What the data for this category looks like
Core data for this category comes from the budget management unified system, project application materials, fund payment data, business system ledgers, and satisfaction surveys. Daily processed documents include performance target forms, self-assessment forms, performance evaluation reports, supporting material lists, and rectification reports. Data update frequency is annual. Documents contain fields such as performance indicators, fund usage details, and supporting material association information. Document volume varies widely per file; supporting materials are mostly scanned documents or structured tables.
What constraints these characteristics impose on vector models and indexing
The annual update frequency means high-frequency incremental synchronization for indexes is unnecessary, and a full batch update mode can be used. Multi-source heterogeneous data requires vector models to support unified vectorization of structured tables and unstructured text, avoiding feature bias. Documents include precise fields like performance indicators and fund details, so indexes must retain field-level association capabilities to ensure retrieval results directly correspond to specific performance targets or fund payment records. Most supporting materials are scanned documents or structured tables; when chunking, original layout association information must be retained to avoid losing key supporting logic after splitting.
Configuration Guidelines
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Aligns with the paragraph structure of performance evaluation reports and self-assessment forms, preventing single chunks from containing content spanning multiple performance indicators |
| Overlap Length | 100–150 characters | Retains association information between adjacent performance indicators and supporting materials, preventing business logic from being split apart |
maxToken | 8192 | Matches the input limit of mainstream vector models, supporting complete vectorization of single performance evaluation reports |
| Single Search Limit | Top 6–10 results | Covers core performance targets and supporting records under a single project, balancing retrieval efficiency and result completeness |
| Similarity Threshold | Calibrated based on actual testing | Adjusted according to the performance verification accuracy requirements of this category, ensuring retrieval result matching meets business standards |
| Maximum Context | 50000–70000 characters | Accommodates the full set of performance document content for a single project, supporting complete service inquiry and response scenarios |
Three Common Misconfigurations
- Enabling the Doubao-embedding-large indexing model, entering a custom request URL and APIKey, then clicking test results in an error. This occurs because the interface format requirements of the vector model are not matched, or request header parameter configurations are incorrect.
- Retrieval results include irrelevant content spanning multiple performance indicators after index chunking. This occurs because the chunk length is set too large, causing a single chunk to contain multiple unrelated performance entries, or the overlap length is set insufficiently, losing association logic between indicators.
- Full index update takes longer than expected. This occurs because a batch update strategy is not configured for the low-frequency annual update characteristic, or invalid historical document versions are not filtered.
How to Verify Proper Configuration
- Run a vector model test request, confirm the returned result has no format errors and matches the input performance document content.
- Import a single performance self-assessment form, check that chunking results are split by performance indicator paragraphs, with no cross-indicator chunk content.
- Initiate a simulated service inquiry, retrieve relevant performance documents, confirm the returned results include corresponding performance targets and supporting materials.
- Trigger a full index update, check the update progress and system logs, confirm no timeout or error messages occur.
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.