What the data for this category looks like
The core data for this category comes from the national petition information system, local petition systems, the 12345 citizen hotline platform, grassroots governance platforms, and historical petition archives. The update frequency is daily. Commonly processed documents include petition registration forms, acceptance notices, transfer and assignment letters, handling opinions, review and re-examination applications, and resolution plans. Each document includes fixed fields such as request number, handling entity, request content, handling progress, and review status, covering the full process from request submission to final review and closure.
What constraints these characteristics impose on vector models and indexes
Multiple heterogeneous data sources require indexes to support unified mapping of export formats from different systems. Daily update frequency requires configuration to adapt to incremental indexing rules, avoiding repeated processing of full datasets. Diverse document types need matching chunking logic with different lengths, preventing disruption of contextual connections in handling workflows. Legal handling requirements for petition matters require that key fields such as acceptance scope and review status be included in the index embedding range, ensuring search results can support acceptance screening and decision-making. A data volume of hundreds of thousands requires that the vector database index performance adapt to the search response needs of daily office work.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxToken | 8192 | Adapts to the maximum length of single-item content in petition-related documents, and aligns with the supported range of mainstream embedding models for FastGPT v4.17.0 |
defaultToken | 2048 | Matches the average token proportion of daily petition request text, ensuring stable execution of basic embedding tasks |
| Chunk Length | 800–1200 characters | Adapts to the integrity of information in core documents such as petition registration forms and handling opinions, preventing overly fragmented single chunks |
| Overlap Length | 50–100 characters | Retains workflow context across chunks, preventing disruption of the logical connection between transfer and assignment letters and subsequent handling opinions |
| Similarity Threshold | 0.75–0.85 | Accurately screens petition acceptance scopes, avoiding recall of irrelevant historical petition data that may trigger repeated petitions |
| Single Search Limit | Top 10 results | Adapts to the information viewing load of grassroots office staff, avoiding returning excessive redundant results |
Three common misconfigurations
- Symptom: A
query timeouterror with status code 504 is returned when performing searches on the PGSQL vector database. Cause: Incremental indexing is not configured for the hundreds of thousands of daily updated petition data, and the single processing volume of full indexing exceeds the processing limit ofdefaultToken. - Symptom: Search results fail to accurately screen petition acceptance scopes, returning a large volume of non-petition request data. Cause: The request type field in petition registration forms is not included in the index embedding range, causing the model to fail to identify acceptance boundaries.
- Symptom: Search results for some review and re-examination applications are not associated with the original handling opinions. Cause: The chunk overlap length is set too small, and the request number association field across documents is not retained, leading to contextual fragmentation.
How to verify the configuration is correct
- Review the field mapping configuration of the vector index, confirm that the request number, handling entity, and request content fields of core documents such as petition registration forms and handling opinions are included.
- Run a search test for a single petition registration form, verify that the results accurately match the handling opinions with the same request number.
- Check the incremental indexing trigger logs, confirm that index updates for newly added data are completed automatically each day.
- Adjust the similarity threshold, verify that recall results under different thresholds meet the needs of petition acceptance screening.
The values listed above are common starting points, and should be evaluated against the user'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.