What This Category of Data Looks Like
Carbon steel data sources include China Iron and Steel Industry Association public statistical data, domestic bulk commodity spot trading platform quotes, steel mill ex-factory price announcements, and professional investment research institution carbon steel supply and demand analysis reports. Update frequency falls into three categories: spot quotes are updated daily, industry association monthly statistical data is released in the following month, and investment research reports are released as needed. Document structure is divided into three categories: structured quotation sheets, semi-structured industry briefings, and unstructured research reports. Structured documents include fields such as product name, specification model, origin, unit price (yuan/ton), and month-on-month change rate. Semi-structured documents include statistical items such as output, inventory, and apparent consumption. Unstructured documents include market sentiment and policy interpretation content.
Constraints Imposed on Conversation Logging and Auditing
The multi-source, high-frequency update, and multi-structure characteristics of carbon steel data impose three constraints on conversation logging and auditing: First, record the carbon steel data source and update timestamp associated with each round of conversation. This ensures that the data version at the time of a call can be traced back during audits, and avoids conclusion deviations caused by data updates. Second, retain specific fields and units of structured data, such as yuan/ton, MPa. This prevents unit confusion or missing fields during audits. Third, associate the position identifier of recalled unstructured research report fragments. This allows verification of whether carbon steel content referenced in answers is accurate during audits. In addition, investment research conversations often involve cross-verification of multiple data sources. Logs must fully record the full chain of questions, recalled data, and generated answers to support compliance audits.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
LOG_RETENTION_DAYS | 180 days | Carbon steel investment research requires audit traceability covering monthly and quarterly reports, and complies with financial industry compliance retention requirements |
LOG_INCLUDE_FIELDS | "question, recalled carbon steel data fragments, answer, data source, update timestamp, unit" | Carbon steel data has multiple fields and units, and complete recording is required to support precise auditing |
ERROR_LOG_THRESHOLD | 600 milliseconds | Carbon steel spot data has a high update frequency, and timeouts will cause conversation results to fail, so timeout errors need to be captured for troubleshooting |
AUDIT_DATA_SCOPE | "structured quotations, semi-structured industry statistics" | Carbon steel investment research relies heavily on this type of data, so the audit scope prioritizes core data sources |
API_KEY_PER_USER_LOG | Enabled | It is necessary to record the call chain of each key to support permission auditing and traceability in multi-user scenarios |
DATA_VERSION_TRACKING | Enabled | Carbon steel data is updated frequently, and it is necessary to record the data version at the time of a call to avoid version deviations during audits |
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 specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Phenomenon: A POST request to delete conversation records returns an abnormal status code, and conversation records are not cleared. Cause: The
LOG_DELETE_API_PERMISSIONparameter is not configured correctly, or a valid management key is not carried in the request header, resulting in permission verification failure. - Phenomenon: The conversation generates an empty answer, and the server log shows that the
messagefield is empty. Cause: The threshold configuration ofERROR_LOG_THRESHOLDis not enabled, or the recalled carbon steel data fragments exceed themaxContextlimit, causing the model to fail to generate valid content. - Phenomenon: When multiple users share a key, it is impossible to distinguish the ownership of conversations through logs. Cause: The
API_KEY_PER_USER_LOGconfiguration is not enabled, and the association between the call key and the user is not recorded, making traceability impossible during auditing.
How to Verify Proper Configuration
- Send a POST request to delete conversation records. Check that the returned status code is 200, and that the corresponding conversation ID cannot be found in the log list of the management backend. This verifies that the log deletion configuration is effective.
- Initiate a conversation that includes a query for carbon steel spot data. View the log details, and confirm that preset fields such as question content, data source, update timestamp, and unit are included. This verifies that the
LOG_INCLUDE_FIELDSconfiguration is correct. - Generate a conversation that includes carbon steel data, and trigger a timeout scenario. Check whether the error log records the timeout time and the call information of the corresponding carbon steel data. This verifies that the
ERROR_LOG_THRESHOLDconfiguration is effective. - View the key management page, and confirm that the call logs of each user's key have been recorded. This verifies that the
API_KEY_PER_USER_LOGconfiguration is enabled.
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.