What the data for this category looks like
The data for this category comes from cell banks and seed lots, process analytics, cleanroom monitoring, MES, LIMS, and equipment integrity testing systems. Daily documents include cell bank or seed lot records, culture and purification records, aseptic filling records, environmental monitoring data, media fill simulation results, sterility test reports, and batch release documents. Data is updated in three ways: after each production batch is completed, via real-time monitoring uploads, and per fixed monitoring plans. Document fields include batch number, culture temperature, cleanroom settleable microbial count, equipment operating duration, and other professional production parameter fields, with units including ℃, CFU/m³, hours, and other relevant industry units.
What Constraints These Characteristics Impose on Knowledge Base Retrieval and Recall
Data sources for this category are scattered across multiple systems, so retrieval and recall must support cross-data source field matching to avoid missing records from critical production steps. Data with different update frequencies requires a combined logic of incremental synchronization and full recall, to ensure both real-time monitoring data and historical batch records can be accurately retrieved. The fixed and rigorous terminology system for professional production documents requires retrieval matching to have high semantic accuracy, and must not generalize to recall irrelevant content. The high compliance requirements of aseptic manufacturing mean retrieval results must cover core documents such as environmental monitoring and sterility test reports, otherwise the completeness of subsequent report generation will be affected.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Professional terminology is dense in biologic production records, requiring a high matching threshold to filter irrelevant content |
limit | 6–10 entries | Production ledger data per batch is large, preventing single recall results from exceeding the context capacity limit |
usingReRank | Enabled, re-rank the top 5–8 results | Perform secondary sorting on initial recall results to prioritize documents from core links such as aseptic control and batch release |
searchMode | fullTextRecall | The query examples emphasize identifiers or specialist terms; test this mode with representative data, not as a product default. |
collectionIds | Bind 1–3 dedicated production ledger datasets | Isolate production data across different batches to avoid cross-batch recall confusing business scenarios |
datasetSearchUsingExtensionQuery | Disabled | Production terminology systems are fixed, so no additional query expansion is needed to prevent matching deviations |
Three Common Mistakes
- Symptom: Retrieval results include unauthorized production data from other batches. Cause: The
collectionIdsparameter is not configured, and content from other datasets is recalled, creating a data leakage risk. - Symptom: Retrieval returns empty results or content with extremely low matching degrees. Cause: The
similaritythreshold is set too high, or correct chunking rules are not configured for production ledger documents, leading to failure to correctly retrieve professional terms. - Symptom: Retrieval results include irrelevant non-production documents. Cause: The
usingReRankfunction is not enabled, orsearchModeis set to generalized matching, leading to redundant recall results.
How to Confirm the Configuration Is Correct
- Log in to the FastGPT v4.17.0 backend, view the dataset binding configuration, and confirm that the target production ledger dataset has been added to the
collectionIdsconfiguration. - Enter the batch number of a single production batch as the query term, and verify that the returned document types include category-specific documents such as cell bank records and culture and purification records.
- Adjust the
similarityparameter, and verify that the matching degree of returned results meets the professional requirements for production records, with no obvious irrelevant content. - Upload a test sterility test record, and confirm that the document can be accurately retrieved without omission or false recall.
The values provided here are common starting points, and should be evaluated against the reader's own samples.