What the data for this category looks like
Construction machinery research report data primarily comes from official statistical reports from a national construction machinery industry association, public operational briefings from leading original equipment manufacturers, and public research reports from third-party industry consulting firms. There are three update schedules: monthly sales data is updated on a fixed monthly cycle; quarterly industry analysis reports are released within 15 working days after the end of the quarter; annual industry white papers are updated by the end of January of the following year.
Typical document structure includes industry macro environment, operational data for segmented equipment models (excavators, cranes, bulldozers, etc.), supply chain price trends, policy interpretations, market competition landscape and future trend projections. Core fields include model name, sales volume (unit: units), revenue (unit: ten thousand yuan), unit price of components (unit: yuan per piece), monthly operating hours (unit: hours). No percentage-based statistical indicators are used.
Constraints on Model Access and Configuration From These Data Characteristics
First, individual research reports are lengthy and dense with professional content, which consumes more context window. Adjust segment and retrieval length parameters to avoid truncating critical data passages. Second, data update cycles vary. Configure knowledge base synchronization rules adapted to different update schedules to prevent old data from interfering with retrieval results. Third, fields have dedicated units and segmented category tags. Configure field extraction and matching rules to ensure retrieval results accurately correspond to dedicated data for the construction machinery category. Fourth, there are many segmented equipment models, and research report content is scattered. Adjust retrieval and reranking parameter thresholds to filter irrelevant general industry content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Professional content in individual segments of construction machinery research reports is lengthy, requiring coverage of complete technical or data passages to avoid truncating critical information |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Individual research reports have a large number of pages, with parsing time exceeding the default threshold. Extend the timeout to ensure complete parsing |
| Number of retrieved passages | 10–15 entries | There are many segmented construction machinery models, requiring retrieval of sufficient relevant passages to cover different models and data dimensions |
| Similarity threshold | 0.75–0.85 | Filter low-relevance general industry research report content, and accurately match segmented construction machinery models and dedicated data fields |
| Number of reranked returned passages | 5–8 entries | Retain the most relevant research report passages to avoid redundant content affecting the accuracy of model generation results |
KNOWLEDGE_UPDATE_CRON | 0 0 2 ? | Adapt to the monthly data update cycle, trigger updates at 2:00 AM daily, ensuring the knowledge base completes synchronization before monthly data is released |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- Symptom: A
408 Request Timeouterror occurs when parsing research reports. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and parsing time for lengthy individual research reports exceeds the default threshold. - Symptom: Non-construction machinery general industry content is mixed into retrieval results, and dedicated fields such as sales volume and operating hours cannot be matched correctly. Cause: The
similarity thresholdis not set or is set too low, and field extraction rules are not configured to match dedicated units and category tags. - Symptom: Mathematical formulas or technical parameter expressions in research reports cannot be rendered properly on the web interface. Cause: PDF embedded formulas are not converted to LaTeX or Markdown format, and only the native PDF file is uploaded.
How to Verify Successful Configuration
- Upload a test construction machinery research report, check that the parsed text fully retains dedicated fields and units such as model name, sales volume, and operating hours, and confirm that no truncation or garbled code exists.
- Enter targeted test questions, such as "What is the revenue situation of loaders in the first quarter of 2024", verify that the retrieved research report passages match the time and category of the question, and confirm that the retrieval logic is correct.
- Enable the reranking model function, verify that the sorting of retrieval results meets relevance expectations, and confirm that the reranking configuration is effective.
- Wait for the preset update cycle to trigger, check that the knowledge base automatically updates the latest research report data, and confirm that the scheduled update configuration is working properly.
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.