What this category of data consists of
This category of data primarily comes from smelting, electrolysis, laboratory testing, and scheduling departments of copper, aluminum, lead-zinc, and other smelting enterprises. Daily documents include batching lists, smelting records, electrolytic cell condition records, laboratory reports, anode and cathode quality records, and environmental protection ledgers. Data sources cover concentrate and auxiliary material analysis, DCS systems, cell voltage and current monitoring, laboratory testing, energy and environmental protection monitoring equipment. Update frequency changes in real time with material batches, furnace heats, and cell conditions. Individual documents typically include fields such as component proportions, process parameters, and test values, with units mostly being percentage, ampere, volt, ton, and similar units.
What constraints do these characteristics impose on the citation source and traceability link?
Documents updated in real time or at high frequency require the traceability chain to quickly associate the latest production data, and avoid citing expired cell condition or smelting records. Multi-source heterogeneous data sources require the traceability system to distinguish the collection nodes and update times of different data, ensuring the timeliness of cited content. The high field complexity of individual documents requires accurate matching of parameters corresponding to the process link during traceability, to avoid confusing component proportions of different material batches. The binding of environmental protection ledgers and production data requires traceability to cover compliance records, to meet subsequent verification needs.
How to configure
The following is the configuration plan for FastGPT v4.17.0:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 8000–12000 token | This category of single process documents has many fields and dense parameters, requiring sufficient tokens to accommodate multi-batch traceability data |
responseData | Full metadata + original text fragments | Matches the multi-source heterogeneous characteristics of this category of documents, making it easy to verify data sources and collection times |
detail | Display grouped by collection node | Clearly distinguish cited data from different sources such as concentrate analysis, DCS monitoring, and laboratory testing |
| Single recall citation count | Top 8–12 entries | Balances the volume of traceability data and the large model's context carrying capacity, and adapts to the high-frequency updated production data |
| Data update time filter | Last 7 days | Matches the update rhythm of material batches and furnace heats in this category, and avoids citing expired process records |
Three common configuration errors
- Symptom: When
quoteMaxTokenis set above 3000, the large model does not receive context data. Cause: This configuration exceeds the platform's default context carrying threshold, triggering the truncation logic which causes the context to not be delivered. - Symptom: Directly passing HTTP response data as a knowledge base citation, and the result does not take effect. Cause: The response data was not converted to the structured format required by the platform, so it cannot be indexed and recalled by the knowledge base.
- Symptom: After configuring the global knowledge base, the workflow does not call the specified knowledge base content. Cause: The target knowledge base ID was not passed in the workflow node, and the system uses the default knowledge base that is not bound to the business scenario by default.
How to confirm the configuration is complete
- View the knowledge base index log, and confirm that the recalled cited data includes category-specific documents such as batching lists and electrolytic cell condition records.
- Test initiating a process Q&A request, and check whether the citation traceability module of the returned result displays the data source and collection time.
- After adjusting the configuration items, verify whether the answer generated by the large model matches the content of the recalled process documents.
- View the platform version information, and confirm that the currently running FastGPT version is v4.17.0.
The values provided are common starting points and should be measured against the reader's own samples.