What the documents look like
For after-sales questions in Store cold-chain receiving, this page examines FastGPT multi-turn prompts. Preserve batches and observation times across temperature, receipt and rejection records so follow-up questions do not assign responsibility prematurely. The examples are hypothetical.
Constraints at the multi-turn prompts step
A proposed service exercise begins with a transport-temperature record identifying a vehicle and recording period, then asks whether this batch should be rejected. The vehicle record has not been linked to the store’s delivery batch; receipt measurements and applicable acceptance conditions are also absent. Specify the required relationships. If one transit observation becomes a conclusion that the entire arrival fails, trace input scope. Without batch correspondence the conclusion remains unverifiable; further questions cannot join unrelated events into fact.
Configuration and implementation checks
| Service-conversation check | Cold-chain event condition | Acceptance action |
|---|---|---|
| Initial record | Vehicle period may not identify the arrival batch | Obtain batch links and receipt conditions |
| Added acceptance note | Retain trip and observation time | Inspect actual history delivery |
| Reference investigation | Identify the document and batch meant by it | Match questions and source identity |
| Rejection reason | Recorded reason is not agreement or liability | Trace the stated handling basis |
| Photo gap | Unobtained versus omitted image | Collect the source or test its input path |
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 an unlinked vehicle-temperature record becomes a batch-rejection decision, inspect vehicle period, batch and acceptance conditions. One transit observation does not establish an entire failed arrival.
- If its relationship to the earlier note uses another batch’s temperature series, compare questions and identities with vehicle trip and receipt time. More context does not establish event attribution.
- If a rejection reason becomes supplier agreement or resolved disagreement, inspect actual handling results. A recorded reason establishes no consent; distinguish unobtained photos from delivery omissions as well.
How to verify the setup
A rejection note records a stated reason that may support the current handling summary, without establishing supplier agreement or resolved disagreement. Trace cited measurements and documents at each turn, then repeat the question with complete sources in a new conversation. Obtain missing inspection photos separately; photos already obtained but absent from their input path require delivery investigation. Text questions do not replace on-site inspection, and unresolved opinions cannot become completed quality testing or service compensation.
| 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 |