What the Data for This Category Looks Like
Military electronic research report sources include securities firm military industry research teams, professional military industry research institutions, and internally disclosed group research documents. Update frequency fluctuates with industry events. Dense updates occur when major equipment is finalized or industry policies are released. Organizations release normal updates weekly or biweekly. Document structures include release date, author unit, core business data, technical parameter modules, risk warnings, and other sections. Core fields include order amount (unit: ten thousand yuan), detection range (unit: kilometer), operating frequency band (unit: gigahertz). Some documents contain long tables and specialized terminology paragraphs.
Constraints Imposed on Deployment and Upgrade
Unified parsing templates must be configured to adapt to report structures from different sources, due to inconsistent formats across multiple data sources. Scheduled task trigger intervals must be adjusted to avoid excessive resource usage, given high-frequency update requirements. Individual research reports can be lengthy, with some exceeding 50 pages. Parsing and segmentation parameters adapted to long texts must be configured. Precise field mapping rules must be set for the vector database to handle specialized fields and units, preventing unit matching errors during retrieval. The upgrade process must be compatible with legacy multi-source access configurations to avoid interrupting existing research report retrieval services.
How to Set Configuration Values
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Military electronic research reports often contain long tables and technical parameter blocks, with longer parsing times than general documents |
maxContext | 8000–12000 characters | The core content of a single research report can reach thousands of characters, requiring adaptation for long-context retrieval |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Some batch research report collection files have large sizes, so upload limits need to be relaxed |
CRON_SCHEDULE | 0 2 * * 1 | Industry research reports are mostly updated every Monday, so data is synchronized on a weekly schedule |
recall_top_k | Top 8 entries | The niche of military electronic research reports is narrow, so an excessive number of highly relevant results is unnecessary |
similarity_threshold | 0.75–0.85 | High matching accuracy is required for industry terminology, so a high threshold must be set to filter low-relevance results |
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 specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: The version number displayed after executing the version query command does not match the target deployment version. Cause: The container image for the corresponding version was not pulled correctly, or relevant service processes were not restarted after the upgrade, causing the old version to remain running.
- Phenomenon: A
Message field is requirederror or 40 status code is returned during model testing. Cause: A valid model invocation key was not configured, or the key was not correctly bound to the application link, preventing model invocation requests from initiating normally. - Phenomenon: Parsed research reports cannot be used by the model to generate responses. Cause: The
maxContextparameter was not adjusted to adapt to long documents, and the retrieved document segments exceed the model's context window and cannot be integrated into the response content.
How to Confirm Proper Configuration
- Execute the version check command to confirm that the currently running FastGPT version matches the planned deployment version.
- Upload a typical military electronic research report, wait for parsing to complete, and verify that the parsed text contains key content such as core technical parameters and business data.
- Manually trigger a configured scheduled synchronization task to check if research reports from the specified data source are automatically pulled, parsed, and stored in the database.
- Initiate a retrieval request targeting core research report questions to confirm that the retrieved results include matching document segments.
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.