What the data for this category looks like
Plastics and rubber market data is sourced primarily from domestic bulk commodity spot trading platforms, industry association market monitoring data, and publicly available futures delivery warehouse receipt data. Updates follow three schedules:
- Spot quotes are updated daily after market close
- Futures prices are updated intraday
- Warehouse receipt data is updated weekly
Single data entry structure includes: variety identifier, origin information, delivery standard grade, quoted value, price change value, and update timestamp. Units are uniformly yuan/ton, and update times use ISO format timestamps.
What constraints do these characteristics impose on multi-turn dialogue and prompt engineering
These characteristics impose clear constraints on multi-turn dialogue and prompt engineering. Varying update frequencies across data sources require clear differentiation of data types in multi-turn dialogue. Prompts must guide users to specify whether they are querying spot, futures, or warehouse receipt data to avoid mixing results from different time dimensions. Fields include detailed information such as origin and delivery grade. Prompts must explicitly require the assistant to return the specified detailed dimensions, otherwise results may deviate from user needs. Multi-turn dialogue must retain historical context. For example, if a user first asks for the spot quote of polyethylene, a subsequent query about price changes requires the system to associate the historical variety information. This means reasonable context retention parameters must be configured. Units are uniformly yuan/ton. Prompts must clearly label the unit of returned results to avoid user misunderstanding of value meanings.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Plastics and rubber market data entries are relatively long. Multi-turn dialogue must retain user questions and historical response results to avoid context overflow |
historyCount | First 3–5 turns of dialogue | Limits excessive historical data from occupying the context window, while retaining sufficient dialogue context to associate subsequent queries |
searchRecallNum | Top 6–8 recall results | Plastics and rubber category data sources include multi-dimensional fields. Sufficient recall results can cover required query conditions such as variety and origin |
reRankThreshold | 0.75–0.85 | Filters low-relevance market data to ensure returned results closely match user queries about plastics and rubber varieties |
pluginTimeout | 600 seconds | Pulling market data from some data sources takes significant time. This avoids dialogue failure due to timeout |
promptTemplate | Fixed format: Please return [user-specified fields] based on [user-specified data type (spot/futures/warehouse receipt)] for [user-specified plastics and rubber variety], and label the unit as yuan/ton | Clarifies prompt format to avoid assistant confusion about data types and units |
The parameter values provided on this page are general recommendations for establishing configuration baselines. 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 Misconfigurations
- Phenomenon: Workflow dialogue displays failure, but model testing works normally and background response logs exist. Cause: Incorrect port mapping configuration for the Docker container, preventing the workflow node from normally calling the internal plugin interface.
- Phenomenon: Historical dialogue content is not included in the current request when calling the searchTest node. Cause: The
historyCountparameter is not configured, or the historical dialogue context field is not correctly carried in the request body. - Phenomenon: Prompts do not function as expected, and returned results include irrelevant non-plastics and rubber category data. Cause: The prompt does not explicitly specify the category scope, causing the assistant to call data sources from other categories.
How to Confirm Proper Configuration
- Initiate a single-turn dialogue, specify a specific plastics and rubber variety and data type, and verify that returned results include fields matching preset prompt requirements and label the correct unit.
- Initiate consecutive multi-turn dialogues, modify query conditions in sequence, and verify that the system correctly associates historical queried varieties and data types with no context loss.
- Check system logs to confirm that dialogue requests carry historical dialogue context, and no timeout errors occur during plugin calls.
- Adjust recall-related parameters, then verify that the number of returned results matches the preset configuration.
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.