What the Data for This Category Looks Like
Film and theater industry research report data primarily comes from theater operation systems, public reports from box office statistics agencies, film project filing and publicity platforms, and monthly reports from industry associations. Update rhythms vary significantly: real-time box office data updates daily, theater operation monthly reports are released monthly, and filing information is updated irregularly based on approval progress.
Document structure falls into two categories: standardized reports and analytical reports. Standardized reports include fields such as theater code, screening sessions, seated patrons, per-hall box office, with units of sessions, patrons, and ten thousand yuan respectively. Analytical reports contain unstructured content such as revenue sharing terms and scheduling planning.
What Constraints Do These Characteristics Impose on Workflow Orchestration?
The varied update rhythms of film and theater research reports require differentiated trigger rules in workflow configurations. This separates tasks for real-time box office pulling and batch processing of monthly operation reports. Differences in multiple fields and units require field mapping and unit validation rules in data parsing nodes. This prevents errors in subsequent calculations. The high proportion of unstructured scheduling and revenue sharing content requires adjusting document segment lengths, to adapt to semantic recall for professional terminology. Differences in multi-source data formats require configuring adapters before the workflow. This unifies data structures pulled from different channels and ensures consistent input for subsequent steps. The high professional density of research report content requires adjusting thresholds and return counts in the recall phase. This avoids introducing irrelevant information or missing critical business content.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Scheduled Trigger CRON | Use */10 * * * * for real-time pulling, and 0 0 1 * * for batch monthly reports | Matches the rhythm of box office data updating every 10 minutes and theater monthly reports being released on the 1st of each month |
Document Segment Length | 800–1200 characters | Adapts to the long, professional sentence structure of film and theater research reports, avoiding splitting professional terms or losing semantic connections |
Recall Similarity Threshold | 0.75–0.85 | Filters low-relevance research report content, balancing recall coverage and precision |
Code Node Timeout | 600 seconds | Covers the maximum time required for theater data pulling and multi-source data merging, preventing task interruptions |
Code Node Storage Type | Global variable storage | Workflows run in a backend environment, which does not support browser-side localStorage, avoiding call errors |
Rerank Return Count | Top 5–7 entries | Streamlines the final output research report information, avoiding redundant generated content |
Three Common Mistakes
- Symptom: Calling
localStorage.getItemin a code node returns the errorlocalStorage is not defined. Cause: Workflows run in a backend execution environment, which has no browser-sidelocalStorageobject. Direct calls to front-end storage interfaces are not supported. - Symptom: After calling the workflow via API, the returned results do not include the AI thinking process field. Cause: The thinking process recording switch is not configured in the AI node of the workflow, or the API request does not carry the
returnThoughts: trueparameter. - Symptom: In the open-source version
V4.8.22, AI nodes outside the workflow cannot be configured with custom reference templates. Cause: The global AI configuration for this version only allows adjustment of basic parameters. The custom template function is only available within workflow nodes.
How to Confirm the Configuration Is Complete
- Manually trigger the workflow once. Check the data pulling and parsing links in the logs. Confirm that all preset film and theater research report fields have been correctly extracted.
- Call the test API to initiate a workflow request. Verify that the recall content in the returned results matches business requirements. Adjust relevant parameters until expectations are met.
- Check the execution logs of the code node. Confirm that there are no storage-related errors, and that global variables can be read and written normally.
- View the execution records of the scheduled task. Confirm that the trigger cycle matches the preset
CRONexpression, and that the task completes on time without abnormal interruptions.
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 targeted analysis. It is recommended to test on your own samples before finalizing settings.
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.