What the documents look like
For staff training in Store cold-chain receiving, this page examines FastGPT multi-turn prompts. Separate measurement guidance, classroom records and site decisions, inspecting inappropriate carryover of an earlier training example. The examples are hypothetical.
Constraints at the multi-turn prompts step
A proposed training page describes how to record the measured object, position and time. First ask learners to restate the steps, then ask whether that value permits acceptance. The page supplies neither this batch’s measurement nor an applicable acceptance standard. Preserve that limitation in the prompt. A pass conclusion requires tracing actual evidence in history. Explaining a measurement procedure does not perform the measurement, and a classroom answer is not an arrival-acceptance record.
Configuration and implementation checks
| Training-conversation check | Measurement-exercise input | Inspection result |
|---|---|---|
| Method and result | Procedure has no actual batch measurement | No pass conclusion from method alone |
| Measured object | Separate vehicle environment and product surface | Retain position and time conditions |
| Optimized question | Keep objects when asking which passes | Compare original and optimized wording |
| Standard source | A value is not a decision rule | Obtain applicable conditions |
| Subsequent scoring | Inspect explanation, parsing and writing separately | No claim of actual site inspection |
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 measurement guidance becomes a measured and accepted batch, inspect actual records and standards. Describing steps does not perform measurement or create acceptance evidence.
- If vehicle-environment and product-surface values become a pass comparison, retain objects, positions and times, checking optimization for lost conditions. Values alone supply no decision rule.
- If a changed batch or position inherits the earlier explanation, compare exercise identities and history. Locate adopted conditions, retaining absent formal standards rather than accepting fluency as completed scoring.
How to verify the setup
Change the measurement position or arrival batch to test whether the explanation refers to current conditions. An answer carried over from the earlier exercise must identify what remains unverifiable. Real acceptance rules for training need an applicable source and owner confirmation; the exercise analyzes only supplied wording. If a subsequent system scores the exercise, inspect structure and evidence correspondence, then actual record writing. A complete explanation does not establish completed scoring, on-site testing or operational recording.
| Material context | Scope |
|---|---|
| Document types | Cold Chain Temperature Records, Arrival Acceptance Slip, Rejection Slip and Supplier Delivery Note |
| Candidate sources | Cold Chain Vehicle Temperature Control, WMS, Store Receiving System and Quality Inspection Photos |
| Technical baseline | FastGPT v4.17.2 |