What the data for this category looks like
Business data for non-ferrous metal smelting originates primarily from real-time production collection systems, quality inspection laboratory reports, ERP work order systems, and equipment operation logs. Data updates follow three rhythms: Equipment operating parameters refresh every 10 seconds. Quality inspection reports are compiled daily. Monthly work order ledgers are updated each month.
A single business document includes fields such as furnace number, smelting temperature, raw material ratio, output volume, and qualified inspection rate, with units of unmarked, ℃, %, tons, % respectively. Some documents also include process code snippets and equipment fault records.
What constraints do these characteristics impose on the "multi-turn dialogue and prompt engineering" link
Real-time high-frequency equipment data requires multi-turn dialogue to quickly sync the latest parameters. Avoid using expired data to guide processes. The multi-field, multi-unit document structure requires prompts to clearly define matching rules between fields and units. This prevents extraction errors. Long business process steps need multi-turn dialogue to track core parameters in variables. Ensure that each step's input is correctly linked to its corresponding process step. Monthly updated ledger data requires periodic cleaning of old data from conversation contexts. This avoids redundant information disrupting current processes.
How to set up configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId binding rule | Bind by smelting work order ID | Ensure multi-turn dialogue contexts for the same work order are not confused, and associated with corresponding business data |
messages length limit | 8000–12000 token | Cover interactive steps and data across the entire smelting process, avoid context overflow |
variables binding scope | Bind furnace temperature, raw material ratio, output volume fields | Focus on core business parameters, reduce invalid context usage |
| Conversation timeout | 600 seconds | Adapt to the multi-turn interaction duration of complex smelting processes, avoid mid-process interruptions |
| Prompt template length | 1000–1500 characters | Cover process steps, field requirements, and unit rules, ensure accurate guidance |
Three Common Misconfigurations
- Phenomenon: The configuration button disappears after referencing a variable, and temperature settings cannot be modified. Cause: Temperature settings were enabled before binding parameters in
variables. Variable referencing in FastGPT v4.17.0 locks some configuration items. - Phenomenon: After calling an interface call workflow, the running data in the conversation log is empty. Cause: The smelting work order ID was not correctly bound to the
chatIdparameter, so the context cannot be associated with corresponding business data. - Phenomenon: When passing an any parameter to the prompt of the "text content extraction" module to extract code snippets, the complete response shows the code snippet as undefined. Cause: The ownership field of the code snippet was not limited in the prompt. Code snippets for non-ferrous metal smelting are mostly process parameters; extraction fails without a clear scope.
How to Confirm the Configuration is Correct
- Initiate a multi-turn dialogue, enter the smelting furnace number and raw material ratio parameters in sequence, check if
variablescorrectly capture and save the input content. - Call the interface, then view the conversation log to confirm that the
messageslist contains complete interactive steps and context data. - Test the text content extraction function, enter a smelting process code snippet, check if the returned result includes the specified fields and units.
- Simulate a long-duration interaction, confirm that the session is not interrupted early within 600 seconds, and the timeout setting takes effect.
The values provided here are common starting points, and should be evaluated against your own specific samples and use cases.
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.