Data Profile for This Category
For the film and theater category within financial industry marketing content and customer acquisition workflows, data comes from four main sources: theater scheduling management systems, third-party ticketing platforms, promotional material libraries, and theater terminal playback logs.
Scheduling data updates on a fixed daily schedule. Promotional materials are updated irregularly during new film scheduling and release cycles. User behavior data is synchronized in real time.
Structured data fields include session ID, theater name, screening time slot, and single-session ticket price. Their units are none, Chinese name, hour-minute format, and yuan respectively. Unstructured promotional materials include poster resolution and trailer duration. Their units are pixels and minutes respectively.
The core aggregation unit for all documentation is individual films. Each film entry links to associated sessions, promotional materials, and user feedback data.
Constraints Imposed on Forms and Interactions
The data characteristics of this category impose the following constraints on forms and interactions:
- The fixed daily update schedule of scheduling data requires form interactions to support scheduled triggering of latest data pull logic. Static caching must be avoided to prevent information lag.
- The multi-format unstructured nature of promotional materials requires forms to support multiple types of file uploads and configured format validation rules.
- The real-time synchronization of user behavior data requires interaction links to set reasonable response timeout thresholds. This ensures real-time query result performance.
- The document structure centered on individual films requires forms to support multi-field linkage. Selecting a film automatically loads associated sessions, materials, and user feedback data.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Film and theater promotional materials (high-definition posters, trailers) typically do not exceed 500 MB per file. This meets upload requirements |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Text parsing and metadata extraction for high-definition trailers require extended processing time. This setting prevents premature interruptions |
Recall count | Top 8 entries | Associated scheduling and user comment data for film and theater marketing content is relatively concentrated. The top 8 entries cover core information |
Similarity threshold | 0.75–0.85 | Accurately matches the relevance between films and their associated scheduling and user feedback data. Filters low-relevance content |
CHAT_RESPONSE_TIMEOUT | 60 seconds | Real-time pulling of latest scheduling data requires certain network request time. This ensures users do not experience timeout during waiting |
UPLOAD_FILE_ALLOW_EXT | ["jpg", "png", "mp4", "mov"] | Covers commonly used promotional material formats for film and theater. Prevents invalid uploads |
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. Each scenario requires targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: After submitting a film query via a form, returned scheduling data fields are empty with no error prompt. Cause: No scheduled trigger rule for pulling latest scheduling data is configured. The form directly uses expired data from static caching.
- Symptom: The chat interaction interface prompts that no knowledge base is selected, but promotional materials and scheduling content can be normally retrieved in debug preview. Cause: Knowledge base binding configuration differs between deployment environment and debug environment. Or the association between knowledge base and application was not synchronized during deployment.
- Symptom: The AI model dropdown list is empty and cannot be selected when configuring a question classification node in a workflow. Cause: No corresponding AI model key configuration and enabling was completed in the backend. Or the current FastGPT version does not grant call permissions for the selected model.
How to Verify Successful Configuration
- Manually trigger a file upload. Verify that upload format and size meet configuration requirements. Confirm that metadata is parsed normally after a successful upload.
- Enter application debug mode. Select any film, then check that automatically loaded associated scheduling and material data is the latest version.
- Initiate a chat query. Verify that the knowledge base selection status displayed in the interface matches backend configuration, and relevant content can be normally retrieved.
- Start a workflow test. Confirm that the question classification node can normally load and select the target AI model, with no configuration errors.
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.