What Data for This Category Looks Like
Technical document data for general mechanical equipment assembly typically comes from PLM/ERP, part inspection data, assembly tool collection systems, test benches, MES, and customer technical agreements. Data is updated per single device or per order. It includes assembly process cards, multi-level BOMs, torque records, gap adjustment records, commissioning reports, factory inspection sheets, and packing lists. Document fields include material codes, assembly torque (unit: Nm), coaxiality tolerance (unit: mm), preload force parameters, and more. The total character count or line count of documents for some single devices is relatively large.
Constraints on Multi-Turn Dialogue and Prompt Engineering Workflows
The multi-source, order-per-update, and fluctuating volume characteristics of this category’s documents impose multiple constraints on multi-turn dialogue and prompt engineering workflows. First, the volume of data such as BOMs and assembly records associated with a single device varies. Context windows must be limited to avoid overflow. Second, multi-source heterogeneous data—such as PLM BOMs and MES torque records—has inconsistent field formats. Prompts must clearly define field alignment rules. Third, data updated per single device or order must bind conversation context via chatId to ensure multi-turn interactions only relate to documents for the current device. Finally, cross-review of complex assembly steps requires multi-turn follow-up questions to confirm parameter details, preventing missed critical information in single input.
Configuration Settings
The following configurations are adapted for FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind to the unique business number of a single device | Ensure multi-turn dialogue only links to full assembly documents for the current device, avoiding cross-order data confusion |
messages | Initialize historical context using the document set for the current order | Limit conversation scope to focus on review requirements for the current assembly task |
variables | Inject current BOM version, torque standard values, and gap tolerance ranges | Allow prompts to directly call business parameters, reducing repeated input |
| Maximum context length | 8000–12000 token | Adapt to the total character count of assembly documents for a single device, avoiding context overflow |
| Single recall limit | Top 5 matching documents | Balance review efficiency and information completeness, avoiding interference from redundant data |
| Automatic follow-up switch | Enable missing parameter follow-up | Automatically initiate multi-turn confirmation for missing fields in assembly documents |
Three Common Misconfigurations
- A CORS cross-domain error is returned when calling the dialogue interface. The cause is failure to add the cross-domain whitelist for the corresponding interface in the privatized deployment gateway configuration, causing front-end requests to be blocked by the browser.
- Token consumption for single-turn dialogue cannot be accurately counted. The cause is failure to enable the context token tracking function, or failure to split context by the document volume of a single device, leading to statistical results that do not match actual consumption.
- Multi-turn dialogue output speed is too slow. The cause is excessive number of recalled matching documents, and failure to limit the context window size, causing the model to process large amounts of redundant data and increasing inference time.
How to Confirm Proper Configuration
- Initiate a test dialogue bound to a single device number, check that
chatIdis properly included in interface request parameters, and that the conversation context only includes documents for the current device. - Upload a typical assembly document for a single device, trigger a multi-turn dialogue, and check that missing business parameters are automatically followed up, matching the preset logic of the prompt template.
- Test upload and parsing of large-volume documents, such as Word documents with 100,000 Chinese characters or Excel tables with 15,000 rows, confirm that the dialogue process starts normally without parsing failure errors.
- View token consumption data returned by the interface, confirm that statistical results match the actual document volume and dialogue turns.
The values provided here are common starting points, and should be evaluated against the reader’s own samples.