Multi-turn Dialogue and Prompt Engineering for Duty-Free Financial Report Analysis

Duty-free financial report data comes mainly from public periodic reports (annual, semi-annual, quarterly) released by enterprises, and special

What the Data for This Category Looks Like

Duty-free financial report data comes mainly from public periodic reports (annual, semi-annual, quarterly) released by enterprises, and special duty-free operation statistics published by industry regulators. Updates follow a regular quarterly, semi-annual, and annual schedule, while some high-frequency operational data updates monthly. The document structure includes modules such as revenue breakdown details, business location data, and customer group consumption characteristics. Special fields include off-island duty-free sales, in-store passenger traffic, and per-customer consumption amount, with units of ten thousand yuan, passenger trips, and yuan respectively.

Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering

The unique business fields and scenario limitations of duty-free financial reports require multi-turn dialogue to retain sufficient context to maintain analysis consistency. For example, if a conversation mentions the "off-island duty-free" scenario, subsequent analysis must maintain this limitation to avoid confusion with general retail data. The difference in update frequency between high-frequency operational data and periodic financial reports means prompts must clearly specify the data’s time range and statistical dimensions, preventing confusion between monthly passenger traffic data and quarterly sales data. Additionally, duty-free business has strong policy relevance, so multi-turn dialogue must retain context of policy changes to ensure analysis results align with the current industry environment.

Configuration Settings

Configuration ItemRecommended ValueRationale
maxContextPrevious 6 turns of dialogueDuty-free financial report analysis requires retaining context information such as scenario limitations and field associations. 6 turns of dialogue balance context completeness and computational overhead
ragTopK8-12 entriesDuty-free financial reports include special fields such as off-island sales and per-customer average consumption, requiring sufficient relevant data to be retrieved to cover the business details needed for analysis
fileParseChunkSize1000-1500 charactersThe segmented operational data paragraphs in duty-free financial reports are relatively long. This chunk length preserves field associations and avoids information fragmentation
systemPromptTemplateAnalyze the specified business modules of duty-free financial reports in combination with the given time range, and output structured contentClearly limit the analysis scenario and format to reduce interference from general retail data
maxResponseToken10000 charactersDuty-free financial report analysis involves multi-dimensional associations. This length can accommodate complete field breakdown and conclusion descriptions
quotaCheckThreshold70%Trigger quota alerts in advance to avoid insufficient_quota errors caused by upstream load saturation

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 specific analysis, and it is recommended to test on your own samples before finalizing.

Three Common Misconfigurations

  • Phenomenon: When the user only requests analysis of the currently submitted financial report segment in a multi-turn dialogue, the system still combines other business data from historical dialogues, leading to analysis deviation. Cause: The prompt fails to clearly limit the use of only the currently submitted context, or the trigger rules for maxContext are not set correctly.
  • Phenomenon: No corresponding parsing result is returned after uploading a voice file to the dialogue box. Cause: The preprocessing function for speech-to-text is not enabled, and the current system does not support direct parsing of voice files.
  • Phenomenon: The Markdown table content output by the model is truncated, with ...[hide 38432 char displayed at the end of the interface, accompanied by an upstream load error. Cause: The maxResponseToken parameter is set too low, and quotaCheckThreshold is not configured for early warning, resulting in output exceeding system limits and triggering a quota error.

How to Confirm Proper Configuration

  • Submit test financial report data that includes special fields such as off-island duty-free sales and per-customer average consumption, check whether the multi-turn dialogue context retains the previously specified business scenario, and confirm that the maxContext configuration meets analysis requirements.
  • Upload structured financial report documents, check whether the parsed text completely retains the association relationship of segmented data without content fragmentation, and confirm that the fileParseChunkSize setting is reasonable.
  • Trigger an analysis request that includes a Markdown table, check whether the output content is fully displayed without truncation prompts, and confirm that the maxResponseToken value meets analysis requirements.
  • Simulate a high-frequency request scenario, check whether the system triggers an alert before the quota usage reaches the preset proportion, and confirm that the quotaCheckThreshold setting is adapted to the business load.

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.