What the data for this category looks like
The daily office documents for this category include maintenance plans, patrol logs, defect disposal forms, road construction permits, road damage compensation forms, and similar items. Data mainly comes from highway maintenance management systems, bridge and tunnel monitoring systems, road patrol systems, and traffic flow monitoring data. The update frequency is daily. Common data fields include facility ID, defect type, disposal deadline, road project scope, compensation amount, and others. Units include kilometers, square meters, cubic meters, workdays, and others. The data volume per document fluctuates based on patrol frequency and project scale.
What constraints these characteristics impose on deployment and upgrade
The multi-source daily updated data, mixed-format documents, and compliance verification requirements for this category impose multiple constraints on deployment and upgrade. These must align with the version features of FastGPT v4.17.0. The daily high-frequency updated patrol and monitoring data require sufficient storage capacity and concurrent processing capacity to be configured during deployment, to avoid data backlog. The differentiated fields and units across multiple document types require preset field mapping rules during the deployment phase, to adapt to subsequent batch data imports. The compliance requirements for road construction and compensation documents require reserved expansion space for permission control and audit modules. During upgrades, ensure that existing work order circulation processes are not interrupted. Data docking across existing maintenance systems must comply with original interface specifications, to avoid disrupting normal operation of internal office and employee services.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
DB_MAX_LINK | 100–150 connections | Aligns with the concurrent query volume of daily high-frequency patrol logs and work order data |
MONGODB_URI | Enter the connection address of a self-built cluster and enable read-write separation | Stores large-volume business data such as unstructured patrol photos and construction permit attachments |
PG_URL | Enter the address of the PostgreSQL instance linked to the existing maintenance system | Connects to structured core business data such as maintenance plans and road property ledgers |
REDIS_URL | redis://:custom password@internal cache address:6379/0 | Caches frequently queried road property information and daily maintenance tasks to reduce pressure on core databases |
STORAGE_S3_ENDPOINT | Enter the endpoint address of the internal object storage service | Stores office documents such as batch-imported patrol logs and defect disposal forms |
FILE_TOKEN_KEY | Calibrated based on actual testing | Generates temporary tokens for document access, ensuring access security for internal office data |
Three common mistakes
- Scenario: A SQL permission error occurs after restarting the Docker container, and road property ledger data from the linked maintenance system cannot be read. Cause: The database configuration file that was originally mounted is not retained when the container is restarted, resulting in lost connection parameters and permission configurations.
- Scenario: After deploying the DeepSeek model hosted by Ollama, the model thinking settings do not take effect, and maintenance-related data in the custom knowledge base cannot be called. Cause: The knowledge base data source and model access permissions are not correctly bound during the configuration phase, so the model cannot read the corresponding documents.
- Scenario: Field parsing fails for some historical patrol logs when skipping intermediate versions during cross-version upgrades. Cause: Field mapping rules are not updated synchronously according to version iteration logic, and the skipped versions include adjustments to document fields.
How to confirm the configuration is complete
- Import a patrol log document in standard format, verify whether the system correctly identifies and maps preset business fields such as facility ID and defect type.
- Call the built-in model testing interface, enter query instructions related to maintenance operations and road property management, confirm that the model can return corresponding data from the knowledge base.
- View the system monitoring panel, confirm that indicators such as database connection count and cache hit rate are within stable ranges, with no abnormal fluctuations.
- Restart the service, verify that internal employees' work order submission and data query functions operate normally, with no error prompts.
The values provided here are common starting points, and should be evaluated 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.