What the data for this category looks like
Industrial metal data sources primarily include real-time quotes from global commodity exchanges, monthly inventory reports from domestic industry associations, and spot transaction ledgers from supply chain enterprises. Update cadences fall into three categories: real-time (spot quotes), trading day updates (futures market trends), and weekly or monthly (industry analysis reports). Document structures typically include fields such as product name, specification grade, origin, same-day transaction price, price change range, total inventory, delivery cycle, and more. Common units include yuan/ton, USD/ton, ten thousand tons, percentage (purity), millimeters (specification dimensions). Single document lengths vary widely. Internal sample statistics or on-site measurement should be used to confirm appropriate values before finalizing.
Constraints on multi-turn dialogue and prompt engineering
The real-time nature of industrial metal data requires multi-turn dialogue systems to prioritize retrieving the latest exchange quotes and inventory data, and avoid using expired knowledge base content. The combination of multiple fields and professional units requires prompts to clearly specify the value range and units of each field, preventing the model from confusing parameters across different categories. Differences across data sources require multi-turn dialogue to guide users to clarify exchange type and data type (spot or futures). It also requires configuring filtering rules to eliminate interference from unrelated categories. The structure of long documents requires dialogue context to retain sufficient historical information, ensuring the model can associate category and specification parameters from the previous interaction round.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Industrial metal marketing conversations involve multiple rounds of details including category specifications, quotes, and inventory data. This range covers the information retention needs of conventional multi-turn interactions, and prevents key context from being truncated |
retrieval count | Top 6–8 entries | Single industrial metal knowledge base documents may include multiple specification quotes and parameters. Retrieving too many entries leads to redundant context, while retrieving too few misses valid data for the target category |
similarity threshold | 0.75–0.85 | Industrial metal purity and specification parameters have high recognizability. A threshold that is too low retrieves unrelated category data, while a threshold that is too high misses valid information for similar specifications |
chunk length | 1000–1500 characters | Industrial metal documents include long paragraphs of specification descriptions and historical quotes. This chunk length balances information completeness and model extraction accuracy |
assign dedicated knowledge base collection | Bind a dedicated collection for the corresponding industrial metal category | Avoid retrieving unrelated data from other major categories such as ferrous metals and precious metals, and accurately locate marketing materials and real-time data for the target category |
DATABASE_QUERY_TIMEOUT | 300 seconds | Industrial metal real-time data queries may involve calls to multiple exchange interfaces. This timeout duration covers conventional interface response times, and prevents query interruptions |
The parameter values provided on this page are conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume, and business rules. Each scenario requires individual analysis. Internal sample statistics or on-site measurement should be used to confirm appropriate values before finalizing.
Three common configuration mistakes
- Phenomenon: The database connection plugin returns a "connection timeout" error after configuration. Cause: The port number of the industrial metal data interface is not added to the allowed access whitelist, or the timeout setting is shorter than the response duration of the exchange interface. This issue is common in database plugin configurations for version V4.9.3.
- Phenomenon: Knowledge base content for the specified industrial metal category cannot be retrieved during multi-turn dialogue. Cause: The dedicated knowledge base collection for the target category is not bound in the configuration. The model retrieves the full knowledge base by default, leading to confusion.
- Phenomenon: The temperature setting button disappears and cannot be adjusted after switching the dialogue mode to variable reference. Cause: Variable reference mode inherits the global temperature configuration by default, and no separate temperature parameter is configured in the dialogue node.
How to confirm successful configuration
- Initiate a test dialogue that includes specific industrial metal categories and specifications. Verify that the retrieved knowledge base content comes from the bound dedicated collection, with no data from other categories included.
- Initiate consecutive multi-round interactions, sequentially asking for category parameters, quotes, and inventory information. Verify that the model retains key information from the previous round of interactions completely, with no context truncation or confusion.
- Trigger a database query action. Verify that the returned data fields include standard units for industrial metals, with no missing or mixed units.
- Adjust the dialogue temperature parameter and initiate a test. Verify that the generated marketing content matches the expected level of rigor or flexibility, and confirm that the parameter configuration takes effect.
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.