What the data for this category looks like
Data for this category comes from the construction project approval management system, construction drawing review system, enterprise qualification database, and public credit platform. The update frequency is daily. Daily documents include construction permit application materials, construction drawing review qualification certificates, quality and safety supervision procedure documents, completion acceptance record forms, and similar items. Data fields cover approval node information, participating construction units' qualifications, personnel qualifications, project progress status, and similar items. A single document typically includes standardized fields such as project number, handling link, and required submission material list. Some cross-system documents have inconsistent field formats.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Daily updated data requires the retrieval pipeline to support incremental synchronization, to avoid performance loss caused by full re-scanning. Multi-source approval documents have inconsistent field formats, so field standardization alignment must be completed before recall, to ensure that qualification and approval node information exported from different systems can be matched uniformly. Approval links are tied to the full compliance of the project process, so the accuracy of retrieval results directly affects approval efficiency and compliance. The relevance threshold of recall results must be strictly controlled, to avoid irrelevant content interfering with window staff judgments. At the same time, inquiries about approval usually focus on specific links, so retrieval results must accurately match the user's link query needs.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Matches the semantic relevance of engineering approval documents, avoids introducing irrelevant content if set too low, and avoids missing matching results for compliance approval requirements if set too high |
limit | Top 8 entries | Covers multiple approval link materials that may be involved in a single service inquiry, while controlling the context length to adapt to model input limits |
searchMode | Semantic retrieval | Adapts to vague query scenarios in service inquiries, such as matching needs for non-precise keywords like "construction permit handling process" |
usingReRank | Enabled | Re-ranks initially recalled results, corrects deviations in approval node order that may occur in semantic retrieval, and improves the logical rationality of results |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands user inquiries, supplements general terms related to engineering approval, and improves matching accuracy for industry abbreviations and professional jargon |
collectionIds | Bind to exclusive dataset for construction project approval | Limits the retrieval scope, avoids mixing approval data from other categories, and ensures recalled content is strongly relevant to housing and urban-rural construction approval scenarios |
Three Common Configuration Mistakes
- The semantic similarity value of retrieval return results is abnormally high, and logs show vector matching scores far exceed conventional thresholds. The cause is that the
similaritymatching parameter is not calibrated when using thebge-m3vector model. The vector generation logic of the model itself causes the high-score interval to be amplified, which does not meet the relevance requirements of the engineering approval scenario. - Unable to normally obtain knowledge base recall results when calling open interfaces, and returns permission errors. The cause is that the external access permission of the corresponding engineering approval dataset is not configured in the FastGPT platform settings, and permission verification for cross-product integration is not completed.
- The model does not automatically call the knowledge base after triggering question answering, only returns general question and answer content, or cannot retrieve approval-related content in the general search engine template. The cause is that the retrieval trigger rule is not configured, or the template is not bound to the exclusive dataset for construction project approval, resulting in the retrieval scope not covering category-specific documents.
How to Confirm Configuration is Correct
- Submit a simulated service inquiry, such as "What materials are required to apply for a construction permit", and check whether the recall results include documents related to construction permit applications.
- View the retrieval log, confirm that the
similarityscore is within the preset interval, and there are no abnormally high or low matching results. - Test the open interface call, confirm that recall data related to engineering approval can be returned normally, and there are no permission errors.
- Trigger model question answering, confirm that the system automatically calls the knowledge base recall link, and the returned content includes approval information in the exclusive dataset.
The values provided 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.