What the data for this category looks like
This category’s data sources include MES systems, testing equipment, laboratory systems, process parameter documents, customer quality standards, and historical defect libraries. Update cadence follows set rules: control plans and release documents are updated per batch, inspection records and SPC reports are collected per shift, and real-time process parameters and test results are collected continuously. Daily documents include control plans, inspection records, SPC reports, final product inspection reports, nonconforming product reviews, release documents, and monthly quality reports. Each document contains fields such as batch number, inspection items, defect level, release threshold, and disposal opinions. Field units include pieces, ppm, hours, and other standard units.
Constraints imposed on multi-turn dialogue and prompt engineering
Multiple heterogeneous data sources require multi-turn dialogue to gradually integrate content from different systems, avoiding overloading a single prompt. Batch and shift-based update cadence requires each dialogue call to automatically pull the latest relevant documents, ensuring timeliness of review basis. Diverse document structures and fields require prompts to clearly specify extraction rules for corresponding documents, avoiding confusion between different types of quality data. Frequently updated real-time data requires dialogue context to be isolated by batch, preventing cross-batch quality data from interfering with current review processes.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Context window size | 1200–1800 preceding characters | Matches the average length of relevant documents per batch, avoids truncating key inspection standards |
| Number of retained dialogue history entries | 3 preceding turns | Focuses on the current batch review process, reduces interference from irrelevant historical dialogue |
| Variable binding | Bind batch number and inspection type variables | Automatically associates inspection records and release document data for the corresponding batch, uses variables for parameter passing |
| Session ID configuration | Bind chatId and batch number | Isolates dialogue contexts for different batches, avoids data confusion |
| Maximum response timeout | 60 seconds | Adapts to the average time required to pull detection data, avoids excessive front-end waiting |
| Initial prompt configuration | Pre-set batch review guidance | Automatically starts the review process, reduces manual operation steps |
| Session cache toggle | Enabled | Adapts to the session cache mechanism of FastGPT v4.17.0, optimizes first response speed |
Three Common Misconfigurations
- Phenomenon: After the workflow executes, output results from all historical dialogue modules are returned, and only the current turn's review results are retained. Cause: No truncation rules for dialogue context are configured, and the requirement to retain only
messagescontent from the current turn is not specified. - Phenomenon: Delay exceeds 3 seconds when initiating a review dialogue for the first time, and subsequent calls return to normal speed. Cause: Session cache is not enabled, and full batch of relevant documents must be pulled for the first time.
- Phenomenon: No automatic prompt appears when opening the dialogue box, the review process must be triggered manually. Cause: The batch number trigger condition in
variablesis not bound, and the initial prompt is not set.
How to Verify Correct Configuration
- Trigger a batch review process, check that the output only includes the current turn's review results, with no redundant historical dialogue content.
- Initiate a review dialogue for the first time, record the delay time, compare it with the delay of subsequent calls to confirm that the cache is effective.
- After binding the batch number variable, upload documents for the corresponding batch, check that the dialogue automatically associates the inspection standards for that batch.
- After configuring the initial prompt, open the dialogue box, confirm that the pre-set review guidance is displayed automatically.
The values provided are common starting points and should be measured against the reader's own samples.