What data for this category looks like
Iron ore investment research data primarily comes from global commodity price reporting services, domestic commodity trading platforms, publicly available futures exchange data, and industry research reports. Spot price data is updated daily. Futures settlement data is synchronized with the end of each trading day. In-depth industry reports are released weekly or monthly.
Document structure includes structured price fields (grade, origin, pricing unit: yuan/wet metric ton), port inventory fields (port name, total inventory in 10,000 metric tons), research report metadata (publishing institution, release date), and unstructured analysis content. Some documents include historical price trend charts and supply and demand balance sheets.
Constraints imposed on knowledge base retrieval and recall by these characteristics
These characteristics create clear constraints for the retrieval and recall process. Frequently updated spot data requires the retrieval pipeline to support incremental synchronization, avoiding excessive computing resource usage from full re-pulling. Multi-dimensional structured fields require the retrieval system to support multi-condition combined recall, such as filtering target quotes by grade and origin, to improve retrieval accuracy.
Mixed storage of structured and unstructured content requires the recall pipeline to support both keyword matching and semantic retrieval, balancing precise matching of structured data and understanding of unstructured research report content. The requirement for unified pricing units means retrieval results must automatically adapt to standard units, avoiding confusion from different pricing methods. Time-related association needs require recall results to include data release timestamps, to help investment research personnel judge information timeliness.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
Recall count | Top 8-12 entries | Iron ore investment research data has multiple dimensions, requiring coverage of quotes and research reports from different origins and grades. Excessive entries will exceed the context window limit |
Similarity threshold | 0.72-0.85 | Semantic similarity of structured price fields requires strict matching to avoid mixing low-correlation data from other commodities in results |
maxContext | 4000-6000 characters | The total length of iron ore research reports and structured data is relatively long, requiring sufficient context for large model integration and analysis |
UPLOAD_FILE_MAX_SIZE | 500 MB | Adapts to the typical size of single industry research report collections or batch historical data files, avoiding upload interruptions |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Adapts to the parsing time of large batch data files, preventing interruptions due to parsing timeouts |
Rerank result count | Top 3-5 entries | Investment research scenarios require precise matching of core data. Excessive results will distract from decision-making focus |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test against your own samples before finalizing.
Three Common Configuration Mistakes
- Symptom: Embedded local images in retrieval results show expiration or fail to load. Cause: Local file persistent storage path is not configured, or image resources are not migrated from the temporary directory to the permanent storage directory.
- Symptom: The number of retrieval return results does not match the configured
Recall count, resulting in quantity deviation. Cause: The mixed recall mode of semantic retrieval and keyword retrieval is not enabled, and only a single retrieval method is used, leading to incomplete result filtering. - Symptom: Global variables customized for knowledge base selection cannot be read by the judge to execute conditional matching. Cause: Permission calls for global variables are not enabled in the judge configuration, or the knowledge base bound to the variable is not correctly associated with the current application workflow.
How to Verify Proper Configuration
- Upload a test iron ore document containing structured price quotes, port inventory data and explanatory images, and check whether parsed fields such as grade, origin and pricing unit are fully extracted.
- Initiate a simulated investment research query, verify that the number and similarity of returned results meet the preset configuration, and that embedded images can be loaded and displayed normally.
- Configure global variables to bind the target knowledge base, set conditional logic based on variable values in the judge, and verify that conditional matching works properly after triggering the workflow.
- Check application running logs to confirm that no timeout, parsing failure or insufficient resource error messages appear in the retrieval link.
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.