Franchise store supervision: after-sales questions with retrieval

Review retrieval for after-sales questions in Franchise store supervision. Check sources, input boundaries, error handling and repeatable test evidence.

What the documents look like

For after-sales questions in Franchise store supervision, this page examines FastGPT retrieval. Retrieve left-right locations, correction scope and feedback stage together in store follow-up. The examples are hypothetical.

Constraints at the retrieval step

A proposed franchise follow-up has a notice requesting labels on the left shelf, a reply completing the right display and a service question about the left now. Both statements can coexist. Right-side completion does not refute a left-side gap. Retrieve location and source identity together, using the literal left-label phrase and full question. Searching completed alone may favour the right. No later left-side record is supplied. A shared store or task does not establish store-wide completion, and records for different sides are not automatically contradictory statements about the same object.

Configuration and implementation checks

Material checkConditions in this testImplementation evidence
Notice locationLeft shelfRetain location wording.
Feedback scopeRight completedDo not expand store-wide.
Question optimizationLeft qualifierInspect before and after.
Reference clippingRight before completedInspect retained text.
Added sourceCurrent store left itemVerify identity before update.

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

First, right-side feedback may answer for the left; compare candidate location, notice subject and original instead of relying on a store match. Second, optimization may drop left; retain original and rewritten questions to inspect search subject. Third, a reference may keep completed while trimming right; inspect actual text under its token limit rather than judging completeness from a filename. These concern subject, question qualification and reference clipping. Threshold or mode changes supply no actual left-side handling outcome missing from the available material.

How to verify the setup

Ask where the notice applies, where the reply reports completion and which left-side evidence is still needed, retaining candidates and adopted references. Compare semantic, full-text and hybrid results with the right-side passage as a discrimination example rather than treating high scores as relevance proof. Later feedback needs the same store and item checked before repeating; updates cover only its location. This exercise conducts no visit or acceptance and claims no real passed correction. Missing follow-up remains pending rather than an inferred refusal or completed task.

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