What the data for this category looks like
The ledger data for non-ferrous metal smelting comes from the smelting workshop DCS control system, material management system, and quality inspection system. The update rhythm falls into three categories: real-time process parameters are updated every 10 seconds, single-batch smelting ledgers are generated within 1 hour after the batch is completed, and monthly summary ledgers are generated on the last working day of each month. A single ledger document includes furnace batch number, smelting duration, material input quantity, output quantity, and number of qualified quality inspection batches, with corresponding units of hour, ton, ton, ton, and piece respectively. There are no nested sub-documents, and all fields are structured numerical content.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
The feature that real-time process parameters are updated every 10 seconds requires that the multi-turn dialogue link supports dynamically pulling the latest data, and avoids using static cached content. The difference in generation rhythm between single-batch ledgers and monthly summary ledgers requires that prompts clearly distinguish the call scope of the three types of data, and avoid confusing fields of real-time, batch, and summary dimensions. The fixed units of structured numerical fields require that the corresponding units must be specified in the prompt, to prevent incorrect numerical matching results from being generated. The characteristic that the number of ledger entries increases with the summary cycle requires that the multi-turn dialogue context limits the valid field range, to avoid exceeding the manageable content length.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
messages | Retain the most recent 15-20 rounds of dialogue context | Non-ferrous metal smelting ledger data is structured, and excessive old context will interfere with current field matching, avoiding interference from redundant information on queries |
variables | Preset three core variables: furnace batch number, smelting duration, and output quantity | The core fields of the ledger are these three types, which can quickly bind structured data from the corresponding system |
chatId | Bind the unique identifier of a single smelting batch | Multi-turn dialogue needs to be associated with ledger data of the same batch, to avoid confusing query results across batches |
| Maximum context length | 8000-12000 token | Monthly summary ledgers have a large number of entries, so context length needs to be limited to adapt to model processing capabilities, calibrated based on actual testing |
| Question optimization | Enable field matching verification | Structured ledger fields are fixed, enabling this feature can automatically verify whether queries contain valid ledger fields, reducing invalid calls |
Three common mistakes
- Symptom: When the concurrent call volume reaches 2-3 calls per second, the workflow returns an empty result. Cause: The maximum number of runs configuration for the workflow was not adjusted, and the default threshold cannot support high-concurrency requests, resulting in requests being blocked.
- Symptom: In the report generated by calling the API, the result of the last variable will overlay the content of the previous variable. Cause: The variable scope was not properly isolated in the multi-turn dialogue context, causing the variable value from the previous round to be carried over to the current round.
- Symptom: After configuring input guidance and the word bank, the expected guidance questions do not appear in the dialogue interface. Cause: The field word bank corresponding to the ledger data was not bound, or the trigger condition for input guidance was not associated with the structured ledger query scenario.
How to confirm the configuration is correct
- Initiate a single-batch ledger query, check whether the returned results include the content of the preset variable fields, and adjust the number of retained context rounds until the results are accurate.
- Initiate consecutive multi-round cross-batch queries, check whether the identifier bound to
chatIdmatches the queried batch, to avoid result confusion. - Adjust the concurrent call volume, verify that the workflow returns a non-empty result, and adjust the corresponding configuration until the concurrency requirements are met.
- Enable the input guidance function, check whether the dialogue interface displays guidance questions related to ledger fields, and adjust the word bank content until it matches the expected results.
The configuration values listed above are common starting points. They 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.