Ledger Summary and Report Generation for Legal Compliance and Major Risk Management: Knowledge Base Retrieval and Recall

Ledger Summary and Report Generation for Legal Compliance and Major Risk Management: Knowledge Base Retrieval and Recall

What the data for this category looks like

Data for this category comes from enterprise contract management systems, compliance risk databases, law and regulation repositories, case management systems, and reporting platforms. The update frequency is monthly. Daily processed documents include compliance risk lists, contract legal review opinions, major issue legal opinions, compliance review forms, and violation report investigation results. Each document includes fixed fields such as risk ID, review date, compliance conclusion, and involved business module. Common document formats are structured tables, semi-structured approval workflow documents, and standard regulatory texts.

Multi-source, heterogeneous data sources require the retrieval link to support different compliance document formats, to avoid missing key information due to format mismatches. The monthly update frequency means index updates do not need frequent triggering; fixed-cycle synchronization is sufficient. The range of document types includes risk lists, review opinions, and other business files, so differentiated weight configuration for different documents is needed to ensure core compliance risk content is recalled first. Additionally, the consequences of errors in this category are severe. The retrieval link must ensure the accuracy of recalled content, to avoid compliance deviations in ledger summary or report generation caused by incorrect recalls.

How to set the configurations

Configuration ItemRecommended SettingRationale
similarity0.72–0.88Legal compliance data has strict requirements for recall accuracy, to avoid introducing irrelevant compliance documents that interfere with ledger summary
limitTop 6–10 resultsLedger summary needs to cover multi-dimensional compliance information. Too many results will exceed the context window limit, while too few may miss key risk content
usingReRankEnabledCompliance documents have strong professionalism. Reranking can filter low-relevance recall results and improve the content credibility of report generation
datasetSearchUsingExtensionQueryEnabledIndustry general expressions related to compliance can be extended into search terms, to cover potentially relevant compliance risk documents
collectionIdsSpecify exclusive collection IDs for legal complianceAvoid retrieving non-category business data, to ensure recalled content only comes from compliance-related data sources

Three common misconfigurations

  • Failing to recreate the vector index after replacing the embedding model. This causes a significant drop in the relevance of knowledge base retrieval results, and some previously imported compliance documents cannot be recalled. The root cause is that the corresponding vector index was not regenerated, and the original index does not match the vector space of the new embedding model.
  • Mixing PostgreSQL and Milvus as vector storage engines. This leads to repeated or missing recall results in some scenarios. The root cause is that the two storage engines have inconsistent vector similarity calculation logic, and retrieval rules were not unified during configuration.
  • Uploading full compliance standard PDFs without chunk optimization. This results in scattered returned content when searching for relevant compliance clauses, making it impossible to match precise compliance requirements. The root cause is that long documents were not properly chunked, leading to dilution of the vector features of key compliance clauses.

How to verify the configuration is correct

  • Check if the vector index has been updated along with the replacement of the embedding model. This can be confirmed by viewing the index update log of the FastGPT v4.17.0 knowledge base collection.
  • Test retrieval of a compliance risk list, and verify that the number of recalled results matches the set similarity threshold.
  • Verify whether the usingReRank function is active. Compare the relevance of retrieval results when reranking is enabled versus disabled to confirm the difference.
  • Confirm that the retrieval scope only covers the legal compliance exclusive collection. Search for non-compliance-related documents to verify that no results are returned.

The values provided here 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.