Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this use case looks like
Engineering consulting supervision data primarily comes from full-cycle project supervision documents. These include supervision plans, on-site inspection records, acceptance reports, change visas, rectification notices, and similar materials. Data update rhythm follows project milestones. Phased documents are generated weekly or monthly during project implementation. After project completion, documents are archived for permanent retention. Individual document lengths vary widely. Some rectification requirements are just a few pages long, while full supervision plans can span dozens of pages. Fields include project number, engineering location, responsible unit, rectification deadline, closed-loop status, and more. Units include square meters, construction days, rectification deadline days, and similar units.
What constraints these characteristics impose during deployment and upgrade
Engineering consulting supervision data is scattered across project folders and internal business systems. During deployment, unified access to multi-source data must be supported. Therefore, STORAGE_S3_ENDPOINT must be configured to connect to internal object storage for unified attachment storage. Document lengths vary greatly. Chunk processing must adapt to different document lengths to avoid context loss caused by improper chunking. Data updates follow project milestones. During upgrade, incremental synchronization configuration must be supported to reduce resource consumption from full synchronization. Additionally, state-owned enterprise and public sector scenarios have strict data security requirements. Authentication logic must be configured via FILE_TOKEN_KEY and ROOT_KEY to prevent unauthorized access to core supervision data.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 1000–1500 connections | Adapts to scenarios where a single engineering consulting supervision project has many associated documents, and prevents database connection exhaustion |
MONGODB_URI | Internal privately deployed MongoDB connection string | Stores structured business data for supervision projects, and ensures data stays within the internal network |
REDIS_URL | Internal Redis address with persistence, connection timeout 600 seconds | Caches frequently queried questions and replies, and reduces repeated query pressure on the database |
STORAGE_S3_ENDPOINT | Access address for internal object storage of state-owned enterprises and public sectors | Stores various document attachments for supervision projects, and complies with internal data security management requirements |
FILE_TOKEN_KEY | 32-character random string | Generates authentication tokens for document access, and prevents unauthorized users from downloading sensitive supervision documents |
ROOT_KEY | Key only known to internal operation and maintenance personnel | Highest permission key for the management platform, and prevents unauthorized modification of core configurations |
Three common misconfigurations
- Symptom: Generated document share links do not trigger identity verification. Any visitor can download supervision documents. Cause:
FILE_TOKEN_KEYparameter is not configured correctly, so authentication logic does not take effect. - Symptom: Connection timeout errors occur when calling embedding models. Cause: The privately deployed bge-m3 interface address from GPUStack is not correctly filled in the model docking configuration, so the private model service cannot be accessed.
- Symptom: Cannot pull the marker image to start the service during local deployment. Cause: Internal image source or domestic mirror acceleration address is not configured, so the base image depended on by marker cannot be downloaded.
How to confirm the configuration is correct
- Access the generated supervision document share link. Enter the correct authentication token to download normally. Enter an incorrect token to receive a 403 error. This confirms that the
FILE_TOKEN_KEYconfiguration takes effect. - Call the embedding model interface. The returned vector results match the local test results from the bge-m3 model. This confirms that the GPUStack deployment model docking configuration is correct.
- Check the MongoDB connection log. The current connection count falls within the
1000–1500 connectionsrange. This confirms that theDB_MAX_LINKconfiguration meets requirements. - Try uploading a supervision project document larger than 1000 MB. The document can be stored normally to the internal object storage. This confirms that the
STORAGE_S3_ENDPOINTconfiguration takes effect.
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.