What this category of data looks like
Cement industry research data mainly comes from industry operation bulletins released by the China Building Materials Federation, public financial reports of cement production enterprises, real-time monitoring platforms for clinker production lines, and building material demand data from local housing and urban-rural development departments. Data update cycles vary: real-time indicators such as ex-factory prices and kiln operation rates are updated daily. Industry production capacity and regional inventory data are updated monthly. Annual industry white papers are released quarterly or annually. Document structures primarily use structured tables, with fields including cement grade (such as P.O42.5, P.C32.5), production origin, ex-factory unit price, inventory volume, unit energy consumption, and others. Units include yuan/ton, ten thousand tons, kilowatt-hour/ton, and similar units.
What constraints do these characteristics impose on deployment and upgrade
The multi-source and heterogeneous nature of cement industry research data requires configuring multi-data source synchronization tasks during deployment, and adapting scheduled scheduling rules for different update frequencies. The high-frequency access requirement for real-time data requires reserving dedicated ports for data pulling during deployment. During upgrades, the real-time synchronization link must not be interrupted, otherwise the latest price and operation rate data will be missing. The feature of multiple structured fields and clearly defined segmented product categories requires the knowledge base vector database to support multi-field joint indexing. During upgrades, indexing rules must be updated synchronously, otherwise recall accuracy for segmented product categories will decrease. In addition, individual large industry reports have a large file size. During deployment, the resource threshold for file processing must be adjusted to avoid triggering system current limiting during batch uploads.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Cement industry research reports and large capacity reports have long individual lengths, requiring sufficient time for parsing |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapt to the upload requirements of large industry white papers and quarterly capacity statistical reports |
RECALL_TOP_N | Top 8 entries | Cement data has many segmented parameters, requiring sufficient dimensions to match precise needs |
SIMILARITY_THRESHOLD | 0.75–0.85 | Balance recall accuracy and coverage, avoid redundant results or missed matches for segmented product categories |
ONEAPI_BASE_URL | Local deployed oneapi service address plus port | Offline deployment scenarios require calling local large model interfaces to avoid reliance on public networks |
NEXT_PUBLIC_DISABLE_LOGIN | false | Version 4.8.15 and above support configuring the identity verification switch; user permission configuration requires enabling this switch |
The parameter values provided on this page are common recommended 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 the settings.
Three common mistakes
- Symptom: Calls to the large model return a 500 status code, and the interface prompts "upstream service unavailable". Cause:
ONEAPI_BASE_URLis not configured correctly, and the default public address is used instead of the local offline deployed oneapi service address. - Symptom: Some long financial reports fail to parse during batch upload of cement industry documents, with the status showing "timeout". Cause:
PARSE_FILE_TIMEOUT_SECONDSis not adjusted, and the default short timeout value is used, which cannot handle long document parsing. - Symptom: The knowledge base recall results have low matching accuracy for segmented cement product categories, and the number of results does not meet expectations. Cause: The values of
SIMILARITY_THRESHOLDandRECALL_TOP_Nare not adjusted according to the segmented characteristics of cement data, resulting in overly strict filtering or insufficient recall coverage.
How to confirm the configuration is correct
- One accesses the interface address corresponding to
ONEAPI_BASE_URL, tests interface connectivity, and confirms that the configured address matches the locally deployed oneapi service. - One uploads a cement industry research report with a length of more than 5000 characters, checks the parsing status, and confirms that the parsing task does not trigger a timeout.
- One initiates a knowledge base recall test, enters keywords for segmented cement product categories, checks the number and matching degree of recall results, and confirms that the configured
RECALL_TOP_NandSIMILARITY_THRESHOLDmeet expectations. - One checks the system version information, confirms that the currently running version is 4.8.15 or above, and verifies that the identity verification configuration module has been loaded.
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.