What the data for this category looks like
Data for this category comes from the national integrated government service platform item database, administrative licensing item list, departmental business approval systems, and electronic certificate repository. The update frequency is daily. Documents processed daily include service guides, application forms, commitment letters, acceptance notices, correction notices, administrative licensing decision documents, license certificates, and more. These are collected as single or batch approval applications. Each document corresponds to one statutory licensing item, and includes fields such as applicant subject information, acceptance number, approval process records, and certificate number. Item, piece, and copy are used as basic statistical units.
What constraints these characteristics impose on the deployment and upgrade phase
The daily data update requirement means the storage service configured during deployment must support high-frequency, stable writing to avoid data loss or synchronization delays. Significant structural differences across multiple types of approval documents require the upgrade process to be compatible with field extraction logic for different documents, ensuring the completeness of ledger summary. The need for cross-department multi-source data access requires interfaces configured during deployment to adapt to data formats of different systems, reducing data conversion loss. Approval process errors can lead to overdue completion or administrative reconsideration. Deployment and upgrade processes must reserve configuration space for error troubleshooting and rollback to ensure service continuity.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:27017/fastgpt_approval | Adapts to the batch storage requirements of government approval data, supports high-frequency read and write operations |
REDIS_URL | redis://:password@host:6379/0 | Used to cache daily updated item lists and electronic certificate metadata, reducing cross-system call frequency |
DB_MAX_LINK | 20–30 connections | Matches daily high-frequency data synchronization and ledger generation tasks, avoiding connection pool exhaustion |
STORAGE_S3_ENDPOINT | Fill in according to the access address provided by the government cloud storage service provider | Adapts to compliance storage requirements in government scenarios, supports uploading large-volume approval documents |
ROOT_KEY | Generate a 32-bit random string | Ensures the security of deployment instance management permissions, complies with permission control specifications of government systems |
Three common mistakes
- Accessing the deployment instance returns a 404 no body error. The cause is incorrect configuration of
MONGODB_URIorREDIS_URL, or core dependent services failing to start and connect properly. - Image materials cannot be recognized during batch import of approval documents. The cause is that
FILE_TOKEN_KEYis not configured, or the image-to-base64 parsing process is not enabled, resulting in failure to properly upload and parse image data. - Ledger summary tasks frequently fail. The cause is that
DB_MAX_LINKis set too low, causing connection pool exhaustion and interrupting data synchronization.
How to confirm the configuration is correct
- Run a single approval data synchronization test, check whether corresponding records are generated in the database corresponding to
MONGODB_URI. - Upload an approval application form containing images, confirm that the
FILE_TOKEN_KEYconfiguration takes effect, and images can be properly parsed and included in the ledger. - Start a batch ledger generation task, observe the connection pool usage, and confirm that no connection exhaustion exceptions occur.
- Access the frontend address configured in
FE_DOMAIN, confirm that the interface loads normally and there are no permission errors.
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.