What the data for this category looks like
Coking coal data sources include publicly monitored data from domestic coal industry associations, market data from coking coal futures exchanges, and public trade ledgers from upstream mines and downstream steel mills. Update frequency falls into three categories: futures market data updates daily, industry supply and demand weekly reports update weekly, and annual production capacity policy reports are released quarterly. Document structure is divided into three types: market snapshots, supply and demand ledgers, and policy interpretations. Each document includes core category parameters, transaction data, and associated industry dynamics. Core parameter fields include ash content index, caking index, and delivery grade, with units of ton, yuan per ton, and kilojoules per kilogram.
Constraints imposed on conversation logging and audit
The multi-update frequency, multi-source attributes, and multi-core parameter characteristics of coking coal data impose three constraints on conversation logging and audit. First, the lifecycle of different data types varies significantly. Futures market data must be retained until the end of the corresponding delivery cycle. Industry weekly reports must be retained until the next issue is released. Automatic archiving rules must be set for logs based on data classification. Second, coking coal core parameters cover multiple dimensions such as ash content and caking index. Audits must track the original document identifier for each parameter reference to avoid parameter confusion across documents. Third, data sources include publicly monitored data and internal trade ledgers. Logs must distinguish permission identifiers for public access and internal calls to ensure audits can trace access subjects and data permission scopes.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
log_retention_days | Set per data classification: 7 days for futures data, 30 days for industry reports | Matches the lifecycle of different coking coal data to avoid invalid storage usage |
audit_log_include_source | Enabled | Required to track the original source of coking coal data and ensure audit verification of reference authenticity |
max_context_length | 8000–12000 characters | Coking coal documents contain multi-dimensional parameters and transaction data, requiring sufficient context length to support complete conversation logic |
api_custom_context_enable | Enabled | Supports passing custom context to adapt to scenarios in coking coal investment research where specific report segments must be directly referenced |
batch_process_timeout | 600 seconds | Sufficient time is required to process long document content when batch parsing multiple coking coal industry reports |
log_tag_enable | Enabled, add tags by data type | Facilitates subsequent retrieval of audit logs by coking coal market and report categories |
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 case-by-case analysis, and it is recommended to test against your own samples before finalizing settings.
Three common configuration errors
- Issue:
log_tag_enableis not enabled, making it impossible to retrieve audit logs by coking coal data type. Cause: No tag rules are configured for coking coal's multi-classified data, resulting in logs without valid classification identifiers. - Issue: In open source version 4.8.11, a
try reducing the size of the batcherror occurs and the process hangs when batch uploading long coking coal documents. Cause: Thebatch_process_timeoutandUPLOAD_FILE_MAX_SIZEparameters are not adjusted, and the total length of batch processed documents exceeds the system's default threshold. - Issue: When passing custom coking coal report segments via API, the system still concatenates historical conversation content, making it impossible to retrieve the specified segments. Cause: The
api_custom_context_enableparameter is not enabled, causing the custom context function to not take effect.
How to confirm successful configuration
- Initiate a conversation related to coking coal futures market data, and check whether the log contains the session's source identifier and data reference tags.
- Upload a coking coal industry report, verify that the batch processing task's timeout time matches the preset configuration, and that parsing completes without errors.
- Generate a login-free share link, initiate a conversation, then retrieve the session record in the audit panel to confirm normal viewing.
- Call the API to pass a custom coking coal report segment, check that the conversation context contains the specified passed content, and that no system-concatenated historical records are included.
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.