What the Data for This Category Looks Like
The data for carbon steel research reports comes primarily from publicly available statistics released by the China Iron and Steel Industry Association, regular financial reports of listed steel enterprises, and industry analysis reports from commodity consulting firms. Three update cycles apply: association statistics are updated weekly or monthly, financial reports are updated quarterly or annually, and industry research reports are released on an as-needed basis.
Document structures typically include carbon steel product grade specifications, market price ranges, upstream and downstream supply and demand data, and policy impact analysis. Core fields include product model, transaction price (unit: yuan/ton), monthly output (unit: 10,000 tons), inventory level, and more. The word count of individual documents varies widely.
Constraints on Knowledge Base Retrieval and Reranking Workflows
The detailed product grades and precise quantitative indicators in carbon steel research reports require retrieval to prioritize matching professional terminology and specific numerical values. This prevents retrieving unrelated generalized content.
Frequently updated price and output data require the knowledge base index update cycle to align with the data release rhythm. This avoids retrieving outdated information.
Structured data across multiple fields requires targeted retrieval rule configuration. This ensures that core indicators have higher recall priority than non-core content.
Segmentation processing for long documents must adapt to the chapter structure of research reports. Splitting that breaks logical connections between upstream and downstream analyses will harm retrieval relevance.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall count | top 10-15 | Core analysis content for carbon steel research reports is concentrated in a small number of documents. Too many recalled entries will increase context redundancy, while too few will fail to cover relevant specialized reports |
similarity threshold | 0.75-0.85 | Professional terminology for carbon steel has high distinguishability. A threshold that is too low will introduce irrelevant generalized commodity content, while a threshold that is too high will miss relevant specialized research reports |
segment length | 800-1200 characters | The logical units of chapters in carbon steel research reports are mostly measured in thousands of characters. Splitting documents at this length preserves complete indicator analysis and upstream and downstream connection logic |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Individual carbon steel research reports contain large amounts of structured data and chart parsing. The default timeout period is insufficient to complete full parsing |
reranked return count | top 5-8 | Core price and output analysis is concentrated in a small number of reports. Reranking filters out non-core content and optimizes context quality |
text understanding model | select a model that supports professional word segmentation | Carbon steel contains a large number of exclusive grades and industry terminology. General word segmentation models may incorrectly split professional vocabulary, which reduces retrieval matching accuracy |
The parameter values provided on this page are all conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: After restoring a project backup, the backend knowledge base and agent list are empty. Cause: The backup only includes project files, and does not synchronize associated knowledge base storage files. The corresponding directory content must be restored at the same time.
- Symptom: Knowledge base responses are truncated, with only partial content output. Cause: The configured
maxContextparameter value is too small to accommodate the complete analysis content of the recalled carbon steel research reports, which causes the model output to be truncated. - Symptom: Timeout errors occur when parsing carbon steel research reports, and the log shows
ETIMEDOUT. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout period is insufficient to complete parsing of long documents containing large amounts of structured data.
How to Confirm Proper Configuration
- Upload a standard carbon steel research report, review the parsed segmented content, and confirm that the segment length falls within the configured range and that chapter logical connections are not broken.
- Enter keywords for core carbon steel indicators, such as "HRB400 inventory", check the number of recalled results and their alignment with the similarity threshold, and confirm that results are concentrated in relevant specialized research reports.
- Review parsing logs, confirm that parsing time does not exceed the configured timeout parameter value, and that no timeout error records exist.
- Initiate complex queries that include multiple indicators, confirm that the model output is not truncated, and that the recalled content in the context meets expected 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.