Deployment and Upgrade for Tourism Attraction Intelligent Due Diligence Reports

Data sources for tourism attraction intelligent due diligence reports include ticket, passenger flow, and revenue reports from internal attraction

Data characteristics for this use case

Data sources for tourism attraction intelligent due diligence reports include ticket, passenger flow, and revenue reports from internal attraction operation systems, qualification filing documents from cultural and tourism regulatory authorities, and public tourist reviews and sentiment data. Update frequencies vary widely: ticket and real-time passenger flow data updates at minute-level intervals. Daily revenue reports update once per day. Qualification filing documents only update when qualification information changes. Document structures include structured CSV operation reports, PDF qualification scans, and unstructured sentiment text. Fields include daily reception volume (unit: person-times), daily revenue (unit: CNY), qualification validity period (unit: days), sentiment keyword mention count (unit: entries), and others.

Constraints during deployment and upgrade

Real-time ticket and passenger flow data requires low-latency data source synchronization links during deployment. Long synchronization intervals cause report data lag, so avoid these. Multi-type mixed document parsing needs require compatible parsing plugins for PDF, images, CSV, and other file formats during upgrades. Attraction data sources include internal operation data and public sentiment data. Configure layered authentication rules to distinguish access permissions for internal and public data. Incremental synchronization requirements demand enabling incremental pull logic during deployment. Full synchronization uses excessive server resources, so avoid this. Differences in units across fields require configuring automatic conversion rules. This ensures consistent data units in final reports.

Configuration recommendations

Configuration ItemRecommended ValueRationale
PARSE_FILE_MAX_SIZE500 MBThe single file size of attraction qualification scans and passenger flow reports usually does not exceed 500 MB
SYNC_DATA_INTERVAL15 minutesReal-time passenger flow data for attractions updates hourly. A 15-minute synchronization interval meets real-time requirements
MAX_RECALL_NUMTop 8 entriesAttraction due diligence reports cover multiple dimensions including passenger flow, revenue, sentiment, and qualifications. 8 recalled entries balance comprehensiveness and efficiency
WORKFLOW_TEXT_SPLIT_LENGTH1000–1200 charactersThe average length of single paragraphs in attraction operation documents is about 1000 characters. This split length ensures context coherence
UPLOAD_FILE_ALLOWED_TYPES["pdf", "jpg", "png", "csv"]Attraction due diligence data includes multiple file types such as qualification scans, passenger flow reports, and sentiment screenshots
API_RESPONSE_TIMEOUT600 secondsThe processing time for aggregating multiple data sources to generate due diligence reports usually does not exceed 600 seconds

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material formats, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.

Three common configuration mistakes

  • Symptom: Variable fields are empty in text concatenation results during API calls. Functionality works normally during debugging. Cause: The API_VARIABLE_PARSE_MODE parameter was not configured correctly during deployment. This disables variable parsing logic in the production environment.
  • Symptom: Docker container stays in loading state after startup, with no valid log output. Cause: Insufficient CPU and memory resources allocated during local deployment, or incorrect permission settings for mounted data source directories.
  • Symptom: HTTP synchronization request returns 405 status code, unable to pull attraction ticket data. Cause: TRACE request support on the remote WWW service was not disabled. This causes protocol detection to block legitimate synchronization requests.

How to verify correct configuration

  • Perform a full data source synchronization. Verify that the number of updates shown in the synchronization log matches the actual number of updates from attraction data.
  • Call the test API, pass test variables and text concatenation instructions. Verify that variable fields in the returned results are correctly replaced.
  • After starting the Docker container, check container logs for no permission errors or resource shortage alerts. Confirm the service started normally.
  • Send an HTTP request. Verify that the returned status code is 200, and the response content includes expected due diligence report fields.

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.