Multi-turn Dialogue and Prompt Engineering for Railway and

What the data for this category looks like

Railway and highway research report data primarily comes from public announcements issued by transportation authorities, monthly operation briefings from railway operating enterprises, annual statistical reports from highway industry associations, and research documents from third-party transportation think tanks. Update cycles follow monthly and quarterly schedules, with annual reports serving as full retrospective reviews. Document structures typically include modules such as line operation data, passenger and freight volume statistics, cost composition, policy impact analysis, and other related sections. Fields include clearly quantified indicators including passenger and freight volume (unit: ten thousand people/ten thousand tons), operation mileage (unit: kilometers), revenue scale (unit: ten thousand yuan), and single-trip operation cost (unit: yuan per kilometer).

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

The update cycles, field characteristics, and document structures of railway and highway research reports create clear constraints for multi-turn dialogue and prompt configuration. First, the high-frequency monthly and quarterly update feature requires multi-turn dialogue contexts to limit the time range of valid research reports, to avoid calling outdated data. Second, segmented fields such as passenger and freight volume and operation mileage have clear attached units, so prompts must enforce that returned results align with specified units to prevent unit confusion. Third, the multi-module document structure requires multi-turn dialogue to guide users to explicitly specify the query module, to avoid returning irrelevant content. Finally, the attributes of the targeted segmented field require prompts to limit retrieval scope to railway and highway track research reports, excluding interference from other categories.

How to set the configurations

Configuration Item	Recommended Value	Rationale
`maxContext`	1200–1500 preceding characters	Single core content of railway and highway research reports is relatively long, so sufficient context must be retained to support multi-turn dialogue logic
`Recall Count`	Top 6–8 results	Research report data has segmented modules; too many recalls will cause context redundancy, while too few will fail to fully cover requirements
`Similarity Threshold`	0.72–0.78	Precise matching of railway and highway-specific fields and units is required to avoid mixing irrelevant content from other transportation categories
`Reranked Return Count`	Top 3–4 results	Focus on core research report modules to reduce information interference in multi-turn dialogue
`PARSE_FILE_TIMEOUT_SECONDS`	90 seconds	Single research report contains multi-module data, so parsing time is longer than that of general documents
`systemPrompt`	Explicitly limit to the railway and highway field, enforce alignment with field units	Retrieval scope and return format must be constrained in advance to avoid cross-category or unit errors

The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to conduct tests on your own samples before finalizing settings.

Three common misconfigurations

Workflow dialogue shows failure but model backend has response logs: The front-end dialogue interface returns a 500 status code, while the backend model logs show normal generation of results. The cause is that the ragResponseFormat parameter is not configured, causing the workflow to fail to correctly parse the format of the research report retrieval results returned by the model.
Retrieval node cannot pass historical dialogue: When calling the retrieval interface, the retrieval results are not associated with the previous user query, and content is generated only based on the current single input. The cause is that the enableHistoryContext switch is not enabled in the node configuration, and the dialogue context variable is not correctly bound.
Prompt does not take effect as expected: The node prompt does not cover all preset rules, and returned results include content outside the railway and highway field. The cause is that the systemPrompt node is not placed as the first node in the workflow, causing subsequent nodes to overwrite the preset field restriction rules.

How to confirm the configuration is correct

Test a single dialogue input, check whether the field units of the returned results meet the preset requirements, and adjust the similarity threshold until the matching accuracy meets the standard.
Initiate two consecutive questions, check whether the retrieval results are associated with the context of the previous round of dialogue, and confirm that the enableHistoryContext switch is correctly configured.
Trigger an abnormal error scenario, check whether the system log generates corresponding records, and confirm that the debugLog switch is enabled.
View the workflow node order, confirm that the systemPrompt node is located before all business nodes, and verify that the prompt rules take effect as expected.

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.