity matching basis after splitting. The index recall logic must also match the semantic association of business fields to ensure the accuracy of service consultation and response.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the field group length of individual business documents to avoid losing personnel identity association after splitting |
| Overlap Length | 100–150 characters | Retains field overlap between adjacent chunks to prevent fragmentation of cross-chunk personnel information |
maxToken | 8192 token | Adapts to the input upper limit of the vector model to ensure complete parsing of the full content of premium verification notices |
| Similarity Threshold | 0.75–0.85 | Filters low-match non-business-related documents to avoid identity matching errors |
| Single Search Limit | Top 10 entries | Controls the number of returned results to meet the rapid response needs of service consultations |
defaultToken | Calibrated based on actual testing | Adapts to vector generation requirements for basic social insurance information |
Three Common Configuration Errors
- Indexing process continues to time out, and the interface displays a request timeout prompt. The cause is that incremental indexing is not enabled, and full scanning of daily updated social insurance data leads to excessive time consumption.
- Fields in vectorized personnel change forms are empty, and the exported dataset has no valid content. The cause is that the structured document parsing switch is not enabled, causing fields to fail to be correctly extracted and vectorized.
- Index data sources cannot be added in a Docker Compose deployment environment, and the platform prompts a connection failure. The cause is that port mapping and environment variables for the vector database are not configured in docker-compose.yml, causing the platform to fail to access the indexing service.
How to Verify Correct Configuration
- Upload a single social insurance registration form, check that the chunks after vector generation retain the integrity of the personnel identification number field.
- Trigger an incremental indexing task, verify that the task duration is not significantly abnormal, and there is no system prompt for full scanning.
- Input a test consultation question, such as "What is the recent premium verification situation of a certain unit", check that the returned results contain key business fields of the corresponding documents.
- View the storage statistics of the vector database, confirm that only newly added social insurance data is synchronized daily, and historical documents are not processed repeatedly.
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.