What the data for this category looks like
The data sources for this category include raw datasets, ETL operation logs, annotation platform output results, and sampling inspection results. Daily maintained documents include cleaning rules, quality inspection sampling tables, abnormal data lists, and delivery reports. Data updates occur daily or after each batch of tasks is completed. Document fields include data identifiers, exception types, processing status, sampling ratios, and no additional custom units. Core fields focus on quality verification and processing workflows for acquired business data.
What constraints do these characteristics impose on the "knowledge base retrieval and recall" link
Diverse data sources and frequent updates require retrieval and recall to cover multi-source heterogeneous data, avoid missing exception records in ETL logs and latest sampling results, and adapt to real-time response requirements in operation duty scenarios. Daily documents have fixed structures and concentrated professional terminology. Precise matching of exclusive terms such as cleaning rules and abnormal lists is needed to avoid generalized recall of irrelevant content and improve the professionalism of ticket Q&A. The daily or per-batch update frequency means the knowledge base must support incremental synchronization. Otherwise, retrieval results will lag behind the latest business data and cannot support the latest quality inspection and cleaning tasks. Core business links rely on abnormal data identification and sampling quality inspection. Recall results must prioritize associated historical processing plans to shorten the troubleshooting time of operation and maintenance personnel.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Match the precision of professional terms for data cleaning and quality inspection, avoid recalling irrelevant general documents |
limit | Top 3–5 entries | Control the number of single recall results, adapt to the needs of quick browsing in operation duty scenarios |
searchMode | Semantic Retrieval | Prioritize semantic association matching of professional documents, adapt to structured documents such as cleaning rules and abnormal lists |
usingReRank | Enabled | Perform secondary sorting on recall results, prioritize displaying highly relevant content related to abnormal data identification and sampling quality inspection |
datasetSearchUsingExtensionQuery | Disabled | Avoid generating additional extended queries that recall non-target documents, adapt to ticket Q&A in fixed business scenarios |
collectionIds | ID list corresponding to the data cleaning and quality inspection knowledge base | Limit the retrieval scope, only call knowledge base files exclusive to this category |
Three common mistakes
- Phenomenon: An input and response reference block of knowledge base retrieval is automatically appended to the end of the answer. Cause: The display switch for retrieval results is not turned off in the FastGPT v4.17.0 workflow configuration, or the reference filtering setting for answer content is not enabled.
- Phenomenon: Retrieval and recall results include general documents unrelated to data cleaning and quality inspection. Cause: The retrieval scope is not limited via
collectionIds, resulting in calls to knowledge base files across the entire platform. - Phenomenon: Retrieval results do not cover the latest abnormal data list or ETL logs. Cause: The incremental synchronization mechanism of the knowledge base is not configured, and only full updates are performed at fixed cycles, which cannot match the daily or per-batch update frequency.
How to confirm the configuration is correct
- Initiate a test ticket containing keywords such as "abnormal data identification" and "cleaning rules", check whether the answer only displays processing plans with no additional reference content.
- Enter the retrieval log page of FastGPT v4.17.0, confirm that only the knowledge base collections exclusive to data cleaning and quality inspection are called, and no cross-category retrieval results appear.
- Submit a new cleaning rule document, trigger a knowledge base update, then initiate a retrieval with the corresponding keywords, confirm that the new document is correctly recalled.
- Check the parameter values of the configuration items, confirm that parameters such as
similarityandlimitmeet the preset recommended values.
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 2026-10-19.