Franchise store supervision: product questions with retrieval

Review retrieval for product questions in Franchise store supervision. Check document scope, failure paths and source evidence through controlled tests.

What the documents look like

For product questions in Franchise store supervision, 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 franchise-display note can state, “Illustration shows positions only; current items follow the period’s list.” This ordinary text supplies neither an actual picture’s contents nor the current product list. Inspect candidates for position illustration and item-list wording, then compare modes with the complete question about current products. A returned illustration reference points to another required source; it does not establish that the list has been obtained.

Configuration and implementation checks

Documented item or implementation checkMaterial and conditionEvidence action
Source scope (implementation check)Distinguish illustration, visit record and item listA visit entry does not supply every prescribed item.
Search modes: semantic, full-text, hybridSeparate position and item-scope queriesIdentify the question supported by each passage.
Citation token limitCurrent items follow the period’s listDo not trim the source down to illustration wording.
Minimum relevanceInspect filtering under semantic search or rerankingA relevant visit record is not the item list.
Question optimizationFollow-up about current-item membershipDo not convert it into an unsupported sales-permission decision.

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 visit form records beverage A on an end display. That is one recorded observation, without replacing the current list. Expanding it into every item that should be displayed substitutes sources with different scopes. Compare original wording, period and returned text. Also inspect citation trimming for the condition that items follow the list, preventing a position illustration from becoming an asserted product-approval scope. A third error uses a visit from another period to determine current item membership. Check the visit period against the applicable current list. Even a complete position sentence cannot confirm present scope across periods merely because the product name matches.

How to verify the setup

Without the period’s list, current-item membership lacks direct support. Inspect whether optimization turns a follow-up about these items into a permission conclusion instead of the original location question, retaining both versions. Once the actual list is supplied, repeat the question and trace new citations, recording source additions separately from settings changes. Check minimum relevance under semantic or reranking conditions. Retrieving a visit entry does not establish product scope or the actual sales requirements.

Material contextScope
Document typesStore Visit Report, Franchise Contract, Rectification Notice and Display Standards
Candidate sourcesSupervisor APP, POS Sales, Franchise System and Store Photos
Technical baselineFastGPT v4.17.2