What Data for This Category Looks Like
Data for this category comes from customer surface treatment specifications, bath chemistry test reports, rectifier operation data, online water quality monitoring records, and hazardous waste management ledgers. Data is updated per bath batch, per shift, or per monitoring requirements. Core documents include bath composition parameter cards, fixture usage records, film thickness and adhesion test reports, and wastewater discharge ledgers. Fields include bath ion concentration, pH value, fixture count, film thickness (μm), current (A), discharge concentration (mg/L), and additional relevant metrics. Field dimensions must be adjusted to match the client’s requirements for a single bid, with no unified fixed format.
Constraints Imposed on Forms and Interactions
The multi-source nature of data and batch-based updates require forms to support quick association of process and monitoring data across different cycles, to avoid manual duplicate entry. Specific field units and non-uniform formats require the interaction layer to include built-in unit verification and format adaptation logic, to prevent parameter mismatches. Compliance checks for hazardous waste and discharge data require forms to trigger validation before submission, to avoid non-compliant data in bid documents. Additionally, bid documents need quick access to the latest bath and client specification data, requiring the interaction layer to support storing and recalling historical data categorized by bid project.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
formInput | Bind automatic filling of customer specifications, bath parameters, and film thickness data | Reduce manual entry errors and ensure bid data aligns with actual processes |
userSelect | Recall the top 10 historical process records categorized by bath batch | Quickly call historical data commonly needed for bids, avoiding excessive redundant information |
| Single recall limit | 5 entries | Limit the scope of background knowledge to avoid irrelevant data interfering with quotation calculations |
| Context length | 8000 token | Cover complete process parameters, client specifications, and monitoring records |
| Field verification trigger timing | Real-time verification before form submission | Detect unit or format errors early and reduce the probability of mistakes in bid documents |
| Timeout threshold | 300 seconds | Adapt to the time required for loading multiple documents and avoid submission failures |
Three Common Configuration Mistakes
- Phenomenon: Quotations returned in conversations include bath data that is 3 months out of date. Cause: No time range was defined for the
userSelectrecall scope, and historical records outside the current bid cycle were retrieved. - Phenomenon: Bid documents generated by the large model include unassociated hazardous waste discharge data that exceeds standards. Cause:
formInputwas not configured to only bind compliance fields required for the bid, leading to inclusion of irrelevant monitoring data. - Phenomenon: Form submission results in verification failure with no clear prompt. Cause: No dedicated error messaging was set for field verification, and only a generic error alert was returned.
How to Verify Proper Configuration
- Submit a film thickness value using a non-standard unit, then check if a field verification prompt is triggered. Adjust verification rules to match the requirements of the current bid client.
- Select a single historical bath batch record, then confirm that only the process data for that record is retrieved, with no information from other batches included.
- Test calling the client surface treatment specification fields, then confirm they are correctly linked to the quotation calculation logic.
- Submit the complete form, then check if the response time meets expectations. Adjust the timeout threshold based on actual document loading conditions.
The values provided here are common starting points and should be measured against the reader's own samples.