What This Category of Data Looks Like
Data for this category comes from online monitoring platforms, automatic pollution source monitoring data, ecological environment law enforcement systems, and third-party test reports, with a daily update frequency. Daily processed documents include on-site inspection records, sampling records, monitoring reports, order for correction decisions, and administrative penalty decisions. Each document contains fields such as sampling points, monitoring factors, law enforcement time, and penalty basis. There is no unified fixed unit, and values change based on testing project or law enforcement document requirements. Data exists in a mixed form of structured monitoring values and unstructured law enforcement documents, covering both real-time uploaded online data and archived historical law enforcement files.
Constraints Imposed on Deployment and Upgrade
Reference only; verify against the target FastGPT release and deployment documentation.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://env_user:env_pass@host:port/fastgpt_env | This category has a large volume of law enforcement and monitoring data. A dedicated database instance must be specified to associate structured data storage from the ecological environment law enforcement system |
REDIS_URL | redis://:env_redis_pass@host:port/0 | Daily updated real-time monitoring data requires caching frequently queried law enforcement point information to reduce database read-write pressure |
STORAGE_S3_ENDPOINT | https://s3-cn-beijing.volces.com (or local object storage address) | Law enforcement documents and monitoring reports require persistent storage. Compatible with multi-region object storage services to meet data archiving requirements |
FILE_TOKEN_KEY | 32-bit random string | Generate unique access tokens for law enforcement documents to prevent unauthorized access to sensitive law enforcement data |
DB_MAX_LINK | 20–30 connections | This category has a large volume of daily monitoring data writes and law enforcement document queries. Limit the number of database connections to avoid resource exhaustion |
ROOT_KEY | Random string with a complexity of no less than 12 characters | Configure the highest-privilege key for private deployments, used to initialize the system and manage user permissions |
Three Common Misconfigurations
- Scenario: The inquiry function returns a 401 unauthorized error after deployment. Cause: The
ROOT_KEYis not configured correctly, or a valid API key is not bound in the application permissions. The system cannot verify the legitimacy of the request. - Scenario: New users cannot register after local Docker Compose deployment. Cause: The default deployment configuration does not enable the public registration switch, and no administrator manual user creation process is configured. New users cannot obtain access permissions.
- Scenario: The third-party large model key cannot be used for normal calls after configuration. Cause: The key is not bound to the application configuration of the corresponding knowledge base, or the access port of the corresponding large model is not opened during deployment. FastGPT cannot establish a connection with the large model service.
How to Verify Successful Configuration
- Run the
docker logs fastgptcommand to view database connection logs. Confirm there are no connection timeout or permission denied errors, and adjust the configuration to match the current data volume. - Upload an on-site inspection record document. Verify that core business fields are correctly extracted after parsing, and confirm that the document can be accessed normally and the storage path configuration is correct.
- Initiate an inquiry test based on monitoring data. Confirm that the returned results include the latest online monitoring data and historical law enforcement files, and verify that the caching logic is working properly.
- Log in to the system backend. Confirm that the administrator account can create new users normally, and verify that the registration function configuration meets business permission requirements.
The values given 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.