What the data for this category looks like
Data for this category primarily comes from the 12345 citizen hotline platform, contractor business systems, knowledge bases, and return visit evaluation data. The update frequency is daily. Daily documents include request registration forms, dispatch records, handling replies, return visit records, delay applications, and more. Each entry contains fields such as request number, public request content, handling deadline, responsible unit, reply content, and return visit result. All documents form a closed association loop via the request number. The content uses a mixed format of structured and unstructured data.
Constraints on vector models and indexing
The daily data update requirement means indexes must support incremental refresh. This avoids resource consumption from full index rebuilding. The presence of multiple document types and associated fields requires retaining key linked information during chunking. This prevents breaking the closed loop of ticket processing. Mixed structured and unstructured data requires index configurations to adapt to content splitting for different formats. Ledger summary requires association across multiple process links. This means indexes must support associated recall of multiple documents, while filtering low-relevance redundant content.
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 average length of a single 12345 ticket entry, avoids splitting associated information between requests and handling |
| Overlap Length | 50–100 characters | Retains key fields such as request number across adjacent chunks, ensures complete ticket context can be restored during retrieval |
maxToken | 4096 token | Matches the length limit for multi-document concatenation during ledger summary, avoids truncating key reply or return visit content |
| Similarity Threshold | 0.75–0.85, calibrated via actual testing | Filters low-relevance non-target tickets, prevents unrelated content from being included in ledger summary |
| Single Search Limit | Top 10 entries | Controls the number of documents returned by retrieval, adapts to information filtering needs during ledger generation |
defaultToken | 2048 token | Configures the basic retrieval context length, balances recall accuracy and computing resource consumption |
Three common mistakes
- Phenomenon: When uploading a document, it initially shows 8 chunks, then later changes to 13 chunks with duplicate entries. Cause: Deduplication verification for the index is not enabled. Duplicate fields within tickets are recognized repeatedly during chunking, or duplicate sharding logic triggers during upload.
- Phenomenon: After upgrading from version 4.9.0 to 4.9.3, previously queryable ticket content can no longer be retrieved. Cause: The index format changed after the upgrade. The vector index for the corresponding ticket was not regenerated, so the old index cannot be matched by the new version.
- Phenomenon: After uploading an Excel-format request statistics table, the index content appears garbled. Cause: No structured data chunking rules are configured. Direct text-based chunking splits table cells, losing row and column association information.
How to confirm correct configuration
- Upload a single complete ticket document, confirm the number of chunks matches expectations, with no duplicate chunk entries.
- Retrieve associated documents for a specified ticket, verify the returned results include full process content such as requests, handling, and return visits.
- Run a ledger summary task, check the returned document set does not include entries exceeding the set search limit.
- Adjust the similarity threshold, compare changes in the relevance of search results, confirm the threshold meets business screening requirements.
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.