What the data for this category looks like
This category covers entities engaged in color printing, label, carton, flexible packaging, and pharmaceutical packaging material processing. Data comes from customer submissions, color management systems, printing press operation data, ink and substrate batch records, spectrophotometers, barcode detectors, and other equipment and systems. Daily documents include pre-press files, imposition sheets, printing process sheets, ink color matching records, first article signing sample reports, barcode inspection results, die-cutting and lamination process records, and more. Data updates trigger with every order, production batch, and plate change. Each document includes fields like text and image versions, color parameters, packaging structure, and process parameters. There is no unified fixed unit; values vary based on the corresponding process type.
What constraints these characteristics impose on knowledge base retrieval and recall
Unlike paper-making categories that only handle substrate data, this category must process three types of data at once: content versions, color parameters, and packaging structures. Retrieval must cover multi-dimensional fields. High-frequency data updates require retrieval to quickly match the latest plate, batch, and process parameters. This prevents recalling outdated incorrect data. Exact matching for fields like barcodes and batch numbers means retrieval results cannot have field misalignment or cross-batch data mixed in. Each document grows larger as more process records are added. Administrators must control the total length of recalled data to avoid exceeding context processing limits. Plate errors can quickly lead to entire batches of scrapped products. Retrieval must prioritize the latest data with the highest match to the current order.
How to set configurations
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Requires precise matching of process parameters and batch identifiers, filtering irrelevant outdated data with low similarity |
limit | Top 8–12 entries | A single production ledger includes multiple process records. This setting covers enough relevant data without exceeding the context limit |
searchMode | mixedRecall | Matches text content, color parameters, and batch numbers simultaneously, balancing semantic relevance and exact matching |
usingReRank | Enabled | Retrieval results for multi-dimensional fields need re-ranking to prioritize process data with the highest match to the current order |
datasetSearchUsingExtensionQuery | Set based on actual testing | Adjust the extended query scope using special packaging requirements for orders to avoid recalling irrelevant data |
Three common errors
- Phenomenon: A parameter error prompt appears when the workflow calls knowledge base retrieval. Cause: The
collectionIdsparameter is not configured correctly, and the knowledge base collection for printing process sheets and batch records is not specified. - Phenomenon: Abnormal format is returned during knowledge base question-and-answer splitting. Cause: The chunking logic is not adjusted for multi-field documents in packaging processing, leading to single chunks containing discontinuous content across processes.
- Phenomenon: A 503 error is returned when uploading pre-press files to the dialog box, but no exception occurs when uploading to the knowledge base collection. Cause: Single file upload size is not restricted, causing temporary cache during the retrieval link to exceed the threshold.
How to confirm the configuration is correct
- Trigger the ledger summary process for a single order, and verify that the current batch's ink color matching record and first article signing sample parameters are included in the retrieval results.
- Check the number of results returned by retrieval, confirming it matches the value range of the
limitparameter. - Upload a new plate file and confirm that the retrieval result prioritizes recalling the latest version of process data.
- Run a workflow test and check for any parameter error or context overflow prompts.
The values provided are common starting points and should be measured against the reader's own samples.