What this category’s data looks like
Coal chemical market and yield data is sourced from domestic coal futures exchanges, industry professional monitoring institutions, and port logistics data platforms. Spot prices are updated daily, futures settlement prices are updated per trading day, and industry supply-demand and capacity operation data is updated weekly. Each data document includes fields such as product name, daily transaction price, port inventory, origin quotation, and transportation cost items. Price units are yuan/ton, inventory units are 10,000 tons, and transportation cost units are yuan/ton. Covered sub-categories include coking coal, coke, methanol, and other coal chemical products, with minor differences in field details across categories.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Differences in update rhythms across multiple data sources require clear distinction of data cycles in multi-turn dialogue, to avoid confusion between expired and real-time information. There are many sub-categories of coal chemical products. Prompts must specify the exact product name, otherwise redundant data from unrelated categories may be retrieved. Data fields and units follow unified specifications. Prompts must explicitly require output that matches the preset fields and units, to prevent unit confusion. Daily updated spot data and weekly updated industry data must be separated by time dimension in dialogue, to avoid result deviations caused by mixing cross-cycle data.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarityThreshold | 0.72–0.78 | There are many sub-categories and rich fields in coal chemical data. This range can filter irrelevant industry data and accurately match market information of target products |
relevantNum | Top 6 entries | A single piece of coal chemical data contains multi-dimensional fields. 6 retrieved results can cover core information while avoiding information overload |
rerankTopN | Top 3 entries | Prioritize sorted high-matching sub-product data to reduce interference from non-target categories |
systemPrompt | Fixed inclusion of "Only output daily/periodic data for specified coal chemical products, with units uniformly in yuan/ton and 10,000 tons" | Restrict AI output format to match the field and unit specifications of coal chemical data |
maxHistoryTurns | 3–5 turns | Coal chemical market data has a high update frequency. Excessive historical dialogue will introduce expired data. Limiting the number of turns maintains data timeliness |
UPLOAD_FILE_MAX_SIZE | 100 MB | Coal chemical industry documents are mostly batch monitoring reports. This size can accommodate complete datasets uploaded in a single batch |
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 specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- A 422 status code is returned during dialogue steps. Cause: The system prompt does not limit retrieval to only coal chemical-related data. The knowledge base retrieves redundant fields across categories, triggering API parameter verification failure.
- Historical records disappear after the front-end dialogue window is refreshed, but complete records can be queried in the background. Cause: The
history_persistparameter is not enabled. The front-end only stores temporary session cache, and does not synchronize dialogue data persisted in the background. - Attempts to hide dialogue output content fail. Cause: The
chat_output_visibleparameter is not configured correctly. The parameter is mistakenly set to the default display mode instead of the hidden mode.
How to Confirm Proper Configuration
- Initiate a single-turn dialogue to ask for the daily price of a specified coal chemical product, and verify that the output includes the preset fields and units.
- Initiate a multi-turn dialogue to sequentially ask for data across different cycles, and verify that the AI can distinguish data sources with different update frequencies.
- Check the channel configuration page to confirm that the exclusive coal chemical knowledge base dataset has been bound, with no cross-category associations.
- Review system logs to confirm that each dialogue request includes the specified product restriction parameters, with no omissions.
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.