What data for this category includes
Non-ferrous metal smelting data sources fall into three categories: real-time process data collected by MES systems (including smelting temperature, furnace pressure, matte grade, and others), production plans and material reports generated by ERP systems, and component test reports and safety compliance documents from quality inspection departments. Data update cycles vary widely: real-time process parameters are updated every 10 seconds, quality inspection reports are updated daily, and compliance documents are revised monthly. Document structures are fixed: process reports include fields such as furnace number, smelting duration, and impurity content, with units including ℃, hour, %, and mg/kg. Document-type materials include fixed sections such as operating procedures, safety thresholds, and approval workflows.
Constraints imposed on model access and configuration
The high-frequency updates of real-time process data require configuring a reasonable context refresh strategy when connecting to the model, to prevent outdated data from compromising drafting accuracy. Professional documents with multiple fields and long-text structures require adjusting the model's context capacity to ensure fully relevant data is included in the generation scope. Different document types (quality inspection reports, safety plans, production plan descriptions) have varying content rigor requirements, requiring differentiated configuration of generation parameters. Retrieval of mixed data sources requires clearly defining the data source scope, to avoid irrelevant data interfering with the final generated document content.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Documents for non-ferrous metal smelting need to carry multiple segments of process parameters and compliance clauses; a long context can fully include the required associated data |
maxTokens | 2000–3000 token | A single drafted document needs to cover the complete process and parameter descriptions, to avoid output content being truncated |
quoteMaxToken | 1500–2000 token | Specific component data in quality inspection reports needs to be accurately cited; limiting the citation length ensures content precision |
temperature | 0.2–0.4 | Document drafting needs to maintain professional rigor, to avoid generated content deviating from actual process requirements |
AIPROXY_API_ENDPOINT | Deployed OneAPI proxy address | Unified management of model call links, facilitating unified configuration and troubleshooting |
AIPROXY_API_TOKEN | Access key corresponding to the proxy | Ensures identity verification security for model calls |
Three common configuration mistakes
- Phenomenon: After enabling the reranking model, the response time for a single document draft exceeds 60 seconds. Cause: The
maxContextparameter is not configured for long documents in non-ferrous metal smelting, causing the reranking model to load excessive document fragments and increasing computational latency. - Phenomenon: After configuring model parameters in config.json, an authentication failure prompt appears during calls. Cause: The model key is duplicated in both OneAPI and FastGPT configurations, causing link authentication conflicts.
- Phenomenon: The generated document only contains general conclusions and does not cite specific smelting parameters. Cause: The
quoteMaxTokenconfiguration value is too small, meaning retrieved quality inspection report fragments are not fully included in the generation context.
How to confirm correct configuration
- Run the FastGPT v4.17.0 test script, input "Draft a flash smelting quality inspection report for furnace number 10", and check if the returned result includes specific parameters such as smelting temperature and matte grade.
- View the model call logs to confirm that the actual effective values of
maxContext,maxTokens, andquoteMaxTokenmatch the configured values, with no truncation prompts. - Compare response times with and without the reranking model enabled, to confirm that the reranking model's processing time falls within a reasonable range and no obvious timeout occurs.
- Verify the validity of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKEN, initiate a test call through the proxy, and confirm that the return status code is 200.
The values provided here are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.