What This Category of Data Looks Like
Data sources include wood pulp and waste paper batch archives, DCS/QCS control systems, paper machine online measurement equipment, laboratory testing systems, energy and water treatment systems. Data update frequencies cover real-time, per shift, and per paper roll production cycles. Daily documents include pulp preparation sheets, beating records, paper machine operation logs, online quality curves, laboratory quality inspection reports, sheet break and product change ledgers. Fields include batch numbers, operating parameters, quality test values, and timestamps. Units match the document type, including tons, cubic meters, degrees Celsius, grams per square meter, and other standard units.
What Constraints Do These Characteristics Impose on Knowledge Base Retrieval and Recall
Multi-source heterogeneous real-time and batch data requires the retrieval pipeline to support low-latency responses, to avoid impacting the timeliness of production ledger summary. Documents updated per paper roll or per shift production cycle must be associated with the context of the corresponding batch during recall, to prevent invalid matching across production cycles. Multiple document types covering operating parameters, quality curves, and quality inspection reports need to support cross-field associated retrieval, while controlling the total length of recall results to avoid exceeding the model context limit. The retrieval priority of abnormal ledgers such as sheet breaks and product changes must align with the response requirements of production emergency scenarios.
How to Configure
These configurations are adapted for FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Matches the parameter precision requirements of pulp and paper production data, filters out low-correlation non-production documents |
limit | Top 6–10 entries | Adapts to the context length limit of production ledger summary, avoids excessive redundant data interfering with model report generation |
searchMode | fullTextRecall | Use full-text retrieval for text content. Field, metadata, batch, and document-type constraints require separate filters and are not enforced by this mode. |
usingReRank | Enabled | Improves retrieval accuracy for abnormal ledgers such as sheet break records, matching the response requirements of emergency scenarios |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands retrieval terms related to production batches, associates cross-document information such as pulp preparation sheets and paper machine operation records |
collectionIds | Configured by production department grouping | Separates exclusive knowledge bases for departments such as material preparation, pulping, and paper making, avoids interference from cross-department data |
Three Common Configuration Mistakes
- No valid results are returned after the business system calls the retrieval interface. The cause is that the
collectionIdsparameter for the corresponding production department is not configured, and the retrieval scope does not cover core production ledger data such as paper machine operation records and pulp preparation sheets. - A configuration error prompt is returned when adding a knowledge base. The cause is that the data synchronization rule is not configured according to the update rhythm of wood pulp and waste paper batches and per paper roll production cycle, leading to abnormal triggering of knowledge base synchronization tasks.
- Too many retrieval results cause the model to fail to complete report generation. The cause is that a reasonable
limitparameter is not set, and redundant historical operation logs exceeding the model context capacity limit are recalled.
How to Confirm Successful Configuration
- Call the retrieval interface with keywords for a specified production batch, check whether the returned results include corresponding documents such as pulp preparation sheets and beating records.
- View the knowledge base synchronization logs, confirm that data has been synchronized according to the per shift and per paper roll production cycle, with no abnormal error records.
- Adjust the
similarityparameter range, verify whether the relevance of retrieval results meets the precision requirements of production data. - Test with abnormal scenario keywords such as "sheet break", confirm that when
usingReRankis enabled, corresponding sheet break and product change ledger records are returned first.
The values provided here are common starting points and should be measured against the reader's own samples.