What the data for this category looks like
Ledger data for government and enterprise IT services originates from daily submission documents for internal communication and operations, project implementation, and customer service. Update frequency aligns with business milestones. Some core operations ledgers are synced daily. Each document combines structured tables and unstructured descriptions, with fields including ledger ID, affiliated operating entity, submission cycle, event details, and disposal result. Supported units include items, person-times, ten thousand yuan, and duration. Individual document length usually falls between 500 and 3000 characters.
What constraints these characteristics impose on knowledge base retrieval and recall
Common structured fields require retrieval to support precise matching by specified fields, to avoid irrelevant results in final reports. Flexible update frequency requires recall logic to adapt to data sources with different sync cycles, ensuring timeliness of retrieved data. Wide variation in individual document length requires adjusting chunking rules to preserve complete key fields, avoiding loss of cross-paragraph associated information. Multiple unit fields require unified unit conversion logic during retrieval, preventing recall failures due to unit mismatches.
How to Configure Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Aligns with structured field matching precision for government and enterprise ledgers, avoids low-relevance results in reports |
limit | Top 8 entries | Balances context length for report generation and information completeness, supports multi-entry ledger summary needs |
searchMode | keyword+vector | Combines structured field keyword matching and semantic recall, covers precise ledger IDs and fuzzy event descriptions |
usingReRank | Enabled | Re-sorts recall results by relevance to the query, corrects bias from single vector recall |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands related fields for user ledger queries, improves recall coverage |
collectionIds | Exclusive dataset ID bound to the business | Isolates ledger data from different government and enterprise customers, prevents cross-tenant information leakage |
Three Common Configuration Errors
- Knowledge base queries return unrelated scattered content, and aggregation by ledger fields is not applied. The cause is failure to set
searchModeto hybrid retrieval mode; only using single vector recall leads to failed field matching. - Generated report content is incomplete, with key ledger entries missing. The cause is failure to adapt chunking rules to long document structure, leading to loss of cross-paragraph field association information after splitting.
- Knowledge base cannot complete file upload, and the interface prompts upload failure. The cause is failure to bind the exclusive dataset corresponding to
collectionIds, or uploaded file format does not meet structured ledger requirements.
How to Confirm Correct Configuration
- Upload a single structured ledger document, check if retrieved results include core field information from the document during retrieval.
- Submit a precise query that includes a ledger ID, verify that the
similarityscore of returned results falls within the preset range. - Submit a summary query across multiple ledgers, confirm that the number of recalled results matches the upper limit set by the
limitconfiguration. - Trigger a query for an unknown business scenario, confirm that the system only returns ledger-related content covered by the knowledge base, with no unsubstantiated generated information.
The values provided here are common starting points, and 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.