What This Type of Data Looks Like
Sources of energy metals research reports primarily include non-ferrous metal industry associations, professional commodity information institutions, securities firm research institutes, and public reports from futures exchanges. Update frequency adjusts dynamically based on industry events. Temporary reports are created when major policies are released or price fluctuations take place. Regular reports are updated on a monthly and quarterly basis. Document structures include core conclusions, supply and demand balance sheets, price trend analysis, and attached data tables. Fields covered include report publishing institution, report date, energy metal variety name, production/consumption volume (unit: ton or ten thousand tons), price (unit: yuan/ton or US dollar/ton), industry rating, and more. Some research reports include comparative data with different statistical standards.
Constraints Imposed on Workflow Orchestration
Energy metals research reports have a high proportion of structured data. Statistical standards vary across different institutions. Workflows must support structured field extraction and standard alignment processing. Update frequencies are inconsistent, and temporary reports are common. Workflows must support on-demand data source updates or high-frequency polling configurations. Document lengths vary significantly, ranging from a few pages to dozens of pages. Workflows must adapt parsing and segment processing for documents of all lengths. Field units are diverse. Unified unit conversion logic must be configured to prevent unit confusion during analysis.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recallTopK | Top 8-12 entries | Energy metals research reports contain large amounts of structured supply and demand data. Sufficient recalled entries are needed to cover core indicator content |
similarityThreshold | 0.72-0.80 | Filter irrelevant general industry research reports, and accurately match specialized analysis content for target energy metal varieties |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Adapt to long-form in-depth research reports, avoid process interruptions caused by parsing timeouts |
chunkSize | 1000-1500 characters | Balance parsing integrity of structured tables and paragraphs, ensure contextual coherence |
globalVarPassMethod | Bind via interface input parameters | Support external platforms to pass global variables such as variety codes and report cycles, adapt to multi-layer user selection scenarios |
ragReRankCount | Top 4-6 entries | Rerank recalled results, prioritize content related to core energy metal indicators |
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. Each scenario requires targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: After the workflow is published as a public interface, incoming energy metal variety parameters passed by external platforms do not take effect. Returned results do not generate analysis content for the specified variety. Cause: Global variable passthrough is not enabled in interface configuration, or input parameter format does not match preset variable binding rules.
- Phenomenon: AI-generated responses do not reference energy metal supply and demand data queried from the database, and only output general analysis content. Cause: The output result of the database query node is not bound to the context input field of the LLM node.
- Phenomenon: Multi-layer user selection question tree processes are interrupted, and subsequent nodes cannot obtain parameters selected in previous steps. Cause: Variable transfer links are not configured correctly, and outputs from previous nodes are not mapped as global variables for use by subsequent nodes.
How to Verify Successful Configuration
- Call the preset test interface, pass in the specified energy metal variety code and report cycle, check if returned results include specialized research report content for that variety.
- View workflow execution logs, confirm that fields returned by the database query node match the preset energy metals research report fields.
- Manually trigger the multi-layer user selection workflow, verify that parameters from each step are correctly passed to subsequent nodes.
- Adjust the similarity threshold, verify that the accuracy of recalled results meets business requirements.
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.