On-demand retail fulfillment: product questions with retrieval

Review retrieval for product questions in On-demand retail fulfillment. Check document scope, failure paths and source evidence through controlled tests.

What the documents look like

For product questions in On-demand retail fulfillment, this page examines FastGPT retrieval. Compare the material received with the sources used in the answer. The examples are hypothetical.

Constraints at the retrieval step

A new instant-retail order test says, “Refill cleaning liquid; spray head selected separately.” A contents question needs the refill description and separate-selection condition together. Inspect candidates for literal product wording, then compare the three retrieval modes for spray-head inclusion. A head-term hit does not make it part of the order, and refill does not establish a complete container or accessory set. The input is proposed order wording only.

Configuration and implementation checks

Documented item or implementation checkMaterial and conditionEvidence action
Source scope (implementation check)Separate purchased contents and stock gapsStill required does not mean included in the order.
Search modes: semantic, full-text, hybridRefill and spray-head inclusion questionsInspect qualifications retrieved by each mode.
Citation token limitSeparately-selected and still-required conditionsRetain the actual source state in citations.
Minimum relevanceInspect filtering under semantic search or rerankingRelated bottled-product text supplies no capacity.
Question optimizationFollow-up about this bottle’s capacityRetain order and product without adding a value.

Documented conditions

Documented item / implementation checkCondition
Associated knowledge basesKnowledge bases associated with one search node must use the same embedding model.
Search modeSemantic, full-text and hybrid modes are available.
Citation limitCitation limits are measured in tokens.
Minimum relevanceRange 0–1; active for semantic search or reranking.
Question optimizationResolves references and expands questions.

Three common errors

A proposed picking list says bottled product, while an out-of-stock note says the spray head is still required. Converting a stock gap into an included order item mixes source roles. Compare order, picking entry and stock note to identify the actual passage returned. Token trimming may also remove still-required or separately-selected conditions. Preserve complete wording beside the result. Inventory state and purchased contents are different targets, without a joint conclusion inferred from shared retrieval. A third error turns a pending spray-head replenishment note into definite current inability to fulfil. Check subsequent applicable replenishment or alternative arrangements for this item. An older inventory note and present fulfilment failure cannot be treated as equivalent.

How to verify the setup

No capacity or actual accessory detail was supplied. Bottled and refill cannot provide a numerical quantity. Inspect whether optimization of a size follow-up keeps the same order without switching product or adding a volume. After obtaining the corresponding explanation, repeat the question and trace new citations, recording source updates separately from retrieval settings. Check minimum relevance under semantic or reranking conditions. An unsupported capacity or accessory needs data-object inspection; a relevance score is not specification evidence.

Material contextScope
Document typesInstant Order, Picking List, Out-of-Stock Report and Delivery Exception Order
Candidate sourcesDouyin Instant Retail, Meituan or JD Daojia Backend, Store Inventory and Rider Tracking
Technical baselineFastGPT v4.17.2