What the data for this category looks like
Thermal coal research reports primarily come from coal industry associations, futures exchange market portals, leading brokerage research departments, and industry information platforms. Update cycles cover daily spot prices, weekly port inventory data, monthly supply and demand balance sheets, and quarterly industry outlook reports. Document structures include core market fields, policy interpretations, and supply and demand calculation modules. Field units are uniformly yuan/ton (for prices), ten thousand tons (for inventories and trading volumes), and kilocalories per kilogram (for calorific value indicators). Some reports include visual attachments such as K-line charts and supply and demand curves.
Constraints Imposed on Model Access and Configuration
The multi-source heterogeneous format, high-frequency update characteristics, and structure with visual attachments of thermal coal research reports impose multiple constraints on model access and configuration. Configure differentiated document parsing rules for multi-source data to adapt to csv-format industry data, encrypted pdf-format brokerage reports, and structured interface data. Adjust the recall time window parameter for high-frequency updated daily market data to avoid retrieving expired and invalid information. Configure field standardization mapping rules for calorific value and inventory fields with clear units to ensure unit consistency in model outputs. Enable multimodal recognition adaptation for visual attachments, and adjust context length parameters to carry the complete content of long documents.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Thermal coal research reports are mostly long documents with multi-page charts and structured data, requiring sufficient parsing time to complete content extraction |
maxContext | 8000–12000 characters | Long documents require complete context to avoid truncation of core data such as supply and demand calculations and port inventories |
RECALL_TOP_N | Top 8–12 entries | High-frequency updated daily market data requires prioritizing the recall of the latest entries to avoid redundant expired information interfering with model outputs |
VISION_ENABLED | Enabled | Research reports include visual attachments such as K-line charts and supply and demand curves, requiring multimodal recognition capabilities to be enabled |
UPLOAD_FILE_MAX_SIZE | 500 MB | Some large quarterly supply and demand balance reports have large file sizes, requiring relaxed upload limits |
EMBEDDING_MODEL | Select Qwen3-Embedding-8B or a same-scale multimodal embedding model based on actual testing | Adapt to text and visual content in research reports to ensure recall accuracy |
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 on your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: After enabling
VISION_ENABLED, when uploading a K-line chart from a research report, the model reply states that image content cannot be provided. Cause: The visual interface key for the multimodal model has not been configured, or the embedding model does not adapt to the visual input format. - Issue: When connecting to the Qwen3-Embedding-8B model deployed via VLLM, a connection timeout or model format mismatch error is returned. Cause: The correct VLLM interface address and port have not been configured on the platform, or the input dimension of the embedding model does not match the platform's preset parameters.
- Issue: When the model calls the research report retrieval tool, the output content is interrupted midway and a complete answer is not provided. Cause: The
maxContextparameter has not been adjusted to adapt to long documents, causing context overflow to trigger model output truncation, or the call timeout parameter is set too short.
How to Confirm Successful Configuration
- Upload a thermal coal quarterly research report that includes a K-line chart, verify that image text and core data fields are successfully extracted after parsing, to confirm that the multimodal recognition configuration is effective.
- Call the embedding model test interface, upload a csv file of thermal coal spot prices, verify that recall results include the latest daily price data, to confirm that the recall parameters and embedding model configuration are reasonable.
- Simulate a user query of "What is the current thermal coal Qinhuangdao Port inventory", verify that the model returns accurate fields and units, to confirm that the field standardization mapping configuration is effective.
- Upload a single research report with a size of 400 MB, verify that parsing and recall complete normally, to confirm that the upload file size limit configuration meets requirements.
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.