What the data for this category looks like
Core data for this category comes from national public resource trading platforms, local trading platforms, project approval systems, and bidding and tendering supervision systems. Data updates occur daily. Daily processed documents include bidding announcements, qualification pre-qualification documents, bidding documents, tender documents, bid evaluation reports, successful bid candidate notices, and successful bid result announcements. Covered structured fields include qualifications, performance records, bill of quantities, and construction periods. It also includes unstructured materials such as review notes and objection and complaint submissions. Data contributors include development and reform departments, industry authorities for housing and urban-rural development, transportation, water conservancy, public resource trading centers, and bidding agency institutions.
Constraints imposed by these characteristics on knowledge base retrieval and recall
Daily updated data sources require retrieval systems to support incremental synchronization and incremental recall. This prevents performance losses from full retrieval. Mixed document types require retrieval modes to balance field matching and full-text search. This accurately matches professional fields like qualifications and bill of quantities. Document volume grows as projects advance. This requires controlling the single retrieval context length to avoid exceeding large language model processing limits. Errors directly affect the validity of bid winning results. This requires recall results to meet high accuracy and relevance standards. The system must also adapt to multi-document associated review business scenarios.
Configuration Settings
FastGPT v4.17.0 includes the following configuration items:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Matches the precision of professional terms in bidding and tendering documents, filters low-relevance non-business data |
limit | Top 10 entries | Covers multi-document association needs for section splitting and qualification condition checking, while controlling the context length of single retrieval |
searchMode | Full-text + field retrieval | Adapts to the mixed characteristics of structured fields and unstructured text in bidding documents and tender documents |
usingReRank | Enabled | Improves sorting accuracy for long documents such as bid evaluation reports and successful bid notices, optimizes associated review effects |
datasetSearchUsingExtensionQuery | Enabled | Supplements implied qualification conditions in bidding announcements, matches qualification and performance requirements in tender documents |
collectionIds | Bind dedicated public resource trading datasets | Limits retrieval scope, avoids interference from cross-category unrelated data in search results |
Three Common Configuration Errors
- Phenomenon: Search results include government procurement documents unrelated to construction bidding and tendering operations. Cause: The
collectionIdsparameter is not configured to limit the dedicated dataset, allowing cross-category public resource data to be included in results. - Phenomenon: Excel-format tender documents and bill of quantities cannot be correctly retrieved. Cause: Corresponding file format parsing capabilities are not enabled, only basic text format document parsing is supported.
- Phenomenon: Single retrieval triggers a context token limit error, or returned results are forcibly truncated. Cause: The
limitparameter is not set appropriately, and theusingReRankoption is not used to compress the context length of valid results, leading to exceeding the large language model’s processing limits.
How to Verify the Configuration
- Import a local bidding announcement and its corresponding tender document, run a retrieval, and check that returned results only include relevant documents for this category, with no cross-category interfering data.
- Upload an Excel-format bill of quantities file, run a retrieval, and confirm that the file content is correctly split and included in the retrieval scope.
- Initiate a batch retrieval test, and observe whether the number of returned results and similarity matching degree align with the preset
similarityandlimitconfigurations. - View retrieval logs, and confirm that the extended query generated by
datasetSearchUsingExtensionQueryis correctly applied to the retrieval request.
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.