What this category’s data looks like
Data mainly comes from standardized party building reading materials issued by the group’s party committee publicity department, monthly learning reports submitted by grassroots party branches, and policy documents released by the superior state-owned assets supervision and administration commission party committee. Update rhythm is adjusted synchronously with the release of superior documents. Routine internal reports are summarized and updated monthly. Most documents use rich-text formats with hierarchical headings, including fields such as document title, issuing authority, document number, and effective date. The main body is mostly formal written language, and the length of single documents varies widely, ranging from thousands to tens of thousands of characters.
What constraints do these characteristics impose on knowledge base retrieval and recall
Party building data sources are scattered across different internal management modules. Associated retrieval across multiple datasets is required to avoid missing learning cases from grassroots party branches and original texts of superior policies. The wide range of document lengths requires retaining chapter integrity during chunking, to prevent disrupting the semantic coherence of process-based content such as three meetings and one lesson and themed party day activities. There are many specialized party building terms, such as dual-carbon party building and standardized branch construction. Professional semantic vectors must be matched to improve retrieval accuracy. The effective date field can be used for time range filtering, helping users retrieve the latest learning materials from recent cycles.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Party building content has high semantic similarity. Too low a value will introduce irrelevant content, while too high a value will miss valid learning materials |
limit | Top 8–12 entries | The context for party building learning Q&A should not be too long, to avoid exceeding token limits, while covering learning cases from multiple branches |
searchMode | Semantic Priority | Most party building content is normative text. Semantic matching better aligns with users' colloquial questions, such as "how to organize themed party day activities" |
usingReRank | Enabled | Multiple similar fragments may be generated after chunking long documents. Re-ranking can screen the core content most relevant to the query |
datasetSearchUsingExtensionQuery | Enabled | Semantic optimization can be applied to users' colloquial questions to match keywords and terms from standardized documents |
collectionIds | Bind the three datasets of party building manuals, branch reports, and superior policy documents | Covers all data sources for party building learning, avoiding missing key learning materials |
Three Common Configuration Errors
- Phenomenon: The returned answer does not annotate metadata such as the title and issuing authority of the source document, making it impossible to verify the authority and source of the content. Cause: The metadata return configuration for retrieval results is not enabled, and the field mapping rules for the associated dataset are not configured.
- Phenomenon: The number of single retrieval results is far lower than the set
limitvalue. Cause:collectionIdsis not configured correctly, and only some party building datasets are bound, leading to restricted retrieval scope. - Phenomenon: The retrieval request returns a timeout error, with a duration exceeding
600 seconds. Cause:usingReRankis not enabled, and the recalled long document chunks are not filtered, resulting in too much redundant content being returned and exceeding the system processing threshold.
How to Confirm Correct Configuration
- Enter the dataset management page of FastGPT v4.17.0, check if the bound dataset IDs include the three target datasets of party building manuals, branch reports, and superior policy documents, to confirm that the
collectionIdsconfiguration is correct. - Initiate a test query, such as "how to carry out themed party day activities for branches", check the metadata fields of the returned results to confirm that information such as document source and release date is included, and verify that the source annotation function for retrieval results is working properly.
- Adjust the
similarityparameter to0.8, initiate the same query again, compare the number of retrieved results and their relevance before and after, to confirm that the similarity threshold configuration takes effect. - After enabling
usingReRank, initiate a query containing a long sentence, check if the returned results are sorted to better match the core needs of the query, and verify that the re-ranking function is working properly.
Note: The configuration values listed above are common starting points. Adjust them based on your own specific samples and use cases.
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.