Multi-turn Dialogue and Prompt Engineering for Thermal Industry Research Report Retrieval

Thermal industry research report data primarily comes from public utility industry association materials, public financial reports of thermal supply

What the data for this category looks like

Thermal industry research report data primarily comes from public utility industry association materials, public financial reports of thermal supply enterprises, monthly operation bulletins from local energy regulatory authorities, and third-party industry research institution reports. Core operational data is updated on a monthly cycle. In-depth analysis reports are released quarterly, and full-year industry summary reports are updated annually. Document structures include core fields such as total thermal supply volume, pipe network loss rate, residential heating coverage rate, and unit heating cost. Field units cover professional measurement standards including gigajoules, square meters, and yuan per gigajoule. Some cross-regional research reports also include comparative data on statistical standards across different cities.

What constraints these characteristics impose on multi-turn dialogue and prompt engineering

Thermal industry research reports have numerous specialized fields and varying unit standards. Multi-turn dialogue must gradually guide users to clarify specific indicators and statistical standards, to avoid response deviations caused by terminology ambiguity. The long document structure requires sufficient space in the context window to retain historical information from multi-turn interactions, while limiting meaningless redundant context. Frequently updated data requires prompts to specify the time range, ensuring retrieved research reports are the latest versions. Correlated data across different dimensions must be gradually linked during multi-turn dialogue, to avoid overwhelming users with excessive information in a single output that hinders understanding.

Configuration Settings

Configuration ItemRecommended Value RangeRationale
maxContext8000–12000 charactersThermal industry research reports have long individual document lengths; multi-turn dialogue requires retaining context while avoiding window overflow
Recall countTop 6–8 resultsThermal industry research reports cover multi-dimensional segmented indicators; enough documents must be retrieved to cover segmented use cases
Similarity threshold0.72–0.80Thermal industry terminology has high professional complexity; balance retrieval precision and coverage
PARSE_FILE_TIMEOUT_SECONDS120 secondsLarge thermal industry research report documents contain multiple sets of correlated data; parsing takes longer time
Chunk size800–1000 charactersThermal industry research report paragraphs contain multiple sets of correlated indicators; segmentation must retain data relevance
WORKFLOW_OUTPUT_LAST_NODEEnabledIn multi-AI dialogue module scenarios, only retain the conversation output results of the final node

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Each situation requires separate analysis, and it is recommended to test on your own samples before finalizing.

Three Common Misconfigurations

  • Symptom: Knowledge base answers are truncated, and simple mode conversations output normally. Cause: The maxContext parameter was not adjusted to fit the long document context of thermal industry research reports, causing window overflow and content truncation.
  • Symptom: A 500 error is returned when importing thermal industry research report documents. Cause: In fastgpt 4.8.10 version, a reasonable PARSE_FILE_TIMEOUT_SECONDS value was not set, or the bge vector model deployed via ollama was not configured with the correct model loading path.
  • Symptom: Results from all AI dialogue modules in the workflow are output. Cause: The WORKFLOW_OUTPUT_LAST_NODE configuration was not enabled, failing to limit retention to only the conversation output results of the final node.

How to Verify Correct Configuration

  • Upload a single thermal industry research report document with more than 10 pages, check if the post-parsing segment length matches the preset Chunk size requirement.
  • Initiate multi-turn questions covering multiple sets of thermal industry indicators, verify that the context is fully retained and no content truncation occurs.
  • Test importing batch thermal industry research report documents, confirm that parsing time does not exceed the duration set by PARSE_FILE_TIMEOUT_SECONDS.
  • Configure a workflow with multiple AI dialogue nodes, trigger operation and confirm that only the conversation results of the final node are output.

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.