What the documents look like
For multilingual work in Multi-store management, this page examines FastGPT vector indexes. Check store identity behind matching Chinese and English document names before transferring any setting. The examples are hypothetical.
Constraints at the vector indexes step
A hypothetical multi-store exercise gives store A a requirement to register gifts separately. An older store B note says a gift ships with a named product. Both files happen to be called Gift instructions. A generic English entry saying gift included could transfer B’s action to A when the Chinese question asks whether A requires registration. Shared file names and similar products do not establish shared store rules. Language entries need to trace the statement to its own store. A proposed English draft for A also remains unreviewed; it cannot serve as an approved bilingual rule that removes the Chinese registration condition.
Configuration and implementation checks
| Store-language check | Document identity | Specific comparison |
|---|---|---|
| Store marker | A registration versus B shipping | Keep the owning store with each entry. |
| Matching names | Both called Gift instructions | Compare originals instead of selecting by title. |
| English draft | An unreviewed A version | Inspect confirmation evidence and version status. |
| Changed store question | Ask about A, then B | Retain the subject and respective citations. |
| Access boundary | Retrieval versus actual authorization | Embedding consistency grants no cross-store access. |
Documented conditions
| Documented item / implementation check | Condition |
|---|---|
Embedding model | Knowledge bases associated with one search node must use the same embedding model. |
Original data and indexes | One original data block can have multiple indexes. |
Index content | Index wording should be complete and focused. |
Image indexes | Where image retrieval is used, inspect descriptions or image vectors. |
Version and result check | After a change, reuse questions to compare originals. |
Three common errors
- If an English entry extends B’s shipping arrangement to A, inspect the target original, store identity and statement to locate the transfer.
- If a matching file name conceals the registration requirement, compare both originals with the actual citation. Matching titles do not make their contents interchangeable.
- If A’s unreviewed English draft becomes a formal rule, inspect version identity and business confirmation evidence. An existing index supplies no approval.
How to verify the setup
Ask the same A-specific gift question in both languages, then ask about B and inspect the original targeted for each store. Retain question identity and actual citations. When A’s confirmed wording arrives, check product and applicable period before determining whether the earlier draft still affects answers. Inspect matching embedding models when one search node associates several bases; model consistency grants no permission to mix store material. Authorization requires its own actual mechanism and evidence. This paper exercise validates no production access and changes no store gift configuration.
| Material context | Scope |
|---|---|
| Document types | Store Authorization List, Price Control Sheet, Channel Diversion Complaint Form and Monthly Sales Report |
| Candidate sources | Various Platform Seller Backends, ERP Channel Prices, Brand Anti-Counterfeiting System and Dealer Reports |
| Technical baseline | FastGPT v4.17.2 |