Data Characteristics of This Category
Data for this category comes from customer surface treatment specifications, bath laboratory reports, rectifier operation data, online water quality monitoring records, and hazardous waste management ledgers. Daily documents include bath analysis records, process parameter cards, fixture usage logs, film thickness and adhesion test reports, hazardous waste ledgers, and wastewater monitoring reports. Data is updated per bath cycle, per shift, or per fixed monitoring requirements. Individual documents typically include fields such as equipment number, test value, and operation time, with no unified standardized format.
Constraints on Knowledge Base Retrieval and Recall
Data update frequencies vary significantly. Real-time online monitoring data requires high-frequency recall, while offline laboratory reports only need periodic updates. This requires the retrieval system to distinguish document update times and adjust recall weights. Daily documents include both numerical test data and textual operation specifications, so the vector recall logic must support multiple content types. Data sources cover production, testing, and compliance workflows, so the retrieval scope must accurately align with supplier audit and process quality control scenarios to avoid retrieving irrelevant documents. Individual document fields are scattered, so targeted retrieval by field keywords must be supported to improve audit accuracy.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Matches the precision requirements for test data and process parameters in this category, filters low-relevance historical records |
limit | Top 10 | Balances audit comprehensiveness and response speed, avoids excessive results exceeding the context window |
searchMode | mixedRecall | Adapts to the content characteristics of this category, which includes both textual specifications and numerical test data |
usingReRank | Enabled | Improves the sorting priority of highly relevant documents, adapting to diverse document types |
datasetSearchUsingExtensionQuery | Enabled | Combines keywords such as batch number and tank number to expand retrieval terms, improving recall coverage |
collectionIds | Bind three collections: electroplating process, bath analysis, and compliance ledgers | Accurately limits the retrieval scope to exclude non-relevant documents |
Three Common Configuration Errors
- Issue: The API knowledge base content interface returns a format error, prompting that the specified content type is not supported. The docx file can be downloaded normally when accessing the link via a browser. Cause: The document parsing plugin is not configured correctly, or the uploaded docx file contains non-standard embedded objects, causing the interface to fail to correctly extract text content.
- Issue: A large number of compliance documents unrelated to electroplating processes are mixed in the retrieval results, failing to match audit requirements. Cause: The
collectionIdsparameter is not configured correctly, and the retrieval scope is not limited to the specified process and test document collections. - Issue: The bath analysis records returned by the retrieval do not match the current audit batch, resulting in low result relevance. Cause:
datasetSearchUsingExtensionQueryis not enabled, and retrieval terms are not expanded using keywords such as batch number and tank number, leading to an overly wide recall scope.
How to Validate Configuration
- Upload a process parameter card and bath analysis record from this category, perform a retrieval, check the number and relevance of returned results, and adjust the
similarityvalue to the required range. - Check the sorting of retrieval results to confirm that highly relevant documents are displayed first, verifying that the
usingReRankconfiguration is active. - Attempt to retrieve test data for a specific tank number, confirm that only documents within the specified collection are returned, verifying that the
collectionIdsconfiguration is correct. - Call the FastGPT v4.17.0 API interface to test the retrieval request, confirm that the returned result format meets expectations, verifying that the interface configuration is correct.
The values provided are common starting points and should be measured against the reader's own samples.