What data is typical for this category
Typical data for basic chemical continuous production comes from DCS/SIS control systems, online analyzers, LIMS laboratory systems, equipment condition monitoring tools, energy metering systems, and raw material storage systems. Data updates follow two schedules: real-time operating condition data, and shift operation records plus daily reports. Daily documents include operating procedures, process index cards, DCS trend charts, laboratory reports, interlock bypass records, special work permits, and shift logs. Document fields cover process parameter values, equipment status indicators, alarm thresholds, work approval status, and similar items. Supported units include common industrial units such as temperature, pressure, and flow rate.
What constraints do these characteristics impose on knowledge base retrieval and recall
The real-time and multi-type data characteristics of this category require knowledge base retrieval to support mixed retrieval of dynamic operating condition data and static documents. Data sources with multiple update frequencies increase the complexity of incremental synchronization. Retrieval workflows must support filtering recall scope based on time granularity. High confidence requirements for content related to strong interlocks and alarms require limiting redundancy in retrieval results to avoid irrelevant information interfering with core decision-making. Differences in document structures require chunking strategies adapted to different content formats such as long-text trend charts and short-text work permits. This ensures retrieval completeness and accuracy.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Matches the precision requirements for basic chemical process parameters, filters low-correlation non-process documents |
limit | Top 8 entries | Covers multi-dimensional reference information required for process documents and exception reports, avoids overly one-sided single results |
searchMode | mixedRecall | Adapts to mixed knowledge base content with structured parameter data and unstructured text |
usingReRank | Enabled | Performs secondary ranking on initial recall results, improves ranking priority for content related to interlock alarms |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands professional term queries related to processes, covers synonyms and industry abbreviations |
collectionIds | Specified via dedicated collection | Isolates dedicated knowledge bases for basic chemical continuous production, avoids confusion with data from other categories |
This configuration is implemented using the knowledge base feature of FastGPT v4.17.0.
Three Common Misconfigurations
- Phenomenon: An error occurs when uploading an XLSX format process file, prompting that the file cannot be read. Cause: Structured table file parsing rules are not configured, and vector extraction for table content is not enabled.
- Phenomenon: Insufficient retrieval results fail to cover the complete exception handling process. Cause: The
limitparameter value is too low, and a sufficient recall upper limit is not set. - Phenomenon: Retrieval results include documents from non-basic chemical categories. Cause: The
collectionIdsparameter is not specified, and a cross-category mixed knowledge base collection is used.
How to Verify Correct Configuration
- Upload a single XLSX parameter table for basic chemical processes, submit the query "Query the process indicators for the ammonia synthesis reaction", confirm that the returned content includes specific parameter values from the table.
- View the retrieval log, confirm that the
similarityscore of the recall results falls within the configured threshold range. - Submit a query for an exception scenario, such as "Disposal process after interlock bypass", confirm that the retrieval results only include documents related to basic chemical continuous production.
- Upload an incremental real-time DCS data file, submit an operating condition query, confirm that the retrieval results include the latest production data.
The values provided here are common starting points and should be measured against the reader's own samples.