What the Data for This Category Looks Like
Ordnance equipment yield rate data primarily comes from public information platforms of the national defense and military industry, operational data officially disclosed by military industry groups, and supporting market reports released by industry associations. Core supporting business yield rate data is updated monthly, while overall revenue indicators related to equipment fielding are updated quarterly. Each data entry includes equipment model identifier, statistical cycle range, associated production entities, input accounting fields, output accounting fields, and corresponding revenue accounting fields. Input and output fields use ten thousand yuan as the unit, and revenue accounting fields use ten thousand yuan per unit capacity as the unit.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
Data is updated on monthly and quarterly cycles. In multi-turn dialogue, the statistical cycle must be clearly specified, otherwise the model cannot match the latest or targeted range of yield rate data. Each single data entry contains multiple associated fields, including equipment model, production entity, etc. Prompts need to preset screening rules to guide users to gradually clarify specific screening conditions, avoiding confusing information across categories or entities. The unit of revenue accounting fields is different from the percentage-based yield rates of other financial categories. Prompts must clearly mark the unit rules to ensure consistent understanding of revenue indicators during dialogue. Public data disclosures are batch-based. In multi-turn dialogue, the user’s required equipment fielding batch or supporting link must be confirmed to narrow down the data scope.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Ordnance equipment yield rate data contains multi-dimensional fields. Multi-turn dialogue needs to retain complete screening conditions and historical interaction information to avoid content truncation caused by context overflow |
systemPrompt | Preset fixed screening rules: Only return yield rate data for ordnance equipment supporting business. Results may only be output after clearly specifying the statistical cycle, equipment model, and production entity. The revenue indicator unit is ten thousand yuan per unit capacity | Data for this category must strictly match specified dimensions. Preset rules can reduce invalid interactions and unify the format and scope of dialogue outputs |
chatHistoryMaxTokens | 2000–4000 characters | In multi-turn dialogue, users only need to supplement gradually clarified screening conditions. Retaining the first two rounds of interaction information meets context requirements and avoids excessive token quota usage |
temperature | 0.1–0.3 | Ordnance equipment yield rate data comes from publicly disclosed information. Output accuracy must be maintained, and content deviating from facts should not be generated |
fileUploadEnabled | Enabled | Supports users to upload local military industry report fragments as supplementary data sources, adapting to personalized data needs in multi-turn dialogue |
toolChoice | auto | Allows the model to independently determine whether to call a data retrieval tool to obtain the latest ordnance equipment yield rate data, adapting to dynamically changing dialogue needs |
The parameter values provided on this page are conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Phenomenon: After calling the dialogue interface to upload a local military industry report, the model fails to extract the ordnance equipment yield rate related content. Cause: The
fileUploadEnabledparameter is not set to enabled, or the system prompt does not explicitly require the model to parse specified fields from uploaded files. - Phenomenon: In multi-turn dialogue, the model cannot reuse the equipment model or statistical cycle conditions specified by the user previously. Cause: The
chatHistoryMaxTokensparameter value is too small, causing the screening conditions from historical interactions to be truncated and unreadable by the model. - Phenomenon: When orchestrating multiple large model dialogue workflows, ordnance equipment yield rate data from different sessions becomes cross-contaminated. Cause: Independent context parameters are not configured for each session, or session isolation settings are not enabled, resulting in unexpected token pool sharing.
How to Verify Correct Configuration
- Initiate a single-turn test dialogue, input "Query ordnance equipment yield rate data", check if the model prompts for supplementary information such as statistical cycle, equipment model, and production entity, to verify that the system prompt rules are effective.
- Upload a simulated military industry report file, initiate a dialogue requesting extraction of yield rate data from it, check if the model correctly associates the content of the uploaded file, to verify that the file upload configuration is effective.
- Initiate two consecutive dialogue turns. In the first turn, specify an equipment model and monthly cycle. In the second turn, only mention "Revenue status of this equipment", check if the model can reuse the screening conditions from the first turn, to verify that the context retention configuration is effective.
- Call the
/api/v1/chat/completionssession interface, check if the request parameters include thesystemPromptfield, and that the content matches the preset screening rules, to verify that the interface parameter configuration is correct.
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.