What data for this category looks like
The data for aerospace equipment financing daily reports comes primarily from publicly available government procurement announcements in the national defense and military industry sector, project disclosure notices from aerospace research institutes, and daily updated financing monitoring databases from industry associations. Data is synchronized with all new financing records from the previous day every early morning. Each daily report document is categorized by project. Each record includes the project name, contractor entity, financing amount, financing round, disclosure date, and application scenario fields. The financing amount unit is uniformly ten thousand yuan. The financing round field includes detailed identifiers such as angel round, Pre-A round, and industrialization implementation projects.
What constraints these characteristics impose on deployment and upgrade
The requirement to synchronize all new records daily requires configuring scheduled incremental pull tasks during deployment. This avoids excessive memory and disk IO usage caused by full pull operations. Structured data with multiple fields requires retaining detailed fields such as application scenarios and financing rounds during the knowledge base parsing phase, to support precise subsequent recall. The project classification logic for different contractor entities requires updating the knowledge base’s tag mapping rules during upgrades, to ensure consistent classification. At the same time, the uniform unit for financing amounts requires configuring a unified numerical formatting script during deployment, to avoid unit confusion during retrieval.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
SYNC_DATA_INTERVAL | 24 hours | Matches the daily update rhythm of aerospace equipment financing daily reports, avoids repeated full data pulls |
PARSE_FIELD_WHITELIST | Project Name, Undertaking Subject, Financing Amount, Financing Round, Disclosure Date, Application Scenario | Retains all core business fields for precise retrieval, filters irrelevant fields to reduce vector database storage overhead |
VECTOR_STORE_BATCH_SIZE | 50 records per batch | Adapts to the feature of multiple fields per record, avoids performance bottlenecks during single batch writes to the vector database |
MAX_PARSE_TIMEOUT | 600 seconds | Reserves sufficient time to parse daily report documents with multiple projects, avoids interrupting parsing tasks midway |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Adapts to the size limit of monthly summary daily report documents, avoids normal files being blocked during upload |
ES_COMPILE_TARGET | es2015 | Adapts to JavaScript rendering requirements of older browsers such as 360 Speed Browser, avoids syntax errors |
The parameter values provided on this page are common starting points for configuration setup. Actual values are influenced by material form, data volume, and business rules. Specific issues require targeted analysis. Testing on local samples is recommended before finalizing configurations.
Three common errors
- Phenomenon: After local deployment, each run’s loading time exceeds the preset threshold, and vector recall results have significant delays. Cause: No incremental synchronization task is configured. Each startup performs a full pull of all aerospace equipment financing daily report data, resulting in excessive memory and disk IO usage.
- Phenomenon: JavaScript syntax errors appear when accessing the platform using 360 Speed Browser, and the page cannot render properly. Cause: The compilation target version is not adjusted to es2015. Versions 4.8.7 and above use es2020 syntax by default, which cannot be parsed by older browsers.
- Phenomenon: A
permission denied while trying to connect toerror occurs during local deployment, and the service cannot start. Cause: The current user is not granted access permissions for the Docker socket file, or the permission configuration for the container mount directory is incorrect.
How to confirm configurations are set correctly
- Execute the scheduled synchronization task, verify that the number of new financing records in the synchronization log matches the number of new records disclosed by the data source on that day.
- Retrieve projects of a specified financing round, confirm that the returned results include the preset core fields, and the field formats meet business requirements.
- Access the platform’s front-end page, use an older browser to verify that JavaScript rendering has no errors, and confirm that the compilation target configuration is effective.
- Check the vector database’s storage metrics, confirm that the vector storage size of each record meets the requirements of the preset batch write parameters.
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.