What this type of data looks like
Insurance research report data is primarily sourced from the official website of the China Insurance Industry Association, domestic professional insurance information platforms, and publicly disclosed research reports from leading insurance companies. Regular reports are updated quarterly and monthly. Regulatory policy interpretation content is updated in real time alongside new industry regulations. Document structure includes header information such as publishing institution and publication date, core business data tables, product term comparison paragraphs, and risk reminder modules. Fields include report number, new individual life insurance premium scale, property insurance claim payout, number of policies, product pricing parameters, and more. Scale-related data is measured in ten thousand yuan. Policy count is measured in ten thousand units. Pricing parameters are measured in annualized values.
Constraints imposed on multi-turn dialogue and prompt engineering
Insurance research reports come from scattered sources with uneven update frequencies. Regular reports are updated on a fixed schedule, while policy-related reports are released in real time. This requires multi-turn dialogue to support real-time retrieval of the latest compliant data sources. Prompts must restrict usage to only the connected public research report content. Documents contain mixed long paragraphs and tables. This requires multi-turn dialogue to support segmented retrieval and structured table parsing, to prevent long text from exceeding the context window. There are many field dimensions with significant unit differences. Prompts must clearly specify reference rules for data fields, to avoid unit confusion during multi-turn interactions.
Configuration settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | A single insurance research report often contains thousands of characters of tables and paragraphs. This range can cover the full context of a single core research report |
recallTopK | Top 8–12 entries | Insurance research reports have high topic segmentation granularity. This range can cover relevant content for core business data and policy interpretations |
RECALL_SIMILARITY_THRESHOLD | 0.75–0.85 | Filters irrelevant research report content, retaining highly relevant business data and policy interpretation snippets |
PARSE_TABLE_ENABLE | Enabled | Insurance research reports contain a large number of business data tables. Enabling this setting allows structured data extraction, improving answer accuracy |
promptTemplate | Explicitly specify that only connected insurance research report data is used, and clearly define field reference rules and unit descriptions | Insurance research report fields have large unit differences. Unified rules must be established in advance to avoid confusion during multi-turn dialogue |
contextClearStrategy | Automatically clear history records older than 10 conversation turns | Multi-turn insurance research report conversations often involve comparisons of multiple data sets. This strategy balances context completeness and window usage |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common misconfigurations
- Phenomenon: After debugging and previewing a conversation, it is not possible to individually clear the historical records of a specific application, and no corresponding cleanup option appears in the interface. Cause: The custom cleanup configuration for
contextClearStrategyis not enabled, and the specified conversation history cleanup interface provided by FastGPT is not called, resulting in mixed historical records that cannot be distinguished. - Phenomenon: In multi-turn dialogue, subsequent questions cannot associate the previous round's conclusion as input content. Cause: No context reference rules are configured in
promptTemplate, and the previous round's conclusion is not included in the context scope of the current prompt. - Phenomenon: The completion reason field returned by AI dialogue is empty, and subsequent components cannot call this field value. Cause: The completion reason log switch for the dialogue component is not enabled, resulting in the field not being properly generated and stored.
How to confirm successful configuration
- Initiate a query containing insurance business data, and verify that the returned data source is the connected compliant insurance research report content.
- Initiate consecutive multi-turn interactions, and verify that the conversation context is not abnormally truncated, and complies with the configured context window rules.
- Initiate a query containing research report tables, and verify that the returned content has structuredly extracted table data.
- Call the specified application's history cleanup interface, and verify that the conversation history of the corresponding application has been correctly cleared.
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.