What This Category of Data Looks Like
Maintenance work is typically handled by bodies such as administrative review and reform offices, government service data management bureaus, departmental legal affairs divisions, or approval divisions. Daily processed documents include basic government service item catalogs, implementation lists, service guides, standard material catalogs, flowcharts, and frequently asked questions. Data is mainly sourced from the national basic government service item catalog, administrative licensing item list, power and responsibility list, and local government service item databases. The update frequency is monthly. Each document includes structured fields such as item code, implementing authority, acceptance conditions, and application material list, plus lengthy explanatory text. Field formats must match the catalogs released by higher-level authorities.
Constraints on Vector Models and Indexes
Bulk data updated monthly requires indexes to support incremental synchronization and batch processing. This prevents excessive single-index load from impacting system stability. Mixed document structures with both structured fields and unstructured text require a chunking strategy that balances field-level precise matching and paragraph-level semantic association. This ensures consistent vector encoding quality across different content types. Consistency across multiple data sources requires vector model encoding to adapt to unified field formats. This prevents vector deviations for identical item types from different sources, which reduces subsequent matching accuracy. Accuracy of item definition requires index recall results to strictly match the actual scope of current-level government services. This avoids cross-hierarchical item confusion that leads to inconsistent service standards.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the natural length of service guide paragraphs and item fields, avoids breaking business semantics during chunking |
| Overlap Length | 100–200 characters | Preserves cross-chunk contextual association, ensures vector integrity for cross-paragraph content such as acceptance conditions |
maxToken | 8192 | Adapts to the maximum input limit of Qwen3-Embedding-8B, avoids truncating critical item codes and material lists |
| Similarity Threshold | 0.75–0.85, calibrated via actual testing | Distinguishes current-level items from similar entries in higher-level catalogs, reduces risk of scope confusion |
| Single Search Limit | Top 10 entries | Matches the hierarchical association count of government items, avoids recalling too many irrelevant entries |
defaultToken | 1024 | Unifies basic token configuration during batch indexing, adapts to the scale of monthly updated bulk data |
Three Common Misconfigurations
- The interface displays files stuck in "indexing" status with no progress updates. This occurs when the local embedding model API access address is not configured properly, or when identically named embedding models are configured simultaneously, resulting in overwritten settings.
- A large number of mismatched items appear between index recall results and higher-level catalogs. This happens when the similarity threshold is set too low, incorrectly recalling non-current-level items that are semantically similar but have different encodings.
- Some application material field vectors are missing after batch indexing. This occurs when the chunk length is set too large, truncating paragraphs that contain complete material lists, leading to failure to encode critical information.
How to Confirm Correct Configuration
- The model management page of FastGPT v4.17.0 is accessed. The embedding model name is confirmed to match the deployed Qwen3-Embedding-8B or M3E, with no duplicate configuration items.
- A single service guide document is uploaded. Indexing is allowed to complete, then the chunk preview is viewed. The chunk length is confirmed to fall within the preset range with no obvious truncation.
- The test query "XX item's application material list" is entered. The number of recalled entries and similarity scores are checked against the preset threshold.
- The monthly batch indexing task is triggered. The indexing logs are checked for token limit exceeded or connection timeout errors.
The values listed here are common starting points. They should be evaluated against local test 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.