What data looks like for this category
Data for this category comes from BIM detailed design documents, rebar and concrete batch ledgers, mold table and curing kiln operation records, laboratory test reports, and component QR code traceability systems. Daily documents include component detailed drawings, rebar cutting lists, mold inspection records, pouring and vibration logs, curing cycle records, and demolding and factory inspection reports. Data updates are triggered for each individual component, each batch of materials, and each curing kiln batch. Core fields include component ID, rebar specification, embedded position parameters, concrete strength grade, and curing duration. Units include millimeters, megapascals, hours, and others.
What constraints these characteristics impose during deployment and upgrade
Multi-source, heterogeneous data sources for precast concrete components require compatibility with multi-format document import and structured extraction during deployment. Corresponding data access channels must be configured. The high-frequency update rhythm per individual component, each batch, and each kiln requires ensuring database connection stability to avoid resource overload during batch processing. Large complete documents for single large components require reasonable configuration of storage and indexing resources to prevent retrieval delays. The one-to-one association between each component and its corresponding on-site lifting position must be supported. During upgrades, retain data association mapping rules to avoid breaking the traceability chain.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 | Adapts to high-frequency data write requests per kiln and batch, prevents connection pool exhaustion |
MONGODB_URI | Points to a security-hardened instance of version 5.0.24 or later | Fixes known security vulnerabilities in MongoDB 5.0.18 and earlier versions, adapts to bulk data storage requirements |
REDIS_URL | Configure a dedicated cache instance, set validity period of frequently queried data to 3600 seconds | Reduces database query pressure, improves retrieval speed for component lists and inspection records |
STORAGE_S3_ENDPOINT | Bind an object storage node that supports large file chunked upload, set chunk size to 8 MB | Adapts to storage requirements for large component detailed drawings and curing logs, prevents upload timeouts |
FE_DOMAIN | Enter a fixed domain name for factory intranet or public network access | Ensures consistent interface access for all roles in the audit process, avoids cross-domain issues |
FILE_TOKEN_KEY | A randomly generated 32-bit string, set token validity period to 168 hours | Ensures secure authentication for large file uploads, prevents unauthorized access |
Three common mistakes
- Phenomenon: After upgrade, the version number displayed in the system interface does not match the actual deployed version. For example, FastGPT v4.13.1 is deployed but the interface shows v4.9.2. Cause: Front-end version configuration files were not updated synchronously during secondary development, causing the version verification logic to read old version identifiers.
- Phenomenon: Connection timeout errors occur when bulk importing large-volume documents such as rebar cutting lists. Cause: The
DB_MAX_LINKconfiguration value was not adjusted, causing connection pool exhaustion during high-frequency data writes. - Phenomenon: Multiple variable update nodes cannot be uniformly integrated with AI replies, and workflow execution fails. Cause: A dedicated cache instance for
REDIS_URLwas not configured, causing context data to fail to synchronize across nodes.
How to confirm configuration is complete
- Access the front-end address corresponding to
FE_DOMAIN, check if the version identifier at the bottom of the system matches the deployed FastGPT v4.17.0. - Bulk import detailed drawing files for 10 components, check if import success rate and response time meet business processing requirements.
- Use a MongoDB connection test tool to verify that the instance configured via
MONGODB_URIis version 5.0.24 or later. - Submit an audit request containing rebar specification, embedded position, and curing duration, check if a unified AI reply content is correctly generated.
The values provided are common starting points and should be measured against the reader's own samples.