What the Data for This Category Looks Like
Data for this category comes from customer-provided Gerber files, drill files, BOM lists, as well as in-plant CAM system data, production equipment parameters, bath test results, AOI inspection reports, electrical test data, and laboratory slice reports. Data is collected continuously alongside production batches and shifts. Daily documents include engineering production instructions, Gerber parsing records, drilling and lamination parameters, chemical analysis records, various inspection reports, and slice reports. Data fields include process parameters, test results, batch information, and more. There are no unified fixed units; values vary based on inspection items and process steps.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
This category has high-frequency, multi-source heterogeneous data updates. Multi-turn dialogue must be tied to the production batch dimension to prevent mixing data across batches. During multi-turn interactions, process parameters and test results from different sources must be aligned gradually. Prompts must clearly guide conversations to focus on specific documents for the current batch, such as Gerber parsing, drilling and lamination parameters, and inspection reports. Data fields and units have no unified standard. Multi-turn dialogue must gradually confirm the corresponding units and meanings of parameters during interaction to avoid audit deviations caused by format differences. The data volume for a single batch is large. The historical length of the dialogue context must be limited to avoid exceeding token consumption thresholds.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind to production batch number | Ensure dialogue context only associates with Gerber files, inspection reports, and other data for the current batch, avoiding interference from cross-batch information |
messages | Retain the last 10 rounds of dialogue content | The data volume for a single batch is large; limit the length of historical dialogue to control token consumption and avoid context overflow |
variables | Preset production batch and inspection type variables | Quickly filter bath test and AOI report data for the corresponding batch, improving retrieval efficiency |
| Maximum context length | 8000–12000 token | Adapt to the total token volume of multiple inspection reports and process parameters for a single batch, calibrated based on actual testing |
| Question Optimization | Enabled | Adapt to FastGPT v4.17.0’s professional term optimization function, aligning with the terminology logic of PCB manufacturing |
| Single Search Limit | Top 6 results | Match core inspection reports and process documents for a single batch, avoiding interference from redundant information during audit judgments |
Three Common Misconfigurations
- Phenomenon: The batch-specific Gerber file uploaded during dialogue is not included in the current knowledge base retrieval scope. Cause: The current production batch number is not bound via
variables, so the system cannot match documents for the corresponding batch. - Phenomenon: The token consumption status of the current interaction cannot be viewed in the dialogue interface. Cause: The global token statistics configuration is not enabled, or the statistics display function is not turned on in the dialogue module.
- Phenomenon: Only one reply is triggered for two consecutive professional questions in a multi-turn audit dialogue. Cause: The context continuation rule for
messagesis not configured; the system defaults to limiting only one user input per round.
How to Verify Successful Configuration
- Initiate a query about Gerber parameters for the current production batch, confirm that the system only returns parsing records and process parameters for the corresponding batch.
- Check the token consumption statistics module in the dialogue interface, confirm that the token usage of each interaction is properly recorded.
- Send two independent audit questions consecutively, confirm that the system generates corresponding replies in sequence.
- Send test report content in Markdown format, confirm that the display format in the dialogue interface meets professional audit requirements.
The values provided here are common starting points and should be evaluated against the reader’s own samples.