What the data for this category looks like
Data comes primarily from publicly disclosed annual and quarterly reports of listed companies, monthly industry operation reports from domestic plastics and rubber industry associations, and spot price data from commodity trading platforms. Update cadence falls into three categories: Annual reports are disclosed before April each year. Quarterly reports are updated within one month after the end of each quarter. Industry monthly data and spot prices are updated daily. Documents are based on a standardized financial report template, with additional category-specific fields for plastics and rubber. These fields include designed production capacity, current period output, raw material procurement costs, finished product inventory, and more. Their respective units are ten thousand tons per year, ten thousand tons, yuan per ton, and ten thousand tons.
What Constraints These Characteristics Impose on Workflow Orchestration
Differences in data formats across multiple sources require workflows to use differentiated parsing nodes. Listed company financial report PDFs contain nested tables, so table structured parsing parameters must be enabled. Industry association data uses Excel format, so header auto-matching rules must be configured. Spot price data uses JSON format, so a dedicated API node must be connected. Data sources with different update frequencies require matching trigger mechanisms. Financial report data uses scheduled triggers for quarterly or annual updates. Spot data uses real-time triggers. Extraction of category-specific fields requires custom mapping rules. This prevents generic parsing nodes from missing key indicators such as production capacity and output. Large annual report files require adjustment of segment length parameters. This avoids parsing truncation of critical business data.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_MAX_SIZE | 150–200 MB | Annual reports of plastics and rubber enterprises usually include multi-page industry operation details, and single file size can reach the upper limit of this range |
PARSE_TABLE_STRATEGY | Full extraction of nested tables | Financial reports contain nested table structures for production capacity and output, so all tiered cell data must be fully extracted |
WORKFLOW_TRIGGER_TYPE | Scheduled trigger + real-time API trigger | Quarterly or annually updated financial report data fits scheduled triggers. Real-time synchronized spot price data fits API triggers |
FIELD_MAPPING_RULES | Match category-specific fields including "designed production capacity" and "current period output" | Generic parsing nodes cannot automatically recognize business indicators specific to the plastics and rubber category, so manual field mapping configuration is required |
PARSE_SEGMENT_LENGTH | 800–1200 characters | Financial report paragraphs are long. Adjust segment length to maintain business logic integrity and avoid context loss or parsing truncation |
BATCH_TASK_CONCURRENCY | 2–4 | When processing monthly industry data in batches, control concurrency to avoid rate limiting from third-party interfaces |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: An error
Load file erroris prompted after uploading a financial report file, while knowledge base upload functions normally. Cause: Dedicated parameters for the file parsing node are not configured in the workflow. Generic parsing rules cannot recognize the nested table structure of plastics and rubber financial reports, leading to parsing failure. - Phenomenon: After uploading a file in a local deployment version, the file parsing node has no task execution records. Cause: The local node execution permission for the workflow is not enabled, or the concurrency count is configured too high and exceeds local resource limits.
- Phenomenon: The code running node returns no results after execution, and Python code cannot run. Cause: Python code execution permission is not enabled in the workflow configuration, or dependency package installation steps are not configured.
How to Verify Successful Configuration
- Upload a single standard-sized annual report of a plastics and rubber enterprise, and check if the parsing node returns complete table data.
- Configure a scheduled trigger task, and verify if the workflow for the corresponding cycle starts automatically at the set time.
- Test the real-time API trigger, and confirm if spot price data can be synchronized into the workflow.
- View workflow logs, and confirm if the custom field mapping rules successfully extract preset dedicated business indicators.
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.