What the data for this category looks like
Knowledge base data for internal office work in the fertilizer and pesticide industry comes primarily from internal enterprise production process manuals, pesticide registration and filing documents, fertilizer quality inspection records, agricultural material distribution scheduling ledgers, and frontline employee operation guidelines. Data updates proceed dynamically in line with industry regulatory requirements, new product launches, and distribution plan adjustments, with no fixed cycle. Most documents combine structured tables and long-form text descriptions, including fields such as product identifiers, production parameters, operation steps, and compliance requirements. Fields often cover production batches, distribution ranges, application dosages, and other related content. Units include grams, kilograms, hectares, mu, and others.
What constraints these characteristics impose on knowledge base retrieval and recall
The mixed multi-structure document format means a single chunk may contain multiple sets of related parameters. Retrieval must avoid parameter confusion across chunks, and ensure the completeness of recalled content. Fields involving precise identifiers such as production batches and distribution ranges require retrieval to support filtering by specific fields, narrowing the scope of invalid recalls. The dynamic update rhythm requires the knowledge base synchronization mechanism to adapt to non-fixed-cycle updates, preventing the use of outdated data during retrieval. The presence of professional measurement units requires the retrieval process to retain unit information, ensuring matching accuracy and preventing incorrect recalls caused by parameter unit mismatches.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting Range | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Matches the accuracy requirements for professional terminology and units in the fertilizer and pesticide industry, balancing recall coverage and relevance |
limit | Top 8–12 entries | Covers typical parameter sets for single production or operation scenarios, avoiding excessive redundant data occupying context space |
searchMode | vector+keyword | Balances semantic matching and precise matching of structured fields, adapting to the multi-structure document characteristics |
usingReRank | Enabled | Rearranges recall results by professional relevance, correcting deviations from single vector matching |
datasetSearchUsingExtensionQuery | Disabled | Professional terminology in the fertilizer and pesticide scenario does not require additional query expansion, avoiding irrelevant matching |
collectionIds | Exclusive collection IDs specified by the business department | Isolates documents of different categories such as production, distribution, and training, ensuring precise retrieval scope |
Three Common Misconfigurations
- Phenomenon: The conversation interface continues loading without responding, repeatedly triggering knowledge base retrieval loops. Cause: The reasonable value of the
limitparameter is not restricted, recalling too many long-text chunks causes context overflow, and the system cannot complete the generation process. - Phenomenon: Retrieval results include content with mismatched units, for example, recalling an application dosage of "grams per mu" as "kilograms per mu". Cause: The keyword matching mode of
searchModeis not enabled, relying solely on vector matching and ignoring precise identification of unit fields. - Phenomenon: Knowledge base IDs and chunk IDs in the knowledge base management interface cannot be copied, making it impossible to accurately locate abnormal documents. Cause: The ID copy permission is not enabled in the background configuration, or the copy interaction is not enabled in front-end rendering.
How to Confirm Proper Configuration
- Enter the knowledge base management interface, verify that the collection corresponding to
collectionIdsincludes the production, distribution, and training documents required for the current business. - Initiate a test query containing professional terminology and units, check whether the relevance and number of retrieval results meet the
limitandsimilarityconfiguration requirements. - Trigger a manual knowledge base update, confirm that after document synchronization is complete, retrieve the differences between old and new documents to verify that the update mechanism is working.
- After enabling
usingReRank, compare the result order before and after rearrangement, confirm that the rearrangement logic is operating normally.
The values given 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.