What the data for this category looks like
Data for this category originates from three primary sources: securities firms’ national defense and military industry research reports, publicly released industrial analysis documents from military industry groups, and industrial white papers published by national defense technology industry associations.
Update timelines align with industry event milestones. Temporary new documents are added when major equipment is finalized or industry policies are released. Regular updates cover quarterly and semi-annual milestones.
Documents typically include core track analysis, upstream and downstream industrial chain data, key enterprise financial indicators, and equipment performance parameters. Fields include equipment model, revenue scale, production capacity, and order amount. Common units are ten thousand yuan, hundred million yuan, units, sets, and megawatts.
What constraints these characteristics impose on tool calling and plugins
Dispersed data sources and non-fixed update milestones require tool calling to support multi-source data pulling and incremental synchronization, to avoid repeated pulling of old documents.
Documents contain professional equipment models and performance parameters. Tool calling must retain precise matching of original fields, and must not arbitrarily rewrite parameter names.
Fields such as revenue and production capacity have clear units. Plugins must automatically associate unit fields during data parsing, to prevent disconnection between numerical values and units.
Uncertainty around temporary new documents requires tool calling to support dynamic identification of new document structures, to adapt to research report content in different formats.
Significant format differences across documents from different sources require plugins to support multi-format parsing and complete unified field mapping.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
RECALL_TOP_K | Top 10-15 results | Military electronics research reports have high sub-track concentration. Too many recalled results introduce irrelevant content, while too few fail to cover core analytical information. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Military electronics research reports often include multi-page charts and complex industrial chain tables, resulting in long parsing times. Default timeout durations are insufficient for complete parsing. |
TOOL_CALL_MAX_RETRIES | 3 attempts | Data sources for military electronics research reports may have temporary access restrictions. Retries reduce the rate of call failures. |
MAX_CONTEXT_LENGTH | 8000-12000 characters | Single military electronics research reports have relatively long content. Excessively long context exceeds model window limits, while excessively short context loses key analytical logic. |
SIMILARITY_THRESHOLD | 0.75-0.85 | Military electronics sub-tracks have many professional terms. A threshold that is too low introduces irrelevant results, while a threshold that is too high fails to recall relevant sub-track content. |
UPLOAD_FILE_MAX_SIZE | 50 MB | Military electronics research reports often include high-definition charts and industrial chain maps, resulting in large single-file sizes. Large file uploads must be supported. |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing values.
Three Common Mistakes
- Phenomenon: Tool calls return the
429 Too Many Requestsstatus code, and research report data cannot be pulled. Cause: Call rate limits and retry parameters are not configured, and concurrent requests exceed the bearing limit of the data source interface. - Phenomenon: Core fields such as equipment models and revenue values in recalled research report data are empty. Cause: Field mapping configuration is not enabled, or parsing rules are not adapted to the professional term format in research reports, resulting in failure to extract key information.
- Phenomenon: When calling the knowledge base question and answer interface from a custom interface, user session identifiers cannot be bound. Cause: User parameters are not passed in the embedded code, so tool calls cannot associate context data for the corresponding user.
How to Confirm Proper Configuration
- Upload a single typical military electronics research report, run a tool call test, and verify that core fields such as equipment models and revenue values are present in the returned results.
- Simulate concurrent requests, check whether the tool call retry mechanism takes effect, and no persistent
429status codes are returned. - Embed a custom interface, pass user identifier parameters, and confirm that tool calls can bind context data for the corresponding session.
- Adjust the recall count configuration, compare result relevance across different values, and confirm that it meets the requirements of track analysis.
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.