What the Data for This Category Looks Like
Duty-free research report data primarily comes from industry deep reports from securities research institutions, quarterly operation announcements publicly released by duty-free operators, and official interpretation documents of offshore duty-free policies. Update cadences fall into two categories: policy-related interpretations are updated in real time as policies are released, industry operation data is updated synchronously on a quarterly basis, and temporary reports are added during major promotional periods. Document structures typically include fields such as policy key point breakdowns, core metrics of passenger flow and sales revenue, sales proportion analysis of various duty-free product categories, and regional market performance analysis. Metric units include ten thousand person-times and ten thousand yuan.
Constraints Imposed on Workflow Orchestration
The multi-source data origins of duty-free research reports require workflows to support integration with securities firm APIs, announcement crawling interfaces, and policy document repositories. Multi-source data parallel pull nodes must be configured. Different update cadences require workflows to distinguish between real-time triggers and scheduled scheduling: policy interpretation data must be pulled when external events occur, and operation data must be triggered for synchronization on a quarterly basis. Specific metric fields in documents require workflows to be configured with precise recall rules, only extracting specified fields such as policy key points and core operation data to avoid redundant content entering the context. Individual research reports have long lengths, so segment splitting and merging rules must be configured to ensure the context length complies with model input limits.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall field filtering | Only retain the fields "policy key points", "core metrics", and "regional analysis" | Duty-free research reports contain significant redundant content; extracting only specified fields reduces context length |
maxContext | 8000–12000 characters | Individual duty-free research reports have long lengths, requiring alignment with model input limits |
scheduled scheduling cycle | Quarterly trigger + event trigger | Operation data is updated quarterly, and policy-related data is triggered by external events |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Long document parsing requires sufficient time allocation |
knowledge base recall count | Top 3 entries | Individual duty-free research reports contain detailed content; excessive recall will exceed context limits |
HTTP request timeout | 60 seconds | Integration with securities firm APIs or announcement interfaces requires adaptation to interface response durations |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfiguration Issues
- Issue: The AI chat node in the workflow directly outputs raw generated content without passing through a text concatenation component. Cause: The
hide raw outputparameter is not configured, causing intermediate generated content to be exposed directly in the conversation chain. - Issue: After knowledge base retrieval results are passed to an HTTP request, the AI cannot correctly associate and reference the retrieved content. Cause: Retrieval data is not passed in the
{"title":"xxx","content":"xxx","url":"xxx"}format, causing reference matching failures. - Issue: The question optimization function of the knowledge base node and the standalone question optimization node are used interchangeably. Cause: The former is only intended for format optimization of knowledge base recall content, while the latter can independently handle text optimization of user input.
How to Verify Proper Configuration
- Review workflow execution logs to confirm that multi-source data nodes only pull files from the specified configured sources.
- Trigger a single test execution to check whether the output content of the text concatenation component complies with the preset field filtering rules.
- Call the workflow test interface to verify whether the returned results include the current workflow's metadata identifier.
- Compare the retrieved fragments from the knowledge base with the original research report text to confirm that only the specified configured fields are extracted.
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.