What the data for this category looks like
Data sources include the Shanghai Futures Exchange, London Metal Exchange, and industry commodity news platforms. Two update schedules apply: main futures contracts refresh real-time quotes every 5 seconds, and spot quotes update twice daily. The data is delivered as structured tables, with fields including product code, delivery grade, today's transaction price, settlement price, total inventory, warehouse receipt quantity, and more. Units are yuan/ton, ton, and lot.
Constraints for Multi-turn Dialogue and Prompt Engineering
High-frequency real-time quote refresh requires dialogue context to verify data timestamps, preventing return of outdated information. Structured multi-field data requires prompts to explicitly specify required fields and units, avoiding redundant output or formatting confusion. Unit differences across exchanges must be pre-agreed in prompts to prevent cross-market data confusion. Low-frequency inventory and warehouse receipt data requires distinguishing real-time and non-real-time data sources in multi-turn dialogue, preventing misuse of data categories. Long table outputs are prone to truncation, so prompts must explicitly specify output length limits and full return requirements.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Industrial metal market data has many fields, requiring space for multi-turn dialogue and complete market data sets |
responseMaxToken | 2000–3000 characters | Matches the length of industrial metal structured market tables, avoiding output truncation |
recallTopK | Top 3–5 entries | Industrial metal market data has concentrated relevance; excessive recall increases context redundancy |
promptTemplate | Must explicitly agree on data sources, units, output format as structured tables, and full return of all specified fields | Adapts to the multi-field, multi-unit characteristics of industrial metal data, avoiding formatting confusion and truncation risks |
sseTimeout | 600 seconds | Cross-exchange data aggregation for industrial metal requires longer wait times, preventing premature request interruption |
apiHistoryFilter | Group by application ID + user ID | Isolates conversation history across different users and applications, avoiding data query confusion |
The parameter values provided on this page are common recommendations used as starting points for configuration. Actual values are affected by material forms, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: Markdown-formatted industrial metal market tables are truncated, with ellipses or hidden character prompts displayed at the end. Cause: Failure to set
responseMaxTokento a value matching the market table length, or failure to explicitly require full return of all fields in the prompt. - Phenomenon: Dialogues return the error
insufficient_quota 当前分组上游负载已饱和，请稍后再试, with a unique request ID attached. Cause:sseTimeoutis configured too short, or multi-turn dialogue context is too large, causing model request processing time to exceed upstream service thresholds. - Phenomenon: After the client actively closes the SSE connection, the complete record of the current conversation is not saved to the database. Cause: Failure to configure automatic archiving logic after conversation interruption, or
apiHistoryFilteris not grouped by application and user ID, leading to incorrect data association.
How to Verify Correct Configuration
- Initiate a test dialogue with multi-turn industrial metal market queries, verify that returned fields and units fully match prompt agreements.
- Call the conversation history query interface, confirm that returned results only include conversation data for the current application and specified user, with no redundant cross-application or cross-user content.
- Simulate the scenario where the client actively closes the SSE connection, verify that all interactive content of the conversation is fully saved in the database.
- Trigger a long table output request, verify that returned content is not truncated and meets preset formatting 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.