What the data for this category looks like
Data sources for state-owned large bank research reports include public and internal reports produced by the internal macro research department and financial markets department, plus targeted cooperative research reports from top securities firms. Three update schedules apply:
- Internal special reports are updated quarterly or monthly
- Public industry reports are synchronized with securities firm release schedules
- Regulatory temporary reports are updated on event trigger
Documents have a fixed structure with four modules: core insights, market data tables, industry policy analysis, and risk warnings. Fields include report number, issuing institution, release date, involved industries, core rating, target price point, and more. Units mostly follow financial standards: percentage, 100 million yuan, basis points. Some internal reports include encrypted permission identifier fields.
What constraints these characteristics impose on workflow orchestration
Hierarchical permission requirements for state-owned large bank research reports require configuring role permission verification nodes to distinguish call scopes between public and internal reports. Fixed document structure requires text extraction nodes to match fixed module keywords directionally, avoiding redundant data from full parsing. Multi-rate update frequency requires setting layered scheduled synchronization rules to adapt to update cycles of different report types. Specialized financial fields require standardization processing before vector database import to avoid semantic deviation during retrieval.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Global Knowledge Base Dynamic Switch Rule | Match the corresponding knowledge base ID based on the user's department/role | Different departments of state-owned large banks focus on different report industries, and there are internal report permission restrictions |
Text Extraction Keyword Matching | Core Insights, Market Data, Risk Warnings | Matches fixed document modules of state-owned large bank research reports to directionally extract core content |
Vector Recall Count | Top 8 results | Research report content has high professionalism. Too many recalls will increase context redundancy. Too few will fail to cover core insights |
Code Run Node Timeout | 600 seconds | Research report data volume is large. Batch parsing and field standardization processing require long execution time |
Database Connection Timeout | 300 seconds | Adapts to network latency of internal databases of state-owned large banks, avoiding connection timeout errors |
Recall Similarity Threshold | 0.75–0.85 | Filters low-relevance search results, matching the professional semantic features of research report content |
The parameter values provided on this page are all conventional recommendations used to determine the starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing values.
Three common mistakes
- Phenomenon: The global variable "Select Knowledge Base" is not dynamically assigned, and AI retrieval only calls the default knowledge base. Cause: No rule configured to match knowledge base ID based on department/role, only a single knowledge base is fixedly bound.
- Phenomenon: Text extraction node returns empty results, workflow verification fails. Cause: Fixed module keywords of state-owned large bank research reports are not matched, or keyword format does not match document typesetting.
- Phenomenon: An error "Workflow verification failed, please check for missing or missing values, and whether connections are normal" is reported when calling the database connection plugin. Cause: Required connection parameters for PostgreSQL are not configured, or access permissions to the internal database of state-owned large banks are not enabled.
How to confirm the configuration is correct
- Trigger a test workflow, check the global variable log, confirm that users from the corresponding department are automatically matched to the correct knowledge base.
- Upload a standard state-owned large bank research report, run the text extraction node, confirm that content from the specified modules is extracted.
- After running the code node, check the input parameters of the AI node, confirm that the result field from code running is correctly bound to the context.
- Test the PostgreSQL database connection, check the workflow verification log, confirm that there are no parameter missing or permission issues.
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.