Reference only; verify against the target FastGPT release and deployment documentation.
What Data for This Category Looks Like
Core data for this category comes from the national basic catalog of government service items, administrative licensing item list, power and responsibility list, and local government service item databases. Daily maintained documents include basic government service item catalogs, implementation lists, service guides, standard material catalogs, flowcharts, and frequently asked questions. Data updates occur on a monthly basis. Each document includes standardized fields such as item code, acceptance conditions, application material details, and service procedures. No non-standard business units are used. All content follows standardized processing rules for government service items.
Constraints on Vector Models and Indexing
The monthly update rhythm requires indexes to support incremental synchronization. This reduces resource consumption during daily maintenance. Multi-source standardized data requires limiting the field range for vector encoding. Only core business fields such as item code, acceptance conditions, and application materials are included. This avoids unstructured annotation content interfering with vector matching. Diverse document types require chunking strategies adapted to different content structures. Long text in service guides must be split to a reasonable length. Associated text for flowcharts must be bound to corresponding nodes. This ensures the integrity of vector semantics. As a background rule maintenance tool, it does not need to generate personalized vectors for individual service cases. Only a unified vector index for global item rules is required.
How to Configure
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the long text structure of service guides and implementation lists, avoids semantic fragmentation |
| Overlap Length | 100–150 characters | Preserves semantic connection between chunks, fits incremental indexing scenarios for monthly updates |
defaultToken | 4096 | Matches the average semantic length of most government documents, meets basic vector generation requirements |
| Similarity Threshold | 0.75–0.85 | Differentiates rule differences between different versions of the same item, avoids mismatching |
| Single Search Limit | Top 10 entries | Covers associated rules for local-level items, meets recall requirements for catalog comparison |
maxToken | 8192 | Adapts to the long document processing limit during batch indexing, avoids truncating core business fields |
Three Common Configuration Mistakes
- The index model dropdown list is empty and cannot be selected. The cause is that the API key or service address for the corresponding model has not been configured, and model access verification has not been completed.
- When using Ollama for local knowledge bases, the matching degree between indexes and text models is low. The cause is that the chunk length has not been adjusted for government standardized fields, leading to deviations in vector semantic matching.
- Timeout errors occur when calling index models accessed via One API. The cause is that
defaultTokenhas not been set to a reasonable value adapted to batch indexing, triggering server-side timeout limits.
How to Confirm Correct Configuration
- Manually import a monthly updated local implementation list document. Check whether the indexing task starts and completes normally.
- Initiate a similarity search for item rules. Confirm that the number of returned results matches the configured single search limit.
- View indexing logs. Confirm that only updated documents are incrementally synchronized, and no full reindexing tasks are triggered.
- Verify the chunked text fragments. Confirm that no core business fields have been truncated.
The values provided here are common starting points. They 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.