Reference only; verify against the target FastGPT release and deployment documentation.
What the Data for This Use Case Looks Like
Expressway operation ledger data comes from four types of data sources: toll collection systems, maintenance inspection systems, pavement monitoring equipment, and road administration law enforcement terminals. Data update rhythms fall into three categories: real-time traffic ledgers sync every 15 minutes, monthly maintenance ledgers update daily, and over-limit incident ledgers update immediately when an incident occurs. Documents primarily use structured tables, with core fields including toll station ID, lane number, passage time, vehicle type classification, toll amount, maintenance section, inspection cycle, equipment operating status, and over-limit times. Corresponding units are serial number, none, YYYY-MM-DD HH:MM:SS, type, yuan, kilometers, days, percentage, and times.
Constraints Imposed by These Characteristics on Deployment and Upgrade Workflows
Multiple data source access requires configuring multiple independent database connection parameters during deployment to avoid storage conflicts between different types of ledger data. Ledgers with different update frequencies require corresponding scheduled synchronization tasks. During upgrades, ensure compatibility between the data source schemas of old and new versions to prevent data read failures. Large monthly summary reports require adapted high-capacity storage configurations to avoid storage overflow. Sensitive toll and over-limit data requires encrypted access tokens to prevent unauthorized access. High-concurrency real-time traffic ledger queries require adjusting database connection pool parameters to avoid connection exhaustion.
How to Set Configuration Values
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 10–15 connections | High concurrent query requests exist for expressway operation ledgers, this range prevents database connection exhaustion |
MONGODB_URI | mongodb://{host}:27017/fastgpt_hwy | Stores unstructured non-relational data such as inspection logs and over-limit incident ledgers |
PG_URL | postgresql://{user}:{pass}@{host}:5432/hwy_charge | Stores structured relational data such as core toll and maintenance ledgers |
REDIS_URL | redis://:{pass}@{host}:6379/0 | Caches frequently queried real-time traffic data to reduce pressure on relational databases |
STORAGE_S3_ENDPOINT | https://s3.{region}.cloudprovider.com | Stores large files such as monthly summary reports to meet high-capacity storage requirements |
FILE_TOKEN_KEY | Randomly generated 32-character string | Encrypts access tokens for ledger files to prevent unauthorized downloading of sensitive data |
Three Common Configuration Errors
- Symptom: Request Timeout error appears during conversations. Cause: Timeout configuration was not adjusted for batch data queries of expressway ledgers, causing summary requests to exceed default time limits.
- Symptom: Dependency pull fails during Docker build. Cause: No compatible mirror acceleration address was configured, and large model-related dependency packages were not pre-cached.
- Symptom: Empty result is returned when calling tools to generate ledger reports. Cause: Access permissions for
PG_URLorMONGODB_URIwere not correctly configured, making it impossible to read core ledger data sources.
How to Verify Successful Configuration
- Execute the
docker pscommand to confirm all dependent containers including databases, Redis, and storage services are running. - Call the built-in data source test interface, use preset test ledger data, and confirm that
PG_URLandMONGODB_URIcan read data normally. - Upload a simulated monthly ledger file to confirm that the storage service configured with
STORAGE_S3_ENDPOINTcan upload and download files normally. - Generate a test ledger summary request to confirm that tool calls can return structured report content normally.
The values provided 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.