What the documents look like
Omnichannel stock transfer operations move goods between stores and warehouses. The working data comes from ERP inventory records, store POS systems, e-commerce orders, and WMS platforms. The documents handled day to day include transfer requests, inventory snapshots, store shortage lists, and transfer logistics notes. Copy drafting for products and marketing is grounded in these documents, and material updates follow a daily or weekly rhythm.
For multi-turn prompts, this shapes what can be referenced. A transfer request records a proposed movement with a status; an inventory snapshot records quantities at a point in time; a shortage list records what a store lacks; a logistics note records movement evidence. Copy drafting must stay inside the subject, object, status, and validity window that these documents actually state. The drafting task is to describe products and marketing content; it is not to certify business facts, approve transfers, or confirm that goods have arrived.
Constraints at the multi-turn prompts step
Multi-turn dialogue carries prior turns into the model context, and that carried history decides what earlier text the model can reference. When a new conversation does not use a FastGPT database session, the context is built entirely from the passed messages. When a non-empty chatId is passed, the interface reads the database session and uses the last item in the messages array as the user question. Copy drafting often involves follow-up questions, so the actual scope of carried context needs checking.
Prompts should state the material scope, the answering task, and how to handle missing evidence, and should not let the model write in business facts that the documents do not contain. Reply format follows downstream handling; when json_schema is selected, the corresponding format requirement must be filled in and the returned structure verified. Retrieval supplies source material and does not perform permission or entity isolation.
Hypothetical paper exercise: The material text reads, "Transfer request A-0715 states that 120 units of product X are to be transferred from the East China warehouse to the Hangzhou Hubin store, status pending approval, request date 15 July 2025." A draft sentence reads, "This batch of product X has been transferred from the East China warehouse to the Hangzhou Hubin store and the store can put it on shelves for sale immediately." In judgment, compare the subject, object, status, and validity scope of the material text against the draft sentence. The material status is pending approval; the draft sentence describes a completed transfer and immediate shelf availability. The two take mutually exclusive values on the same field, and the draft sentence is not supported by the material.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison method |
|---|---|---|
| AI model | Select a model that supports long context | Check the model maximum context against the copy material length; compare whether it accommodates multi-turn follow-up |
| Memory turns | Start with a smaller number of turns | Compare whether the reply, after carrying prior text, cites content beyond the material scope |
| Temperature | Start with a lower value | Compare whether wording stays stable across repeated outputs from the same prompt |
| Reply upper limit | Start with a value that fits a complete paragraph | Compare whether output is cut off mid-paragraph |
| Reply format | Keep the default first | If a downstream flow reads a fixed structure, select json_schema and fill in the format requirement |
| Thinking configuration | Select default first | Compare whether switching levels produces an error; revert to default on error |
These values are hypothetical starting points for this exercise, not official defaults. Memory turns, reply upper limit, and temperature all need adjustment after comparison with this material length and output requirement.
Three common errors
- Writing a pending-approval status as a completed transfer. Input is the sample material text and the draft sentence. Compare the status value on the same field, and observe whether the draft sentence is mutually exclusive with the material. The material states pending approval; the draft sentence claims completion and shelf availability, and that statement is not supported.
- The prompt does not state how to handle missing evidence. Input is the prompt and the sample material text. Compare whether the model output adds authorization or effective information not present in the material, and observe whether unsourced definite statements appear.
- Treating retrieval similarity as a permission filter. Input is the returned quoteList and score. Compare whether returned records belong to the target retrieval scope, and observe whether out-of-scope records appear. Similarity does not perform entity or permission isolation.
How to verify the setup
- Input the sample material text and the draft sentence. Compare the four items of subject, object, status, and validity scope for shared origin, and observe whether the draft sentence takes a mutually exclusive value on the same field as the material. The expected result is that the draft sentence is not supported and requires human review before finalization.
- Input a multi-turn conversation with follow-up questions and a prompt. Compare whether the carried history exceeds the material scope, and observe whether the reply cites business facts not stated in the material. The expected result is that the reply uses only content stated in the material.
- Input a retrieval query. Compare whether the returned record identifiers belong to the same vector model library, and observe whether cross-model association appears. An empty result can be checked against a downstream handling design using the explicit paper input []. The expected result is that actual observations are recorded and missing evidence remains a gap.
An unsigned termination is not a completed termination; a pending request is not approval; an offered option is not execution. Where a document field is not provided, it remains unknown.