What Data for This Category Looks Like
Data for this category primarily comes from the Food Safety Sampling and Monitoring System, the State Administration for Market Regulation Sampling Results Inquiry System, the laboratory information management system (LIMS) of inspection institutions, and the ledgers of food producers and operators. The update frequency is once per month.
Commonly involved documents include sampling plans, sampling slips, inspection reports, unqualified food verification and disposal reports, and risk control announcements. Data fields cover sampling batch, inspection item, non-conforming item, disposal measures, and more. Each document is linked to a unique sampling number and inspection report number. The core data structure centers on the sampling-inspection-disposal workflow.
What Constraints Do These Characteristics Impose on Deployment and Upgrade
The monthly update frequency requires deployed scheduled synchronization tasks to align with this cycle. This avoids frequent requests to external government and inspection systems that could trigger rate limiting.
Multi-source data docking requires cross-system permissions, field mapping, and format conversion rules to be configured during initialization. This adapts to the different data formats of government systems, LIMS, and enterprise ledgers.
The requirement that core documents are tied to unique sampling numbers means data deduplication and association verification logic must be deployed. This prevents duplicate entry or incorrect associations.
Sensitive disposal data requires configured encrypted storage and hierarchical access rules. This meets regulatory data security requirements.
How to Configure
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://admin:secure_pass@10.0.0.5:27017/fs_inspect?authSource=admin | Stores structured data including monthly updated sampling ledgers and inspection reports, binds to a dedicated business database and configures access authentication |
REDIS_URL | redis://:redis_secure@10.0.0.6:6379/1 | Caches the status of monthly data synchronization tasks and sampling number mapping tables, reducing repeated requests to external government systems |
DB_MAX_LINK | 20–30 | Adapts to the concurrency requirements of monthly bulk data pulls, avoiding exceeding connection number limits of external regulatory systems |
STORAGE_S3_ENDPOINT | https://s3-gov.local.gov.cn | Stores large files including inspection reports and unqualified food verification and disposal reports, complying with government storage compliance requirements |
FILE_TOKEN_KEY | 12-hour valid signature key | Generates access signatures for sampling documents, controlling file access permissions for internal staff and regulatory departments |
Three Common Misconfigurations
- Symptom: FastGPT containers deployed via Docker cannot pull sampling data from the State Administration for Market Regulation, with connection timeout errors in logs. Cause: The container is not configured with correct external network access rules, or the host firewall restricts outbound network permissions for the container.
- Symptom: Calling code plugins to generate sampling reports returns an AxiosError 404 status code. Cause:
STORAGE_S3_ENDPOINTor internal data interface access addresses are not configured correctly, causing the plugin request resource path to not exist. - Symptom: The internally deployed aiproxy component continuously attempts to connect to external GPT services. Cause: External model calls are not disabled in the aiproxy configuration, or local model docking parameters are not configured.
How to Verify Successful Configuration
- Run the monthly data synchronization task, check whether bulk data from the Food Safety Sampling and Monitoring System and LIMS can be successfully pulled, with no connection timeouts or format parsing errors.
- Upload an inspection report file, check whether it is properly stored to the specified S3 storage node, and that the generated access link can be accessed normally by authorized users.
- Enter the advanced orchestration module, create a test workflow including a judge and AI chat, verify that initial sampling requirement parameters can be passed to subsequent AI chat modules.
- Check database connection counts via system monitoring, confirm that concurrent connection counts do not exceed the
DB_MAX_LINKsetting, and that rate limiting from external systems is not triggered.
The values provided here are common starting points, and should be evaluated against local actual 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.