What Data Looks Like for This Category
Data sources for this category include customer drawings and special characteristic lists, ERP/MES systems, in-process gauges, equipment process parameters, and supplier quality certificates. Daily maintained documents include control plans, process flowcharts, work instructions, first article and patrol inspection records, SPC reports, PPAP materials, and 8D reports. Data is collected and updated per batch, per shift, or continuously. Fields include batch number, process parameters, test values, defect types, and supplier codes. Units cover production-specific measured values such as torque, thickness, and pressure.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Configurations for multi-turn dialogue and prompt engineering in this category must adapt to integration requirements for multi-source heterogeneous data. First, high-frequency updated data from mass production requires limiting the valid batch range in dialogue context to avoid interference from redundant historical data. Second, structured fields from dedicated production documents require clear mapping rules in prompt engineering to ensure the AI can identify key identifiers such as batch numbers and special characteristics. Third, business processes constrained by vehicle customers require multi-turn dialogue to strictly follow quality system logic, without deviating from established problem traceability paths. It also requires adapting to format differences across data sources to avoid confusion between cross-system data.
Configuration Settings
The following configurations are based on the functional logic of FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind the three core fields: batch number, process parameters, and defect type | Adapt to the core need for batch-based traceability in this category, and clarify the business variables to be called during dialogue |
| Maximum context length | 8000–12000 characters | Cover full process documents and test data for a single batch, and avoid truncation of key traceability information |
| Maximum number of single dialogue turns | 6 | Match the routine troubleshooting steps for quality analysis, and prevent resource consumption from meaningless redundant dialogue |
| Knowledge base recall count | Top 4 | Focus on historical anomaly records for the same batch and same process, and improve traceability accuracy |
messages | Sort by business logic: customer requirements → process data → anomaly records → rectification plans | Follow the routine thinking path of quality traceability, and guide the AI to output results through a systematic process |
chatId | Bind production batch ID | Ensure context isolation for dialogue within the same batch, and avoid confusion between cross-batch data |
Three Common Misconfigurations
- The configured input guidance questions do not display in the dialogue interface. The cause is failure to enable the input guidance switch in Dialogue Interface Configuration, or the word bank is not bound to the current application's dialogue scenario.
- Variable values appear superimposed in multi-turn dialogue outputs. The cause is failure to correctly use the
variablesparameter to isolate context, leading to variable results from the previous dialogue round being carried over to the current round. - The application cannot repeat the contents of XLSX files stored in the knowledge base. The cause is that document parsing rules are not configured, or the uploaded XLSX files are not preprocessed according to the structured fields of production documents, leading to the AI being unable to identify key information such as batches and test data in the table.
How to Verify a Complete Configuration
- Manually enter production parameters for a known batch, and check whether the dialogue automatically associates historical anomaly records for the corresponding batch.
- Initiate a traceability dialogue with no more than 3 turns, and check whether the output results only include relevant data for the current batch, with no redundant cross-batch information present.
- View the knowledge base upload log, and confirm that the XLSX file has been successfully parsed and corresponding vector data has been generated.
- Enter the application configuration page, confirm that the input guidance switch is enabled, and that the word bank has been bound to the current application.
The values provided are common starting points and should be measured against the reader's own samples.