What the data for this category looks like
Data related to fertilizer and pesticide business processing mainly comes from pesticide registration announcements issued by the Ministry of Agriculture and Rural Affairs, national fertilizer standard texts, and compliance filing documents of production enterprises. The data update rhythm aligns with the release of newly registered products and revisions of national standards. There is no fixed update cycle, but single update volumes are large.
Document structures uniformly include fields such as product name, registration certificate number, active ingredient content, applicable crops, application dosage, pre-harvest interval, and manufacturer. Most units use agricultural production-specific measurement standards such as g/L, kg/mu, and mL/hectare. Some documents include illustrations that explain usage scenarios.
What Constraints These Characteristics Impose on the Knowledge Base Retrieval and Recall Link
The professional measurement attributes of data fields require retrieval to strictly match parameter units. This avoids result failure caused by unit conversion errors.
Document structures are fixed but have strong field correlations. Segmented retrieval must retain field context, otherwise matching deviations such as separated applicable crops and application dosages will occur.
Data updates have no fixed cycle and large single volumes. The recall link must support incremental indexing to avoid excessive time consumption from full index reconstruction.
Agricultural product materials with similar product names have parameter differences. Retrieval sorting must accurately distinguish active ingredients and content, to prevent unrelated products from being included in results.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Fertilizer and pesticide data includes precise dosage and crop matching requirements. A threshold that is too low introduces unrelated agricultural products, while a threshold that is too high may miss compliant results. This range is calibrated based on actual testing. |
limit | Top 8 entries | A single agricultural product document contains relatively large amounts of information. Too many results exceed the context window. 8 entries cover most compliant business scenarios. |
searchMode | vector_only | Business processing requires precise matching of product parameters. Full-text retrieval easily introduces unrelated content. Vector retrieval better fits professional field matching logic. |
usingReRank | Enabled | Agricultural product materials have similar product names but large parameter differences. Reranking corrects vector retrieval sorting deviations and improves result matching accuracy. |
datasetSearchUsingExtensionQuery | Disabled | Business process guidance requires strict matching of official registration data. Extended queries easily introduce non-official content, which does not meet compliance requirements. |
collectionIds | Specify official agricultural product knowledge base collection ID | Limit retrieval scope to only official registration data, avoid mixing non-compliant documents, and ensure business processing authority. |
Three Common Mistakes
- The phenomenon is that a network search is triggered during retrieval, a JSON parsing error occurs, and an abnormal format prompt is returned. The cause is that
datasetSearchUsingExtensionQueryis not disabled, triggering unnecessary network searches that lead to JSON format parsing failure. - The phenomenon is that garbled text is returned in retrieval results, which only occurs when using a thinking model. The cause is that the knowledge base includes scanned copies of old paper documents that have not been correctly transcoded. The thinking model does not filter unstructured garbled content during calls. Replacing with a non-thinking model avoids the issue but does not resolve the root cause.
- The phenomenon is that retrieval results do not include application dosage information from illustrations. The cause is that the image OCR indexing function is not enabled. Illustrations in fertilizer and pesticide documents often include dosage charts. Failure to index these charts leads to missing key information.
How to Confirm the Configuration Is Correct
- Manually enter the registration certificate number of a registered pesticide, check whether retrieval results include complete applicable crops and application dosage fields, and confirm that parameter matching is accurate.
- Adjust the
similarityparameter range, observe changes in retrieval result matching accuracy, and confirm that the threshold meets the compliance requirements of the business scenario. - Upload a new agricultural product document, wait 10 minutes before performing retrieval, and confirm that the new document can be normally recalled.
- After enabling
usingReRank, compare result sorting before and after reranking, and confirm that parameter distinction for products with similar product names has improved.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.