B2B marketplaces: product questions with retrieval

Review retrieval for product questions in B2B marketplaces. Check document scope, failure paths and source evidence through controlled tests.

What the documents look like

For product questions in B2B marketplaces, 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 B2B quotation test can state, “The valve body uses a standard interface; sealing material requires separate confirmation for the intended use.” Interface form and material suitability need different evidence. Retrieve the interface wording, then compare semantic, full-text and hybrid search with the complete use-qualified question. Returning the product name does not answer the material question. Citations must retain “separate confirmation,” without extending one description into established suitability for every application.

Configuration and implementation checks

Documented item or implementation checkMaterial and conditionEvidence action
Source scope (implementation check)Quotation and sample record remain distinct sourcesA demonstration record does not replace material information.
Search modes: semantic, full-text, hybridLiteral interface wording and the use-qualified questionCompare originals returned by the three modes.
Citation token limitKeep the use restriction beside the interface descriptionInspect any omitted separate-confirmation condition.
Minimum relevanceInspect filtering under semantic search or rerankingA high score does not establish application suitability.
Question optimizationFollow-up asking whether this model can be usedCheck that optimization adds no permission or use assumption.

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 separately proposed sample record says only that the interface style was demonstrated. Use it to inspect whether nearby terminology displaces the actual use restriction. Retain both source identities and establish which candidates come from the quotation or demonstration record. Check whether the answer converts a demonstration into verified suitability. Citation limits are token-based, beyond snippet counts. If the use condition is trimmed, record the omitted location and repeat the same question against the original.

How to verify the setup

Without the sealing-material explanation, the supplied evidence consists of an interface description and a sample record. Question optimization may resolve references but cannot provide the absent material support, including an invented application permission for “can this model be used?” After obtaining the corresponding explanation, repeat the question and inspect entry of the new original into candidates and citations. Check minimum relevance under semantic or reranking conditions, without treating a score as a decision on actual suitability.

Material contextScope
Document typesBusiness Certification Documents, Inquiry and Quotation Sheet, Electronic Contract and Platform Settlement Statement
Candidate sourcesB2B Platform, National Enterprise Credit Information Publicity System, Payment Transaction Records and Logistics Tracking
Technical baselineFastGPT v4.17.2