What the Data for This Category Looks Like
Data sources for this category include food safety sampling monitoring systems, the State Administration for Market Regulation sampling results query system, laboratory LIMS systems, and food producer and operator ledgers. Daily documents include sampling plans, sampling forms, inspection reports, unqualified food verification and disposal reports, and risk control announcements. Data is updated monthly. Core fields include sampling number, inspection items, unqualified judgment basis, disposal process, and others. Core evidence consists of inspection reports issued by laboratories. Different job roles such as supervision departments, grassroots offices, and inspection institutions use different document types.
What Constraints These Characteristics Impose on the Knowledge Base Retrieval and Recall Link
The monthly update frequency requires the knowledge base synchronization cycle to align with regulatory departments’ monthly sampling rhythm. This prevents data lag from affecting the timeliness of party building learning. There are large structural differences across multiple document types. Inspection reports contain professional test data. Sampling forms have fixed format fields. Targeted chunking rules must be configured to retain core business information. Core evidence is laboratory inspection reports. Retrieval must prioritize recalling relevant fragments of this document type to ensure the accuracy of regulatory processes during party building learning. Different job roles use different document sets. Data set groups must be divided by user role to precisely limit retrieval scope. This avoids irrelevant content interfering with learning. There are many professional fields and strong terminology. Retrieval matching logic must be optimized to improve recall accuracy. This meets the professional Q&A needs of party building learning.
How to Set the Configurations
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
similarity | 0.75–0.85 | This category has many professional fields, requiring a high matching threshold to filter irrelevant recall results |
limit | Top 5–7 results | Inspection reports have long content; too many results will exceed the context window, avoiding interference from redundant information |
searchMode | vector+keyword | Balances vector matching for professional terminology and precise retrieval for policy keywords |
usingReRank | Enabled | When retrieving mixed document types, re-ranking improves the sorting accuracy of highly relevant fragments |
datasetSearchUsingExtensionQuery | Enabled | Adapts to party building learning Q&A scenarios, optimizing retrieval coverage by expanding query terms |
collectionIds | Data set IDs divided by supervision department, grassroots office, and inspection institution | Limits retrieval scope to avoid mixing irrelevant content from cross-role document sets |
Three Common Mistakes
- Retrieval results cannot be linked to the original document’s online preview. Cause: The knowledge base’s original file storage path is not configured, or the fragment-to-original-file association mapping function is not enabled.
- No chunking options appear after uploading sampling report PDFs. Cause: The pdf-marker container linkage configuration was not completed in the FastGPT v4.17.0 deployment environment, causing the document parsing service to fail to activate.
- The number of retrieval results does not match the configured
limit. Cause:collectionIdsare not correctly limited, resulting in content recalled across multiple data sets not being truncated according to the configuration.
How to Confirm the Configuration Is Set Correctly
- Navigate to the knowledge base management page, check the number of uploaded sampling document chunks, and confirm they match the original documents’ content structure.
- Submit a sampling-related Q&A question for party building learning, and check if the returned results include core fragments of the corresponding business documents.
- Click the original file link of the retrieval result, confirm that it redirects to the online preview page.
- Adjust the
similarityparameter range, observe changes in the relevance of retrieval results, and confirm that the parameter configuration has taken effect.
Note: The configuration values listed above are common starting points. Adjust them based on your own specific samples and use cases.
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.