What the documents look like
For product questions in B2B marketplaces, this page examines FastGPT vector indexes. Can product-name matches lead back to the original data and its stated use condition? The examples are hypothetical.
Constraints at the vector indexes step
A proposed quotation describes an industrial temperature sensor for indoor equipment only. Inspecting an index requires more than finding the word sensor: trace the match to its complete original data. One data block can have several indexes, so the test can propose a product-name question and a use-context question, recording the original reached by each. Check whether the indoor condition returns with the citation. A final suitability decision needs the corresponding specification; the match score does not supply it.
Configuration and implementation checks
| Check | Input or condition | Reading target |
|---|---|---|
| Embedding model | Associated bases use matching embedding models | Actual model and this material's input type |
| Original data and indexes | One data block can have multiple indexes | Originals reached by name and use-context questions |
| Index wording | Keep indoor and outdoor source identities separate | No unsupported merged suitability conclusion |
| Image indexing | Inspect the actual ingestion path for an image source | Check extracted text where used; inspect descriptions or image vectors for the image-retrieval path. |
| Version comparison | Reuse the same questions after a model or index change | Temperature evidence and conditions still absent |
Documented conditions
| Documented item / implementation check | Condition |
|---|---|
Embedding model | Knowledge bases associated with one search node must use the same embedding model. |
Original data and indexes | One original data block can have multiple indexes. |
Index content | Index wording should be complete and focused. |
Image indexes | Where image retrieval is used, inspect descriptions or image vectors. |
Version and result check | After a change, reuse questions to compare originals. |
Three common errors
- If the index retains the sensor name but loses its indoor restriction, compare index text, original data and citation to locate the loss. A score establishes no outdoor suitability.
- If outdoor-control-box wording is mixed with the indoor quotation, inspect both sources’ models, versions and index targets before treating them as one product.
- If a temperature-range question returns only a name but produces values, trace the specification original. Receiving an image does not establish that its values were read; inspect the actual processing output.
How to verify the setup
The quotation supplies no operating-temperature range, and a product-name hit cannot provide it. If the supplementary specification is supplied only as an image, first establish the actual ingestion path. Where it was converted to text, compare that text with the original. Where image retrieval is used, inspect the relevant description or image vector, then trace a temperature-range question to the source. Record receipt, searchable content and support for a specification separately. Missing conditions remain gaps; similarity or image receipt does not establish complete specifications.
| Material context | Scope |
|---|---|
| Document types | Business Certification Documents, Inquiry and Quotation Sheet, Electronic Contract and Platform Settlement Statement |
| Candidate sources | B2B Platform, National Enterprise Credit Information Publicity System, Payment Transaction Records and Logistics Tracking |
| Technical baseline | FastGPT v4.17.2 |