Model Integration and Configuration for Steel Trade Research Report Retrieval

Data sources include official monthly reports from the China Iron and Steel Industry Association, weekly inventory reports from coastal ports, daily

What Data for This Category Looks Like

Data sources include official monthly reports from the China Iron and Steel Industry Association, weekly inventory reports from coastal ports, daily production and sales reports from steel mills, delivery data from futures exchanges, and internal research reports from leading traders. Core price and inventory data is updated daily. Overall industry analysis is updated weekly. Full industry research reports are released monthly. Document structure includes fixed fields such as regional output, price per ton (yuan/ton), inventory volume (10,000 tons), month-on-month change rate, upstream and downstream supply and demand linkage, and policy interpretation. Some long research reports include cross-page tables and historical data comparisons.

Constraints Imposed During Model Integration and Configuration

These characteristics create constraints during the model integration and configuration phase:

  • Daily updated high-frequency data requires limiting the recall range to the last 7 days, to avoid including outdated data.
  • Fixed professional fields and units require the model to accurately identify entities such as yuan/ton and 10,000 tons, to prevent extraction errors.
  • Long tables and multi-dimensional data require a sufficient context window to hold multiple recalled segments, avoiding truncation of key information.
  • Dispersed multi-source data requires configuring multi-path recall rules to cover research report content from industry associations, ports, traders, and other sources.

Configuration Settings

Configuration ItemRecommended ValueRationale
maxQuoteCountTop 8-12 entriesSupply and demand data in steel trade research reports is scattered across multiple segments, requiring sufficient citations to cover upstream and downstream linkage information
chunkSize1200-1800 charactersAvoid splitting core price tables and cross-page data, preserving the integrity of indicator fields
similarityThreshold0.72-0.80Filter low-relevance results from general industry research reports, retaining precise matching content in professional steel field
recallTopK15-20 entriesSteel data has multiple dimensions, requiring sufficient recall volume before screening core information via reranking
rerankTopNTop 5-7 entriesFocus on three key research report segments: price, inventory, and policy, to avoid redundancy
maxContext8000-12000 charactersAccommodate multiple recalled research report segments, ensuring the model can integrate upstream and downstream data for analysis
parseTimeout120 secondsLonger processing time is required for table parsing and field extraction in long research reports

The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Misconfigurations

  • Phenomenon: Setting maxQuoteCount to 2000 shows matched content in recall logs, but no segments are cited in model outputs. Cause: The maxContext parameter is not adjusted synchronously. Out-of-window citation segments are truncated, so the model cannot access valid citation content.
  • Phenomenon: Locally deployed models return steel price data that does not match actual research reports, with unit confusion. Cause: No professional domain entity recognition rules are configured, and priority use of unit fields such as yuan/ton and 10,000 tons from research reports is not specified.
  • Phenomenon: The custom model configured for the application is displayed as another model in the chat interface. Cause: Environment variables for model mapping are not correctly configured, or proxy forwarding rules are not bound to the specified model interface.

How to Verify Successful Configuration

  • Upload a latest steel industry research report, check if the parsed segments retain core tables and indicator fields, and verify the rationality of segment splitting.
  • Initiate a query about the price of a specific steel variety, check if the number of recall results and reranking priority meet configuration requirements.
  • Adjust the maxQuoteCount parameter, verify if the model output correctly cites the corresponding number of research report segments.
  • View model invocation logs, confirm that the actual used model matches the configured one, with no proxy forwarding exceptions.

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.