What this category of data looks like
Data sources for this category include manufacturing enterprise MES systems, online testing equipment, laboratory records, process parameter libraries, customer quality standards, and historical defect libraries. Data is updated by production batch and shift, with some real-time testing parameters collected continuously. Associated daily documents include control plans, patrol inspection records, SPC reports, finished product inspection reports, nonconforming product review forms, release forms, and monthly quality reports. Data fields include batch identifiers, test item values, nonconformance types, inspection results, release approval status, and more. Units change dynamically based on the type of test item.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Data sources for this category are scattered and update rhythms vary significantly. Multi-turn dialogue must gradually retrieve ledger content from different data sources such as MES and testing equipment to avoid overloading single requests. Different document types correspond to exclusive fields, so prompts must clearly match the field rules of documents such as control plans and finished product inspection reports. For data without unified units, dialogue must guide supplementary unit descriptions to prevent result deviations. Release approval is associated with permission data, so the scope of dialogue queries must be limited to avoid unauthorized access. The data volume of a single batch is large, so the context window size must be controlled to ensure smooth dialogue logic.
How to set up configurations
All configurations must be completed based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Maximum Context Window | 10000–15000 token | Adapts to the total data volume of single-batch ledgers for this category, avoiding context overflow that disrupts dialogue logic |
chatId binding rule | Bind unique chatId by production batch | Ensures correct association of dialogue history for the same batch, avoiding confusion of cross-batch data |
variables preset fields | Preset batch number, inspection date, release status | Quickly retrieve corresponding ledger data, reducing redundant input steps |
| Historical dialogue call limit | Top 8 historical dialogues | Adapts to the conventional dialogue rounds per shift or batch for this category, filtering redundant information |
messages format requirement | Organize in the order of user question - assistant reply | Complies with the interaction logic of multi-turn dialogue, facilitating accurate context parsing |
| Context retention duration | 24 hours | Matches the production cycle per shift for this category, ensuring traceability of dialogue history for the same shift |
Three common configuration mistakes
- Dialog history-bound test images fail to load when not logged in. Cause: Unique
chatIdis not bound by production batch, so the system cannot match the image resource path for the corresponding batch. - After calling the application with this configuration via workflow, no ledger summary report for the corresponding batch is generated. Cause: Core variables such as batch number and inspection date are not preset in
variables, so the application cannot retrieve ledger data from the specified data source. - The form input node dialog box always displays in nested workflows. Cause: Interaction rules for external calls are not adjusted in the application configuration, so the pop-up logic in nested scenarios is not properly covered.
How to confirm the configuration is correct
- Initiate a multi-turn dialogue for the corresponding production batch, check whether
chatIdautomatically updates with batch switching, and whether historical dialogue only associates data from the current batch. - Enter the preset
variablesto verify whether the application can automatically retrieve documents such as control plans and inspection reports for the corresponding batch. - After initiating a multi-turn dialogue, check that the context window does not contain redundant cross-batch data, and that the dialogue logic does not have abnormal interruptions.
- Test the nested workflow call scenario to confirm whether the form input node dialog box hides as expected.
The values provided are common starting points and should be measured against the reader’s own samples.