What the data for this category looks like
Data related to steel trade yield comes from three sources: public market data from domestic steel spot trading platforms, internal enterprise purchase-sales-stock ledgers, and inventory records from futures delivery warehouses. There are two update schedules: external spot market data updates hourly, with a full-category daily summary report generated after daily market close; internal enterprise ledgers update in real time with each transaction. Data is stored in structured CSV or JSON format. Each record corresponds to the full-cycle cost and revenue of one trade, and includes fields such as traded product specification, purchase settlement price, sales settlement price, per-ton transportation cost, per-ton storage cost, per-ton gross profit, settlement date, and trading counterparty. The unit for prices is yuan/ton, and the units for costs and revenue are yuan/ton.
What Constraints Do These Characteristics Impose on the Conversation Logging and Auditing Workflow
Steel trade data has two source types: external market platforms and internal purchase-sales-stock ledgers, with differing update rhythms. The conversation logging and auditing workflow must record full end-to-end information for both external data source calls and internal system queries, to ensure the basis for revenue calculation is traceable. Since different steel product categories have distinct cost structures, logs must be bound to the corresponding traded product’s specification field to avoid mixing data across categories. Revenue calculation for a single trade relies on multi-dimensional cost fields, so the auditing workflow must verify that cost items in logs match fields in transaction records. Additionally, steel trade transaction cycles vary widely, so log retention must cover the full transaction cycle to ensure completeness for cross-cycle audits.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
logRetentionDays | 180 days | Covers the semi-annual transaction cycle of most steel trades, meeting full-cycle audit traceability requirements |
enableDataSourceLog | Enabled | Steel trade data includes external market data and internal purchase-sales-stock ledgers. Each data call’s source and timestamp must be recorded to ensure the basis for revenue calculation is traceable |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Steel trade daily summary reports have large data volumes. This setting prevents missing structured log records due to timeout |
similarityThreshold | 0.85–0.90 | Steel trade transaction records have many fields and large specification differences. A high matching threshold ensures accurate log association with conversations, avoiding incorrect cross-category data association |
maxHistoryMessages | First 8 messages | Balances conversation context completeness and retrieval efficiency, preventing knowledge base retrieval delays caused by overly long context |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. Testing against in-house samples is recommended before finalizing configuration.
Three Common Configuration Errors
- Symptom: After multiple consecutive steel trade-related questions in the same conversation window, knowledge base retrieval time exceeds 60 seconds. Launching the same questions in a new blank window restores normal latency. Cause: The number of retained historical conversations is not limited. Excessively long context requires loading large volumes of historical data for each retrieval, increasing retrieval overhead.
- Symptom: A workflow configured for conversation logging and auditing cannot achieve multi-turn conversation linkage, with no clear error logs output. Cause: The
enableDataSourceLogconfiguration is not enabled. The workflow cannot associate historical transaction logs, leading to incorrect binding of multi-turn conversation context. - Symptom: After uploading a steel trade daily summary report, the parsing log shows a
PARSE_ERRORstatus code, and the report fails to import successfully. Cause: ThePARSE_FILE_TIMEOUT_SECONDSvalue is set too low. Large structured reports are terminated before parsing completes.
How to Verify Proper Configuration
- Access the platform’s log management page, check the value of the
logRetentionDaysconfiguration item, and confirm it matches the preset retention period. - Launch a simulated steel trade conversation, check the log list on the conversation details page, and confirm that data source call records and internal system query records are included.
- Test multiple consecutive questions, observe changes in knowledge base retrieval latency, and confirm that latency does not increase significantly as the number of conversation turns increases.
- Upload a test steel trade structured report, check the parsing log, and confirm that no
PARSE_ERRORstatus code records are present.
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.