What the data for this category looks like
This category's data originates from engineering quality and safety supervision systems, construction site real-name platforms, supervision logs, and test reports. The update frequency is weekly. Daily generated business documents include supervision plans, supervision inspection records, hidden danger rectification notices, quality problem handling forms, and completion acceptance supervision reports. Each document includes fields such as supervision subject, project information, inspection content, rectification requirements, and acceptance conclusions. There is no unified fixed unit, and values are adjusted dynamically based on specific project parameters.
What constraints these characteristics impose on deployment and upgrade
Bulk data updated weekly requires configuring stable scheduled synchronization tasks during deployment, to prevent excessive server resource usage from real-time synchronization. Heterogeneous data from multiple sources requires completing format adaptation configuration during the deployment phase, to adapt to the return formats of different interfaces such as supervision systems and real-name platforms. Processing large volumes of structured and unstructured documents requires reserving sufficient file storage and parsing computing power during upgrades. Permission division requirements for different users require completing multi-role permission configuration during deployment, to match the operation scope of usage scenarios including housing and urban-rural development quality and safety stations, construction units, and supervision units.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 10–15 connections | Adapts to database connection requirements for weekly bulk synchronization, avoids connection pool exhaustion that disrupts data import |
MONGODB_URI | Assemble the standard MongoDB connection format using the intranet address of the local deployment instance | Stores heterogeneous document data from multiple sources, supports fast retrieval of business documents such as supervision plans and rectification notices |
REDIS_URL | redis://localhost:6379/0 | Caches frequently accessed supervision inspection record data, improves query response speed for internal employees |
FE_DOMAIN | Exclusive secondary domain name of the internal office system | Adapts to the access path of the internal office network, ensures that permission control rules take effect |
FILE_TOKEN_KEY | 32-bit random string determined through actual testing | Encrypts download tokens for sensitive files such as test reports, prevents unauthorized access |
ROOT_KEY | Key string aligned with the internal identity system | Verifies the legitimacy of platform internal interface requests, ensures permission security for sensitive operations |
Three common mistakes
- Symptom: An invalid token message appears when connecting to a domestic large model, and the interface returns a 401 status code. Cause:
ROOT_KEYis not configured correctly, or the interface key of the domestic large model is not synchronized to the FastGPT environment variables, resulting in failed request identity verification. - Symptom: A source-deployed WeChat project cannot connect to a FastGPT service deployed via Docker. Cause:
FE_DOMAINand the service intranet address are not configured correctly, cross-origin requests are blocked, or port mapping is not exposed. - Symptom: Parsing fails when bulk importing supervision logs, and some fields are empty. Cause: Parsing rules adapted to supervision log formats are not configured in advance, causing heterogeneous data to fail to map correctly to FastGPT knowledge base fields.
How to confirm configuration is complete
- Run the database connection test tool included with FastGPT v4.17.0, confirm that the number of connections configured for
DB_MAX_LINKis not exhausted, and no timeout errors occur. - Access the internal address bound to
FE_DOMAIN, verify that the page loads normally, and that permission configurations for employees of different roles take effect. - Upload a standard-format supervision log document, confirm that the parsed fields match the preset business rules, with no missing content.
- Call the domestic large model interface, verify that token verification passes, and return normal question-and-answer results based on the knowledge base.
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.