What the data for this category looks like
Typical data sources for this category include the unified budget management system, departmental staffing system, prior-year final accounts, project library, and Ministry of Finance budget formulation notices. Daily processed documents cover departmental budget drafts, project application forms, performance target forms, personnel expense calculation forms, and budget approvals. Data update frequency is annual. Data fields include project codes, expense amounts, staffing numbers, performance target indicators, and other relevant items. Document formats vary across different sources; some require format adaptation after export from official systems before import processing.
What constraints these characteristics impose on the deployment and upgrade phase
Since data updates occur annually, high-frequency real-time synchronization is not required during deployment, but support for batch import of full annual historical data is necessary. Multi-source heterogeneous data formats and field differences require that parsing rules compatible with multiple document types be configured during deployment. Annual budget data volumes are large, and calculation and summary links involve extensive field calculations. Sufficient computing and storage resources must be reserved during deployment. During the upgrade process, compatibility with historical budget data must be maintained to avoid preventing previously imported historical documents from being retrieved normally due to version updates. In addition, audit results are directly linked to fund arrangements, so a stable permission control mechanism must be configured during deployment.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:your_password@host:27017/fastgpt_budget?authSource=admin | Stores historical final accounts, project library, and other structured budget data; requires authentication to ensure connection security |
REDIS_URL | redis://:your_redis_pass@host:6379/1 | Caches frequently called budget fields and intermediate calculation results to shorten response times for cross-departmental data summarization |
DB_MAX_LINK | 200–300 | Adapts to requests from multiple departments submitting budget data imports simultaneously, preventing service lag caused by exhausted connection pools |
STORAGE_S3_ENDPOINT | http://your-local-storage:9000 | Stores unstructured documents such as departmental budget drafts and project application forms, ensuring stable large-file upload and download |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Encrypts access tokens for budget documents to prevent unauthorized users from accessing sensitive budget data |
ROOT_KEY | Complex random string of at least 16 characters | Manages super administrator permissions for FastGPT v4.17.0, ensuring security of system configuration |
Three common errors
- Interface lag occurs when loading budget data after deployment, and AI conversation responses time out. The cause is failure to adjust memory allocation based on the volume of budget documents and failure to limit the connection count for
DB_MAX_LINK, resulting in excessive resource occupation. - Unable to obtain a complete snapshot when exporting FastGPT data from the Sealos environment, with an error showing database connection timeout. The cause is incorrect configuration of authentication parameters for
MONGODB_URI, or failure to temporarily turn off Sealos network isolation policies. - Slow responses when submitting a budget calculation request after deployment, or even 504 gateway timeout errors. The cause is failure to configure
REDIS_URLto cache intermediate calculation results, resulting in repeated full-field calculations for each request and excessive computing resource occupation.
How to confirm proper configuration
- Run the built-in database connection test tool to verify that the connection status of
MONGODB_URIandPG_URLis normal, with no authentication or timeout errors. - A small departmental budget draft document can be uploaded to check whether the storage node configured via
STORAGE_S3_ENDPOINTcan receive the file normally and generate an accessible link. - A simulated personnel expense calculation request can be submitted to observe whether the response time meets the expected threshold, and confirm that cache and computing resource allocation is reasonable.
ROOT_KEYcan be used to generate a super administrator token, verify that the permission control logic is normal, and confirm that ordinary accounts cannot modify core system configurations.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.