What Data for This Category Looks Like
Ledger data for residential construction general contracting comes primarily from on-site forms including construction logs, material incoming acceptance receipts, progress payment declaration forms, and subcontract settlement statements. Data updates occur daily or weekly, synced with daily construction milestones. Most documents use structured fields: project number, building number, material name, incoming quantity, acceptance date, construction team, and others. Units include cubic meters, square meters, tons, man-days, and similar units. Some documents include on-site photos or scanned documents as supporting attachments.
What Constraints Do These Characteristics Impose on Knowledge Base Retrieval and Recall
Many structured ledger fields and clear units can cause semantic retrieval matching deviations. For example, "incoming quantity" may be incorrectly matched to content about construction duration. Daily or weekly update cycles require knowledge base retrieval to quickly sync latest ledger data. This avoids using outdated content. Unstructured attachments such as on-site photos and scanned documents add content parsing complexity during retrieval. Retrieval logic must support multimodal content. Single ledger entries vary widely in length, from tens of-word acceptance records to hundreds-word progress descriptions. This creates additional constraints for chunking and recall matching accuracy.
How to Configure Settings
These configuration specifications use FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.6–0.75 | Residential construction ledgers have many structured fields. This range balances precise matching and recall coverage. A too-high threshold misses relevant acceptance records. A too-low threshold introduces irrelevant content |
limit | Top 10–15 entries | Ledger data has many fields. Control the number of recalled entries per batch to avoid context overload. This prevents disruption to subsequent ledger summary and report generation logic |
usingReRank | Enabled | Ledgers contain many similar field descriptions. Reranking filters redundant semantically similar results. This improves the content validity of report generation |
datasetSearchUsingExtensionQuery | Enabled | This setting automatically expands field-associated queries for ledgers. For example, it links "steel material incoming" to documents related to "material acceptance receipts". This adapts to structured data retrieval |
collectionIds | Dedicated collection ID for residential construction ledgers | Isolate knowledge base data from other categories. This avoids retrieving irrelevant content from non-residential construction projects and ensures accurate retrieval scope |
Three Common Misconfigurations
- Specified building and steel material incoming ledger records do not appear in retrieval results. The cause is a too-high
similaritythreshold, such as above 0.8. This filters out many semantically relevant structured records. - A 402 insufficient credit error returns when calling the knowledge base API. Retrieval cannot complete. The cause is missing enterprise-owned API key configuration. Only the platform’s default credit consumption channel is used. Third-party account API calls are not supported.
- Search tests return empty results. The corresponding chunked files contain clear project numbers and material name fields. The cause is disabled
datasetSearchUsingExtensionQuery. Automatic field and document type association cannot run. Structured data is not correctly recalled.
How to Confirm Proper Configuration
- Enter the FastGPT knowledge base test retrieval page. Enter a query term with a specific building number and material name. Check if returned results include the corresponding ledger’s structured fields.
- View the retrieval log. Confirm the called
collectionIdsparameter matches the residential construction ledger dedicated collection. No other category knowledge base data is included. - Adjust the
similaritythreshold. Compare recall results across different thresholds. Confirm a balance between accuracy and recall coverage. - Trigger a full ledger summary task. Check if the knowledge base content referenced in the generated report matches the latest data for the current construction milestone.
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.