What the documents look like
For product questions in Franchise store supervision, this page examines FastGPT vector indexes. A shelf label clip and a similar word in a food name identify different objects. The examples are hypothetical.
Constraints at the vector indexes step
In proposed Chinese-language convenience-store material, an equipment name and food name share a character. Their explanatory English renderings are shelf price-label clip and filled pastry. A visit request uses a short expression, rendered here as replenish clips. The overlap occurs in the proposed Chinese wording; procurement identity still needs checking. Entries should retain complete names and traceable originals. A food brief cannot supply hardware specifications from that overlap, while the request itself does not establish completed equipment selection or purchasing. Preserve categories before expanding the short query.
Configuration and implementation checks
| Original-data/index check | Specific subject relationship | Acceptance action |
|---|---|---|
| Material categories | Equipment differs from food | Check complete names. |
| Alias subject | Replenish clips remains ambiguous | Check intended object. |
| Specification coverage | Equipment list supplies name only | Do not add size or fit. |
| Business state | Request differs from completed purchase | Inspect selection and records. |
| Entry update | New detail and older food target | Compare actual original citations. |
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, a clip entry may target the food description; inspect material category and complete name. Second, an equipment index may add dimensions or rack compatibility absent from the name-only original; inspect actual specification support. Third, a visit request may become purchased label clips; inspect selection and purchase records. These require category, attribute coverage and business-action evidence separately. One alias cannot perform all checks. If new equipment detail is added but food text still returns, record the actual target rather than treating repeated queries as proof that mapping was repaired.
How to verify the setup
Acceptance should ask for the equipment name, food name and the object intended by replenish clips, then inspect the original returned for a natural specification question. The names can be separated while equipment details and request identity remain unresolved without invented values. After adding a cross-reference or list, inspect processing and indexes before same-question comparison. Several entries may offer different questions for the full equipment name, but every route still needs the equipment original. Matching an overlapping word cannot establish a shared meaning or physical object.
| Material context | Scope |
|---|---|
| Document types | Store Visit Report, Franchise Contract, Rectification Notice and Display Standards |
| Candidate sources | Supervisor APP, POS Sales, Franchise System and Store Photos |
| Technical baseline | FastGPT v4.17.2 |