This document applies to FastGPT v4.17.0.
What Data for This Category Looks Like
This category of data comes from slab or billet batch records, heating furnace operating parameters, mill automatic control systems, online thickness and width measuring equipment, surface inspection systems, and MES systems. Data is generated in real time for each coil or individual steel billet. Daily documents include rolling plans, heating schedules, rolling specifications, plate shape and thickness records, surface quality reports, and quality certificates. Data fields include rolling temperature, reduction amount, plate shape deviation, surface defect type, and more, with corresponding units such as degrees Celsius, millimeters, meters per second, and others.
Constraints Imposed by These Characteristics on Model Integration and Configuration
Real-time, high-frequency data per coil or individual billet requires model integration configuration to support low-latency calls, to avoid timeouts that disrupt inspection response speed. Full-link documents and batch data associated with each coil require context length configuration to match the total character count of single-coil data, ensuring the model can fully access full-link inspection and maintenance data for that coil. Multi-source heterogeneous equipment operation and online inspection data require clear tool call permissions in the configuration, to support recalling corresponding inspection and maintenance documents from different data sources. Real-time updated parameters require configuration that supports dynamic knowledge base synchronization, to ensure the model uses the latest heating and rolling parameters during calls.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
AIPROXY_API_ENDPOINT | http://192.168.1.100:11434/v1 or the corresponding oneAPI forwarding address | Matches the actual access path of locally deployed models such as deepseek8b in steel rolling scenarios, and adapts to forwarding rules of oneAPI or ollama |
AIPROXY_API_TOKEN | Local model access key, such as ollama or a token generated by oneAPI | Used to verify model call permissions, and adapts to authentication requirements for locally deployed models |
maxContext | 8000–12000 token | Matches the total character count of rolling and quality inspection documents for a single steel coil, ensuring the model can fully access full-link inspection and maintenance data for that coil |
maxTokens | 2000–3000 token | Limits the output length of a single maintenance Q&A, to avoid exceeding response time requirements for equipment inspection scenarios |
quoteMaxToken | 1000–2000 token | Limits the maximum character count of a single recalled document, ensuring the model can associate multiple related documents simultaneously |
temperature | 0.3–0.5 | Reduces random output, ensuring consistency between maintenance recommendations, rolling specifications, and historical inspection records |
Three Common Misconfigurations
- A permission error or 404 status code occurs during test calls. This is caused by incorrect configuration of
AIPROXY_API_TOKEN, orAIPROXY_API_ENDPOINTnot matching the actual access path of the local model, leading to authentication failure or address mismatch. - Model calls in workflows fail to generate streaming output results. This is caused by not enabling the streaming response option in the model configuration, or the code execution module not correctly processing the streaming data format returned by the model.
- Q&A results fail to associate historical inspection records for a single steel coil. This is caused by excessively small
maxContextorquoteMaxTokenconfigurations, which cannot recall enough related documents, preventing the model from referencing complete maintenance historical data.
How to Confirm Successful Configuration
- Run a model connectivity test, observe the response status returned by the interface, and confirm that the configuration of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENcan normally call the model. - Enter a typical inspection question for a single steel coil, verify whether the model output associates the corresponding rolling specifications and historical maintenance records, and confirm that the context and recall parameter configurations cover the required document range.
- Test the response delay of multi-turn Q&A, and confirm that the output length configuration meets the time efficiency requirements of equipment inspection scenarios.
- Check the knowledge base synchronization logs, and confirm that real-time updated rolling and quality inspection data has been correctly synchronized to the knowledge base used for model calls.
The values provided here are common starting points, and should be evaluated against the reader's own samples.