What the Data for This Category Looks Like
Power industry financial report data mainly comes from public annual and quarterly reports of listed power enterprises, as well as monthly industry operational reports released by local energy regulatory agencies. Data updates follow annual and quarterly core cycles, with monthly operational data updated synchronously. Document structures include three modules: core financial indicators, power production and operation data, and grid connection and consumption status. Fields include installed capacity (unit: ten thousand kilowatts), power generation utilization hours (unit: hours), average electricity sales price (unit: yuan/megawatt-hour), and fuel procurement cost (unit: yuan/ton). Some data require linking with settlement details from power trading platforms.
What Constraints These Characteristics Impose on Deployment and Upgrade
The multi-source and multi-format nature of power financial reports requires support for parsing PDF, Word, CSV and other document types. Single annual financial report documents have large length, which increases parsing time, so adjust timeout and chunk processing parameters. High-frequency update requirements for monthly operational data require configuration of trigger interval parameters for scheduled synchronization tasks. Different power segments (thermal power, wind power, photovoltaic) have different report fields, so preset custom field mapping rules. Power data involves industry regulatory requirements, so configure data desensitization trigger rules during deployment to avoid sensitive information leakage.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Power financial report documents have large length, default timeout settings cannot complete full parsing |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Single annual financial report includes multiple pages of operational attachments, requires support for large file uploads |
maxContext | 8000–12000 characters | Financial reports include multiple types of field data, sufficient context must be retained for accurate extraction |
RECALL_TOP_N | Top 10 entries | Multiple historical financial reports and industry data need to be recalled to support cross-verification analysis |
SYNC_TASK_CRON | 0 0 2 * * * | Trigger synchronization daily at 2 AM, adapts to the update rhythm of monthly operational data |
FIELD_MAPPING_RULES | Calibrated based on actual testing | Different power companies have different field naming conventions for financial reports, custom mapping rules must be configured |
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. Specific issues require case-by-case analysis, and it is recommended to test on in-house samples before finalizing.
Three Common Misconfigurations
- Phenomenon: After local deployment, running the financial report analysis workflow has slow response, and interface loading times out. Cause: Memory and CPU allocation parameters are not adjusted according to the large file parsing requirements of power financial reports. Default configurations are insufficient to support parallel processing of multiple financial reports.
- Phenomenon: After modifying the Docker configuration file, port 3005 cannot call the model normally, while port 3000 service operates normally. Cause: The corresponding relationship between container-mapped ports and internal service ports is not updated synchronously, or the model access parameters in the configuration file are not correctly associated with port 3005.
- Phenomenon: When calling the workflow, the returned financial report fields are empty, or the extraction results do not meet expectations. Cause: Custom field mapping rules are not configured, and the general parsing template is directly used to match field names unique to the power industry, resulting in failure to correctly identify specific indicators such as installed capacity and utilization hours.
How to Confirm Proper Configuration
- Upload a locally stored public financial report document of a power company, check whether the parsing task status shows completed, and there are no timeout-related errors.
- Manually trigger a configured scheduled synchronization task, check whether the synchronized dataset includes industry operational data for the corresponding cycle.
- Configure a test workflow to extract indicator fields unique to the power industry, verify whether the returned results match the actual content in the document.
- Call the API interface of the corresponding port, test the model call and workflow execution process, confirm there are no connection errors or parameter abnormalities.
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.