What the Data for This Category Looks Like
Data sources for minor metal research reports include specialized research reports from securities research institute non-ferrous metal teams, monthly industry reports from the Minor Metal Branch of China Nonferrous Metals Industry Association, and daily trading data from professional spot trading platforms. Update frequencies vary: securities research reports are released immediately with industry trends, with no fixed cycle; industry reports are updated monthly; spot trading data is updated daily. Single research reports range from 5000 to 10000 characters in length. Their structure includes five sections: core data summary, supply and demand analysis, price trend, policy interpretation, and downstream applications. Fields include minor metal variety name, spot transaction price, total inventory, and monthly import and export volume. Corresponding units are none, yuan/kilogram, ton, and ton respectively.
What Constraints Do These Characteristics Impose on Model Access and Configuration
Dispersed data sources and varying update frequencies require configuring classified synchronization rules for multi-source data. Long length of single research reports requires adjusting the model's context window parameter to fully carry complete report content. Differences in field units across varieties require configuring standardized mapping rules to unify data formats. Dense professional terminology and industry abbreviations require configuring professional knowledge base recall to improve retrieval accuracy. Daily updates of spot data require setting high-frequency synchronization tasks to ensure data timeliness.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single minor metal research report is mostly 5000-10000 characters in length; complete context must be retained to support accurate question answering |
chunkSize | 1000–1500 characters | Professional paragraphs in minor metal research reports are moderately long; segmentation balances recall accuracy and context integrity |
recallTopK | Top 6–8 results | Minor metal research report data dimensions cover supply and demand, price, policy and other directions; sufficient content covering core information must be recalled |
vectorSimilarityThreshold | 0.75–0.85 | Many professional terms exist in minor metal materials; low-related recall results must be filtered to ensure relevance of retrieved content |
syncInterval | Once daily | Spot trading data is updated daily; monthly synchronization tasks can be added to adapt to the update cycle of industry reports |
modelTemperature | 0.1–0.3 | Accurate factual answers are required for minor metal research report retrieval; lower temperature parameters reduce output randomness |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Calling the model test interface returns
Api response error: /api/core/ai/model/test?model=Doubao-l. The cause is that the model's API key is not configured correctly, or the model name is spelled incorrectly, preventing the specified model from being called. - After configuring
enableThoughtOutputto off, the model output still contains thinking content starting with<think>. The cause is that the model's system prompt does not explicitly disable thinking process output, or the model itself does not support this switch configuration. - Attempting to access a text-to-image model for research report retrieval scenarios returns results that do not meet text question and answer requirements. The cause is that a large model adapted for text retrieval was not selected, and a model that only supports image generation was incorrectly accessed.
How to Confirm Proper Configuration
- Enter the model test interface, enter a query related to minor metals, and verify whether the returned results include core data from the corresponding research report.
- View the vector database recall logs, and verify whether the number of recalled research reports matches the configured
recallTopKparameter. - Check the running records of data synchronization tasks, and confirm that daily and monthly data source updates have been successfully triggered.
- Switch between different AI models, and verify that the recall result logic remains consistent for the same query.
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.