What this category of data looks like
Data sources include the engineering construction project approval management system, construction drawing review system, enterprise qualification database, and credit platform. Update frequency is daily. Daily documents include construction permit applications, construction drawing review qualification certificates, quality and safety supervision procedures, and completion record forms. Document structure includes fields such as project unique identifier, participating unit qualification level, personnel practice qualification, and approval node status. Single-page document lengths vary significantly, and some materials include multi-page attachments and associated approval numbers.
What constraints do these characteristics impose on the knowledge base retrieval and recall workflow
Daily updated data sources require the retrieval pipeline to support incremental synchronization to avoid full-volume repeated pulls that consume system resources. Document structures with multiple fields and associated unique project identifiers require retrieval to accurately match core fields such as project numbers and participating unit qualifications, to avoid recalling approval materials from unrelated projects. Significant variation in single-page document lengths and the presence of multi-page attachments require the total length of recalled context to fit the model window, preventing overflow that causes content loss or invalid citation markers. The accuracy of participating unit qualifications and personnel practice information directly affects approval outcomes, requiring recalled documents to have high confidence to avoid introducing incorrect information that leads to unpermitted construction or failed completion record filing.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75-0.85 | Engineering approval documents have strict field requirements. This threshold filters irrelevant recall results while retaining core qualification and approval materials |
limit | Top 10 entries | Balances context length and material coverage, avoiding excessive redundant content that exceeds the model window |
searchMode | Exact match | Engineering approval documents have clear fields and business logic. Exact matching avoids recalling approval materials from unrelated projects |
usingReRank | Enabled | Documents with multiple field associations require reranking to optimize relevance sorting, improving recall accuracy for qualifications and approval nodes |
datasetSearchUsingExtensionQuery | Enabled | Approval scenarios involve a large number of technical terms. Expanded queries match synonymous expressions, improving cross-document associated recall effectiveness |
collectionIds | Bind the exclusive knowledge base collection ID for engineering construction project approval | Ensure retrieval only calls compliant data for this category, avoiding introduction of unrelated business documents |
Three Common Misconfigurations
- Setting
limitto 2000 results in no recalled knowledge base content included in model outputs. The total length of recalled documents exceeds the default context window of FastGPT v4.17.0, causing the system to truncate and lose citation association markers. - Knowledge base queries return results in local tests but no output when called via external release channels. This occurs because
collectionIdsis not properly configured, so external channels cannot access the bound exclusive knowledge base collection, and only the default dataset is used during local testing. - Recall results include a large number of approval materials from non-target projects, requiring manual additional filtering of invalid content. This happens because the
similaritythreshold is set below 0.70, and fuzzy matching recalls qualification and application documents from unrelated projects.
How to Verify Proper Configuration
- After enabling
datasetSearchUsingExtensionQuery, run a query using the term "Construction permit application material list", and confirm that recall results include target documents such as construction permit applications and construction drawing review qualification certificates. - Adjust the
similaritythreshold to 0.75, run a query for "a construction company's qualification level", and confirm that recall results only include qualification filing documents for that company, with no information from unrelated enterprises. - Configure
limitto Top 8 entries, review reference fragments in model outputs, and confirm that key field content for at least 3 core approval materials is included. - Check call logs for external release channels, confirm that correct
collectionIdsare included in request parameters, with no permission errors or dataset mismatch prompts.
The values provided are common starting points and should be evaluated against the applicable sample data.
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.