What the data for this category looks like
Trading rule data primarily originates from official business manuals of financial institutions, compliant regulatory documents, and backend configurations of core trading systems. Update cycles are not fixed, and are triggered by adjustments to regulatory policies, optimization of business processes, or changes to customer group rules. Document structures typically include five core modules: applicable scenarios, trigger conditions, operational procedures, exception cases, and compliance basis. Fields include rule ID, effective time, expiration time, applicable customer groups, transaction types, fee standards (unit: percentage or yuan), exception handling procedures, and more. There is no unified short-text format, and some rules include nested sub-clauses.
What constraints these characteristics impose on the deployment and upgrade workflow
Decentralized data sources require format alignment and field mapping across multiple source documents before deployment. Otherwise, rule content may be missing or incorrect. Unfixed update cycles require the upgrade process to support hot updates, to avoid interrupting online services. Complex document structures with nested sub-clauses require correct parsing of hierarchical relationships during deployment. Otherwise, key rule details may be omitted during question answering. Fields include clear units, so unit validation logic must be added during deployment to prevent business risks caused by unit mismatches.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
TRADING_RULE_SYNC_INTERVAL | 3600 seconds | Trading rule updates have no fixed cycle; hourly synchronization balances timeliness and server resource usage |
RULE_PARSE_CHUNK_SIZE | 800–1200 characters | Most trading rule documents include long procedural descriptions; this range preserves semantic integrity |
VALIDATION_CHECK_ENABLED | Enabled | Trading rule fields include units such as percentage or yuan; validation helps avoid configuration errors |
DEPLOYMENT_ROLLBACK_TIMEOUT | 600 seconds | Trading rule changes have a wide impact scope; sufficient rollback time reduces business impact |
XINFERENCE_MODEL_ENDPOINT | Fill in according to the deployment instance | Specify the correct service address when accessing a locally deployed large model to meet the accuracy requirements for trading rule question answering |
WORKFLOW_EXPLICIT_MODEL_PERM | Enabled | Avoid implicit calls to unconfigured models and reduce error logs without trigger sources |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: In FastGPT v4.9.0, a
gpt-4o-mini model not founderror occurs during workflow runtime, but no model call node is configured. Cause: The context associated with the trading rule knowledge base triggers implicit model calls, and call permissions are not explicitly declared in the workflow. - Symptom: After accessing a model deployed via Xinference, the question answering returns empty results. Cause:
XINFERENCE_MODEL_ENDPOINTand model name mapping are not correctly configured, causing requests to fail to reach the local service. - Symptom: The service cannot be accessed via a secondary domain name after Docker deployment. Cause: No routing rule for the secondary domain name is added in the reverse proxy configuration, and no mapping is completed between the container port and the server port.
How to confirm successful configuration
- Trigger a manual synchronization task, and verify that there are no prompts for field validation failures or missing content in the synchronization logs.
- Submit a test query containing trading rule keywords, and confirm that the returned results match the preset rule content and format.
- Perform a simulated upgrade rollback operation, confirm that the process can be completed within the configured timeout period, and no data abnormalities occur.
- Access the bound secondary domain name, verify that the service page loads normally, and the interface response has no timeouts or errors.
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.