B2B marketplaces: staff training with multi-turn prompts

Review multi-turn prompts for staff training in B2B marketplaces. Check document scope, failure paths and source evidence through controlled tests.

What the documents look like

For staff training in B2B marketplaces, this page examines FastGPT multi-turn prompts. Compare the material received with the sources used in the answer. The examples are hypothetical.

Constraints at the multi-turn prompts step

A B2B training exercise can distinguish delivery commitments in an electronic contract from transaction status in a settlement statement. One source records an agreement and the other a particular state; transaction status does not establish performance of every after-sales commitment. Define the current lesson and source scope in the prompt. Compare the actual history for an initial question and follow-up, checking for a conclusion about another transaction carried from an earlier task. Each training judgment should trace to current material.

Configuration and implementation checks

Conversation or implementation checkB2B training source relationshipAcceptance trace
Source rolesSeparate commitments from transaction statusNo inferred completion of all service commitments
History inputDistinguish the current transaction from other tasksAn older conclusion entering the answer
Version referenceRetain old and new identities and conditionsCorrect subject after optimization
Empty-history comparisonUse the current originals for the same questionDistinguish source change from historical carryover
Process gapAdmission and service rules need evidenceInspect actual input and citations after addition

Documented conditions

Documented item / implementation checkCondition
Prompt and taskDefine sources, the task and evidence-gap handling.
Conversation historyInspect the history actually submitted.
Question optimizationReview reference resolution and question expansion.
Model and lengthInspect context and reply length separately.
Reply formatjson_schema needs its format and parsing validation.

Three common errors

  • If settlement status becomes complete service performance, compare contract promises and status wording with actual events. The sources perform different evidentiary roles.
  • If a new-contract follow-up returns to an earlier version or transaction, retain identities, actual history and rewritten question. Compare current-source-only input to locate failed handoff.
  • If quotations or settlement produce purported confirmed admission and handling procedures, trace each step. Obtain actual internal instructions and retest; complete fields establish no complete training basis.

How to verify the setup

Quotation or settlement wording alone does not supply complete supplier-admission or service procedures. For a follow-up asking what happens next, inspect whether the answer invents review steps from history, then identify the internal process source still needed. After adding it, retain the version and repeat the original and boundary questions, checking actual input and citations. A valid format or continuing conversation does not establish a complete training source set.

Material contextScope
Document typesBusiness Certification Documents, Inquiry and Quotation Sheet, Electronic Contract and Platform Settlement Statement
Candidate sourcesB2B Platform, National Enterprise Credit Information Publicity System, Payment Transaction Records and Logistics Tracking
Technical baselineFastGPT v4.17.2