What the Data for This Category Looks Like
Data sources for special steel research reports include industry monitoring reports released by the China Special Steel Enterprise Association, special research reports publicly released by domestic special steel production enterprises, and on-site survey data from steel industry chain research institutions. Core varieties receive monthly updates for price and production volume data. Full-category supply and demand in-depth analysis is released quarterly. Real-time supplementary documents are triggered for sudden industry events. Document structure includes product grade classification, core production and sales data, upstream and downstream industry chain linkage analysis, policy impact interpretation, and future market prediction modules. Available fields include product grade, monthly production volume, average ex-factory price, raw material procurement cost, and downstream application field sales proportion. Corresponding units are none, ton, yuan per kilogram, yuan per ton, and proportion of total sales respectively.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Special steel research reports cover multiple sub-categories such as mold steel, stainless steel, and bearing steel, with highly recognizable professional terminology. Multi-turn dialogue must continuously track the specific product grade currently under discussion to avoid generalized retrieval that results in off-target outcomes. Research report update rhythms are layered. Core varieties have monthly production and sales data updates, while full in-depth analysis is released quarterly. Prompts must clearly specify the data update time range to prevent the use of outdated historical data. Documents contain multiple independent modules. Multi-turn dialogue must guide users to clarify their required content type to avoid confusion between production and sales data and policy interpretation content. There are subtle differences in field units. For example, price is measured in yuan per kilogram, while production volume is measured in tons. Prompts must uniformly limit the unit format to prevent unit confusion in output.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single in-depth special steel research report is usually 5000-8000 characters long. Multi-turn dialogue needs to retain 3 rounds of context, total length adapts to documents and conversation content |
recallTopK | Top 8–12 results | There are many sub-categories of special steel research reports. Too many recalled entries will introduce irrelevant content, too few will fail to cover all relevant data of the target category |
similarityThreshold | 0.72–0.78 | Special steel industry terminology is highly professional. Low-similarity irrelevant research report content must be filtered to avoid retrieval results deviating from the target |
rerankTopN | Top 3–5 results | Retain the most relevant special steel sub-category research reports after re-ranking, to avoid information overload during multi-turn dialogue |
promptTemplate | Template that fixedly includes the currently discussed special steel grade and data update time range | Special steel research reports have strong sub-category attributes. Retrieval scope must be clearly limited to prevent recalling content from non-target categories |
emptyResponsePrompt | Return “No research report data for the corresponding special steel category found. Please adjust keywords or add supplementary explanations” | Avoid conversation interruption caused by empty responses, clearly inform users of adjustment directions |
The parameter values provided on this page are common starting points for configuration setup. 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
- Phenomenon: The content returned after invoking the knowledge base dialogue is unrelated to the queried special steel category. For example, asking for the price of H13 mold steel returns quotations for ordinary steel. Cause: The special steel sub-category is not limited in the prompt, leading to recall of research report data from non-target categories.
- Phenomenon: The AI dialogue node occasionally returns empty content, and the log shows the
chat:LLM_model_response_emptyerror code. Cause: There are many professional terms in special steel research reports. Some models have insufficient understanding of context in sub-fields, leading to breaks when generating responses. - Phenomenon: Unclosed quotation marks appear at the end of AI output content, which is automatically corrected in subsequent conversations. Cause: Output format is not uniformly specified in the prompt, leading to format errors when the model generates long text.
How to Verify Proper Configuration
- Initiate a single-turn query specifying a specific special steel grade and data type, verify that the recalled research reports match the target content, adjust
recallTopKandsimilarityThresholduntil the results meet expectations. - Initiate 3 consecutive rounds of dialogue, verify that the system can track the special steel category and data time range mentioned in the previous round, adjust
maxContextto ensure context is correctly retained. - Trigger an empty response scenario, such as entering a non-existent special steel grade, verify that the returned content matches the preset empty response prompt, adjust
emptyResponsePromptto ensure clear prompts. - Initiate a long-text query, verify that the output content has a unified format with no unclosed quotation marks, adjust
promptTemplateto add format constraints.
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.