What Data for This Category Looks Like
Bid-related data for general mechanical equipment assembly primarily comes from PLM/ERP, part inspection data, assembly tool collection, test benches, MES, and customer technical agreements. Data is updated per single device or per order. Daily documents include assembly process cards, BOMs, torque records, gap adjustment records, commissioning reports, factory inspection sheets, and packing lists. Data fields include material codes, assembly torque (unit: N·m), gap values (unit: mm), test parameters, and other items. Document structures are slightly adjusted for different customized orders.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
Data for this category is updated per single device or order, requiring multi-turn dialogue to bind exclusive data for the corresponding order to avoid cross-order data confusion. There are many document types and fields with specific units, so prompts must explicitly require retaining units and distinguishing the purpose of different documents. Matching assembly commissioning data with bidding requirements requires multi-turn context support. The messages parameter must maintain order information and adjustment records from historical conversations, and variables must pass in the order number to associate with the corresponding BOM and process files in PLM, preventing data misalignment.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 token | Adapts to the total length of multiple assembly documents, bid documents, and historical conversations |
| Single recall result limit | Top 10 entries | Matches the typical entry scale of single-unit assembly data, avoiding interference from redundant information |
variables parameter configuration | Pass in the current order number | Associates with BOM and assembly process data for the corresponding order in PLM/ERP |
messages parameter handling | Append system prompts and user input by turn | Maintains context consistency for multi-round quotation adjustments during the bidding process |
| Timeout threshold | 600 seconds | Adapts to the time required for complex BOM verification and multi-document recall |
| Variable passing switch | Enabled | Enables dynamic binding of order-specific data |
Three Common Misconfigurations
- An uncaught exception is returned when calling the dialogue component, with logs showing failure to load assembly data for the corresponding order. The cause is that the binding path of the
variablesparameter is not correctly configured in a private deployment environment, making it impossible to associate exclusive data in PLM. - The generated bid document does not reference assembly cost data from the knowledge base, and the reply does not include material unit prices from the BOM. The cause is that the prompt fails to explicitly require prioritizing the use of current order BOM fields for calculation, and fails to associate historical context in
messages. - The dialogue page crashes, with browser console showing rendering timeout. The cause is that the number of documents recalled in a single call is set too high, exceeding the page rendering cache threshold of FastGPT v4.17.0.
How to Verify Correct Configuration
- Pass a test order number, check if the dialogue automatically associates fields from the corresponding BOM and assembly process card, and if the returned results include correct material codes and assembly torque units.
- Initiate a multi-round quotation adjustment request, check if the
messagesparameter correctly appends each round of conversation content, and that historical order information is not lost. - Trigger a complex BOM verification task, check if the returned results include fields from the corresponding documents, with no missing data or unit errors.
- View system operation logs, confirm that no uncaught exception errors appear, and that page loading has no crashes.
The values provided are common starting points and should be measured against the reader's own samples.