What this category's data looks like
Core data for the complete vehicle final assembly scenario is generated around individual vehicle VINs. Data sources include ERP/MES systems, VIN and configuration management systems, supplier batch ledgers, tightening tool collection data, end-of-line (EOL) off-line inspection lines, and quality traceability systems. Daily documents cover production orders, VIN lists, assembly work instructions, tightening torque records, off-line inspection reports, rework records, and consistency release documents.
Data update frequency is per single vehicle. Core configuration data is synchronized in real time, and batch production data is summarized per shift. Document fields include unique VIN, part batch number, torque value (unit: newton meters), configuration item details, inspection results, and more. Data must be associated and integrated per vehicle.
What constraints do these characteristics impose during deployment and upgrade
Data in this scenario is split by VIN and has a high update frequency. Single-batch production generates a large volume of incremental documents. Deployment must adapt to high-concurrency indexing requests. Core data includes sensitive fields such as torque values and inspection results, so access permissions must be strictly controlled.
For offline deployment scenarios, cloud APIs cannot be relied on, so embedding models and rerank models must be deployed locally. Bid document and quotation preparation requires real-time matching of the latest VIN configurations, so deployment must ensure real-time synchronization of datasets, and adapt to field mapping rules for multi-source heterogeneous documents.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 | Adapts to high-concurrency indexing requests generated by single-batch production, prevents database connection exhaustion |
REDIS_URL | redis://:custom password@local deployment IP:6379/0 | Caches VIN and configuration matching data, reduces repeated database queries, improves response speed for quotation preparation |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Protects access permissions for dataset files, prevents unauthorized users from downloading sensitive tightening data and inspection reports |
ROOT_KEY | Random string with a complexity of no less than 16 characters | Serves as the security credential for the admin backend, restricts access to configuration and data management pages to authorized personnel only |
FE_DOMAIN | Public IP of the deployment server or bound domain name | Limits the access scope of the FastGPT frontend service, prevents cross-domain request exceptions |
Three common mistakes
- Phenomenon: After importing VIN lists and tightening data, the dataset remains in indexing for a long time. Cause: The
DB_MAX_LINKparameter was not adjusted to a value adapted to high concurrency, causing the database connection pool to be exhausted and indexing processes to block. - Phenomenon: After deploying the rerank model locally, the FastGPT interface does not display the model option. Cause: The port of the rerank service was not added to the allowed access list of
FE_DOMAIN, and the rerank service address was not correctly linked in the FastGPT configuration file. - Phenomenon: Unauthenticated share links can directly access the admin backend configuration page. Cause: The
ROOT_KEYsecurity credential for the admin backend was not set, or permission boundaries for the share service and login port were not restricted.
How to confirm successful configuration
- Log in to the FastGPT v4.17.0 admin backend, go to the dataset management page, check the indexing status of imported VIN list documents, confirm that indexing completes within 600 seconds.
- Go to the model configuration page, add the locally deployed rerank service address, initiate a test request, confirm that the request returns results normally.
- Access the generated bid document share link, confirm that it cannot jump to the admin backend login page, and only authorized document content can be viewed.
- Log in to the server to check Redis logs, confirm that VIN matching cache data has been normally written and read, with no connection errors.
The values provided are common starting points and should be measured against the reader's own samples.