What the Data for This Category Looks Like
Ordnance and equipment financial report data draws primarily from periodic reports of subordinate listed companies, public industry data released by the National Defense Science, Technology and Industry Administration, and information disclosed by industry associations. Updates follow fixed annual and semi-annual report cycles. Teams release temporary announcements irregularly alongside project progress. Document structures include modules such as revenue composition (split by civilian-military products and equipment model segments), R&D investment, order data, assets and liabilities. Unique fields include civilian-military product revenue proportion, equipment equipping progress, production capacity planning, and more. Accepted units include ten thousand yuan, hundred million yuan, units/sets, and others. Some disclosed items use different units across documents.
Constraints on Tool Calling and Plugins from These Characteristics
Tool calling must integrate multiple data sources including exchange announcement parsing and industry data interfaces to handle decentralized data sources. Plugins must support real-time pulling and parsing to address the sudden release of temporary announcements. Tools must accurately extract field content from specified segments such as civilian-military products and equipment models to match complex document structures. Tools must include structured field recognition and unit conversion capabilities to handle unique fields and cross-document unit differences, avoiding numerical deviations in extraction results.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Ordnance and equipment financial report PDFs typically have a high number of pages, including complex sections such as civilian-military product breakdowns and R&D investment, so parsing time exceeds that of general documents |
UPLOAD_FILE_MAX_SIZE | 300 MB | A single annual financial report PDF for ordnance and equipment typically does not exceed 250 MB. A reasonable buffer is reserved to support batch uploads |
maxContext | 12,000 characters | Core paragraphs of financial reports (such as revenue composition) have strong contextual relevance. Sufficient long context must be retained to accurately extract segment data |
Recall Count | Top 8 entries | Key disclosure items in ordnance and equipment financial reports (such as civilian-military product revenue and order data) are scattered across different sections. A sufficient number of retrieved segments must be included to cover target information |
Similarity Threshold | 0.75–0.85 | Low-relevance irrelevant financial report paragraphs must be filtered out, while relevant content from segmented topics must be retained |
Reranked Return Count | Top 5 entries | After reranking retrieved segments, only the most relevant core segments are retained for tool calling to avoid interference from redundant data |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume and business rules. Analyze specific cases individually, and test on your own samples before finalizing settings.
Three Common Misconfigurations
- The text extraction tool call returns a
400 Invalid JSON payload received. Unknown nameerror. This occurs because the request body is not constructed according to the field specifications of ordnance and equipment financial reports, and non-standard disclosure fields are passed additionally. - When calling a configured workflow via API, preset context information cannot be obtained. This occurs because the session association identifier is not correctly passed in the request parameters, so the workflow cannot load the previously uploaded financial report context from historical interactions.
- When calling a tool to process financial report classification, the results do not match the preset rules for problem classification. This occurs because the
modelparameter is not configured with a dedicated model adapted for financial report structured parsing, and a general question-answering model is used for the classification task.
How to Verify Correct Configuration
- Upload an annual financial report PDF for ordnance and equipment, check if the file parsing status shows "Completed" with no parsing failure prompts.
- Initiate a text extraction tool call, verify that the returned results include unique field data for ordnance and equipment financial reports such as civilian-military product revenue and R&D investment.
- Call the API to send a request that includes a session ID, check if the workflow can correctly associate and use the previously uploaded financial report data.
- View the tool calling logs, confirm that the
modelparameter matches the current task type, and there are no parameter format errors.
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.