What the data for this category looks like
Data sources include the MES manufacturing execution system for steel smelting, PLC device collection system, enterprise OA office platform, and employee attendance and payroll system. Update frequencies are divided into real-time (device operating status, production line progress), daily (production reports, material inventory), and monthly (payroll, performance). Document structure is divided into structured fields (such as furnace temperature, operating duration, device ID) and unstructured documents (such as device maintenance logs, employee training materials). Fields include unique identifiers, timestamps, numerical or text types, with units compliant with industrial scene specifications, such as degrees Celsius, hours, tons.
What constraints these characteristics impose on deployment and upgrade
Reference only; verify against the target FastGPT release and deployment documentation.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 | Matches the multi-source concurrent data request volume of steel smelting, avoids connection pool exhaustion |
MONGODB_URI | Points to the enterprise's dedicated internal MongoDB instance, configure dedicated authentication parameters | Stores unstructured maintenance logs and employee conversation data, ensures internal data isolation |
REDIS_URL | Configured as a locally clustered Redis instance, memory quota 8 GB | Caches real-time production line data and employee service session contexts, reduces database access pressure |
FILE_TOKEN_KEY | Valid for 7200 seconds | Matches the typical session duration of employee services, avoids token expiration causing conversation interruptions |
STORAGE_S3_ENDPOINT | Points to the intranet address of the enterprise's internal object storage service | Stores large-capacity device maintenance documents and training materials, complies with intranet data security requirements |
Three common mistakes
- Symptom: After running
docker compose up, a prompt indicates that thepackages/plugins/registerdirectory or file is missing. Cause: The plugin registration script was not executed during the initialization phase, or the deployment package does not fully include the plugin configuration directory. - Symptom: In the workflow configuration interface, when the number of nodes exceeds 10, obvious lag occurs when entering text. Cause: Reasonable front-end resource caching and back-end interface timeout parameters were not configured, and a large number of node renderings trigger excessive DOM redraws and interface requests.
- Symptom: After running
docker compose pull && docker compose up, a database connection error occurs. Cause: The original database configuration file was not retained during the upgrade process, or the database connection parameters of the new image do not match the original instance.
How to confirm the configuration is correct
- Run the
docker compose pscommand to confirm that all service containers are in a running state - Upload industrial device maintenance log documents to verify that the document parsing module can normally extract structured and unstructured content
- Initiate a simulated employee consultation conversation request to verify that the session context cache and call process are working properly
- View the database monitoring panel to confirm that the database connection count does not exceed the configured
DB_MAX_LINKthreshold
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.