What the data for this category looks like
Core data sources for coking coal research reports include the Coking Coal Branch of the China Coal Industry Association, the Dalian Commodity Exchange, top brokerage research institutes, and industry vertical portals. Update frequencies fall into three categories: daily updates for spot prices and port inventory data, weekly updates for industry supply and demand weekly reports, quarterly updates for full industry analysis reports, and real-time interpretation documents generated during sudden policy or market changes. Document structure follows a fixed format: core viewpoint summary, coking coal output and import data, steel mill operating rate and inventory status, price trend analysis, policy interpretation and risk warnings. Fields and units have clear industry-specific characteristics. Output is measured in ten thousand tons, spot prices are measured in yuan per ton. Some documents mark specific parameters for coking coal delivery grades such as main coking coal and 1/3 coking coal.
What constraints do these characteristics impose on model integration and configuration?
Coking coal research reports have dense professional terminology, a high proportion of structured data, and uneven update frequencies. These factors create multiple constraints for model integration and configuration. First, professional terms such as "colloid layer thickness" and "main coking coal ratio" require the embedding model to have domain adaptation capabilities. An embedding model that supports professional text must be configured. Second, a large number of structured tables must be correctly parsed and retain the correspondence between fields and units. Otherwise, the embedding model will lose key quantitative information. Third, frequently updated spot data requires the vector database refresh interval to not be too long. The system must adapt to short-cycle incremental update logic. Fourth, single research reports are generally 3000 to 5000 words in length. A sufficiently large context window must be configured to avoid truncating core content.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Coking coal research reports contain a large number of professional tables and technical parameters. 800-1200 characters can retain the semantic integrity of a single segment of text and avoid splitting that destroys professional expressions |
max_context_window | 8192 tokens | The average length of a single coking coal research report is approximately 3000-5000 words. 8192 tokens can fully load the context of a single research report and avoid truncating key supply and demand data |
refresh_interval | 1 hour | Coking coal spot prices and port inventory data are updated daily, and industry research reports are updated weekly. A 1-hour refresh ensures the timeliness of vector database data |
rerank_top_n | Top 3–5 results | Core information of coking coal research reports is concentrated in top relevant documents. Excessive recall will introduce irrelevant cross-category industry data |
parse_table_enable | Enabled | Coking coal research reports contain a large number of structured supply and demand tables. Enabling table parsing retains the correspondence between fields and units and prevents the embedding model from losing structured information |
similarity_threshold | 0.72–0.78 | The semantic similarity of coking coal professional terms is relatively high. A threshold that is too low will introduce irrelevant research reports, and a threshold that is too high will miss relevant segmented category data |
The parameter values provided on this page are all conventional recommendations used to determine the starting point for configuration. 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 mistakes
- Phenomenon: The embedding model returns empty content, and the log shows
500 Internal Server Error. Cause: The embedding model does not adapt to the input format of coking coal professional terms. Locally deployed embedding models do not enable long text support, resulting in the inability to generate vectors for ultra-long research report segments. - Phenomenon: The model request times out, and the interface displays the
Request timed outstatus. Cause: The configuredPARSE_FILE_TIMEOUT_SECONDSvalue is too short. Coking coal research reports contain a large number of tables that require longer processing time for parsing. - Phenomenon: The reranking model returns empty content, and the console shows
response data is empty. Cause: The request authentication information of the reranking model is not configured correctly, resulting in the interception of third-party model interface requests.
How to confirm the configuration is complete
- Upload a single coking coal research report, check the vector database index record, and confirm that the generated vector dimensions match the embedding model configuration.
- Initiate a search with keywords related to coking coal, check the document source and update time of the recall results, which conform to the preset refresh interval.
- Trigger a reranking model test, check that the number of returned results matches the
rerank_top_nconfiguration, and there are no empty content errors. - View the parsed text fragments, confirm that table fields and units such as yuan per ton, ten thousand tons have been correctly retained.
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.