What this category of data looks like
Data for this category originates primarily from CAD/CAM software, order BOMs, sheet metal inventory systems, laser cutters, bending machines, and MES systems. Daily documents include 3D part unfolding drawings, CNC cutting programs, bending process cards, nesting diagrams, first-piece inspection records, and process transfer cards. Fields cover bending coefficients, unfolded dimensions, nesting leftover materials, bending sequences, and additional relevant metrics. Common units are millimeters, square meters, and sheets. Data updates trigger with order creation, daily inventory checks, and each equipment changeover adjustment, with update frequencies aligned to production flow rhythms.
What constraints do these characteristics impose on the citation and traceability process
The multi-source, high-frequency update and order-bound nature of this category of data creates multiple constraints for citation traceability. First, daily documents cover multiple types such as drawings and process cards. AI Q&A results must be accurately bound to unique identifiers of the corresponding documents, including CAD drawing numbers and bending process card numbers. Second, data updates frequently alongside orders and equipment changes. Traceability must link to the latest version of data for the current production batch, to avoid referencing expired bending coefficients or nesting plans. Finally, the multi-variety, small-batch production model requires traceability results to distinguish exclusive process parameters for different orders, preventing confusion from cross-order reference.
How to configure the settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 characters | Matches the average content length of a single bending process card or nesting diagram for this category, ensuring complete citation of core parameters |
| Single Recall Limit | Top 3 entries | Aligns with the number of core process documents associated with a single order, avoiding redundant citations that complicate production scenarios |
detail | Enable full traceability display | Shows specific identifiers of cited documents, such as CAD drawing numbers and process transfer card numbers |
responseData | Enable standard citation format | Ensures output includes traceable citation IDs, preventing format irregularities |
| Context Window | 1000–1500 tokens, calibrated via actual testing | Adapts to the production data context length after multi-system integration |
Three common configuration errors
- Phenomenon: Citation markers in conversation output appear garbled, and display as standard quotation marks in the final result. Cause: The standard citation format for
responseDatawas not configured correctly, causing output citation identifiers to fail to render per specifications. - Phenomenon: Irrelevant document citations are returned even when the query falls outside the knowledge base scope. Cause: The automatic citation toggle for no recall results was not disabled, incorrectly associating process data from non-target batches.
- Phenomenon: No associated citation ID field appears in results returned after calling the conversation API. Cause: The full traceability display setting for
detailwas not enabled, so the API did not return traceability-related data.
How to confirm the configuration is complete
- Initiate a query that includes specific bending parameters or nesting plans, then check if the output includes standard citation identifiers with no garbled characters or missing fields.
- Input a process question not included in the knowledge base, then confirm the returned result does not include citation markers for irrelevant documents.
- Call the conversation API, then check if the returned data includes traceability-related field information.
- View the knowledge base search card, then confirm variable references can be bound to the process document path for the target order.
The values provided here are common starting points and should be evaluated against the reader's own samples.