What the data for this category looks like
Energy metals research report data mainly comes from industry associations, mining enterprises, futures exchanges, and third-party consulting institutions. Update cycles cover daily spot quotes, weekly supply and demand reports, monthly industry updates, and quarterly/annual in-depth analyses. Document structures include core price indicators, supply and demand balance sheets, capacity plans, policy interpretations, and rating conclusions. Fields include spot price (unit: yuan/ton), reserves (unit: 10,000 tons), capacity (unit: 10,000 tons/year), publishing entity, and publishing date. Some research reports include high-definition industry chain maps and historical data comparison charts.
What constraints do these characteristics impose on deployment and upgrade?
Multiple dispersed data sources require configuring multiple data source connections and unified parsing rules during deployment to avoid cross-source data format conflicts. High-frequency spot and weekly report data requires incremental synchronization mechanisms optimized for short-cycle pulls. Full synchronization consumes excessive cluster resources and extends deployment time. Documents with high proportions of long text and structured tables lengthen parsing time, requiring sufficient service switching windows during upgrades to avoid prolonged business interruptions. Metadata mapping with many professional fields and strict unit uniformity requirements means that if parsing configurations are adjusted during upgrades, field extraction logic must be synchronized and verified to prevent data loss or format errors.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Energy metals research reports often include high-definition industry chain maps and long text, so single-file sizes are generally large |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | In-depth research reports have many pages, requiring processing of large amounts of structured tables and charts, leading to long parsing times |
maxContext | 8000–12000 characters | Research reports contain multiple sections of professional terminology and long sentences, requiring sufficient context to ensure semantic coherence |
| Number of recalled entries | Top 8–12 entries | Supply and demand data for energy metals research reports is scattered across different sections, requiring a sufficient number of recalled fragments to cover core indicators |
| Similarity threshold | 0.72–0.80 | There are many professional terms, requiring a balance between retrieval precision and coverage to avoid missing associated research reports for segmented categories |
AUTO_SYNC_INTERVAL | 3600 seconds | Spot price and weekly report data updates daily, so incremental synchronization adapts to short-cycle pulls to reduce cluster load |
The parameter values provided on this page are common starting points for configuration setup. Actual values are influenced by material format, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing configurations.
Three common mistakes
- Running
docker compose down && docker compose upto upgrade the version results in lost vector database data. This occurs because persistent storage volumes for vector data were not mounted, and directly updating the container clears the data. - Professional fields such as
LME nickel inventoryin retrieval results are empty or have format errors. This occurs because structured field extraction configuration was not enabled, so table data in research reports cannot be correctly extracted. - The
conversationIdfor a specified session cannot be obtained when calling the chat interface. This occurs because session persistence configuration was not enabled, or correct session identification parameters were not included in front-end requests.
How to confirm configurations are properly set
- Upload a typical energy metals research report, check that the parsed text includes complete supply and demand tables and price data, and verify that the parsing timeout matches the configured value.
- Initiate a retrieval request, confirm that the number of returned recalled entries falls within the configured range, and verify the filtering effect of the similarity threshold.
- Perform a version upgrade operation, restart the service, check that vector data in the knowledge base is not lost, and confirm that persistent storage mounting is functioning correctly.
- Initiate a chat request with a session identifier, verify that
conversationIdcan be properly obtained and reused.
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.