What the data for this category looks like
The marketing content data for industrial parks mainly comes from the park investment promotion management system, settled enterprise ledger, weekly operation reports, surrounding supporting facility survey data, and product information from cooperative financial institutions. Data update rhythm is synchronized in real time with investment promotion nodes and enterprise financial demand changes. Daily operation and financial product policy data are updated weekly.
The document structure includes structured ledger tables, semi-structured investment promotion brochures, settlement agreements, and financial product introduction documents. Core fields include park unique identifier, settled enterprise industry classification, rental area, settlement time, supporting facility type, and enterprise financial demand type. Units include square meters, units, pieces, ten thousand yuan, and other standard units.
What constraints these characteristics impose on workflow orchestration
Industrial park data has a high proportion of structured content, but fields are dynamically adjusted with investment promotion and financial needs. Workflows must support dynamic field mapping and flexible data source binding rules, to avoid configuration failures caused by new settled industries, rental area tiers, or enterprise financial demand types.
The update rhythm of different data types varies greatly. Weekly updated operation weekly reports and financial product policies, as well as real-time changes in investment promotion and enterprise financial demands, need to be adapted to mixed workflow nodes with scheduled triggers and real-time triggers respectively. This ensures data timeliness.
Marketing content must be generated directionally based on fields such as settled enterprise industry, rental area, and financial demand. Workflows must include built-in field filtering, financial product matching, and formatting nodes, to ensure output content matches the needs of target customer groups.
Semi-structured settlement agreements, investment promotion brochures, and financial product introduction documents must be processed in split paragraphs. Segment length parameters must be configured to adapt to long text parsing, to avoid content generation deviations caused by overly long single paragraphs.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Industrial park investment promotion brochures, settlement agreements, and financial product introduction documents are mostly long texts; 300 seconds covers the complete parsing process |
workflow_trigger_mode | Hybrid trigger (scheduled + real-time) | Industrial park data includes weekly updated operation weekly reports, financial product policies, real-time investment promotion changes, and enterprise financial demands; hybrid trigger adapts to both types of data update rhythms |
field_filter_condition | Filter by settled enterprise industry classification, rental area, and financial demand type | Marketing content needs to directionally match target investment promotion customer groups and financial demands; core business fields must be used to filter data sources |
segment_length | 800–1200 characters | Semi-structured documents for industrial parks have relatively long lengths; this segment length balances parsing efficiency and context completeness |
external_api_timeout | 60 seconds | Interfaces for surrounding supporting facility data and cooperative financial institution products need to be called; 60 seconds covers normal response durations for most third-party interfaces |
workflow_parallel_node_limit | 3 nodes | Industrial park workflows include three core parallel links: data pulling, field processing, and content generation; 3 nodes avoids resource congestion |
financial_product_match_threshold | 0.75–0.85 | Financial product matching combines enterprise demands and product qualifications; this threshold balances matching accuracy and recall volume |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Symptom: After saving workflow node configurations, both the workflow configuration and bound knowledge base become blank after service restart, while interface calls return normal. Cause: The
workflow_config_persistenceparameter is not configured, resulting in non-persistent storage of configurations. - Symptom: Knowledge base search nodes cannot correctly reference the park ID variable, and generated marketing content matches incorrect park data or financial products. Cause: Variable scope is not configured correctly, and park ID or enterprise financial demand is not passed as a workflow global variable.
- Symptom: The workflow can only complete one round of queries, and cannot perform multi-round questioning to refine investment promotion customer groups or enterprise financial demands. Cause: The
workflow_multi_round_switchparameter is not enabled, and context retention nodes for multi-round conversations are not configured.
How to confirm configurations are set correctly
- Manually trigger the workflow once, check if the generated marketing content includes the core business fields of the current park and matching financial product information.
- View workflow execution logs, confirm that links such as data pulling, field processing, and content generation have all executed normally, with no timeout or error messages.
- After restarting the service, check if the workflow configuration and bound knowledge base still retain the original settings.
- Adjust the park ID or enterprise financial demand variable value, trigger the workflow, and verify if the generated content matches the new parameter configuration.
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.