What the Data for This Category Looks Like
This category of data mainly comes from daily production documents of electroplating plants, electronic connector and hardware surface treatment workshops, including bath solution analysis records, process parameter cards, fixture ledgers, film thickness and adhesion reports, hazardous waste management ledgers, and online water quality monitoring records. Data sources cover customer surface treatment specifications, bath solution test results, rectifier operation data, real-time water quality monitoring results, and hazardous waste disposal records. The update rhythm is performed per bath batch, per shift, or according to a fixed monitoring cycle.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
The update rhythm of data in this category is scattered and linked to production nodes. Multi-turn dialogue must retain key context such as bath number and shift parameters to avoid confusion across batches. The data includes structured detection values and unstructured ledger documents. Prompt engineering must clearly distinguish the retrieval priority of the two types of data, ensuring that structured parameters take precedence in matching process deviations. At the same time, the data involves environmental compliance content, so dialogue must limit the retrieval scope to publicly available production documents to avoid leakage of sensitive ledgers. In addition, frequently updated bath solution data requires that the duration of dialogue context is adapted to the shift production cycle to prevent expired data from interfering with analysis.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind unique identifier linked to the current shift production batch | Ensure multi-turn dialogue context is tied to the corresponding bath or fixture batch, avoiding cross-batch data confusion |
messages | Retain the most recent 20 rounds of dialogue content | Adapt to the dialogue interaction cycle of a single shift, preventing context overflow |
variables | Pass three core variables: bath number, shift temperature, and film thickness requirements | Quickly anchor the benchmark parameters of the current production scenario |
| Chunk length | 800–1200 characters | Adapt to the average length of single documents in this category, fully extracting bath solution analysis or process parameter content |
| Single search limit | Top 8 retrieval results | Cover the number of bath solution analysis and process records for the current shift, avoiding interference from redundant information |
| Query optimization | Calibrate based on actual measurements | Adapt to the analysis needs of multi-parameter correlation in this category, optimizing retrieval keyword matching accuracy |
This document is compatible with FastGPT v4.17.0.
Three Common Misconfigurations
- Symptom: After uploading documents such as bath solution analysis records and process parameter cards during dialogue, the system cannot read the content, but the documents can be retrieved normally when uploaded separately to the knowledge base. Cause: The file parsing configuration for the dialogue scenario is not synchronized with the parsing rules of the knowledge base, resulting in failed format recognition.
- Symptom: When searching for defect analysis-related content during dialogue, no results are returned, but target documents can be retrieved when testing separately in the knowledge base. Cause: Variables in the dialogue context do not correctly pass the current bath number, leading to incorrect retrieval scope restrictions and failure to match documents for the corresponding batch.
- Symptom: A 404 Invalid URL (POST /api/chat/completions) error is returned when initiating a multi-turn dialogue. Cause: The API gateway port for the deployed FastGPT instance is not correctly mapped, or the
chatIdparameter format does not comply with the verification rules of the deployment environment.
How to Verify Proper Configuration
- Initiate a dialogue linked to a known bath number, upload the bath solution analysis record for the corresponding bath batch, and verify that the system can read and extract relevant numerical content.
- Input a question involving film thickness deviation or abnormal bath solution concentration, and confirm that the retrieval results include the current shift's process parameter cards and fixture records.
- Initiate no more than 20 consecutive rounds of dialogue, and verify that the context is not interfered with by cross-batch historical data.
- Check deployment logs to confirm that there are no
chatIdformat errors or invalid API path error reports.
The values provided here are common starting points and should be evaluated against applicable in-house samples.