What the Data for This Category Looks Like
Defense electronics marketing content data within the financial industry is primarily sourced from model development archives, supply chain supporting ledgers, public bidding announcements, and customer technical meeting minutes. Data update frequency fluctuates with project milestones. Parameter documents for finalized products have long update cycles. Bidding information is updated monthly. Research and development iteration documents are updated irregularly alongside technical breakthroughs. Each document typically includes three structural components: a structured parameter table, long-form technical descriptions, and accompanying drawing attachments. Core fields include equipment model, operating frequency band, rated power, delivery lead time, and applicable scenarios. Some classified documents require desensitization processing. Units mostly follow internationally recognized defense industry standard units, such as MHz, kW, and hours.
Constraints on Tool Calling and Plugins
The data characteristics of defense electronics marketing content create multiple constraints for the tool calling and plugins workflow. The mixed document structure of structured parameters and non-text attachments requires plugins to support both text field parsing and format recognition for unstructured attachments such as engineering drawings. The presence of classified fields requires a pre-processing desensitization verification step for tool calls, filtering sensitive information before subsequent processing. Fluctuating update frequencies for data sources require plugins to support a combined strategy of on-demand synchronization and scheduled caching, adapting to the low-frequency updates of finalized documents and the high-frequency updates of bidding information. Fields using specific standard units require plugins to include built-in defense industry unit validation rules to avoid parameter conversion errors.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Defense electronics documents often include long-form technical descriptions and large-volume drawing attachments, requiring longer parsing durations |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Meets the upload requirements for marketing documents with high-definition engineering drawings |
plugin_sensitive_check_enabled | Enabled | Defense electronics documents contain classified fields, requiring pre-processing sensitive information filtering |
max_context_length | 8000–12000 characters | Adapts to the splitting and context passing requirements of long-form technical descriptions |
tool_call_max_retry | 3 retries | Prevents single call failures caused by desensitization verification or network fluctuations |
dataset_chunk_size | 1000–1500 characters | Adapts to the splitting logic of mixed structured parameters and long-form text in defense electronics documents |
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 individual analysis, and testing against local samples is recommended before finalizing settings.
Three Common Mistakes
- Scenario: Using JavaScript code to run a plugin for JSON element extraction in the
saas4.9version returns a null value. Cause: Matching logic was not developed for deeply nested JSON structures in defense electronics documents, so target elements cannot be correctly identified. - Scenario: The basic chart plugin outputs
noneafter inputting correct parameters. Cause: Sensitive information filtering was not enabled. Classified parameters in defense electronics documents are automatically blocked, leading to missing core data required for chart generation. - Scenario: Garbled text appears after uploading a CSV-format defense electronics marketing ledger. Cause: The encoding format of the CSV file was not specified. Chinese technical terms and special symbols in defense electronics documents cause encoding parsing errors.
How to Confirm Proper Configuration
- Upload a single typical defense electronics marketing document, verify the completeness and format correctness of parsed fields, and confirm that the parsing configuration adapts to the mixed structured and unstructured document structure.
- Run a JSON extraction test case for the code execution plugin, verify that the returned result includes preset target elements, and confirm that the extraction logic adapts to the document field rules.
- Upload a test document marked with classified content, trigger a plugin call, verify that sensitive information is not leaked, and confirm that the sensitive verification configuration is active.
- Run the test process for the basic chart plugin, verify that the output result is not empty, and confirm that core parameters are not blocked by the sensitive filtering mechanism.
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.