What the Data for This Category Looks Like
Ordnance equipment financial report data comes primarily from official disclosures of military industry groups, publicly available information from the National Defense Science, Technology and Industry Administration, and regular exchange announcements. Updates follow quarterly and annual core cycles, with simultaneous release of temporary announcements related to equipment induction and capacity adjustments. A single financial report document includes modules such as order contract details, R&D investment ratio, and core component capacity data. Unique fields include annual order contract amount, induction delivery quantity, and localization supporting rate, with units mostly being 100 million yuan, units/sets, and percentage.
Constraints Imposed on Workflow Orchestration by These Characteristics
The multi-source and dispersed nature of ordnance equipment financial reports requires workflow configuration to pull data from different channels across multiple parallel nodes, to avoid missing temporary announcements when pulling data from a single node. The mixed update rhythm of quarterly and temporary announcements requires the workflow to support both scheduled periodic triggers and event trigger modes, to adapt to different information update scenarios. Unique fields and military-specific terminology require configuring a knowledge base custom field mapping node in the workflow, to ensure the large language model recognizes exclusive data such as order contract amount and localization rate. The relatively long length of single documents requires adjusting document segmentation and recall parameters, to avoid analysis gaps caused by content truncation.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Ordnance equipment financial reports include multi-module detailed content, and standard timeout durations cannot complete full parsing |
recall_top_k | 8-12 entries | Financial report analysis requires recalling multiple types of data such as proprietary terminology and order details, so the number of recalled entries needs to be increased |
global_variable_scope | Workflow global | Core indicators such as order contract amount need to be reused across multiple analysis nodes, to avoid repeated pulling |
llm_temperature | 0.1-0.3 | Financial report analysis requires rigorous output, and low temperature reduces the probability of generating fabricated data |
kb_file_filter | Specify dedicated ordnance equipment financial report directory | Differentiate military industry category knowledge base content from other industry content, to avoid interference from irrelevant data |
trigger_mode | Dual scheduled and event triggers | Adapt to different update rhythms of quarterly regular financial reports and temporary equipment induction announcements |
The parameter values provided on this page are general recommendations for establishing configuration starting points. 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 Errors
- Phenomenon: When the downstream workflow node calls a global variable, an error prompt indicating empty input is returned. Cause: The global variable scope is not configured as workflow global, and is only limited to the current node's private scope, resulting in inability to read variable values across nodes.
- Phenomenon: When selecting a variable-referencing large language model for the AI conversation node, no temperature setting entry can be found. Cause: The
llm_temperatureparameter is not explicitly set in the node configuration, and the default unadjusted temperature base mode is used. - Phenomenon: The knowledge base search node recalls financial report data from non-ordnance equipment categories. Cause: The
kb_file_filteris not configured to specify a dedicated file directory, and the default full knowledge base content is recalled, mixing in irrelevant industry data.
How to Verify Successful Configuration
- Manually trigger the workflow to pull a single ordnance equipment financial report, and check whether the parsing node output includes all core fields with no content truncation.
- View the global variable configuration panel, confirm that the scope has been switched to workflow global, and verify that no errors occur when calling variables across nodes.
- Run the knowledge base search node, check that the file sources of the recalled results are from the specified ordnance equipment financial report directory, with no irrelevant category data.
- Adjust the
llm_temperatureparameter, compare the rigor differences between the two AI outputs, and confirm that the configuration takes effect.
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.