What the data for this category looks like
Energy metals-related data comes mostly from publicly disclosed information of domestic and international commodity exchanges, industry associations, and supply chain enterprises. Spot price data updates after daily market close. Industry inventory and production survey data updates monthly. Policy documents are released irregularly. Most documents combine structured tables with brief analysis. Fields include product name, specification model, price range, total transaction volume, statistical cycle, and publishing unit. Common units are yuan/ton, ton, and kilogram. Some import-related data include USD-denominated fields.
What constraints do these characteristics impose on model integration and configuration?
The structured nature of energy metals data requires enabling structured parsing during integration to avoid field misalignment from non-general splitting. Differences in update rhythms across data sources require configuring differentiated knowledge base refresh rules to prevent outdated data or redundant updates. Diverse pricing units require preset unified conversion logic in configurations to stop the model from confusing calculation results across units. The short-text focused document structure needs retrieval strategies adapted for small context windows to avoid irrelevant long-text interference.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_STRUCTURED_TABLE | Enabled | Adapts to the structured table format of energy metals data to avoid splitting errors |
RECALL_TOP_N | 3-5 entries | Single documents for energy metals have short content; excessive retrieval will introduce irrelevant data |
SIMILARITY_THRESHOLD | 0.75-0.85 | Filters low-match irrelevant product data to avoid confusion between different metal categories |
KNOWLEDGE_REFRESH_CRON | 0 0 (spot data), 0 0 1 * (industry data) | Matches the update rhythms of different data sources |
API_REQUEST_TIMEOUT | 600 seconds | Adapts to response delays of industry data interfaces to avoid timeout interruptions |
maxContext | 8000-12000 characters | Adapts to the total context length after short text concatenation to avoid exceeding model limits |
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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: A 401 Unauthorized error is returned after configuring the model URL and key. Cause: Key permissions for the model service provider are not correctly set, or the URL points to a non-official interface address.
- Phenomenon: A Connection error is returned during API calls. Cause: Outbound port permissions for the server hosting FastGPT are not enabled, or the model interface has access restrictions.
- Phenomenon: The model only returns a single matching text block instead of combining multiple results. Cause: The
RECALL_TOP_Nparameter is set to 1, or the similarity threshold is set too high, filtering all low-match but relevant results.
How to confirm the configuration is complete
- Enter the model debugging interface, input queries referencing energy metals such as lithium and cobalt, and verify that returned results include structured data fragments from multiple sources.
- View refresh records on the knowledge base management page, confirm that spot data updates daily and industry data updates monthly as scheduled.
- Call the configured API interface, check that the response status code is 200 and the returned content includes multiple matching document fragments.
- Modify the
SIMILARITY_THRESHOLDparameter, confirm that the number of retrieved text blocks changes as expected with threshold adjustments.
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.