What the Data for This Category Looks Like
Thermal coal investment research data primarily comes from National Energy Administration monthly supply and demand reports, daily spot quotes from coastal ports, Dalian Commodity Exchange thermal coal futures trading data, industry association inventory and transport statistics, and broker coal industry research reports. Data update rhythms fall into three categories: spot quotes are updated daily, futures trading data is updated in real time per trading day, and research reports and policy documents are released irregularly. Individual documents mostly combine structured tables and text analysis, including fields such as spot price, port inventory, transport cost, and supply-demand gap. Corresponding units are yuan/ton, 10,000 tons, and yuan/ton·km respectively.
How These Characteristics Create Constraints for Dialogue Logging and Audit
Thermal coal data’s varied update frequencies, structured fields, and multiple sources create multiple constraints for dialogue logging and audit. First, update frequencies differ significantly across data sources. Logs must accurately record the source and corresponding timestamp of each data point referenced in a dialogue. During audits, staff must verify that referenced data falls within its current valid period, to avoid using expired spot or futures data. Second, structured fields have clear defined units. Logs must capture the specific numerical values and units of referenced data. During audits, staff must check for unit conversion errors or mixed statistical standards. Third, irregularly released research reports require unique identifiers, to ensure traceability back to original documents during audits.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Thermal coal research reports, supply and demand reports and other documents have long lengths, requiring sufficient time to complete structured parsing and avoid truncation of critical data due to parsing timeout |
LOG_RECORD_CUSTOM_FIELDS | ["data_source", "data_timestamp", "field_unit"] | Thermal coal data requires traceability of source, timestamp and unit information, enabling full traceability of referenced specific content during audits |
AUDIT_EXPIRY_DAYS | 7 days | Thermal coal spot and futures data has strong timeliness. Historical data older than 7 days must be marked as expired during audits to avoid using outdated information |
maxContext | 8000–12000 characters | Investment research dialogues need to associate multiple long documents. Expanding the context window preserves complete historical references and data associations |
LOG_RETENTION_PERIOD | 180 days | Meets audit compliance requirements of the financial investment research industry, retaining sufficient duration of interaction records for traceability |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are influenced by material form, data volume and business rules. Specific issues require targeted analysis, and it is recommended to test against your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: Dialogue logs do not record data sources and timestamps, making it impossible to trace referenced thermal coal spot or futures data during audits. Cause:
LOG_RECORD_CUSTOM_FIELDSis not configured to add the corresponding custom fields, only basic user and assistant dialogue content is recorded. - Issue: A
400 Bad Requeststatus code is returned when calling the dialogue log API, or log entries lack the field information required for audits. Cause: Custom log field parameters are not passed according to interface specifications, or the parameter format is incorrect. - Issue: Structured fields are split and disorganized when importing thermal coal research reports or supply and demand balance sheet documents, with key data such as prices and inventory separated from their units. Cause: The
segment lengthparameter is not adjusted, and the default segmentation rules disrupt the structured format of the document.
How to Verify Correct Configuration
- Manually initiate a dialogue that references thermal coal data, then check if the backend log records the data source, timestamp and field unit, to confirm the
LOG_RECORD_CUSTOM_FIELDSconfiguration is active. - Call the dialogue log query API, then check if the returned results include the configured custom fields, to verify the API call’s log output meets requirements.
- Upload a thermal coal supply and demand balance sheet document, then check if the parsed text fully retains the structured table fields and units, to confirm the document parsing configuration is correct.
- Check the system log retention period setting, then confirm that the log retention cycle meets the preset audit requirements and has not been cleaned up early.
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.