What the data for this category looks like
Duty-free research report data primarily comes from public industry association documents, regular reports of listed duty-free enterprises, and compliant industry information channels. Updates follow a fixed quarterly cycle, with temporary additions when offshore duty-free policy adjustments or major holiday passenger flow changes occur. Document structures include fields such as policy details, regional passenger flow data, category revenue proportions, supply chain dynamics, and more. Passenger flow statistics use ten thousand person-times as the unit, while revenue statistics use ten thousand yuan. Some research reports include coordinate data for regional store layouts.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
The fixed-cycle and temporary update nature of duty-free research reports requires multi-turn dialogue to support real-time recall of the latest policy and revenue data, to avoid citing outdated content. Fields include passenger flow and revenue data with units, plus regional coordinates. Prompts must clearly specify statistical dimensions and units to prevent confusing numerical outputs. Some research reports include regional store layout information, so multi-turn dialogue must support location-related follow-up questions to match users' regional query needs. Temporary updated content may have data differences from prior reports, so version verification logic must be added to the conversation context chain to ensure consistent data versions of cited research reports across the dialogue.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single duty-free research report content is lengthy. Multi-turn dialogue needs to retain context for multiple follow-up questions to avoid truncating key policy or revenue data |
recall_top_k | Top 10–15 entries | Core data of duty-free research reports is scattered across multiple sections such as policies, revenue, and regional layouts. Sufficient fragments must be recalled to cover potential needs of multi-turn follow-up questions |
similarity_threshold | 0.72–0.80 | Terminology and policy expressions in the duty-free industry have high similarity. A threshold that is too low will introduce irrelevant fragments, while a threshold that is too high may miss relevant research report content |
chunk_size | 800–1200 characters | Duty-free research reports include multi-field paragraphs. This segment length adapts to field splitting, avoiding information loss caused by cross-field truncation |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large single duty-free research reports takes a long time. Timeouts will cause parsing failures, making the report unavailable for retrieval |
workflow_concurrency_limit | 1–2 requests per second | High concurrent calls will trigger resource overload, leading to empty return values. Limiting concurrency prevents such issues |
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. Specific issues require targeted analysis. It is recommended to test on relevant samples before finalizing settings.
Three common errors
- Phenomenon: After upgrading to FastGPT 4.9.13, dialogue return results display symbols tracing retrieval rules at the end. Cause: The system enables the updated retrieval trace prompt configuration by default, and this switch has not been manually disabled.
- Phenomenon: When concurrent call volume reaches 2–3 requests per second, the MCP workflow returns empty values. Cause: The workflow concurrency limit is not configured, and resource overload causes requests to fail normal processing.
- Phenomenon: Revenue or passenger flow data with units cannot be correctly extracted during multi-turn dialogue. Cause: The prompt does not clearly specify field units and statistical dimensions, leading the large model to confuse numerical values from different research reports.
How to confirm correct configuration
- Initiate multi-round follow-up questions covering regional passenger flow and revenue data, verify that returned content includes the latest policy update information, and confirm full context retention.
- Adjust concurrent call volume, observe MCP workflow return results, and set an available upper limit matching current resources after confirming no empty values.
- Review parsed research report fragments, confirm segments are not truncated across fields, and that field units and statistical dimensions are correctly identified.
- Check system prompt configuration, confirm that field rules and unit requirements for duty-free research reports are clearly specified, to avoid confusing large model outputs.
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.