Context and Token for Refractory Material Investment Research Knowledge Base Construction

Refractory material investment research data comes primarily from public reports from national refractory industry associations, technical manuals and

What the data for this category looks like

Refractory material investment research data comes primarily from public reports from national refractory industry associations, technical manuals and factory quality inspection reports from production enterprises, kiln operating condition monitoring data, bulk commodity price data for raw materials including bauxite and magnesia, and national and industry-related standard documents. The update cadences of various data types differ significantly: raw material prices are updated weekly, operating condition monitoring data is updated daily, industry research reports are released quarterly, and standard documents are revised every 3 to 5 years.

Document structure includes technical parameter tables with fields such as material grade, chemical composition and refractoriness, operating condition analysis documents, and supply chain data documents. Most core fields have clear units: refractoriness is measured in degrees Celsius, and bulk density is measured in grams per cubic centimeter.

Constraints on context and token handling

Document token lengths vary widely across data sources. Short items like quality inspection parameter tables are hundreds of characters long, while in-depth industry reports can reach tens of thousands of characters. Context recall mechanisms must adapt to this wide range of content lengths. This avoids scenarios where a single recalled item is too long to exceed token limits, or too short to cover all parameters required for investment research.

Core fields with clear units require context recall to retain unit information, preventing models from confusing parameter values with different units. Multi-source data with varying update frequencies requires regular synchronization of knowledge base vector data, to prevent context recall of outdated price or operating condition data. When comparing multiple batches of refractory material performance in bulk, context must recall multiple related documents, further increasing token consumption pressure.

Configuration Settings

Configuration ItemRecommended ValueRationale
maxContext8000–12000 tokenAdapts to the mixed recall needs of split industry reports (tens of thousands of characters) and short parameter tables, avoids single-round context exceeding model limits
chunkSize800–1200 charactersRefractory material technical documents combine structured parameter tables and long-text analysis. This segment length balances token utilization and information integrity
topKTop 6–8 entriesInvestment research requires comparing multiple batches of material performance. Too many recalled items increase token consumption, too few fail to cover sufficient comparison dimensions
rerankThreshold0.75–0.85Filters low-relevance non-refractory material documents, retains context content directly related to target grades and operating conditions
PARSE_CHUNK_OVERLAP100–150 charactersPrevents segment splitting from destroying the integrity of continuous fields such as chemical composition and temperature ranges
maxTokenPerMessage4000 tokenLimits the total token count of a single round of user questions and context splicing, prevents triggering 422 errors

The parameter values provided on this page are conventional recommendations used as starting points 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 settings.

Three Common Configuration Mistakes

  • Triggering the 422 "Messages token length must" error: The total token count of context and user question splicing in a single session exceeds model limits. maxTokenPerMessage or maxContext parameters are not configured correctly.
  • Context cannot be maintained across turns in multi-session conversations: The global context synchronization switch is not enabled, or context variables are not correctly bound in the workflow, resulting in loss of historical material grade parameters required for investment research.
  • Irrelevant construction material data appears in recall results: The rerankThreshold is not set, or no refractory material category filter is added during recall, resulting in non-target category documents being mixed into the context.

How to Verify Correct Configuration

  • Upload a typical refractory material technical manual, check if the parsed segment length matches the chunkSize configuration, and if keyword fields are retained in segment overlaps.
  • Initiate a question involving comparison of multiple batches of material parameters, verify that the number of recalled context documents falls within the topK configuration range, and that no irrelevant category content is present.
  • Test initiating three or more consecutive investment research questions in a single session, confirm that historical parameters are correctly included in the context window.
  • Check system logs to confirm that no Messages token length must related errors appear, verifying that the maxContext and maxTokenPerMessage configurations are active.

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.