What this category of data looks like
Trading rule data comes from official regulatory platforms in securities, insurance and other industries, as well as public documents from licensed institutions. Updates occur irregularly alongside regulatory policy adjustments and business process optimizations. Single updates cover either single-category or full-category rules.
The document structure includes four core modules: applicable entities, execution periods, operation thresholds, and exception handling processes. Fields include applicable entity code, period start/end markers, operation threshold value, and handling process number. Units are none, hour-minute format, integer, and number format respectively.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Trading rule data is scattered, and updates follow no fixed cycle. This means the multi-turn dialogue link must support real-time pulling of the latest rule sources, and cannot rely on static cached knowledge base content.
The modular document structure requires prompts to guide users to clearly specify key parameters such as applicable entities and execution periods. This avoids rule matching deviations caused by generalized queries.
Non-standardized units and encoding formats for fields require the dialogue process to perform format verification on user-input parameters. Examples include verifying that periods conform to the hour-minute format, and that thresholds are valid integers.
Irregular rule updates also require configuring an automatic verification mechanism. This mechanism regularly checks the consistency between currently recalled rule versions and official sources.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 800–1200 characters | The length of single-module trading rule documents falls within this range, to avoid truncation of core rule content |
ragRecallNum | Top 3–5 entries | Valid matching clauses for trading rules usually do not exceed 5 entries; excessive recall increases context redundancy |
ragSimilarityThreshold | 0.75–0.85 | Trading rule expressions are precise, requiring a high matching degree to avoid incorrect recall of irrelevant clauses |
promptTemplate | Fixed template including guiding language for "clearly specify applicable entities, execution periods, and operation scenarios" | Trading rule parameters have strong dependencies, requiring constraint of query accuracy to avoid generalized queries |
customUidSessionFilter | Enable and bind user identification | Financial scenarios require isolation of different user sessions to prevent sensitive information leakage |
ragUpdateCycle | Every 24 hours | Trading rule updates have no fixed cycle; regular verification ensures recalled content is the latest official version |
The parameter values provided on this page are all conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: After calling the API with
customUidspecified, the obtained session records include content from non-target users. Cause: ThecustomUidSessionFilterconfiguration is not enabled, or the user identification parameter is not correctly bound when initiating a session. - Phenomenon: Uncleaned thinking tag content remains in multi-turn dialogue return results. Cause: The format cleaning step in the workflow does not cover all scenarios, or the trigger timing is later than the result output link.
- Phenomenon: The trading rules recalled in the dialogue do not match the currently officially released version. Cause: No regular verification mechanism is configured, and old version rule data from static cache is relied on.
How to confirm the configuration is complete
- Initiate a test session, pass the preset
customUid, call the history record interface, and check that the returned results only include session content corresponding to thiscustomUid. - Construct a query including applicable entities and periods, check that the AI returned rule content matches the official document, and no redundant or truncated information appears.
- Modify the effective time of a test rule, wait for the configured verification cycle to end, initiate the corresponding query, and check that the returned content is the updated rule.
- Trigger AI dialogue to generate results, check that no uncleaned format markers appear in the returned content.
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.