Multi-turn Dialogue and Prompt Engineering for Thermal Utility Financing Daily Reports

The data for thermal utility financing daily reports comes from public thermal enterprise pipeline monitoring platforms, billing settlement systems

What the Data for This Category Looks Like

The data for thermal utility financing daily reports comes from public thermal enterprise pipeline monitoring platforms, billing settlement systems, and energy consumption reporting ports. Full data for the previous day is compiled each early morning, with updates occurring daily. The output is delivered as structured tables, including fields such as heat exchange station number, supply and return water temperature, pipeline pressure, daily heat supply amount, cumulative billing amount, and abnormal alarm entries. The unit for heat supply is gigajoules, pressure is megapascals, temperature is degrees Celsius, and amount is Chinese yuan.

Constraints for Multi-turn Dialogue and Prompt Engineering

The full structured fields for thermal utility financing daily reports are numerous and include physical units. This requires multi-turn dialogue to track context identifiers specified by the user, such as heat exchange stations or regions, to avoid repeated requests for basic filter conditions. The daily updated batch data structure requires prompts to explicitly specify the units and statistical specifications of fields to avoid output confusion. The discrete nature of the abnormal alarm entry field requires multi-turn dialogue to support users in asking for details of a single abnormal entry, and the abnormal entry ID from the previous interaction must be retained. The volume of full data requires the dialogue context window to adapt to moderately long historical information to prevent loss of critical context.

Configuration Settings

Configuration ItemRecommended ValueRationale
maxContext6000–10000 charactersAdapts to the content length of a single thermal utility financing daily report and the storage requirements for multi-turn interaction history
maxHistoryTurns3–5 turnsMeets the context retention needs for multi-turn interactions such as users asking for heat exchange station parameters or abnormal details
systemPromptFixed matching of heat exchange station ID/region name, explicitly specify field units and statistical specifications, associate abnormal entry IDAdapts to the structured feature of multiple fields with units in thermal utility financing daily reports, avoiding confusion in model output
showChatMessageOnly display core interaction node outputs in node orderResolves chat confusion caused by simultaneous outputs from multiple AI dialogue nodes
contextWindowStrategyRetain context per session, automatically truncate the earliest non-core interactions when thresholds are exceededPrevents model response timeouts or information loss caused by long contexts
retryOnError2 timesAddresses occasional data interface fluctuations that cause dialogue interruptions, improving interaction stability

The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test against your own samples before finalizing settings.

Three Common Misconfigurations

  • Phenomenon: The specified heat exchange station ID from the user is not retained during multi-turn dialogue, requiring re-entry for each interaction. Cause: maxHistoryTurns is not configured or the value is set too low, causing historical context to be automatically truncated.
  • Phenomenon: After the workflow runs, replies from all AI dialogue nodes are displayed in the chat panel. Cause: Non-core nodes do not have showChatMessage configured to the disabled state.
  • Phenomenon: Units are not specified in the prompt, and the model’s output for heat supply amount does not label gigajoules or confuses temperature and pressure units. Cause: The system prompt does not explicitly specify field units and statistical specifications, and does not constrain the model’s output format.

How to Verify Proper Configuration

  • Initiate a test dialogue: First specify a heat exchange station ID, then ask for the heat supply amount of that station. Confirm that the model returns the result directly without requiring the heat exchange station to be specified again.
  • Configure a workflow with multiple AI dialogue nodes, run the workflow, and check the chat panel to confirm that only replies from core nodes are displayed.
  • Input a query that contains unit confusion, and confirm that the model correctly identifies and outputs results using the specified units.
  • Initiate more than 3 consecutive follow-up questions, and confirm that the model retains all context information without any context loss.

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.