Regional dealer stock: product questions with retrieval

Review retrieval for product questions in Regional dealer stock. Check document scope, failure paths and source evidence through controlled tests.

What the documents look like

For product questions in Regional dealer stock, 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 dealer-replenishment request can state, “Short-version shelving; reinforcement-part list attached separately.” Version and accompanying parts need separate checks. Inspect candidates for the literal terms, then compare the three modes for the full inclusion question. The source refers to a list without providing its entries. Relevant wording identifies the required material; it cannot turn the short version into a shelf set with an established complete part configuration.

Configuration and implementation checks

Documented item or implementation checkMaterial and conditionEvidence action
Source scope (implementation check)Separate requested version and outbound categoryA set name does not supply part details.
Search modes: semantic, full-text, hybridVersion, reinforcement terms and full inclusion questionCompare actual sources under each mode.
Citation token limitSeparately attached list conditionLocate omission in candidates or citations.
Minimum relevanceCheck relevance under semantic or reranking conditionsHigh relevance does not establish compatibility.
Question optimizationFollow-up about the applicable versionDo not invent unknown part models.

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 outbound order says only “shelving set,” providing a test for a broad name substituted for details. If the answer lists reinforcement parts, inspect whether the list actually reached input. Set alone does not specify every component. Check token limits for omission of the attached-separately condition, retaining the request, outbound entry and returned passage. Joint retrieval does not establish correspondence between the outbound object and the requested version.

How to verify the setup

Without the part list and fit explanation, a follow-up about using these parts on the short version lacks support. Inspect whether optimization converts unknown parts into a model instead of obtaining evidence. After adding corresponding material, repeat the question and compare new candidates and citations, recording source and setting changes separately. Check minimum relevance under its conditions. A leading passage does not establish compatibility; actual structural or installation requirements need their corresponding professional source.

Material contextScope
Document typesReplenishment Request, Inventory Turnover Sheet, Outbound Order and Payment Collection Plan
Candidate sourcesDealer ERP, Brand Ordering System, Warehouse Inventory and Sales Collection
Technical baselineFastGPT v4.17.2