Brand repair services: after-sales questions with retrieval

Review retrieval for after-sales questions in Brand repair services. Check document scope, failure paths and source evidence through controlled tests.

What the documents look like

For after-sales questions in Brand repair services, this page examines FastGPT retrieval. Retrieve inspected items and pending scope without turning a partial check into restored use. The examples are hypothetical.

Constraints at the retrieval step

A proposed brand-repair case completes an indicator-light check, leaves startup testing pending and asks whether every function is restored. Partial checking and unresolved testing can coexist without a whole-device result. Retrieve indicator and startup subjects with their states, comparing the complete question with literal test names. A completed check cannot cover every function, while pending startup testing does not establish a fault. The question requires applicable inspection evidence; changing wording does not create it or determine the actual condition of a device from these hypothetical service records.

Configuration and implementation checks

Material checkConditions in this testImplementation evidence
Inspection scopeIndicator itemDo not expand to all functions.
Pending testStartupRetain in reference.
Optimization scopeStill all functionsDo not narrow task.
Clipped positive stateComplete needs its itemInspect actual text.
Added resultDevice, item and versionUpdate matching scope only.

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, local completion may establish full restoration; inspect candidate test and conclusion scope. Second, optimization may replace all functions with whether the light was checked; retain question scope rather than narrowing the task before saying complete. Third, reference trimming may remove pending testing; compare the original with text actually delivered. These concern evidence scope, task scope and reference completeness. Scores, record counts and longer answers cannot supply a whole-device state when the available source only covers one finished check and another unresolved item.

How to verify the setup

Ask which check finished, which remains pending and what full restoration would require, expanding actual quotations. Compare semantic, full-text and hybrid modes using the same questions, retaining item names with finished or pending states under token limits. Added inspection needs device, item and version matched, updating only its supported scope. This exercise diagnoses nothing, prescribes no repair and decides no warranty responsibility. It guarantees no real restored function. Missing outcomes remain unresolved rather than a usable device inferred from a relevant completed-check passage.

Material contextScope
Document typesWarranty Card, Repair Work Order, Inspection Report and Exchange Approval
Candidate sourcesAfter-Sales System, Store Orders, Repair Service Point Feedback and National Three Guarantees Catalog
Technical baselineFastGPT v4.17.2