What Data for This Category Looks Like
Data for this category originates from the unified budget management system, centralized treasury payment system, accounting system, and asset management system. Updates occur once per year. Daily documents include department final account statements, balance sheets, income and expenditure final account statements, final account explanations, and government financial reports. The overall structure combines multiple structured tables and unstructured explanatory text. Data fields include revenue and expenditure details, asset and liability balances, budget execution difference explanations, and other items. Field units adhere to general financial accounting standards.
Constraints Imposed on Vector Models and Indexing by These Data Characteristics
Annual one-time updates create large data volumes during storage ingestion, which imposes requirements on concurrent processing capabilities for batch indexing. Structured statements and unstructured explanatory text coexist, so vector encoding logic must support both structured fields and long text blocks. Data from multiple homologous systems must use consistent field names and formats, otherwise field matching errors will occur during indexing. The length of unstructured difference explanation texts varies significantly, so a flexible chunking strategy is needed to avoid semantic fragmentation. The annual update rhythm does not require frequent incremental indexing, so a full-update indexing scheduling mode can be used.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Meets semantic integrity requirements for mixed structured tables and unstructured explanatory text, balances vector dimensionality and retrieval efficiency |
| Overlap Length | 100–200 characters | Prevents semantic fragmentation after long text chunking, maintains coherence of cross-block associated information |
| Similarity Threshold | 0.75–0.85 | Filters low-match results unrelated to financial professional content, ensures accuracy of inquiry responses |
| Single Search Limit | Top 5 results | Department final account data entries are relatively concentrated; too many results increase context processing overhead |
defaultToken | 8192 | Meets long text context carrying requirements for financial reports |
maxToken | 16384 | Supports long text context input after merging multiple tables, ensures response completeness |
Three Common Misconfigurations
- Retrieval results fail to link to specific document sources. The symptom is that the original document name and location of the corresponding text block are not shown in the response. The cause is that the document source tracing switch for the knowledge base is not enabled, or metadata fields such as document ID and file name are not retained during chunking.
- Vector model call returns an error. The symptom is that a model call failure status code is displayed on the interface. The cause is that the specified embedding model (such as Doubao-embedding) is not added to the available model list, or the model call key and interface address are not configured correctly.
- Full indexing task times out. The symptom is that indexing progress stalls or fails directly. The cause is that batch processing parameters are not adjusted based on annual data scale, and the number of documents processed in a single batch exceeds the system processing limit.
How to Confirm Configurations Are Correct
- Navigate to the knowledge base indexing configuration page, confirm that the chunk length and overlap length settings match the preset values.
- Submit a test inquiry, check whether the retrieval results include metadata information from the original document.
- Submit a small batch of test data for indexing, verify that the task status completes normally with no error prompts.
- Validate the vector model call link, confirm that normal vector results are generated after inputting test text.
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.