What the data for this category looks like
Insurance product yield data comes from official product manuals and annual actuarial reports released by insurance companies. It also comes from product information filed with regulatory authorities. The update cadence varies significantly across different insurance types. Fixed yield data for traditional protection products is updated at a low frequency. Settlement yields for universal and unit-linked products are updated daily or weekly. Each data entry includes these fields: unique product identifier, product name, coverage term, payment method, corresponding yield indicator, and effective period. All fields have clear business meanings and associated units. For example, payment term is measured in years. Sum insured is measured in ten thousand yuan.
What constraints these characteristics impose on forms and interactions
Insurance product yield data has scattered sources and highly varied update cadences. This requires the forms and interactions link to support multi-source data pull configuration. It also requires presetting update frequency verification rules based on insurance type. All fields are bound to clear business meanings and units. Input items must match the exclusive fields of insurance products. Field identifiers cannot be adjusted arbitrarily. Field complexity varies greatly across different insurance types. Universal and unit-linked products require loading multiple account yield fields. The interaction must support dynamic expansion and collapse of corresponding modules. The data effective period must match the query time. The interaction link must enforce verification that the query time entered falls within the data effective range. This avoids returning invalid information.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Insurance product data includes multiple fields. A long context can fully transmit product information and avoid truncating critical yield indicators |
recall_top_k | Top 8–12 entries | There are many insurance products. Too many recalled entries will increase processing delay. Too few will fail to cover the target products of user queries |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Filing documents for insurance products are usually lengthy. Sufficient time must be reserved for parsing and field extraction |
form_field_validate | Enabled | Insurance product fields have strict business rules. Enabling verification can prevent invalid inputs from entering the workflow |
workflow_input_trigger | Trigger based on specified field matching | Insurance queries must focus on yield-related fields to avoid triggering the workflow with irrelevant inputs |
The parameter values provided on this page are common recommendations used as starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: After the workflow runs, the final reply includes the full content of a previous AI conversation. Cause: The context truncation parameter is not configured, or
maxContextis not set to retain only the target input range, causing previous conversation content to be included in the final output. - Phenomenon: A
408 Request Timeouterror is returned after form submission. Cause:PARSE_FILE_TIMEOUT_SECONDSis set too short, causing a timeout before parsing of the insurance product document is completed. - Phenomenon: The knowledge base recall results include the text
Citation Marker: [1]. Cause: The knowledge base citation marker hiding configuration is not enabled, or the configuration item is not correctly associated with the recall link of the current workflow.
How to Confirm the Configuration Is Complete
- Upload a single insurance product filing document. Check whether the
PARSE_FILE_TIMEOUT_SECONDSconfiguration matches the time required for document parsing. Confirm that there are no timeout errors during the parsing process. - Simulate a query containing specific insurance product keywords. Check whether the number of recall results falls within the range configured by
recall_top_k. - Trigger a workflow test. Check whether the final output only includes the content of the target AI conversation, with no residual previous conversation content.
- Submit form inputs that do not comply with business rules. Check whether the
form_field_validateverification logic is triggered and a corresponding error prompt is returned.
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.