What the documents look like
For procurement in Dealer ordering events, this page examines FastGPT vector indexes. Index fabric feel, garment pattern and material selection against their separate originals. The examples are hypothetical.
Constraints at the vector indexes step
A proposed dealer-ordering packet describes a soft fabric sample for feel reference only, a loose-fit garment and an unresolved material-selection discussion. A draft index says a soft fitted garment is selected. The question asks about ordering the fitted design. Softness changes no garment pattern, the garment source states loose fit and selection has no outcome. Inspect each indexed attribute against its original rather than recombining different sources into a nonexistent product. A shared collection heading also establishes no identity between the particular fabric sample and every garment under that collection.
Configuration and implementation checks
| Original-data/index check | Specific subject relationship | Acceptance action |
|---|---|---|
| Attribute category | Feel differs from pattern | Inspect cross-attribute additions. |
| Garment specification | Loose fit | Do not change to fitted. |
| Selection state | Adoption unresolved | Do not call it selected. |
| Older-design target | Historical fitted page | Inspect actual linked block. |
| Actual effect | No touching or fitting | Do not promise performance. |
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, soft feel may become fitted shape; compare sample purpose with garment specification for cross-attribute additions. Second, whether to adopt may become selected; inspect material-selection records and current confirmation instead of inferring an outcome from a discussion title. Third, an older fitted-design index may serve the current loose garment; compare collection, pattern and version rather than transferring through fabric similarity. These concern attribute category, selection state and source target. Vector scores or semantic proximity cannot establish actual garment specifications or confirm the requested current ordering arrangement.
How to verify the setup
Ask what the fabric sample establishes, which pattern the garment has and how far selection has progressed, inspecting actual references and index links. After edits, repeat softness, fitted and loose questions, recording returned originals without promising every answer is exact. Missing fitted-supply evidence remains unresolved. An absent search hit does not establish that the product does not exist. These texts include no real touching, fitting or production tests. Model and index changes confirm no order and establish neither fabric performance nor wearing effects. Actual specifications and supply still require their corresponding evidence beyond the proposed source relationships.
| Material context | Scope |
|---|---|
| Document types | Ordering Manual, Ordering Contract, Sample List and Credit Approval |
| Candidate sources | Ordering Fair System, Historical Sales, Dealer Inventory and Financial Credit Granting |
| Technical baseline | FastGPT v4.17.2 |