What this category's data looks like
Coal chemical industry financial reports and related data come from periodic reports of publicly traded coal chemical enterprises, industry operation data released by coal industry associations, environmental impact assessment and completion acceptance announcements for coal chemical projects, and public capacity planning documents. Update cycles vary across data types: annual enterprise reports are released yearly, semi-annual reports are updated twice per year, monthly industry data is updated each month, and project phased data is released alongside construction progress. Documents include structured financial tables, descriptions of capacity and energy consumption metrics, and detailed project construction information. Covered fields include output, unit energy consumption, raw material procurement volume, revenue composition, and more. Corresponding units are ten thousand tons, kilograms of standard coal per ton of product, ten thousand tons, and hundred million yuan.
How this category's data characteristics constrain retrieval and recall
The data characteristics of the coal chemical category impose multiple constraints on the retrieval and recall workflow. First, data sources are dispersed. The retrieval system must support unified indexing and correlation of multi-source documents, covering enterprise financial reports, industry association data, and project files. Second, update cycles vary significantly. The system must differentiate synchronization frequencies for annual, monthly, and phased data to prevent outdated data from interfering with retrieval results. Third, documents contain structured tables and specialized terminology. The retrieval system must recognize field-level information and match professional semantic meanings. Finally, field units have granular differences. The system must ensure unit consistency during retrieval to avoid confusion between metrics.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Recall Count | top 10-15 results | Coal chemical financial reports contain multi-dimensional segmented metrics such as capacity, energy consumption, and revenue. A single document has a large amount of information. Too many recalled results will exceed the context window limit, while too few will fail to cover key business metrics |
Similarity Threshold | 0.75-0.85 | The coal chemical field has a large number of specialized terms and segmented metrics. Balance retrieval accuracy and recall completeness to avoid missing key data |
Chunk Length | 800-1200 characters | Financial report documents contain long paragraphs of project analysis and energy consumption calculation content. Chunk length adapts to the semantic completeness of professional expressions, avoiding splitting that disrupts context association |
PARSE_FILE_TIMEOUT_SECONDS | 300-600 seconds | A single coal chemical annual report or industry research report contains a large number of charts and raw data, which takes a long time to parse. Extending the timeout period avoids file parsing failures |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Coal chemical financial report documents contain multi-page charts and structured data tables. Allow larger file uploads to fully import all materials |
Incremental Update Cycle | daily/weekly | Configure incremental synchronization for monthly industry data and quarterly enterprise financial reports according to their update cycles to ensure the timeliness of knowledge base data |
Three common configuration errors
- When calling the
/api/v1/chat/completionsAPI endpoint, specifying an appId does not return uploaded knowledge base content. This occurs when the association binding relationship between the knowledge base and the application is not configured, or the correct knowledge base association parameters are not included in the request body. - The
PARSE_FILE_TIMEOUTstatus code is returned when parsing coal chemical financial report documents. This happens when thePARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and the default timeout period is insufficient to parse long documents containing a large number of charts and raw data. - Unit-mismatched metric data appears in retrieval results, such as confusing kilograms of standard coal and tons of standard coal. This occurs when field-level unit matching verification is not enabled, or the similarity threshold is set too low, resulting in the recall of a large number of non-target category document contents.
How to verify correct configuration
- Upload a quarterly financial report document from a coal chemical enterprise, and check that the parsed chunks retain complete professional expressions without obvious sentence breaking errors.
- Initiate a retrieval request, enter keywords specific to coal chemical industry metrics, and confirm that the document sources of the returned results are the uploaded financial reports and industry materials.
- Check the knowledge base incremental update tasks to confirm that the latest industry data and enterprise financial reports are automatically synchronized according to the preset cycle.
- View the interface request logs to confirm that the knowledge base association parameters are correctly passed, with no missing or incorrect configuration items.
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
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.