What Data for This Category Looks Like
Refinery industry financial report data primarily comes from periodic reports disclosed by domestic and overseas stock exchanges, monthly operational monitoring data from industry associations, and production and operation announcements voluntarily published by enterprises. Data update cycles are divided into three categories: annual reports, quarterly reports, and monthly operational data. Document structures typically include core fields such as crude oil processing volume, refined oil yield, unit production cost, plant operating rate, and revenue composition. Some segmented sectors such as aromatics and olefins include dedicated process parameter fields. Units mostly adopt industrial measurement standards such as ten thousand tons, yuan per ton, and hundred million yuan.
Constraints Imposed on Tool Calling and Plugins
The multi-source and dispersed nature of refinery financial report data requires tool calling to integrate interfaces for exchange disclosures, industry association monitoring, and enterprise public announcement parsing plugins, and configure multi-source data aggregation logic. Data sources with different update cycles must be bound to corresponding trigger rules: monthly operational data should be set for scheduled monthly calls, and annual reports should trigger full data synchronization. The large content volume from lengthy document structures requires setting segmented parsing thresholds for tool calling to avoid exceeding request length limits. The presence of dedicated process fields requires plugins to support custom field mapping rules to adapt to the unique parameter naming and unit systems of refinery sectors.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300-600 seconds | Refinery financial report PDFs include multi-page plant details and detailed data, requiring sufficient parsing time |
UPLOAD_FILE_MAX_SIZE | 100-200 MB | Large refinery annual report PDFs typically have large file sizes, requiring adaptation for large file uploads |
maxContext | 8000-12000 characters | When splitting financial report segments for tool calling, sufficient process and financial context must be retained |
Recall Count | Top 6-8 entries | Core fields of refinery financial reports are concentrated in revenue, processing volume, cost and other sections; excessive recall will introduce redundant data |
Similarity Threshold | 0.75-0.85 | Misalignments between general industry terms and refinery-specific terms must be filtered out to retain highly relevant financial report segments |
PLUGIN_TRIGGER_INTERVAL | 1800-3600 seconds | The frequency of calls for pulling monthly operational data must be controlled to avoid triggering third-party interface rate limits |
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 on-site analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Parsed markdown documents contain large amounts of garbled text or lost industrial charts, caused by failing to configure dedicated parsing plugin rules for the professional typesetting and chart formats in refinery financial reports.
- Tool calling returns an error stating "insufficient knowledge base recall count", caused by failing to adjust the
Recall Countconfiguration based on the field density of refinery financial reports, leading to core business data not being fully recalled. - Calls to locally deployed large model plugins return connection timeout errors, caused by failing to fill in the correct local model interface address and port number in plugin configurations, or failing to enable corresponding network access permissions.
How to Confirm Proper Configuration
- Upload a local refinery financial report PDF, check if the parsed markdown format retains core process fields and data tables, to confirm that file parsing and upload configurations are effective.
- Initiate a tool calling request, verify that the number of returned financial report segments matches the
Recall Countconfiguration, to confirm that the recall rule matches business requirements. - Test calling a locally deployed large model plugin, check that the interface address and port configurations are correct, to confirm there are no connection errors.
- Trigger a plugin pull task for monthly operational data, check that the data update time matches the interval set in the
PLUGIN_TRIGGER_INTERVALconfiguration.
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.