What the data for this category looks like
Data sources primarily include monthly monitoring data released by industry associations, thematic analysis from securities research institutions, and industry dynamics from industry portals. The core update cycle is monthly. Core metrics such as regional prices and capacity utilization are updated each month. Extra releases cover event-driven reports, including staggered production policy implementation and raw material price fluctuations. Document structures include regional market analysis, core metric tables, upstream-downstream linkage logic, and policy impact interpretation. Core fields include:
- Regional cement average price (unit: yuan/ton)
- Monthly output (unit: 10,000 tons)
- Enterprise inventory (unit: 10,000 tons)
- Policy implementation cycle (unit: month)
Single document word counts vary widely. Some in-depth reports include nested structured tables.
What constraints do these characteristics impose on multi-turn dialogue and prompt engineering
Decentralized data sources require multi-turn conversations to explicitly limit usage to only cement research report data in the uploaded knowledge base. Prompts must mark the authoritative boundaries of data sources to avoid confusion between external public information and internal knowledge base content. The large number of regional divisions and detailed field subdivisions require multi-turn conversations to support precise query condition limiting. Prompts must require returning specified field values for designated regions and time intervals to prevent mixing of cross-regional and cross-time data. The large word count and nested tables in single documents require multi-turn conversations to limit the context window length. Prompts must prioritize extracting structured fields instead of restating full text, and adapt to parsed table structures to ensure uniform return formatting. The monthly update cadence requires multi-turn conversations to support user requests for the latest cycle data. Prompts must automatically match time keywords in user questions to retrieve report content from the corresponding interval.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single cement research reports have relatively high word counts. An overly long context window may cause model output overflow. This range balances context completeness and computational efficiency |
RECALL_TOP_N | Top 10–15 results | The cement industry has detailed regional divisions, requiring coverage of research report data from different regions. This value range ensures coverage of recall results while avoiding redundancy |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Cement research reports often contain nested structured tables, leading to longer parsing times. This duration covers the parsing needs of most in-depth reports |
PROMPT_TEMPLATE | Match the region and time interval specified in the user's question, extract the specified field values from the corresponding cement research reports, and mark the source chapter | The core requirement for cement research reports is structured metric querying. This template guides the model to return required content accurately |
UPLOAD_FILE_MAX_SIZE | 200 MB | Single in-depth cement research reports can reach tens of thousands of words. Bulk uploads require sufficient space to accommodate multiple documents |
SIMILARITY_THRESHOLD | Calibrate based on actual testing | The cement industry has a large number of exclusive terms. Adjust the threshold based on actual recall results to ensure relevance |
The parameter values provided on this page are general recommendations for starting point configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Scenario: An error triggers when uploading cement research report PDF or Excel files, but plain text questions run normally. Cause: The
PARSE_EXCEL_STRUCTUREparameter is not configured, or nested merged cells and dynamic tables in the file exceed parsing adaptation ranges. Cement research reports often contain multi-region nested tables, which are prone to parsing exceptions. - Scenario: Multi-turn dialogue responses take a long time, with loading delays displayed on the interface. Cause: A reasonable limit for
RECALL_TOP_Nis not set, ormaxContextis set too large. After structured data from cement research reports is recalled, additional organization is required. Excessive recall increases computational overhead. - Scenario: The
Unexpected end of JSON inputerror occurs repeatedly when using thechatglm2model. Cause: TheMODEL_MAX_TOKENSparameter is not set, or its value is lower than the output length required for a single round of cement research report responses. The model's output is truncated, preventing generation of a complete JSON format response.
How to Verify Proper Configuration
- Upload a single regional cement research report, initiate a question such as "Extract the regional cement average price from the current report", and check whether the returned result includes the corresponding value and source chapter.
- Initiate consecutive multi-turn follow-up questions, such as first querying the monthly output of a specific region, then asking about the statistical cycle corresponding to that data, and check whether the conversation context retains the limiting conditions from the previous question.
- Upload a batch of cement research report files, test that the upload process has no errors, and check that the parsing progress of uploaded files completes normally.
- Adjust the value of
SIMILARITY_THRESHOLD, test questions containing industry-exclusive terms, and check whether the relevance of recall results meets 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.