Data characteristics for this use case
Data sources for rural commercial bank intelligent due diligence reports include internal credit ledgers, People's Bank credit inquiry APIs, National Enterprise Credit Information Publicity System, and local banking and insurance regulatory submission documents. Update frequencies vary by data type. Regulatory submission files update quarterly. Single credit inquiry results take effect immediately. Internal credit approval documents generate in real time alongside approval workflows. Documents use a mixed format of structured tables and unstructured attachments. Fields include unified social credit code, credit subject name, credit limit, approval date, and regulatory rating level. Credit limit is measured in ten thousand yuan. Approval dates use the standard YYYY-MM-DD format.
Constraints for citation sources and traceability workflows
The scattered multi-source nature of due diligence data requires traceability workflows to add unique identifiers for content from different channels. This distinguishes internal credit ledgers from external public data. Inconsistent update frequencies require traceability information to include exact timestamps of data acquisition. This prevents use of expired data across update cycles. The mixed structured and unstructured document structure requires traceability to support both line number association for structured fields and paragraph location for unstructured attachments. The presence of unique identifier fields requires traceability linking keys to prioritize the unified social credit code. This avoids matching errors for subjects.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
retrieve_top_k | Top 8-12 entries | Rural commercial bank due diligence reports require coverage of multi-dimensional compliance and financial data. Too many entries causes content redundancy. Too few entries misses critical associated information |
similarity_threshold | 0.72-0.85 | Due diligence data for rural commercial banks mostly uses standardized field content. A threshold that is too low introduces irrelevant public documents. A threshold that is too high misses associated data for the same subject |
source_tag_enable | Enabled | Due diligence reports must clearly label data sources to meet local regulatory compliance disclosure requirements |
citation_chunk_length | 800-1200 characters | Due diligence documents are mostly long-form text. Too long a chunk causes unclear traceability location. Too short a chunk splits complete compliance clauses |
timestamp_record_enable | Enabled | Update cycles vary across data channels. Timestamps verify the timeliness of cited data |
unique_id_field | Unified social credit code | This field serves as the unique identifier for rural commercial bank subjects. It accurately links multi-source data for the same subject |
The parameter values listed on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Scenario: The application outputs identical content when referencing a knowledge base ID or variable, but an error occurs when passing the variable to the knowledge base configuration. Cause: Variable scope is not configured correctly. Global variables are incorrectly bound to knowledge base retrieval steps that only support context variables.
- Scenario: Mixed retrieval scenarios fail to filter non-due diligence related knowledge base content. Output results include irrelevant general financial documents. Cause: No document type-based retrieval filtering rules are configured. The retrieval scope is not limited to the rural commercial bank due diligence exclusive document library.
- Scenario: After setting a knowledge base citation limit, the number of cited entries exceeds the set value. Cause: The
retrieve_top_kparameter is not synchronized with the front-end displayed citation limit. Only the front-end display parameter is modified, and the actual retrieval parameter is not updated.
How to confirm correct configuration
- Run a single document retrieval test: Upload a single due diligence document labeled with a unified social credit code. Enter a query term for the corresponding subject. Check that returned results include correct document identifiers in their source markers.
- Review traceability information: Open the detail panel for cited content. Confirm that exact data acquisition timestamps and document paragraph location information are present.
- Perform a subject association test: Enter a query term for the same unified social credit code. Check that documents from different sources are correctly linked to the same subject.
- Validate configuration effectiveness: Adjust the similarity threshold. Compare the number of retrieval results before and after the change. Confirm that the configuration has been applied and is active.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.