What the Data for This Category Looks Like
Data for non-ferrous metal smelting policy and regulatory basis primarily comes from official government disclosure platforms of the Ministry of Industry and Information Technology, Ministry of Ecology and Environment, and Ministry of Emergency Management. It also includes official industry documents released by the China Nonferrous Metals Industry Association. Update frequency adjusts irregularly alongside policy revisions. Most documents use long text structures, with wide variation in single-document length. Available fields include policy title, release date, applicable smelting link (such as copper smelting or aluminum smelting), core clauses, quantitative indicators, and applicable regional requirements.
Constraints Imposed by These Characteristics on Vector Models and Indexing
The high share of long text requires chunking strategies that balance semantic completeness and token limits. This avoids single chunks that are too long to fit within model processing ranges, or too short and causing semantic fragmentation. The timeliness and classification attributes of policies require indexes to bind metadata such as release date and applicable smelting category, to support filtered retrieval of results by conditions. The irregular update characteristics require configuring incremental indexing rules to reduce resource consumption from full index reconstruction. The accuracy of quantitative indicators and professional terms requires retaining complete fields and units during chunking to avoid semantic matching deviations.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the long paragraph structure of non-ferrous metal smelting policy documents, avoids semantic fragmentation of clauses |
| Overlap Length | 100–150 characters | Retains cross-chunk policy context, ensures complete clauses are correctly retrieved |
| Similarity Threshold | 0.72–0.85 | Filters low-match results to focus on valid policy basis |
| Maximum Search Results per Request | Top 8 | Adapts to multi-clause reference needs of policy Q&A, avoids redundant results |
maxToken | 4000 token | Matches large language model context window limits, supports content from multiple policy documents |
defaultToken | Calibrated via actual testing | Adapts to FastGPT v4.17.0 vector model video memory usage, avoids memory overflow |
Three Common Misconfigurations
- Phenomenon: Knowledge base retrieval takes over 60 seconds, and loading timeout is displayed on the interface. Cause: Chunk length is set too large, causing single-batch vector generation volume to exceed model processing limits, leading to task queue backlog.
- Phenomenon: Vector indexing task is stuck, and cannot be restored even after indexing model configuration is commented out. Cause: Old indexing cache queue is not cleared, residual tasks occupy system resources, preventing new tasks from starting.
- Phenomenon: Index entries in the dataset increase irregularly. Cause: Deduplication configuration is not enabled, and overlap length is set too high, causing the same policy text to be split into multiple duplicate chunks, leading to duplicate index generation.
How to Confirm Correct Configuration
- Upload a typical non-ferrous metal smelting environmental protection policy document, check if the chunked text retains complete clauses and quantitative indicators.
- Initiate a policy keyword search, verify that the matching degree of returned results falls within the preset similarity threshold range.
- Check system logs to confirm that vector generation task duration stays within a reasonable range, with no continuously backlogged queues.
- Manually trigger an incremental index, check that the number of index entries in the dataset does not grow irregularly.
The values provided are common starting points and should be evaluated 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 2026-09-28.