What this category's data looks like
Data for this category comes from slab or billet batch ledgers, heating furnace operating parameters, mill automatic control logs, online thickness and width measurement data, surface inspection reports, and MES systems. Daily documents include rolling plans, heating schedules, rolling regulations, single-coil plate shape and thickness records, surface quality reports, and final product quality certificates. Data is synced in real time each time a coil or individual steel product is produced. Single data entries include fields such as batch number, specification parameters, temperature curves, defect levels, and inspection values. Field units include millimeters, degrees Celsius, square meters, and other common industrial units.
What constraints these characteristics impose on model integration and configuration
Tender document and quotation preparation for this category requires linking full-lifecycle data for individual coils or steel products. As such, model integration must support batch reading of multi-dimensional real-time data. Data updates frequently, and each single data entry is small in size. Configuration must adapt to high-frequency, small-batch data calls to avoid timeouts. Different documents have widely varying fields. For example, rolling regulations include reduction rate parameters, while quality certificates include mechanical performance indicators. Configuration must support adaptive parsing of multiple document structures. Bidding quotations involve cross-departmental data integration. The model must link multiple system data sources, so integration configuration must reserve multiple API connection ports. This configuration was adapted for FastGPT v4.17.0.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the total volume of full-lifecycle documents and data for a single steel coil, avoiding context overflow |
maxTokens | 2000–3000 token | Matches the single-section output length of bidding quotation documents, meeting the integration needs of multi-batch data |
quoteMaxToken | 1500 token | Limits the total length of referenced rolling data and quality certificate content, ensuring context reasonableness |
temperature | 0.3–0.5 | Controls the rigor of quotations and documents, preventing parameter fluctuations from exceeding industrial standard ranges |
AIPROXY_API_ENDPOINT | Enterprise-internal deployed FastGPT proxy address | Adapts to the intranet data access security requirements of steel rolling enterprises |
AIPROXY_API_TOKEN | Enterprise-specific authentication token | Implements permission control for data sources, preventing unauthorized access to production data |
Three common errors
- Phenomenon: An embedded FastGPT chat box fails to load page content, and the console returns a cross-origin error. Cause: The frontend domain name was not added to the cross-domain whitelist in the
AIPROXY_API_ENDPOINTconfiguration, causing requests to be blocked. - Phenomenon: When uploading rolling documents in batches, only the first dozen or so entries are processed normally, and subsequent entries return no results. Cause: The
maxContextparameter is set too small to accommodate the total context volume of multi-batch data, triggering automatic truncation logic. - Phenomenon: Configuration fails when attempting to connect casdoor identity authentication, with an insufficient permissions prompt. Cause: The enterprise organization ID was not bound in the FastGPT v4.17.0 identity authentication module, causing identity verification to fail.
How to confirm the configuration is complete
- Access the model integration management page of FastGPT v4.17.0, and verify that the configuration values of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENmatch the enterprise's internal parameters. - Upload the rolling plan and quality certificate documents for a single steel coil, trigger the model to generate a quotation snippet, and check whether the output includes the correct batch number and specification parameters.
- Upload more than 10 rolling documents in batches, confirm that all entries are parsed without truncation or omission.
- Test logging in with a casdoor account, confirm that model configuration and data call functions can be accessed normally.
The values provided here are common starting points and should be evaluated against local samples.