What the data for this category looks like
The data for the cement industry mainly comes from monthly supply and demand reports released by the China Building Materials Federation, daily quotes from cement spot trading platforms, regular financial reports of publicly listed companies, and regional policy documents. Update frequencies fall into three categories: spot quotes are updated daily, industry supply and demand data is updated monthly, and financial reports and policy documents are released quarterly or on an ad-hoc basis. Document structures include three types: structured tables (such as regional cement prices and clinker production capacity), unstructured research report text, and official policy texts. Fields include P.O42.5 cement ex-factory price (unit: yuan/ton), clinker production capacity (unit: 10,000 tons/year), regional inventory days (unit: days), and some documents include cross-regional market correlation data.
What Constraints Do These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering?
The multi-source nature and varied update rhythms of cement data require that multi-turn dialogue must distinguish the recall priority between real-time spot data and historical industry data, to avoid confusing information from different time dimensions. The mixed structured and unstructured characteristics of documents require that prompt engineering must specify different parsing and output rules for documents of different formats. For example, extract field associations for tabular data, and extract core logic for research report text. The specific unit requirements for fields require that prompt engineering must enforce matching the units of corresponding fields during output, to prevent unit errors. The large number of granular dimensions, including regional and product model variations, require that multi-turn dialogue must track the user's question context, retain key parameters such as region and model, and avoid incorrect cross-dimensional matching.
How to Set Configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single cement investment research documents are relatively long. Multi-turn dialogue needs to retain key context such as product model and region from previous rounds, to avoid losing critical information due to context truncation |
recallCount | Top 6–8 results | Cement data has many granular dimensions, including labels such as region, product model, and time period. Too many recall results will cause context redundancy, while too few will miss relevant segmented data |
segmentLength | 1000–1500 characters | Cement industry documents contain a large number of long table paragraphs. Too long segments will destroy the field associations in tables, while too short segments will split business logic across paragraphs |
similarityThreshold | 0.75–0.85 | Cement data has many granular labels. A threshold that is too low will introduce irrelevant data from incorrect regions or models, while a threshold that is too high will miss critical segmented data with slightly lower matching scores |
promptTemplate | Match the cement model, region and time range specified in the user's question, and annotate the data source and update time when outputting | Cement data has strong timeliness and many granular dimensions. Prompt engineering must enforce output format and traceability requirements |
rerankCount | Top 3–4 results | Retain the most relevant segmented data after reranking, to avoid context overload during multi-turn dialogue |
The parameter values provided on this page are general recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing the configuration.
Three Common Misconfigurations
- Issue: A
401 Unauthorizederror is returned when calling the API, and dialogue requests cannot be initiated normally. Cause: The application key and appId are not correctly distinguished, and the appId is incorrectly passed as the key in the request header. - Issue: The execution results of tool calls during multi-turn dialogue are not included in the context, and subsequent questions cannot reference these results. Cause: The context splicing logic for tool outputs is not configured, and tool return content is not written to the dialogue context queue.
- Issue: Unit confusion appears in responses, for example, marking the clinker production capacity unit as yuan/ton. Cause: The prompt engineering does not clearly specify unit matching rules for specific fields in the cement industry, and does not verify the field units of structured data.
How to Verify Correct Configuration
- Initiate a multi-turn question that includes cement model and region, check whether the context window retains the key parameters from previous rounds. This can be confirmed by viewing the context field in the dialogue log.
- Upload a cement spot price quotation table, trigger knowledge base recall, and check whether the number of recalled results and reranked results fall within the configured value range. This can be verified by viewing the recall list in debug mode.
- Enter a test question that contains unit confusion, check whether the response automatically matches the correct field units. This can be validated by modifying the prompt template and reinitiating the test.
- Initiate a tool call test, check whether the results after tool execution are included in the context of subsequent dialogues. This can be confirmed by viewing the dialogue context queue.
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.