What the data for this category looks like
This category of data covers daily production documents of enterprises engaged in color printing, labels, cartons, flexible packaging, and pharmaceutical packaging materials, including pre-press files, imposition sheets, printing process sheets, ink color matching records, first-piece sample signatures, barcode detection records, and die-cutting and lamination records. Data sources include customer manuscripts, color management systems, printing press operation data, ink and substrate batch records, spectrometer and barcode detector output results. Data updates occur per order, per batch, or each time a plate is changed. A single document includes fields such as version number, color value parameters, batch number, barcode number, and die-cutting size, with units including pixels, pascals, meters, and others.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
This category of data is updated frequently and triggered by orders, plate changes, or batches. Multi-turn dialogue contexts must be bound to the exclusive document set of the corresponding order to avoid cross-batch data confusion. Documents contain multiple types of content including text, images, color values, and barcodes. Prompts must clearly distinguish different tasks such as content review, parameter verification, and compliance checks to prevent the model from confusing verification logic across different fields. Data sources are diverse and field units are inconsistent. Each round of multi-turn dialogue must supplement unit descriptions for context fields to avoid the model making misjudgments of parameter thresholds. The number of documents associated with a single order is relatively concentrated. The scope of the document set called in a single round of dialogue must be limited to prevent context overload from reducing response efficiency.
How to configure the settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the current order | This category of data is updated per order, plate change, or batch. Isolating the context of different orders via chatId avoids cross-batch data confusion, and adapts to the session isolation logic of FastGPT v4.17.0 |
| Maximum context length | 800–1200 characters | The number of documents associated with a single order is relatively concentrated. An overly long context will cause model response delays, matching the document scale characteristics of this category |
variables | Pass the batch number and version parameters of the current order | Documents in this category include exclusive fields such as batch number and version number. Passing context constraints via variables ensures the accuracy of model verification |
| Single search limit | Top 4 results | The number of relevant documents for a single order is concentrated. Too many search results will increase the model's processing burden and improve interaction efficiency |
messages | Supplement unit descriptions of document fields per interaction round | Data sources for this category are diverse and field units are inconsistent. Passing unit context for each round of interaction via messages avoids the model making misjudgments of parameter thresholds |
| Timeout duration | 600 seconds | Some documents in this category include images and complex color value parameters, which require longer processing time for the model, adapting to the response requirements of production scenarios |
Three common misconfigurations
- Phenomenon: Dialogue return content carries a large number of meaningless punctuation marks such as # and *. Cause: The prompt fails to explicitly require filtering non-business-related format symbols, and no format verification rules for dialogue content are configured.
- Phenomenon: The dialogue does not return the knowledge base document identifiers referenced in this interaction. Cause: The document set identifier of the current order is not bound in the
messagesparameter, causing the session context to fail to associate with the corresponding knowledge base, so reference information cannot be output. - Phenomenon: Printed sample images in the knowledge base cannot be displayed in the dialogue. Cause: The URL address of the image is not correctly embedded in the
variablesparameter, and the prompt fails to explicitly require the model to reference the image link for display, adapting to the pre-press file review scenario of this category.
How to confirm the configuration is complete
- Initiate a test dialogue targeting the documents of a single order, and check whether the session context only contains the exclusive document content of that order.
- View the dialogue return results, and confirm whether non-business-related format symbols are filtered out, leaving only the text and parameter information required for review.
- Verify the dialogue return reference information, and confirm whether it includes the knowledge base document identifiers associated with the current order.
- Test the scenario of passing an image URL, and confirm whether the image link and related descriptions are correctly displayed in the dialogue.
The values provided here are common starting points and should be measured against the reader's own samples.