What the documents look like
For product questions in Amazon FBA preparation, this page examines FastGPT vector indexes. Unfolded form and folded storage need their respective settings preserved. The examples are hypothetical.
Constraints at the vector indexes step
A proposed FBA structural note says side panels form a support surface when unfolded and fold back for storage. An inbound brief requires packing in the storage state. A question about arrival already unfolded needs actual event evidence: structure describes possible states and the brief describes a packing requirement. An entry turning forms a support surface into shipped unfolded would exceed both originals. Distinguish capability, packaging instruction and actual event, preserving the source each question reaches rather than treating shared product identity as a completed fulfilment chain.
Configuration and implementation checks
| Original-data/index check | Specific subject relationship | Acceptance action |
|---|---|---|
| Structural capability | Unfolding forms support surface | Do not treat as actual arrival form. |
| Packing condition | Storage state required | Check applicable setting. |
| Target original | Display differs from inbound | Check incorrect entry target. |
| Execution gap | Rule does not establish execution | Inspect actual event. |
| Same-node association | If several bases associated | Check applicable model condition. |
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
First, unfolding capability may become actual shipment form; inspect applicable packing or delivery records. Second, a storage-state entry may target a display description; inspect the setting and subject of the original data. Third, matching both state entries may be treated as executed packing; inspect an actual operational result rather than retrieved rules. These require event evidence, setting mapping and factual state separately. Search wording cannot turn proposed structural material and an inbound brief into proof of real handling, even when the passages together describe a plausible arrangement.
How to verify the setup
Acceptance should ask whether the item unfolds, how storage is described and whether current material proves arrival form. Inspect citation roles. The first two can be explained within supplied text; the last requires event evidence, without inferring non-arrival from a missing record. Added records need goods and version checks before original-data and index comparisons. Several entries for one passage do not add event evidence. Where bases are associated with the same retrieval node, apply the documented matching-model condition within that scope rather than extending it to every knowledge source used across an entire workflow.
| Material context | Scope |
|---|---|
| Document types | FBA Inbound Plan, Carton Label, Inventory Report and Compensation Application |
| Candidate sources | Amazon Seller Central, FBA Inventory Report, Freight Forwarder Tracking and ERP Purchase Order |
| Technical baseline | FastGPT v4.17.2 |