What the documents look like
For staff training in Cross-border settlements, this page examines FastGPT multi-turn prompts. Inspect the periods needed for a trend question and prevent other product records entering the lesson. The examples are hypothetical.
Constraints at the multi-turn prompts step
The training exercise asks for a sales trend for Product M, but sales quantity and amount alone do not establish a trend comparison. First inspect whether comparable periods and their records were supplied. Limit the lesson to reading the available data or identify the comparison material still needed. In a follow-up, check that an earlier Product G copywriting task does not enter the Product M training question. Match the cited settlement statement with the actual input instead of treating another task’s summary as this lesson’s source.
Configuration and implementation checks
| Check | Material needed by the lesson | Inspection |
|---|---|---|
| Learning objective | Product M lacks a complete trend comparison | Identify whether comparable periods were supplied |
| Follow-up subject | Separate Product M training from Product G copy | Inspect history for a summary of another task |
| Two amount entries | Trace Product N to both records | Do not presume source priority in a follow-up |
| Reference handling | Retain Product N and its source identities | Check for importing Product H from history |
| Training gap | Product O still needs a manual or description | Retain new sources, actual history and answers separately |
Documented conditions
| Documented item / implementation check | Condition |
|---|---|
Prompt and task | Define sources, the task and evidence-gap handling. |
Conversation history | Inspect the history actually submitted. |
Question optimization | Review reference resolution and question expansion. |
Model and length | Inspect context and reply length separately. |
Reply format | json_schema needs its format and parsing validation. |
Three common errors
- If M’s quantity and sales value become a rising or falling trend, inspect comparable periods and sources. Historical G summaries cannot supply the missing comparison.
- If N’s two-record follow-up becomes H or loses one source, retain questions and input. Restore identities, period, currency and definitions without teaching automatic priority for one record.
- If O’s product training borrows historical features, trace an actual manual or description. Settlement supplies sales information only; continued questions cannot obtain a missing manual. Add it and retest.
How to verify the setup
Product O’s features require a training manual or product description; its settlement statement contains sales information. Repeated questions do not make the absent manual part of the input. Inspect whether the answer distinguishes sales records from product-training evidence and whether it transfers a feature discussed earlier to Product O. After adding the manual, repeat the original lesson question and a follow-up, retaining the new source, actual history and answers separately to identify the evidence change.
| Material context | Scope |
|---|---|
| Document types | Platform Settlement Statement, Exchange Rate Sheet, Service Fee Invoice and Collection Reconciliation Sheet |
| Candidate sources | Platform Settlement Center, Bank Statement, Payment Institution Backend and ERP Orders |
| Technical baseline | FastGPT v4.17.2 |