What the data for this category looks like
Data sources for plastics and rubber financing daily reports include commodity spot trading platforms, futures exchange delivery data, industry association statistics, and customs import and export record information. Data is updated to fully reflect the previous workday’s figures every early morning. The document structure includes fields such as product category, same-day spot closing price, main futures contract closing price, standard warehouse receipt inventory, margin trading and short selling balance, import and export volume, and more. Price fields use yuan/ton as their unit, warehouse receipt and inventory fields use ton, and balance fields use ten thousand yuan. Each data entry is tied to a unique statistical date identifier.
What constraints these characteristics impose on multi-turn conversation and prompt engineering
The daily update timeliness requirement mandates that multi-turn conversations strictly limit the data scope to the daily report of the current statistical cycle, to avoid introducing outdated historical data. The professional nature of multiple fields requires prompts to clearly guide the AI to extract corresponding indicators for the specified product category, to prevent confusion between parameters of different plastics and rubber varieties. The unified unit requirement must be enforced in conversations, to avoid missing or mixing units. The high degree of data correlation requires that multi-turn conversation contexts fully retain previously asked category and date information, to ensure logical consistency for follow-up questions.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 1500–2500 characters | The plastics and rubber financing daily report has a large single-document data volume. This range preserves the previously shared category and date context in multi-turn conversations, avoiding information loss from context overflow |
systemPrompt | "Answer only based on the same day's plastics and rubber financing daily report data. Clearly mark corresponding units in outputs. Disable Markdown formatting, only retain plain text and necessary line breaks" | Matches requirements for data timeliness, unit accuracy, and unformatted output. Restricts the AI to only use the current daily report as the data source |
recallTopK | Top 6–8 entries | The financing daily report covers multiple core indicators including spot, futures, and warehouse receipt data. Too many recalled entries will introduce irrelevant data, while too few will fail to cover the full information required for the query |
similarityThreshold | 0.75–0.85 | Filters low-relevance historical daily report data, ensuring that recalled content strongly matches the current query’s plastics and rubber category and statistical date |
responseFormat | Plain text | Prohibits automatic generation of Markdown headings, lists, and other formats, matching user requirements for concise outputs |
conversationMode | Continuous conversation | Supports retention of multi-turn context, avoids creating a new thread for each conversation, and meets usage scenarios requiring follow-up questions |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: The AI reply is only displayed in a side floating window and not directly embedded in the conversation area. Cause: The
enableInlineReplyconfiguration item is not enabled, and the side pop-up reply mode is enabled by default. - Symptom: A new conversation is automatically created each time a new query is initiated, and context cannot be continued. Cause:
conversationModeis not set to continuous conversation, or the conversation context was manually reset. - Symptom: The AI reply automatically uses Markdown formatting to generate lists, headings, etc. Cause: Non-plain text formatting is not explicitly prohibited in
systemPrompt, orresponseFormatis not configured as plain text.
How to Verify Proper Configuration
- Initiate consecutive multi-turn queries, for example, first ask "What is the daily warehouse receipt quantity for natural rubber?" then follow up with "What is the corresponding margin balance?" Confirm that context is not lost and the reply logic is consistent.
- Review the AI’s reply content, confirm that there are no Markdown headings, lists, etc., only plain text and necessary line breaks, and all indicators are marked with their corresponding units.
- Test queries for different plastics and rubber categories, for example, switch from natural rubber to polypropylene, confirm that recalled content matches the current query’s category and data scope.
- Check the output configuration of the AI conversation node in the workflow, confirm that the trigger logic of the question classification node is not automatically bound, ensuring that the current branch is exited after the AI replies.
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.