What the data for this category looks like
Data for this category comes from enterprise internal control systems, ERP systems, financial sharing systems, audit management systems, and procurement contract project systems. Daily generated documents include internal control self-assessment reports, audit notices, audit working papers, issue lists, rectification ledgers, and rectification closure certificates. The data update frequency is annual. Most document structures include business subject information, issue descriptions, rectification requirements, and supporting material association items. Fields cover responsible departments, rectification time limits, verification results, and more. Statistical dimensions are primarily based on projects, batches, and copies.
What constraints these characteristics impose during deployment and upgrade
Data sources are scattered and require integration with multiple internal enterprise systems. During deployment, adaptation to the interface formats of different systems is required, and configuration items for multi-data source integration must be reserved. Data update frequency is low, but single-batch data volume is large. During upgrade, stability of batch data import must be ensured to avoid interruptions. Document fields are numerous and association relationships are complex. During deployment, field mapping rules must be configured to ensure extracted information accurately corresponds to document templates. Supporting materials related to rectification closed-loop processes must be stored with associations. During upgrade, compatibility of storage services must be confirmed to avoid loss of association relationships. The post-hoc sampling characteristic of audit processes requires that document generation be associated with business sample vouchers. During deployment, association indexes for sample data must be configured.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | Enterprise audit management system MongoDB instance address | Core data for this category, including audit working papers and issue lists, is stored in the MongoDB database of the audit management system, and direct connection is required for data retrieval |
PG_URL | Enterprise ERP and financial sharing system PostgreSQL instance address | Business samples and voucher data are stored in the PostgreSQL database of the ERP and financial sharing systems, used to extract business data required for audits |
STORAGE_S3_ENDPOINT | Enterprise internal compliant object storage service access address | Supporting materials such as rectification closure certificates must be stored in enterprise-compliant object storage, and the corresponding access endpoint must be configured to ensure file association |
REDIS_URL | Enterprise internal cache service address | Used to cache frequently accessed audit issue templates and rectification ledger data, reducing query pressure on internal systems |
DB_MAX_LINK | 10–15 connections | Adapts to scenarios with simultaneous connections to multiple data sources, avoiding excessive connection counts that cause high load on internal systems |
FE_DOMAIN | Enterprise internal office domain name | Used to generate access links for documents, ensuring only internally authorized personnel can access generated documents |
Three common configuration errors
- A POST /api/admin/initv4818 404 status code is returned when executing the upgrade command, with a duration of 76ms. The cause is that
ROOT_KEYis not configured correctly, or the initialization script path under the deployment directory does not match the command parameters, resulting in the interface not loading properly. - After deployment is complete, the login interface prompts invalid username or password, and initial credentials cannot be queried. The cause is that the initialization script was not executed to generate user credential files, or
FILE_TOKEN_KEYwas not configured for encrypted storage of user credential information. - The generated audit working papers lack business sample association fields. The cause is that the connection count threshold for
DB_MAX_LINKwas not configured correctly, resulting in failure to pull all business sample data, or field mapping rules were configured incorrectly.
How to confirm correct configuration
- Execute the database connection test command to verify that the configurations for
MONGODB_URIandPG_URLcan properly connect to the corresponding data sources, with no connection timeouts or permission errors. - Upload a sample file of a rectification closure certificate, check that the storage service configured via
STORAGE_S3_ENDPOINTcan properly receive and store the file, with no upload failure prompts. - View the Redis service logs to confirm that the cache service configured via
REDIS_URLcan properly read and write data, with no connection exception errors. - Access the internal address corresponding to
FE_DOMAIN, confirm that the front-end interface loads properly, and that the document generation module displays template options adapted to this category.
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.