What the Data for This Category Looks Like
Data sources for thermal coal research reports include industry public monitoring data, professional coal information channels, and enterprise public operational reports. Daily monitoring data is updated every day. Special reports are released weekly or monthly. Immediate updates are made for sudden supply and demand changes. Documents typically include four core sections: supply and demand overview, price trends, transportation links, and policy interpretation. They also include quality and trading indicators such as calorific value and price. Calorific value is measured in large calories per kilogram, and price is measured in yuan per ton. Most texts contain technical terms and long paragraphs.
Constraints Imposed by These Characteristics on Deployment and Upgrade
Daily updated data covering full monitoring information requires configuring scheduled tasks for daily synchronization to avoid data lag. Research reports contain long texts and unique quality and price indicators. Parsing and context window parameters must be adjusted to ensure complete information extraction and accurate matching. Cross-version upgrades must be compatible with historically synchronized data source formats and field mapping rules to prevent historical data disruption. Decentralized data sources require configuring synchronization permissions for multiple sources to ensure stable data acquisition.
Recommended Configuration Values
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Thermal coal research reports are mostly long documents with extensive tables and text paragraphs, resulting in longer-than-average parsing times |
maxContext | 8000–12000 characters | Research reports contain multiple sections of technical terms and long sentences, requiring a sufficient context window to maintain semantic coherence |
RECALL_TOP_K | Top 10 entries | Thermal coal research report data has concentrated dimensions; excessive recall will introduce irrelevant information |
DATA_SYNC_INTERVAL | 86400 seconds | Daily monitoring data is updated daily, so daily synchronization covers all valid data |
VECTOR_FIELD_MAPPING | Set based on actual testing | Thermal coal research reports contain unique fields such as calorific value and price, requiring matching with vector database storage formats |
UPLOAD_FILE_MAX_SIZE | 200 MB | Large special research report documents have larger file sizes, so upload limits need to be relaxed |
The parameter values provided on this page are conventional recommendations used as a starting point 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 on your own samples before finalizing values.
Three Common Misconfigurations
- Phenomenon: After restarting the Docker container, a database connection error
Access denied for user 'root'@'localhost'occurs. Cause: Local volume permissions are reset after restart, and the originally configured database access permissions are not retained. - Phenomenon: Historical research report data fields are missing after cross-version upgrade. Cause: Upgrade scripts were not executed in version order, and skipped versions included compatibility updates for field mappings.
- Phenomenon: Only one GPU is occupied after deploying the model, while other GPU resources remain idle. Cause: Environment variables for multi-GPU scheduling are not configured, and the visible GPU range is not specified.
How to Confirm Configuration Is Correct
- Run a manual synchronization task, check if the synchronization logs include unique fields such as the calorific value and price of research reports, to confirm that the field mapping configuration takes effect.
- Upload a single test thermal coal research report document, check the segmented text after parsing, to confirm that it matches the context window parameter settings.
- Initiate a targeted retrieval and query, verify that the number of returned results matches the configured recall parameters, to confirm that the retrieval logic is working properly.
- Check server hardware resource monitoring, confirm that multiple GPUs are being scheduled for use, to verify that the multi-GPU configuration takes effect.
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.