What This Category's Data Looks Like
Data for industrial metals mainly comes from industry association public quotation platforms, real-time trading APIs of spot trading markets, and futures exchange contract market APIs. Spot data updates every 15 minutes to 1 hour, while futures data updates on a scheduled basis per trading day. Documents include two categories: structured tables and unstructured text. Structured fields include product name, specification, origin, daily average price, price change range, and total inventory, with units mostly yuan/ton and kg/hand. Unstructured content includes industry research reports and regional supply and demand analysis, with a wide range of single text lengths.
Constraints Imposed on Model Integration and Configuration
Multi-source heterogeneous data structures require targeted field extraction rules to avoid invalid data mixing into context. High-frequency updated market data requires matching the cache expiration time of model calls to the data update rhythm, preventing expired information from being used to generate marketing content. Mixed input of long-text research reports and structured tables requires adjusting parsing and context truncation parameters to ensure core information is not lost. Marketing content needs to combine real-time market data, so the trigger timing of model calls must align with data update nodes to avoid content lag.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Industrial metals marketing content needs to combine research reports, real-time market data and product parameters, with per-round context length requirements higher than general scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Batch parsing of industrial metal inventory reports and cross-regional market summary files takes a long time, default parameters cannot complete full parsing |
Recall Count | Top 6–8 entries | Industrial metals marketing requires precise matching of market data for specific specifications and origins; excessive recall leads to content redundancy |
Similarity Threshold | 0.72–0.78 | Industrial metal product names and specifications have high recognizability, too low a threshold will introduce irrelevant category data |
Reranked Return Count | Top 3–4 entries | Marketing content needs to highlight core market and supply and demand information; too many return results distract the audience |
UPLOAD_FILE_MAX_SIZE | 200 MB | Industrial metal quarterly supply and demand research reports and full-category inventory reports have large file sizes, requiring adaptation of upload limits |
The parameter values provided on this page are common starting points for configuration. The actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Phenomenon: The origin and specification fields of industrial metals are empty in model return results. Cause: No dedicated industrial metal entity fields are specified in the configuration, causing the model to fail to recognize valid business information.
- Phenomenon: A 504 timeout status code is returned after triggering a model call on the hour. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and the default short timeout value is used, which cannot complete the parsing of batch market data. - Phenomenon: The interface prompts no available channels, the model connectivity test via oneapi succeeds but FastGPT calls fail. Cause: The interface-specific identifier of the industrial metal data source is not correctly matched, or the model alias configuration does not meet the data source requirements, causing channel group verification to fail.
How to Confirm Proper Configuration
- Pass industrial metal spot market data and a preset marketing copy template to the test interface, and check whether the returned content includes the specified product name, origin and price fields.
- View the model call log to confirm that the context of each call does not trigger truncation, and the timeout time matches the configured value.
- Simulate triggering a model call on the hour, check whether it executes as expected, with no additional automated tasks interfering.
- Verify the channel group configuration, confirm that the model alias completely matches the interface identifier of the industrial metal data source, with no spelling errors.
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.