What data for this category looks like
Data sources for precast concrete components include BIM detailed design documents, rebar and concrete batch ledgers, mold table and curing kiln operation records, laboratory test reports, and product QR code traceability data. Daily documents include component detailed drawings, rebar cutting lists, mold inspection records, pouring and vibration records, curing records, demolding and factory inspection reports. Data is updated per individual component, per batch of materials, and per curing kiln batch. It includes fields such as component number, rebar specification, curing temperature, demolding strength, and others. Units include millimeters, degrees Celsius, megapascals, hours, and more.
What constraints these characteristics impose on deployment and upgrade
The multi-source, high-frequency updated data of this category requires stable, long-lasting storage and database connections to be configured during deployment, to avoid data synchronization interruptions. Significant structural differences exist between different types of on-site documents, so expansion space for multi-format parsing adaptation must be reserved during deployment. The fine-grained update logic per individual component, per batch, and per kiln requires that batch association relationships of data not be disrupted during the upgrade process. Real-time data docking requirements for equipment terminals (mold tables, curing kilns) require interface adaptation configurations to be planned in advance during deployment, to avoid compatibility issues during subsequent docking. The risk of database restart failure caused by power outages also requires automatic restart and health check mechanisms to be configured during deployment.
How to set configurations
The following configurations are formulated based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
PG_URL | postgresql://fastgpt:password@127.0.0.1:5432/fastgpt?sslmode=disable | Structured inspection ledger and batch data for precast concrete components require persistent storage, and PostgreSQL supports complex query requirements |
MONGODB_URI | mongodb://fastgpt:password@127.0.0.1:27017/fastgpt?authSource=admin | Stores unstructured documents such as component detailed drawings and curing records, and supports flexible field expansion |
REDIS_URL | redis://:fastgpt@127.0.0.1:6379/0 | Caches frequently queried component numbers and test data to reduce database load |
DB_MAX_LINK | 20–30 | Matches the thousands of daily equipment inspection and data update requests for this category, to avoid connection exhaustion |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Encrypts access tokens for files such as component drawings and test reports, to protect sensitive data security |
STORAGE_S3_ENDPOINT | http://127.0.0.1:9000 (local storage) or address provided by cloud service provider | Adapts to batch storage requirements for multi-format documents, and matches the high-frequency updated data storage rhythm |
Three common errors
- Symptom: After deploying with Docker Compose, accessing the registration page fails to submit new user information, and a user registration failure prompt appears on the interface. Cause: The default deployment configuration does not enable the public registration switch, and an administrator account is not generated via
ROOT_KEYbefore adding ordinary user permissions, which cannot meet the account requirements for multi-team collaborative inspection. - Symptom: PostgreSQL or MongoDB fails to start after a power outage restart, and the log prompts connection refused. Cause: Data volume persistent storage is not configured during Docker deployment, and the power outage causes database files inside the container to be corrupted, making it impossible to load business data normally.
- Symptom: After configuring a third-party API key, normal calling fails, and the conversation interface returns empty results. Cause: The key is not correctly filled in the corresponding environment variable, or the professional term model is not bound in the FastGPT knowledge base configuration, making it impossible to accurately parse precast concrete component inspection and maintenance issues.
How to confirm the configuration is complete
- Run the
docker pscommand, confirm that the STATUS fields of the PostgreSQL, MongoDB, and Redis containers are all Up, with no abnormal exit records. - Access the domain configured in
FE_DOMAIN, log in with the administrator account generated viaROOT_KEY, attempt to upload a rebar cutting list document, and verify that the file upload and parsing process works normally. - Call the database connection test interface, confirm that the current number of connections does not exceed the threshold configured in
DB_MAX_LINK, with no connection timeout or refused error reports. - Simulate a power outage and restart all containers, confirm that all database services start automatically, with no connection refused or data loss prompts.
The values provided are common starting points and should be measured against the reader's own samples.