What This Category of Data Entails
This category covers data related to fiscal expenditure performance evaluation for party building learning Q&A. Data sources include the unified budget management system, project application materials, fund payment records, business ledgers, and satisfaction surveys. The update frequency is annual. Daily documents include performance target forms, self-assessment forms, performance evaluation reports, supporting material lists, and rectification reports. Some documents also link performance indicators that integrate party building and business work. Data fields mostly involve project numbers, fund amounts, performance indicator completion status, rectification measures, and other items. There are no fixed unified units. Information association must be matched based on specific project scenarios.
Constraints Imposed on the Knowledge Base Retrieval and Recall Link
The annual update frequency means high-frequency incremental indexing is not needed. However, single-batch indexing data volume is large, so the process must support batch indexing. Significant structural differences exist across multiple document types. The retrieval link must be compatible with text parsing results of different formats. Data fields include project numbers, fund amounts, performance indicator completion status, and other items. Retrieval must accurately match project-related information to avoid interference from irrelevant results. For the party building learning Q&A scenario, results must cover content that integrates policies and business work. This raises the accuracy requirement for semantic matching. The system must also link supporting materials and performance report content. The recall link must support cross-document associated retrieval to ensure information covering the complete performance evaluation workflow is retrieved.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Meets accuracy requirements for matching performance evaluation text. Prevents irrelevant results if the threshold is too low, and avoids missing relevant supporting materials if the threshold is too high |
limit | Top 10–15 results | Covers multiple document types required for single-project performance evaluation, including self-assessment forms, reports, and supporting materials. Prevents incomplete information caused by too few recalled results |
searchMode | Semantic search | Adapts to semantic matching needs for unstructured text such as performance indicators and rectification measures. Meets the scenario of combining policies and business work for party building learning Q&A |
usingReRank | Enabled | Performs secondary ranking on initial recall results. Corrects deviations in semantic matching and prioritizes content with higher relevance to performance targets |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands relevant performance evaluation keywords based on user questions. Supplements hidden associated information such as project numbers and fund categories |
collectionIds | Performance evaluation-specific dataset ID | Limits retrieval scope to document collections related to fiscal expenditure performance evaluation. Prevents data from other categories from being included |
Three Common Misconfigurations
- Issue: The number of results returned after a search is far lower than the value set in the
limitconfiguration, or no relevant results are returned. Cause: Thesimilaritythreshold is set too high, filtering out supporting materials with weak but relevant association to performance targets. - Issue: Retrieval results include non-performance evaluation documents such as budget preparation materials. Cause:
collectionIdsis not limited to the performance evaluation-specific dataset, so the retrieval scope covers document collections from other categories. - Issue: Search results do not link to project supporting materials, and only return content from performance self-assessment forms. Cause:
datasetSearchUsingExtensionQueryis not enabled. The system does not automatically expand associated keywords such as project numbers and fund categories, so it cannot cover cross-document associated information.
How to Confirm Configuration Is Correct
- Access the knowledge base management page of FastGPT v4.17.0. Check whether
collectionIdsare bound to the performance evaluation-specific dataset. - Submit a test question such as "The integration of performance self-assessment and party building for a certain project". Check whether the number of returned results matches the value set in the
limitconfiguration. - Review the ranking of retrieval results. Confirm that high-relevance performance evaluation reports and supporting materials appear at the top to verify whether
usingReRankis active. - Test the extended query function: Enter a question that only includes the project name. Confirm that the system automatically supplements relevant keywords such as performance indicators and fund amounts.
The values provided here are common starting points. Adjustments should be made based on actual samples and scenarios.
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.