Reference only; verify against the target FastGPT release and deployment documentation.
What this category's data looks like
This category's data primarily comes from the food safety sampling and monitoring system, the State Administration for Market Regulation sampling results query system, laboratory LIMS, and food producer and operator ledgers. Daily documents include sampling plans, sampling slips, inspection reports, non-compliant food verification and disposal reports, and risk control announcements. Data is updated monthly. Core content covers three key modules: sampling locations, inspection results, and disposal processes. No unnecessary custom fields are included.
What constraints these characteristics impose on deployment and upgrade
Monthly updated data sources require configuring scheduled synchronization tasks during deployment to ensure consistency between the knowledge base and official data. Differences in data formats across multiple sources require reserving multi-data source adaptation configuration items during deployment to comply with interface specifications of different systems. Document types include structured sampling slips and unstructured inspection reports, requiring configuring mixed parsing rules during deployment to ensure correct extraction of different document formats. Core evidence comes from inspection reports issued by laboratories, requiring strengthening data verification links during deployment to prevent erroneous data from entering the Q&A knowledge base. Significant differences in deployment environments between grassroots supervision institutes and testing institutions require upgrading to support running on low-specification nodes.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:27017/fastgpt?authSource=admin | Adapts to the storage needs of multi-source monthly synchronization for this category, specifies authentication source to ensure data access security |
DB_MAX_LINK | 50–80 | Matches concurrent connection counts for monthly batch synchronization, prevents database connection exhaustion |
REDIS_URL | redis://:password@host:6379/0 | Used to cache frequently queried regulatory documents and sampling results, reducing database load |
FE_DOMAIN | https://your-domain.com | Configures the access domain name for the Q&A interface, ensuring normal access links for grassroots supervision institutes and testing institutions |
FILE_TOKEN_KEY | Random string calibrated through actual testing | Used to encrypt access tokens for sensitive files such as inspection reports, preventing unauthorized access |
ROOT_KEY | Custom strong password string | Used to configure system administrator permissions, ensuring initial access security after deployment |
Three common errors
- After starting the container, the service status shows normal, but the Q&A interface cannot be accessed. Logs prompt a database connection failure. Manual verification of the database account and password shows no access permission. The cause is that the
MONGODB_URIconfiguration does not correctly specify the authentication source or the account permission configuration is insufficient. - After completing local deployment, the model configuration and management interface cannot be accessed, and API key configuration cannot be completed. The cause is that
ROOT_KEYis not correctly configured, leading to failed administrator permission verification. - An index error occurs during batch import of monthly sampling data, and the synchronization task times out. The cause is that the
DB_MAX_LINKparameter is not set reasonably, leading to database connection exhaustion.
How to confirm the configuration is correct
- Run the database connection test command to verify that the account and password configured in
MONGODB_URIcan normally access the target database. - Access the configured
FE_DOMAINaddress to confirm that the front-end interface loads normally and administrator login is completed successfully. - Import a standard sampling plan document to verify that the corresponding Q&A corpus can be generated normally after document parsing.
- Configure the monthly data synchronization task, manually trigger a synchronization, and confirm that data can be normally written to the knowledge base without 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.