What the documents look like
Sample inspection happens before a livestream goes live. The decision under review is whether a product can be sold and whether it suits on-camera demonstration. The working materials are supplier files, testing-agency reports, platform negative lists and historical return rates. The daily documents are sample evaluation forms, quality inspection reports, supplier qualifications and prohibited-sale lists. These materials update weekly and per item, so any conclusion cited inside a multi-turn conversation needs its batch and date attached.
Order fulfilment and after-sales question handling usually run inside one continuous session. A single conversation may ask about sample status, qualification validity and who carries after-sales responsibility. The materials themselves can sit in different states: pending review, awaiting supplementation, or expired. A multi-turn conversation has to keep those state differences intact. A report mentioned in an earlier turn does not become a verified conclusion in a later turn.
Constraints at the multi-turn prompts step
Multi-turn dialogue carries earlier messages forward. The memory-round setting controls how many prior rounds the AI may reference. A larger value makes earlier dialogue easier to reach, brings in more content, and can raise consumption and slow the response. Customer service and knowledge-base question answering typically keep only a small number of history rounds. In the chat interface, a non-empty chatId pulls the session from the database automatically and uses the last item in the messages array as the user question, ignoring the remaining messages. When chatId is absent, no platform context is used and the passed messages build the whole context.
The prompt needs to state the material scope, the answering task, and how to behave when evidence is missing. Fields not recorded in the materials stay unknown; the model does not fill in business facts. Reply format stays at default for ordinary customer-service question answering. Only when a downstream step must read a fixed structure does the choice move to json_schema with the matching format requirement filled in.
Hypothetical paper exercise sample: the material text supplied for checking reads "Sample evaluation form: Model A insulated tumbler, submitted for testing on 10 March 2025, testing-agency report number JC-2025-0310, conclusion pending supplementation of the heat-resistance test; supplier qualification document valid until 30 June 2025; the platform negative list does not include this product." The draft sentence reads "Model A insulated tumbler has completed quality inspection, can go live, and after-sales service is guaranteed." The request awaiting a decision reads "Please confirm this product's qualification is valid and it can be fulfilled directly."
Configuration and implementation checks
| Configuration item | Hypothetical trial starting point for this page | Reason and comparison method |
|---|---|---|
| AI model | A model that supports multimodal recognition | Sample photos and report screenshots must be read; compare recognition output against a model without multimodal support |
| Memory rounds | Set to 3 rounds | Customer-service scenarios keep a small number of history rounds; compare follow-up coherence against 1 round and 6 rounds |
| Temperature | Set low | After-sales answers need stability; compare consistency of the same question against a higher setting |
| Reply cap | Enabled, slider left at its default position | Avoids early truncation; compare whether a long explanation stays complete against a lowered value |
| Reply format | Left at default | No downstream node reads a fixed structure here; compare returned structure against json_schema |
| Multimodal recognition | Image recognition enabled | Sample images and report screenshots must be read; compare whether the model receives image content when this is off |
These values are hypothetical trial starting points for this page and are not official defaults. The low temperature and the 3-round memory setting are choices made here; whether they meet the need is judged only after comparing against adjacent values.
Three common errors
- Treating "conclusion pending supplementation of the heat-resistance test" as completed quality inspection. Input is the material text above plus the draft sentence; the comparison is whether "pending supplementation" and "completed" point to mutually exclusive values of the same field; the observable result is that the draft sentence has no support in the materials.
- Treating the supplier qualification valid until 30 June 2025 as passing review. Input is the validity-date field and the phrase "qualification is valid"; the comparison is whether validity date and review status are the same field; the observable result is that review status is not recorded in the materials.
- Treating absence from the platform negative list as authorization to go live. Input is the negative-list absence and the phrase "can go live"; the comparison is whether listing status and livestream authorization are the same fact; the observable result is that authorization is not recorded in the materials.
How to verify the setup
- Input the hypothetical material text above together with the draft sentence. Compare whether the draft sentence goes beyond the recorded "pending supplementation of the heat-resistance test" state. The condition is met when the answer keeps that state and states that quality inspection is not complete.
- Input the pending request "Please confirm this product's qualification is valid and it can be fulfilled directly." Compare whether the answer equates the qualification validity date with passing review. The condition is met when the answer states that review status is not recorded and requires separate verification.
- Input the follow-up in the same session, "Then who handles after-sales." Compare whether the answer cites a responsibility assignment not recorded earlier. The condition is met when the answer keeps that point unknown and notes that further materials are needed.
All three checks use the paper hypothetical sample as input and were not actually executed. For an empty-result handoff, a clearly stated paper input [] can be used to check the downstream design; this does not claim that a fabricated rule search returns empty. The relevance score of a retrieval result does not carry permission or entity-isolation judgement, and retrieval itself is not authorization.