What the data for this category looks like
Thermal coal market data primarily comes from the Dalian Commodity Exchange futures market, domestic core port spot quotation platforms such as Qinhuangdao Port, and daily industry reports from the China Coal Industry Association. Data update cadence is as follows: futures data is pushed in real time during trading days, spot quotations are updated each morning, and industry inventory and transportation data is updated every two days. A single daily report document includes fields such as statistical date, producer average price, port clearance price, car plate price, month-on-month change, trading volume, and position count. The unit of core price fields is yuan/ton, and the unit of trading volume is 10,000 tons.
Constraints imposed by these characteristics on multi-turn dialogue and prompting
Thermal coal data sources are scattered and update cadences vary significantly. Multi-turn dialogue processes must clearly distinguish between futures and spot data scenarios to avoid returning mixed results. There are many core field dimensions, so multi-turn dialogue must retain user-specified query dimensions (such as producing area, port) through context association, without repeating questions. Different data has different update timeliness, so prompts must mandate specifying the query time range and data type to prevent retrieving expired or mismatched information. Some fields have unit differences, so prompts must explicitly require returning standard units to avoid unit confusion issues.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Thermal coal daily reports contain multiple sets of price and trading data. Longer context can retain query dimensions and data type requirements from multi-turn dialogue |
UPLOAD_FILE_MAX_SIZE | 50 MB | A single thermal coal yield daily report document typically does not exceed 20 MB, reserving sufficient space to support batch uploads |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Large daily report documents contain multiple pages of historical data, requiring sufficient time to complete structured parsing |
Recall count | Top 6 entries | Thermal coal data has many fields. An appropriate number of recalls can cover different query dimensions and avoid information overload |
Similarity threshold | 0.75–0.85 | Thermal coal price data has high keyword matching precision requirements. This range can filter low-correlation historical documents |
WORKFLOW_ERROR_HANDLER | Trigger alerts and record logs | Exceptions often occur during file parsing and data calls in multi-turn dialogue, requiring timely issue localization |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Each scenario requires specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Symptom: A
400 Bad Requesterror is returned when calling the document parsing tool after configuring a file upload component in the workflow. Cause: The file storage configuration is not correctly associated, causing the parsing tool to fail to read the actual path of the uploaded file. - Symptom: The results returned by the knowledge base call in multi-turn dialogue do not match the current query's thermal coal data dimensions. Cause: The query scenario (spot/futures) and time range are not explicitly specified in the prompt, causing the system to recall irrelevant historical documents.
- Symptom: An uncaught exception prompt pops up when running a multi-turn dialogue workflow in a private deployment environment. Cause: Database or object storage connection parameters in the configuration file are filled incorrectly, causing data read/write failures.
How to Confirm Proper Configuration
- Upload a standard thermal coal daily report document, check if the parsed fields cover core content such as statistical date, price, and trading volume, to confirm that the parsing rules adapt to the data structure of this category.
- Initiate a multi-turn dialogue: first query the spot price of a specified port, then initiate a secondary query without specifying the location, check if the system can associate context to return data of the corresponding dimension.
- Trigger the file upload and parsing link in the workflow, view the system logs to confirm that normal parsing results are recorded and there are no abnormal error codes.
- Call the API to initiate a dialogue, check if the returned results include the reference identifier of the knowledge base document, to confirm that the API call is bound to the correct knowledge base configuration.
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.