What the data for this category looks like
Typical entities in printing and packaging processing include color printing, label, carton, flexible packaging, and pharmaceutical packaging enterprises. Documents involved in daily audits include pre-press files, imposition sheets, printing process sheets, ink color matching records, first article sign-off samples, barcode inspection records, and die-cutting and lamination records. Data sources cover customer manuscripts, color management systems, printing press operation data, ink and substrate batch records, spectrometer test results, and barcode detector readings. Data update frequency is per order, per batch, and each time the plate is changed. Pre-press files include text layout and image material fields. Imposition sheets mark plate number and station parameters. Printing process sheets specify printing speed in m/min. Barcode inspection records correspond to the qualified status of the batch.
What Constraints These Characteristics Impose on the Multi-turn Dialogue and Prompt Engineering Link
The multi-turn dialogue and prompt configuration for this category must adapt to fast data updates, multiple document types, and scattered fields. High-frequency data updates require conversation context to bind order batches via chatId, avoiding repeatedly loading irrelevant batch data. Scattered fields across multiple document types require prompts to guide information extraction classified by document type, ensuring audit dimensions cover text plate numbers, color parameters, packaging structures, and more. Batch association requirements mean variables must bind fields such as order number, plate number, and ink model, ensuring each audit round corresponds to accurate business data. The trait that plate errors can spread rapidly requires multi-turn dialogue to real-time verify the matching relationship between plate number and first article sign-off samples, preventing batch errors from entering production links.
How to Set the Configuration
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context | 18–22 previous conversation turns | Covers the full audit session from pre-press design to die-cutting completion for a single order, calibrated via on-site testing |
chatId | Bind to order batch number | Associates each conversation turn with the corresponding batch's business data, preventing confusion of audit information across orders |
variables | Bind to plate number, ink batch, barcode number | Extracts core fields from printing process sheets and barcode inspection records, for real-time calling and verification by prompts |
messages | Load grouped by document type | Loads context for imposition sheets, first article sign-off samples, and die-cutting records separately, reducing interference from irrelevant data on audit logic |
| Single Search Limit | Top 5–7 matching documents | Matches multiple types of audit documents including pre-press files and process sheets; 5–7 entries cover core audit basis |
Three Common Mistakes
- Phenomenon: After configuring variable references, the temperature setting button disappears, and custom generation parameters cannot be adjusted. Cause: The independent context for parameter configuration is not retained in the fields bound by
variables, causing the system to automatically hide advanced setting options. - Phenomenon: After calling the workflow, the running data in the conversation log is empty. Cause: The session and workflow batch association is not bound via
chatId, causing the data generated by the workflow to not be attached to the current session. - Phenomenon: The Markdown content generated by copying the conversation has no line breaks, and a prompt to manually select text pops up. Cause: The
messagescontext loading rules are not split by document type, causing the formatting of multiple types of audit documents to be merged.
How to Confirm the Configuration is Correct
- Initiate a test conversation that includes plate number and ink batch, check whether
variablescorrectly extract the corresponding fields. - Copy the conversation content, check whether the generated Markdown splits line breaks according to document type.
- Call the workflow associated with the batch, confirm that the corresponding running data is displayed in the conversation log.
- Adjust the generation parameters, check whether setting options such as temperature are normally displayed and take effect.
The values provided here are common starting points and should be measured against the reader's own samples.