This document applies to FastGPT v4.17.0.
What this category of data looks like
Documents in this category include batch production records, material balance sheets, reaction and purification records, cleaning validation records, impurity profile reports, deviation change documents, equipment inspection records, maintenance logs, and more. Data is sourced from registered process documents, raw material batch ledgers, DCS control systems, weighing systems, LIMS laboratory information management systems, chromatography data systems, and QMS quality management systems. Updates follow the rhythm of each production batch and process step. Single records include fields such as process parameters, batch information, impurity test data, equipment number, operator, and timestamp. Core focus areas include multi-step reaction routes, intermediate transfer rules, and solvent residue control indicators.
What constraints do these characteristics impose on knowledge base retrieval and recall
Multi-source heterogeneous data sources require associating field mappings across different systems during retrieval to ensure accurate matching between equipment inspection and maintenance records and corresponding process batches. High-frequency batch-level updates require the knowledge base to support incremental synchronization mechanisms to avoid retrieval delays caused by full imports. Complex multi-step reaction and impurity control documents require a professional terminology vector library for precise recall to reduce irrelevant results. High field density per record requires limiting the length of returned context to avoid exceeding model processing limits and affecting Q&A accuracy.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Matches the recall accuracy of API manufacturing professional terminology, balances recall rate and result relevance, and meets the precise retrieval needs of equipment inspection and maintenance |
limit | Top 8 entries | Controls the number of documents returned per retrieval round to avoid context overload, and adapts to the average length of single-batch process documents |
searchMode | mixedRecall | Matches equipment numbers, process step keywords, and professional terminology semantics at the same time, adapting to the retrieval needs of multi-source heterogeneous documents |
usingReRank | Enabled | Re-ranks initial recall results to filter irrelevant content such as impurity profiles and yield data, and focuses on entries related to equipment inspection and maintenance |
datasetSearchUsingExtensionQuery | Enabled | Expands query terms based on equipment inspection and maintenance scenarios, supplements common fault terminology and process-related words to improve recall coverage |
collectionIds | Specify corresponding collection IDs by business category | Only retrieves knowledge base collections containing equipment inspection, maintenance records and process documents, narrowing the retrieval scope and reducing retrieval delay |
Three common mistakes
- Phenomenon: Retrieval response time exceeds 30 seconds, and the interface times out during loading. Cause: Incremental synchronization is not configured for high-frequency batch-level updates, and full retrieval of a large number of documents causes excessive resource usage.
- Phenomenon: A maxLength error is triggered when importing documents into the knowledge base via API, with status code 413 returned. Cause: Long documents are not split into block lengths compliant with platform requirements, and single imported content exceeds system limits.
- Phenomenon: Unable to export documents related to equipment inspection and maintenance by business category, only the entire knowledge base can be exported. Cause: An independent knowledge base collection is not created for equipment inspection and maintenance scenarios, so the export granularity cannot be refined to business categories.
How to confirm the configuration is correct
- Perform a simulated retrieval, enter a question related to equipment inspection, and check whether the returned results include corresponding batch process records and maintenance logs.
- View the retrieval log to confirm that only the knowledge base collections of the specified business category are retrieved, and no irrelevant documents are recalled.
- Test the incremental import function, upload a newly generated batch production record, and confirm that only the newly added content is synchronized to the knowledge base.
- Adjust the
similarityparameter range, and verify whether the change in the relevance of recall results meets business expectations.
The values provided are common starting points and should be measured against the reader's own samples.