What the data for this category looks like
Precious metals investment research data primarily comes from exchange real-time quotes, industry association supply and demand reports, official reserve data, and professional research reports. Real-time quote data updates every second. Monthly supply and demand reports and quarterly industry analysis are released on fixed schedules. Temporary policy announcements have no fixed rhythm.
Documents include structured price tables (fields include product code, real-time price, price change, trading volume, units are yuan/gram, London ounce), semi-structured industry research reports, and unstructured policy interpretation texts. Field formats vary widely across different data sources. Some overseas data sources use non-Chinese encodings and international units.
What constraints these characteristics impose on vector models and indexing
Second-level updates for real-time quotes require indexes to support incremental refresh. This avoids retrieval delays caused by full index rebuilding. Multiple units and field differences require unified formatting before vector ingestion. This prevents vector feature drift.
Mixed documents of unstructured text and structured tables require multi-modal vector extraction logic. This avoids incorrect truncation of structured data. Encoding issues from overseas data sources may cause tokenization errors. Encoding conversion rules must be configured in advance.
Small-volume data with high-frequency updates is not suitable for overly large batch indexing strategies. Such strategies will consume excessive server resources.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Adapts to the paragraph length of precious metals research reports and price tables, avoids field breaks from splitting structured data |
incremental_index_enabled | Enabled | Matches the second-level update requirement for real-time quotes, reduces resource consumption from full index rebuilding |
recall_top_k | Top 10–15 results | Covers multi-dimensional quote and research report information, avoids limitations of single recall results |
similarity_threshold | 0.75–0.85 | Filters mismatches between low-relevance unstructured text and structured data |
index_batch_size | 50–100 items per batch | Adapts to small-volume data with high-frequency updates, prevents excessive server memory usage from single index requests |
file_encoding | Auto-detection + forced UTF-8 conversion | Resolves encoding differences from overseas data sources, ensures normal tokenization and vector extraction |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Index interface calls return a 400 status code with an empty response body. Cause: Pre-validation for the multi-unit format of precious metals data was not completed, leading to request parameter formats that do not meet index service requirements.
- Phenomenon: Excessively high server memory or disk read/write usage occurs daily after local deployment. Cause: A reasonable value for
index_batch_sizewas not configured, and an overly large batch indexing strategy was used. Cumulative incremental index requests for high-frequency quote data lead to resource exhaustion. - Phenomenon: Knowledge base file uploads occasionally get stuck during the 1st or 2nd indexing stage, observed when using the
m3e-largemodel. Cause:chunk_sizewas not set to adapt to the structured table splitting logic, leading to failure of some structured data to vectorize normally, blocking tasks.
How to confirm proper configuration
- Upload a test file containing structured price tables and research reports, verify field integrity after vector ingestion, and confirm no field breaks.
- Submit an incremental index request, compare the time taken with full indexing, and verify that the incremental switch is active.
- Simulate high-frequency data update requests, observe server resource usage, and confirm no abnormal peaks occur.
- Call the retrieval interface, verify that the relevance of returned results matches the preset threshold rules.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.