What the data for this category looks like
Thermal coal financial report data comes primarily from periodic reports of domestic and overseas publicly traded thermal coal companies, monthly industry association monitoring data, and spot transaction ledgers from major ports. Data updates follow three tiers: monthly, quarterly, and annual. Monthly data includes short-term operational metrics such as current-period futures prices and port inventory levels. Quarterly and annual data covers long-term strategic analysis dimensions including production capacity layout, cost structure, and downstream demand share. Document structure uses structured tables and professional paragraph descriptions. It includes dedicated fields such as calorific value (unit: kilocalories per kilogram), tax-included selling price (unit: yuan per ton), and transportation cost (unit: yuan per ton-kilometer). No vague general industry statistical items are included.
What constraints these characteristics impose on model access and configuration
The multi-cycle update schedule of thermal coal financial report data requires the model access link to adapt to synchronization rules for different time-granularity data sources. This prevents analysis deviations caused by mismatched cycles. Dedicated fields and fixed units require the configuration link to preset field mapping rules. This prevents unit confusion or missing fields after parsing. The long document and multi-field structure requires the model context window to accommodate the content volume of a single financial report. It also requires limiting recall ranges to avoid interference from irrelevant information. Additionally, thermal coal domain has a large number of professional terms. This requires embedding models and dialogue models to support semantic understanding of domain vocabulary, to improve analysis result accuracy.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single thermal coal financial report documents contain many tables and professional paragraphs. A long context window is required to fully parse content |
recall count | Top 6 entries | Financial report data has many fields. Sufficient associated fields must be recalled to cover all information needed for analysis |
similarity threshold | 0.72–0.85 | Numeric fields such as thermal coal prices and production capacity are highly sensitive. Low-correlation recall results must be filtered |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Parsing a single financial report PDF or Excel file takes significant time. Extend the timeout period to avoid parsing interruptions |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Large annual financial report documents have significant file size. Relax the upload file size limit |
embedding model | Domain-specific embedding model | Thermal coal financial reports contain many professional terms. A dedicated embedding model improves semantic recall accuracy |
The parameter values provided on this page are common recommended starting points for defining configurations. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing the configuration.
Three Common Configuration Mistakes
- Phenomenon: After entering
CHAT_API_KEY, the model returns authentication failure or no response. Cause: The API address format for local deployment, local area network deployment, and cloud models is not distinguished. A correct custom API endpoint is not configured when calling a thermal coal domain-specific model. - Phenomenon: After replacing the embedding model, the recall result similarity value is abnormally high, and the same content is returned repeatedly. Cause: The
similarity thresholdparameter is not adjusted, embedding vectors are not normalized, and numeric fields in thermal coal financial reports are not standardized for mapping. - Phenomenon: The edit entry for large model response content cannot be found, and AI dialogue output in the workflow cannot be received by subsequent modules. Cause: The
custom response editingandworkflow output synchronizationconfiguration switches are not enabled. These switches are hidden by default in the advanced settings menu of the model configuration.
How to Confirm Successful Configuration
- Upload a single thermal coal quarterly financial report document. Check if preset dedicated fields are included after parsing, and confirm no parsing timeout error is triggered.
- Submit a targeted financial report analysis query. Check if the returned result includes correct field units and mapping relationships, with no abnormal values or missing information.
- Adjust the
similarity thresholdand verify that recall result correlation meets expectations, with no excessive or insufficient recall. - Configure a custom API endpoint and enter
CHAT_API_KEY, then submit a test call. Confirm the model returns a normal response with no authentication 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.